Personality as a Factor Affecting the Use of Language Learning Strategies: The Case of University Students 3031252543, 9783031252549

Table of contents :
Preface
References
Contents
1 Approaches to Investigating Personality
1.1 Introduction
1.2 Research Paradigms in Investigations of Personality
1.2.1 Psychodynamic Theories
1.2.2 Behaviorist Perspective
1.2.3 Phenomenological (Humanistic) Approach
1.2.4 Cognitive Social Learning Approaches
1.2.5 The Trait Approach
1.3 The Five Factor Model of Personality
1.3.1 Historical Perspective
1.3.2 Major Theoretical Assumptions of the Five Factor Model
1.3.3 The ‘Big’ Five Personality Traits
1.4 Conclusion
References
2 Language Learning Strategies
2.1 Introduction
2.2 Good Language Learner Studies
2.3 The Construct of LLS
2.3.1 Early Definitions of LLS
2.3.2 Strategy Features
2.3.3 Recent Approaches to Conceptualizing LLS
2.4 Classifications of LLS
2.4.1 Rubin’s (1981) Classification of LLS
2.4.2 LLS Classification by O’Malley et al. (1985)
2.4.3 Oxford’s (1986, 1989/1990) Early Taxonomies of LLS
2.4.4 Macaro’s (2001, 2007, 2018) Classifications of LLS
2.4.5 Griffith’s (2013) Taxonomy of LLS
2.4.6 Cohen’s (1998, 2014) Typologies of LLS
2.4.7 Oxford’s (2011, 2017) Classification of LLS
2.5 LLS and the Concept of Self-regulation
2.5.1 Theoretical Assumptions and Models of Self-regulated Learning (SRL)
2.5.2 Selected Studies Investigating SRL
2.5.3 Self-regulated Language Learning (SRLL)
2.5.4 Empirical Investigations of SRLL
2.6 Variables Affecting LLS Use
2.6.1 The Language Learnt
2.6.2 Language Learning Experience
2.6.3 Cultural Variables
2.6.4 Age
2.6.5 Gender
2.6.6 Learners’ Beliefs
2.6.7 Learning Styles
2.6.8 Language Aptitude
2.6.9 Motivation
2.6.10 Language Learning Attainment
2.6.11 Language Learning Task
2.7 Conclusion
References
3 Research into the Role of Personality in L2 Learning
3.1 Introduction
3.2 Personality and L2 Use in Different Contexts
3.3 Personality and L2 Attainment
3.4 Personality and Specific L2 Skills
3.5 Personality and Affective Variables
3.6 Personality and the Use of LLS
3.7 Conclusion
References
4 Methodology of the Research Project
4.1 Introduction
4.2 Pilot Study
4.2.1 Participants, Data Collection, and Research Instruments
4.2.2 Preliminary Findings and Implications for the Main Study
4.3 The Design of the Main Study
4.3.1 Research Questions
4.3.2 Participants
4.3.3 Research Instruments
4.3.4 Data Collection
4.3.5 Analytical Procedures
4.4 Conclusion
References
5 Findings of the Research Project
5.1 Introduction
5.2 Participants’ Reports of LLS Use and Personality Traits
5.2.1 LLS Use
5.2.2 Personality Traits
5.3 Participants’ Profiles
5.3.1 Results of Two-Step Cluster Analysis
5.3.2 Results of k-means Cluster Analysis
5.4 Semi-structured Interviews
5.5 Discussion
5.5.1 Participants’ Use of LLS
5.5.2 Participants’ Personality Traits
5.5.3 Clusters of Language Learners Distinguished by LLS Use and Personality Traits
5.5.4 Limitations of the Study
5.6 Conclusion
References
6 Conclusions, Pedagogical Implications, and Directions for Future Research
References
Appendices
Appendix A: Values of Bivariate Item-Scale Spearman’s Correlation Coefficients for LLS Scales
Appendix B: Values of Bivariate Item-Scale Spearman’s Correlation Coefficients for Personality Scales
Appendix C: Interview Guide (Translated into English): The Relationships Between LLS and the Learner’s Personality

Citation preview

Second Language Learning and Teaching

Jakub Przybył Mirosław Pawlak

Personality as a Factor Affecting the Use of Language Learning Strategies The Case of University Students

Second Language Learning and Teaching Series Editor Mirosław Pawlak, Faculty of Pedagogy and Fine Arts, Adam Mickiewicz University, Kalisz, Poland

The series brings together volumes dealing with different aspects of learning and teaching second and foreign languages. The titles included are both monographs and edited collections focusing on a variety of topics ranging from the processes underlying second language acquisition, through various aspects of language learning in instructed and non-instructed settings, to different facets of the teaching process, including syllabus choice, materials design, classroom practices and evaluation. The publications reflect state-of-the-art developments in those areas, they adopt a wide range of theoretical perspectives and follow diverse research paradigms. The intended audience are all those who are interested in naturalistic and classroom second language acquisition, including researchers, methodologists, curriculum and materials designers, teachers and undergraduate and graduate students undertaking empirical investigations of how second languages are learnt and taught.

Jakub Przybył · Mirosław Pawlak

Personality as a Factor Affecting the Use of Language Learning Strategies The Case of University Students

Jakub Przybył Faculty of Modern Languages and Literatures Adam Mickiewicz University Pozna´n, Poland

Mirosław Pawlak Faculty of Pedagogy and Fine Arts Adam Mickiewicz University Kalisz, Poland

ISSN 2193-7648 ISSN 2193-7656 (electronic) Second Language Learning and Teaching ISBN 978-3-031-25254-9 ISBN 978-3-031-25255-6 (eBook) https://doi.org/10.1007/978-3-031-25255-6 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

The process of second or foreign language (L2) learning and teaching has been consistently shown to be moderated by a wide range of individual difference (ID) factors (cf. Dörnyei, 2005; Dörnyei & Skehan, 2003; Dörnyei & Ryan, 2015; Ehrman & Oxford, 1995; Gregersen & MacIntyre, 2014; MacIntyre et al., 2016; Oxford, 2011, 2017; Pawlak, 2021; Pawlak & Kruk, 2022). It is therefore not surprising that this line of inquiry remains among the most robust in the field of second language acquisition (SLA). Among learner characteristics, language learning strategies (LLS) appear to be of particular importance as their application has commonly been associated with greater L2 achievement, both in general and with reference to specific skills (Altan, 2003; Bialystok & Fröhlich, 1978; Magogwe & Oliver, 2007; Olivares-Cuhat, 2002; Szyszka, 2015; Wong & Nunan, 2011), as well as linked to self-regulated language learning (Chularut & DeBacker, 2004; Oxford, 1999; Rose & Harbon, 2013; Seker, 2016). However, as is the case with ID factors, LLS do not operate in a vacuum and their employment is moderated by other learner-related variables, one of which is personality. Even though investigations of the links between personality traits and strategic learning do exist, they are still scarce and to a large extent fragmentary, often relying on different research instruments, some of which are not reflective of the latest developments in the respective fields. For example, among the studies conducted so far, a great deal has addressed the impact of extraversion/introversion on L2 learning and performance, yet, after an explosion of empirical interest, the trait soon became an “unloved variable” due to the apparent inconsistency in findings (cf. Dewaele, 2022; Dewaele & Furnham, 1999). In addition, in the case of studies which have actually focused on personality as such, many have relied on questionable instruments, such as the Myers-Briggs Type Indicator (MBTI, Myers & Briggs, 1976), and a vast majority have addressed the impact of specific traits on various aspects of L2 learning in isolation rather than in clusters (cf. Piechurska-Kuciel, 2020). This last point also applies to LLS since relatively few attempts have been made to determine how clusters of personality traits may affect the use of different types of LLS. Addressing some of these gaps, the study reported in the present book attempts to link the application of LLS reported by tertiary L2 learners in Poland to their personality traits. However, its main aim is not simply to account for the psychological v

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Preface

profile of a good language learner (cf. Dewaele, 2022) but, rather, extract clusters of L2 learners who are similar in terms of their levels of personality traits and reported LLS use. This is done in accordance with the belief that such an approach may directly contribute to supporting L2 learners and teachers in individualizing the process of instruction and thus enhancing its effectiveness. It also complies with the recommendation made by Biedro´n and Pawlak (2016), according to which practical implications of studies into the role of personality in SLA could focus on catering instruction to the needs of learners, promoting awareness raising and, finally, diversifying classroom activities and tasks to adjust instruction to different personality-related profiles. In this way, the present book may also be seen as a contribution which fully subscribes to the learner-centered approach, which assumes that for L2 learning to be effective, learners need to be engaged in this process, involved in the decisions about what and how to learn, as well as encouraged to engage in the negotiation of the goals to be achieved (Nunan, 2015). The present volume consists of six chapters, the first three of which provide an overview of relevant theoretical issues. Accordingly, Chap. 1 offers a description of different models of personality with a particular focus on the five-factor model (FFM; Costa & McCrae, 1985, 1992). Chapter 2 shifts the focus to the concept of LLS, shedding light, among others, on the different definitions, classifications, factors affecting LLS use as well as the concept of self-regulation. In Chap. 3, an attempt is made to provide a brief overview of research into the role of personality in L2 learning and use, with a special emphasis on empirical investigations of how personality traits may influence strategy use. The last three chapters focus on the empirical study, describing its methodology, presenting and discussing its results, and addressing its limitations. Finally, in the conclusion, the results of the study are summarized, some pedagogical implications are made, and directions for future research are considered. Pozna´n, Poland Kalisz, Poland

Jakub Przybył Mirosław Pawlak

References Altan, M. Z. (2003). Language learning strategies and foreign language achievement. Education and Science, 28, 25–31. Bialystok, E., & Fröhlich, M. (1978). Variables of classroom achievement in second language learning. The Modern Language Journal, 62, 327–336. Biedro´n, A., & Pawlak, M. (2016). The interface between research on individual difference variables and teaching practice: The case of cognitive factors and personality. Studies in Second Language Learning and Teaching, 6, 395–422. Chularut, P., & DeBacker, T. K. (2004). The influence of concept mapping on achievement, self-regulation, and self-efficacy in students of English as a second language. Contemporary Educational Psychology, 29, 248–263. Costa, P. T., Jr., & McCrae, R. R. (1985). The NEO personality inventory manual. Psychological Assessment Resources.

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Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI) manual. Psychological Assessment Resources. Dewaele, J. M. (2022). Personality. In: Gregersen, T., & Mercer, S. (Eds.), The Routledge handbook of the psychology of language learning and teaching (pp. 112–123). Routledge. Dewaele, J. M., & Furnham, A. (1999). Extraversion: The unloved variable in applied linguistic research. Language Learning, 49, 509–544. Dörnyei, Z. (2005). The psychology of the language learner. Lawrence Erlbaum Associates. Dörnyei, Z., & Ryan, S. (2015). The psychology of the language learner revisited. Routledge. Dörnyei, Z., & Skehan P. (2003). Individual differences in second language learning. In C. Doughty & M. H. Long (Eds.), The handbook of second language acquisition (pp. 589–630). Blackwell Publishing. Ehrman, M. E., & Oxford, R. L. (1995). Cognition plus: Correlates of language learning success. The Modern Language Journal, 79, 67–89. Gregersen, T., & MacIntyre, P. (2014). Capitalizing on language learners’ individuality: From premise to practice. Multilingual Matters. MacIntyre, P. D., Gregersen, T., & Mercer, S. (Eds.). (2016). Positive psychology in SLA. Channel View Publications. Magogwe, J. M., & Oliver, R. (2007). The relationship between language learning strategies, proficiency, age and self-efficacy beliefs: A study of language learners in Botswana. System, 35, 338– 352. Myers, I. B., & Briggs, K. (1976). The Myers-Briggs type indicator. Consulting Psychologists Press. Nunan, D. (2015). Teaching English to speakers of other languages: An introduction. Routledge. Olivares-Cuhat, G. (2002). Learning strategies and achievement in the Spanish writing classroom: A case study. Foreign Language Annals, 35, 561–570. Oxford, R. L. (1999). Relationships between second language learning strategies and language proficiency in the context of learner autonomy and self-regulation. Revista Canaria de Estudios Ingleses, 38, 108–126. Oxford, R. L. (2011). Teaching and researching language learning strategies. Longman. Oxford, R. L. (2017). Teaching and researching language learning strategies. Self-regulation in context (2nd ed.). Routledge. Pawlak, M. (2021). Individaul differences and good languages learners. In C. Griffiths & Z. Tajeddin (Eds.), Lessons from good language teachers (pp. 121–132). Cambridge University Press. Pawlak, M., & Kruk, M. (2022). Individual differences in computer assisted language learning research. Routledge. Piechurska-Kuciel, E. (2020). The big five in SLA. Springer International Publishing. Rose, H., & Harbon L. (2013). Self-regulation in second language learning: An investigation of the kanji learning task. Foreign Language Annals, 46, 96–107. Seker, M. (2016). Scenario-based instruction design as a tool to promote self-regulated language learning strategies. SAGE Open, 6, 2158244016684175. Szyszka, M. (2015). Good English pronunciation users and their pronunciation learning strategies. Research in Language, 13, 93–106. Wong, L. L., & Nunan, D. (2011). The learning styles and strategies of effective language learners. System, 39, 144–163.

Contents

1 Approaches to Investigating Personality . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Research Paradigms in Investigations of Personality . . . . . . . . . . . . . 1.2.1 Psychodynamic Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Behaviorist Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Phenomenological (Humanistic) Approach . . . . . . . . . . . . . 1.2.4 Cognitive Social Learning Approaches . . . . . . . . . . . . . . . . . 1.2.5 The Trait Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 The Five Factor Model of Personality . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 Historical Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Major Theoretical Assumptions of the Five Factor Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.3 The ‘Big’ Five Personality Traits . . . . . . . . . . . . . . . . . . . . . . 1.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 1 2 4 8 9 11 14 16 16

2 Language Learning Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Good Language Learner Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 The Construct of LLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Early Definitions of LLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Strategy Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Recent Approaches to Conceptualizing LLS . . . . . . . . . . . . 2.4 Classifications of LLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Rubin’s (1981) Classification of LLS . . . . . . . . . . . . . . . . . . 2.4.2 LLS Classification by O’Malley et al. (1985) . . . . . . . . . . . . 2.4.3 Oxford’s (1986, 1989/1990) Early Taxonomies of LLS . . . 2.4.4 Macaro’s (2001, 2007, 2018) Classifications of LLS . . . . . 2.4.5 Griffith’s (2013) Taxonomy of LLS . . . . . . . . . . . . . . . . . . . . 2.4.6 Cohen’s (1998, 2014) Typologies of LLS . . . . . . . . . . . . . . . 2.4.7 Oxford’s (2011, 2017) Classification of LLS . . . . . . . . . . . .

45 45 46 47 47 49 51 54 54 55 56 59 60 61 62

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2.5 LLS and the Concept of Self-regulation . . . . . . . . . . . . . . . . . . . . . . . . 66 2.5.1 Theoretical Assumptions and Models of Self-regulated Learning (SRL) . . . . . . . . . . . . . . . . . . . . . . 66 2.5.2 Selected Studies Investigating SRL . . . . . . . . . . . . . . . . . . . . 68 2.5.3 Self-regulated Language Learning (SRLL) . . . . . . . . . . . . . . 72 2.5.4 Empirical Investigations of SRLL . . . . . . . . . . . . . . . . . . . . . 75 2.6 Variables Affecting LLS Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 2.6.1 The Language Learnt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 2.6.2 Language Learning Experience . . . . . . . . . . . . . . . . . . . . . . . 85 2.6.3 Cultural Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 2.6.4 Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 2.6.5 Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 2.6.6 Learners’ Beliefs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 2.6.7 Learning Styles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 2.6.8 Language Aptitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 2.6.9 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 2.6.10 Language Learning Attainment . . . . . . . . . . . . . . . . . . . . . . . 97 2.6.11 Language Learning Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 2.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 3 Research into the Role of Personality in L2 Learning . . . . . . . . . . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Personality and L2 Use in Different Contexts . . . . . . . . . . . . . . . . . . . 3.3 Personality and L2 Attainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Personality and Specific L2 Skills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Personality and Affective Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Personality and the Use of LLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

119 119 120 123 127 130 135 138 140

4 Methodology of the Research Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Pilot Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Participants, Data Collection, and Research Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Preliminary Findings and Implications for the Main Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 The Design of the Main Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 Research Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.5 Analytical Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

147 147 148 148 151 154 154 154 155 162 162 166 167

Contents

5 Findings of the Research Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Participants’ Reports of LLS Use and Personality Traits . . . . . . . . . . 5.2.1 LLS Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Personality Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Participants’ Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Results of Two-Step Cluster Analysis . . . . . . . . . . . . . . . . . . 5.3.2 Results of k-means Cluster Analysis . . . . . . . . . . . . . . . . . . . 5.4 Semi-structured Interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.1 Participants’ Use of LLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.2 Participants’ Personality Traits . . . . . . . . . . . . . . . . . . . . . . . . 5.5.3 Clusters of Language Learners Distinguished by LLS Use and Personality Traits . . . . . . . . . . . . . . . . . . . . . 5.5.4 Limitations of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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171 171 172 172 174 176 177 180 181 184 185 186 187 191 193 194

6 Conclusions, Pedagogical Implications, and Directions for Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

Chapter 1

Approaches to Investigating Personality

1.1 Introduction Empirical investigations of personality have constituted a valid area of research since the very early days of scientific and philosophical investigations. References to the views of ancient thinkers that can be found in contemporary handbooks of psychology include such notions as Plato’s division of the forces that drive human behavior, that is, reason, emotion, and appetite, and Aristotelian ideas of biologically-conditioned psyche, consisting of three composites: the nutritive faculty, the perceptual faculty, and the intellectual faculty (Ellis et al., 2009). One of the most popular classifications of personality types (sanguine, choleric, melancholic, and phlegmatic) dates back to 2AD, that is the time when Galen, influenced by Hippocrates’ theory of four humors, attempted to scrutinize the study of temperament (Loehlin & Martin, 2018). It could be argued that the interest in human personality was at least partly induced by the inherent belief that knowledge of an individual’s characteristics can make their behavior more predictable and serve better mutual understanding among human beings. The view that personality determines or, at least, interacts with people’s actions, is not rare among psychologists; however, it is the wealth of existential domains which are likely to be influenced by personality that is really impressive. According to Zawadzki (1970), personality is a modifier of development and a determinant of actions; it affects learning and people’s personal goals, at least partly accounts for people’s needs and desires, affects attitudes, and even influences the components of thinking. Language and personality are inseparable. The use of language is determined by the speaker’s personality, regardless of whether it is a native language (Beukeboom et al., 2013), a second language (Dewaele & Furnham, 2000), or a foreign language (Studenska, 2011). Contrariwise, any investigation of personality is bound to involve verbal descriptions of individual characteristics, depends on the thoroughness of the descriptions, and is likely to tackle the problem of the multitude of personality adjectives. Indeed, even the wording of the definition of personality in layman’s terms is far from obvious. Interestingly, the variety of descriptions offered by online dictionaries © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6_1

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of English, referring to “the type of person” (Cambridge Dictionary), “the combination of characteristics or qualities” (Oxford Dictionary of English), “someone’s character” (Longman Dictionary of Contemporary English), or “the part of a person that makes them behave in a particular way in social situations” (MacMillan Dictionary), seems to testify to the lack of uniformity in how personality psychologists explain the construct. The plurality of views on personality which have shaped the contemporary perception of the phenomenon is also accounted for in the present chapter. Section 1.2 contains descriptions of various research paradigms and overviews the most influential theories in the realm of personality. Section 1.3 provides a detailed account of the FFM (Costa & McCrae, 1985, 1992). The model is given particular attention since, for one thing, it underlies a vast body of research into personality in general, and for another thing, it constitutes the theoretical framework for the research instruments applied in the empirical study discussed in Chaps. 4 and 5. Concluding remarks regarding alternative frameworks for personality investigations and the status quo in empirical investigations of the construct are provided in Sect. 1.4.

1.2 Research Paradigms in Investigations of Personality Choosing a framework of investigation seems indispensable in personality studies; however, it needs to be stressed that no definite answer has been provided regarding the superiority of a particular approach or perspective over the years. It could be argued that the development of all issues in the domain of psychology, including personality psychology, has been dialectic in nature, and thus it has involved the emergence of a number of thesis proposals, responded to a number of antitheses, and subsequently aimed to integrate different viewpoints (Sternberg & Sternberg, 2012). For example, researchers scrutinizing defense mechanisms have attempted to provide scientific evidence for their existence or non-existence, but even more than 100 years after Freud’s revelations, there seems to be no consensus in this respect (Cramer, 1991; Freud & Breuer, 2004). It can be concluded that such factors as scientific progress resulting from the rise of new technologies, increasing availability of information, and the speed of its spread, all work in favor of accessibility of knowledge and the opportunity to exchange views, but at the same time, no ultimate solutions have been offered for the examination of key concepts, such as cognition, behavior, wellness, or personality. Consensus is present among scholars with regard to the very existence of personality, except for extreme situationists, who only account for the differences in human behavior and attribute them to the dissimilarity in cultural or situational backgrounds (Ellis et al., 2009). According to Ashton (2017), personality studies usually adopt one of two perspectives, that is, the idiographic perspective or the nomothetic perspective. The former is more common for in-depth investigations which are based on the general assumption of any individual’s uniqueness, such as, in the first place, case studies. The latter focuses more on personality characteristics that are universal, investigates a greater number of individuals, thus underlying the quest to describe

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tendencies rather than unique properties. The study discussed in Chap. 5 recognizes the value of both perspectives. Consequently, the description of the differences in LLS use among individuals with different levels of personality traits is followed by an attempt to identify and describe clusters of language learners who are relatively homogenous in terms of strategy use and personality traits. Apart from falling into either of the two above categories, personality studies typically subscribe to a specific theory, and embrace its methodology, which relates in particular to personality assessment. In other words, theoretical speculations tend to be cast into testable forms and studied empirically (Mischel & Mischel, 1973). The major approaches to the investigation of personality discussed in contemporary handbooks of psychology include the psychodynamic approach, the behaviorist approach, the phenomenological approach (sometimes also referred to as humanistic), the social learning approach and the trait approach (cf. Strelau, 2008). Some theorists also claim that psychobiological findings constitute a separate approach (Chamorro-Premuzik, 2011). However, although treating the human person as a biological entity is by all means valid from a scientific angle, a number of psychologists maintain that the scope to which biological factors have been considered in personality models is relatively limited as such (Magnusson & Törestad, 1993). Even though examples of empirical research into the biological foundations of different aspects of the human psyche can be provided (Eysenck, 1990; Strelau, 2008), the conclusions of relevant studies usually proclaim that the biological perspective can only be used in personality investigations in selected research areas. It is necessary to comment here on the development of positive psychology and its impact on the area of L2 learning, which has been explored in recent years (MacIntyre & Mercer, 2014; MacIntyre et al., 2016). Although it is methodologically correct to distinguish between humanistic psychology and positive psychology (Waterman, 2013, 2014), the latter has not developed a separate theory of personality, and hence, by considering it as a concept related to within-person traits, beliefs, attitudes, goals, and predictors of human behavior (Hefferon & Boniwell, 2011), it actually accepts the foundations of the trait approach. It could be argued that the personality theories which have been developed since the beginning of the previous century are not simply equivalents of the approaches referred to above, but at the same time, no approach could exist without a theoretical framework. This view is shared by Ellis et al., (2009, p. xvi), who writes: Underlying all clinical approaches is a theory of human personality. This theory can be tacit or explicit, but it is requisite. One cannot diagnose an infirmity without a model of health. Nor can one treat it without a conceptualization of its etiology. A personality theory provides the foundation for understanding how both healthy and dysfunctional personalities develop, and it makes the distinction between the two. In addition, such a theory provides a framework for the research and experimental testing of both itself and the clinical approaches based on it.

A brief description of the major research paradigms for personality investigations constitutes the following part of the present chapter. Thus, the consecutive subsections discuss the main assumptions of psychodynamic, behaviorist, humanistic/phenomenological, social-cognitive, and trait theories of personality.

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1.2.1 Psychodynamic Theories Freud’s (1910) concept of personality derives from psychoanalysis. Accordingly, the psychodynamic assessment of personality has commonly employed free association and analysis of dream reports or aimed to free the flow of attention, “which turns inward to the observer’s ruminations while remaining turned outward to the field of observation (…) rather waits to be impressed by recurring themes” (Erikson, 1958, p. 72). Yet, while the original Freudian theory emphasizes the importance of psychosexual concepts of personality development, a vast number of Freud’s followers have focused on more social concepts (Adler, 1957; Erikson, 1968). According to Freud (1910, 1923), human behavior is influenced by emotions, largely formed on the basis of memories, some of which are expressed as neurotic symptoms; however, at the same time, they may also be affected by resistance and repression, both of which could prevent conscious access to memories. Freud’s (1923) structural model of personality assumes the existence of id, ego and superego. While the first pillar may be explained as a representation of instinctual energy operating on an unconscious level, the second may be understood as remembering, considering, orchestrating, and actually performing actions required to obtain need gratification, and the final one refers to internalizing the values, norms or beliefs acquired in socialization (Quintar et al., 1998). The constituents of human personality are, in the classical psychoanalytic view, governed by different principles, that is, the pleasure principle (operating for id), and the reality principle (operating for ego). Guidelines for making judgements provided by the superego are based on two superego constituents, that is, conscience, related to actions considered unacceptable according to social standards, and ego ideal, reflecting an individual’s ideals and aspirations (Freud, 1923). Consequently, wish fulfilment can be seen as subject to mediation between the id and the outer world, which does not allow direct gratification of some behaviors, especially those not socially accepted (Mischel et al., 2008). Accordingly, three relevant distinct types of anxiety can be identified, that is, objective anxiety (caused by external threats), neurotic anxiety (caused by the conflict between the id and the ego) and moral anxiety (resulting from the conflicts between the ego and the superego). In order to handle them, defense mechanisms are developed by the ego against each of the above types of anxiety, which serve two functions, that is, protecting the ego and minimizing anxiety (Larsen et al., 2013). Table 1.1 contains a description of defense mechanisms and connects them with particular threats against which they are used. The list is inclusive of the mechanisms originally introduced by Freud (1923) and complemented with those added by his daughter (Freud, 1992). Psychodynamic views on personality are far from unanimous. While literally all of them stress the significance of an individual’s past and childhood, according to Adlerian psychologists, the roles of both nature and nurture in human development need to be recognized (Ansbacher & Ansbacher, 1964). At the same time, it is crucial how they are interpreted by specific individuals and what use those individuals make of these aspects of life (Adler, 1957). Consequently, personality according to the Adlerian stance may be regarded as “the individual’s creative exercise or use of self

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Table 1.1 Defense strategies (adapted from Edgcumbe, 2000; Quintar et al., 1998) Defense strategy

Function/description of operation

Denial

Blocking of threatening external stimuli from entering awareness

Projection

Attribution of ego-dystonic material onto others

Undoing

Attempts to dismiss unacceptable acts

Reaction formation

Management of anxiety-provoking impulses by expressing opposite ones

Rationalization

Employing apparently logical responses to explain anxious behavior

Displacement

Substitution of a less threatening behavior for a more anxiety-generating one

Sublimation

Transformation of unacceptable impulses into socially acceptable activities

Introjection

Internalization of external values, beliefs or attitudes

Identification

Wish to become similar to another, sometimes feared, person/object

Regression

Primitivization of behavior to an earlier stage of development

Intellectualization

Avoidance of anxiety-arousing situations by dismissing the emotional factor

Repression

Maintenance of anxiety-provoking thoughts within the unconscious

Identifying with aggressor

Finding active ways in becoming the aggressor

Altruism

Deriving pleasure from helping others fulfil desires (projective identification)

with others in the world” (Bitter, 2011, p. 422). The links between the individual and others are also notably present in Erikson’s concept of psychosocial development and his theory of the adult. According to Hoare’s (2002) claim, Erikson was the first illustrator of the social world in an individual’s psychological apparatus. Conversely, Quintar et al. (1998) summarize Erikson’s views as that of an ego psychologist, yet, at the same time, related to object relations theorists, primarily regarding human development theory. From Erikson’s (1966, 1968) perspective, personality should be seen as both dynamic and dependent on the interaction with a number of institutions and other people. Encountering them, individuals employ the strategies of ritualization, and their egos progress through a sequence of eight stages of psychosocial development, each one resulting in crisis resolution and a new virtue as an added value (Erikson, 1968). Erikson’s stages of psychosocial development are listed in Table 1.2, which also includes information on relevant processes, names the stages, and accounts for the resolved conflicts. While the construct of personality, structured as an autonomous system, owes numerous expansions to Jung (1921), it is the new interpretation of the unconscious, and the distinction between collective unconscious and the personal unconscious, that could be seen as a paradigm shift in opposition to Freudian psychology. Castilho

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Table 1.2 Stages of psychosocial development (adapted from Erikson, 1966, 1968) Psychosocial crisis

Age

Resolution and gained virtue

Trust versus mistrust

1

Acquisition of basic trust, the virtue of hope, and the numinous idea of mother’s presence versus idolism—unreal, perfect bond between mother and child

Autonomy versus shame and doubt

2

Sense of autonomy, and the virtue of will versus legalism

Initiative versus guilt

3–5

Developing the sense of purpose and achieving authenticity versus impersonation

Industry versus inferiority

6-puberty

Ego’s development, and the virtue of competence, accompanied by formality, versus formalism

Identity versus role confusion

Adolescence

Fidelity and ideology versus totalism

Intimacy versus isolation

Early adulthood

Love and affiliation versus elitism

Generativity versus stagnation

Middle age

Care and transmission of societal values to offspring versus authoritism

Ego integrity versus despair

Old age

Wisdom and integration versus salietism

(2014) interprets Jung’s personal layer of the unconscious as the more superficial one, and the collective layer as universal or innate. Drapela (1995) briefly summarizes the early Jungian model of human personality as a composite of four elements, including the ego, the self , and the twofold unconscious. As aptly pointed out by Wilde (2011), the real added value to the post-Freudian concept is the introduction of three axiomatic postulates. These are summarized in Table 1.3. Table 1.3 Jung’s axiomatic postulates (based on Wilde, 2011) Postulate 1: Extraversion—introversion It is necessary to distinguish between extraversion, that is, the outward flow of psychic energy outward, and introversion, understood as a flow of the flow of psychic energy towards the interior psyche (E-I) Postulate 2: Psychological functions A perceptual contrast exists between sensing, literally involving the senses in collecting information and using it as a basis in decision making, and intuition, involving heavy reliance on the unconscious (S–N) Judgmental processes vary, for thinking implies a strong cognitive orientation manifested through forming conclusions while feeling involves as deeply subjective valuation (T-F) Postulate 3: Perception and judgement An implicit difference exists between perception, understood as information collection, and judgment, understood as decision making (J-P)

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As reflected in Table 1.3, eight overall typological constituents of human personality can be distinguished in Jung’s (1921) vision of the psyche on the basis of grouping individuals according to their attitudes, that is, introversion or extraversion, and, for each of the two attitudes, four modes of orientation, that is, thinking, sensation, intuition and feeling (Sharp, 1998). Importantly, the attitudes and the modes serve together as pillars underlying the construction of introspective tools which rely on Jungian concepts in personality measurement, such as the Jungian Type Survey (Gray et al., 1964), the Temperament Sorter (Keirsey & Bates, 1998), and, most notably, The Myers–Briggs Type Indicator (MBTI) (Myers & Briggs, 1976). It is the latter instrument that has been frequently used in research into language learners’ individual characteristics (see Chap. 3) and hence deserves a closer examination. Relying on the four dichotomies mentioned above (see Table 1.3), personality measurement based on the MBTI involves calculating four separate indices, each related to one of four basic preferences determining individuals’ perception and judgment. It is assumed that the outcome of using the questionnaire is predictive of real-life choices made by individuals concerning information selection and absorption, decision making, and forming judgements—all of these being of vital importance for proper self-regulation of the L2 learning process. Interpreting MBTI scores ultimately boils down to assigning the person tested to one of 16 personality types (ISTJ, ISFJ, INFJ, INT,…) and providing an account of their basic preferences rather than traits or expected behaviors. For example, individuals diagnosed as extraverts (E) are expected to be more effective dealing with the outer world and other persons than their more introverted counterparts (I). At the same time, sensers (S) are more apt in paying attention to the present, physical reality than considering possibilities, which are the domain of those relying on intuition (N), one’s preferences for thinking (T) or feeling (F) affect their situational judgements, and, finally, relying on judgement (J) instead of perception (P) predisposes individuals in organizing life events rather than in experiencing and adapting to them (Wilde, 2011). In short, according to Myers and Briggs (1976), individuals who vary on the basis of the above categories experience the world differently, which is caused by the interplay of the four functions of sensation, intuition, feeling and thinking (Jung, 1923). The psychodynamic view of personality maintains a strong presence in personality investigations and, perhaps an even more robust one, in therapeutic treatment. It has evolved over the years and been embraced in modern approaches to the human self, such as the object relations theory, which attempts to account for people’s existence along two dimensions, the external and the internal one, and explore the relationships between them (Greenberg & Mitchell, 1983). Although psychoanalysts remain heavily criticized for providing insufficient scientific support for their claims, their theories have exerted a considerable influence on modern psychology, including personality psychology, and the popularity of the psychoanalytic approach is reflected in the popularity of the psychodynamic therapeutic treatment (Caligor et al., 2018).

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1.2.2 Behaviorist Perspective It is impossible to dismiss behaviorist insights into the study of the human person in the present volume because of their profound interest in learning (Thorndike, 1911, 1931), and their impact on L2 teaching methodology as reflected, for instance, in the principles of the audiolingual approach (Richards, 2002). As the term behaviorism suggests, demonstrable behavior, approached as a series of observable events, constitutes the primary area of interest for researchers falling into the broad category of behaviorists (Skinner, 1974). At the same time, the belief in the power of the stimulus constitutes the rationale for the two core concepts of behaviorism, that is, classical and operant conditioning (Romero, 1995). While both behaviorist and social behavior theories of personality can be considered as shifting the focus of interest from the individual’s intrapsychic processes to environmental influences, considerable variation exists in the extent to which their representatives subscribe to social determinism. Firstly, it is reflected in beliefs concerning individuals’ control over shaping their own personality and, secondly, it pertains to the extent of control over life that is left to the individual. Furthermore, behaviorism is sometimes believed to have given rise to the cognitive approach, and laid the foundations for the social learning approach (Staddon, 2014). The most prominent example of an approach which can be seen as an overlap of all three perspectives is Bandura’s (1986) conceptualization of social learning, also discussed in Sect. 1.2.4. Some behaviorists, such as Skinner (1953, 1974), adopt extreme positions and their research derives, to a large extent, from earlier experiments on animals (Pavlov, 1928). According to Skinner (1974), human behavior is determined by purposes, incentives and goals, all of which are involved in the concept of operant conditioning. Epstein (1991) points to two key concepts brought forward by Skinner: operant behavior, originally labelled as emitted, not elicited by a stimulus and, therefore, assumed to be in a way spontaneous, and determinism, explained by genetic endowments and environmental histories. Based on behavioral analysis, personality is defined by Skinner (1974, p. 172) as: a locus, a point at which many genetic and environmental conditions come together in a joint effect. As such, he [an individual] remains unquestionably unique. No one else (unless he has an identical twin) has his genetic endowment, and without exception no one else has his personal history. Hence no one else will behave in precisely the same way. We refer to the fact that there is no one like him as a person when we speak of his identity.

Other behaviorists, such as Staats (1971, 1996), chose to abandon the extreme position in order to include the biological and evolutionary perspective, thus allowing for a more systematic outlook on individual variation. Their views underlie the contemporary psychological behaviorism, whose main assumptions according to Staats (1996), could be summarized as follows: . a child has no inborn behavioral repertories, only sensory mechanisms and unorganized response mechanisms;

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. a child can develop sensory-motor, language-cognitive, and emotionalmotivational repertoires through learning, which results in particular behavior and characteristics; . personal characteristics are provided by an individual’s basic behavioral repertoires (BBRs), unique for everyone given the uniqueness of everyone’s environment (and thus experience), and the overall number of BBRs; . BBR is both a dependent and independent variable; . mechanisms of behavior are biologically determined while learning provides content; . behavior can be treated as a demonstration of some BBRs, which are considered to be general, not situation-specific; . abnormal behavior can be approached as a demonstration of verbal or motoric repertoire rather than the result of unresolved past conflicts. Behaviorists’ strong preference for experimental methodologies explains why they have developed virtually no descriptive, non-experimental, questionnaire-like research instruments for personality measurement (McCann & Endler, 2000). Yet, their approach remains relevant to the investigation of the links between students’ personal characteristics and their use of LLS. For one thing, strategy use is, to a large extent, demonstrable behavior, and constitutes a vital part of learners’ overall self-regulation in learning (Oxford, 2011, 2017). Moreover, the study of personality is permeated with insights from the cognitive approach (McCann & Endler, 2000). Some of these insights, particularly those related to schema formation, have facilitated the understanding the processes involved in organizing knowledge and contributed to the efficiency assessment of cognitive routines. Finally, language educators who dismiss demonstrable behavior as a source of knowledge about a person and neglect their environment or, broadly speaking, experience as the source of influence and individual variation, face the risk of not fulfilling their basic responsibility, which is assisting their learners in the process of L2 learning.

1.2.3 Phenomenological (Humanistic) Approach Introduced as the third force in psychology (Bugental, 1964), the humanistic approach developed as a response to both Freudian views, focusing on non-conscious drives that the person would be governed by, and behaviorists’ convictions concerning the determining role of environmental conditioning. Instead, humanistic psychologists suggest accounting for the possibly holistic picture of the human person, taking into consideration such concepts as cognition, emotion, feeling, will, morality, ethics, aesthetics, as well as intrapersonal, interpersonal and transpersonal relationships (Rennie, 2007). As proclaimed by Maslow (1999), humans are active agents equipped with free will, yet they do exhibit universal needs of physiological, safety, belonging and love, esteem, as well as cognitive needs. Importantly, according to Maslow (1954,

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2019), individuals’ actions could eventually compensate for disadvantageous biological inheritance that they had been endowed with as well as unfavorable constitutional factors originating in the environment. In Maslow’s (1954, 2019) view, people who self-actualize are equipped with a coherent personality syndrome and can be regarded as psychologically healthy and functioning in an optimal way. Although criticized for its apparent insufficient rigor and inadequate recognition of the meaning of cultural factors in personality development (Neher, 1991), Maslow’s (1954, 2019) humanistic theory of personality certainly constitutes an interesting framework for researchers focusing on individuals’ subjective experiences, the notion of free will, and the process of self-actualization. Importantly, self-actualization has been included by contemporary psychologists in the self-determination theory (Ryan & Deci, 2000), and is frequently referred to by contemporary researchers of motivation in FLL (Dörnyei & Ryan, 2015; Dörnyei & Ushioda, 2009; Pawlak, 2012). Rather than relying on classical personality inventories, supporters of humanistic psychology aim to pursue individuals’ ways self-actualizing by accounting for the hierarchy of their personal values. One example of an instrument developed to that end is the Personal Orientation Inventory (POI), introduced by Shostrom (1964). The inventory is built of four scales, further divided into subscales (listed in parentheses): orientation (time orientation and core centeredness), polarities (strength, weakness, anger, and love), integration (synergistic integration and potentiation), and awareness (being, trust in humanity, creative living, mission, and manipulation awareness). It has been used as a diagnostic tool in the measurement of self-actualization (Shostrom et al., 1976) as a way of identifying self-actualizers and non-actualizers. The instrument has also been successfully employed in educational psychology in measuring the effects of pedagogical intervention aimed to improve students’ feelings of competency and self-confidence, as well as its effects on self-acceptance and spontaneity (Fogarty, 1994). Moreover, as demonstrated by Sandhu (2020), the tool exhibits a huge potential in longitudinal investigations of personality and its indices of personal growth, inner directedness and time competence significantly correlate with levels of openness to experience and conscientiousness measured by the NEO Personality Inventory (NEO-PI-I; Costa & McCrae, 1985, 1992). The development of phenomenology as an alternative direction in psychology was closely linked not merely to an alternative outlook on such notions as the observer’s frame of reference, but also the novel approach to the Freudian ego and the self. Hartman (1950) distinguished between the phenomenal construct, the self , and the non-phenomenal, the subjective construct of the ego. This stance was also shared by Smith (1950), according to whom “(t)he distinction is that between a dynamic configuration of on-going processes, inferred from many facts of biography and behavior, and a phenomenal entity resulting from these processes and affecting them” (p. 519). The traces of this philosophy can also be found in Rogers’s works (1969, 1981, 2011), who, like Maslow (1954, 2019), dedicated much of his studies to actualization, and shared the humanist conviction that individuals can choose the best directions, even in their own therapy. According to his person-centered theory, individuals have an innate, gradually developing need for positive regard (Rogers, 1969, 1981). His view of the human being can be best summarized with his own words: “The good life is a

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Table 1.4 The structure of personality as proposed by Rogers (adapted from Ewen, 2003, pp. 199– 204) Key concept

Explanation

Experience

Everything available to an individual awareness at a given moment, i.e., thoughts, emotions, perceptions, and needs; only a small proportion of experience is conscious

The organismic valuing process

Humans’ innate ability to value positively whatever is, in their view, actualizing, whereas value negatively anything that is not

Self-concept

Conscious representation of experience

Self-actualization

Tendency to satisfy the demands of self-concept

Conflicts between actualizing and self-actualizing tendencies

Parents’ unconditional positive regard vs. conditional positive regard, i.e., positive self-regard becomes dependent on satisfying introjected (most often imposed by parents) conditions of worth, which replace the organismic valuing process as an inner guide to behavior (incongruence of actualizing and self-actualizing tendencies)

Defense

Concerns experiences which result in incongruence and results in change of behavior or attitude

Personality development

No distinction of specific personality development stages is drawn; the final stage in personality development is characterized by absence of conditions of worth (not satisfying the introjected standards of other people); manifests e.g. by the individual’s ability to form successful interpersonal relationships

process, not a state of being. It is a direction, not a destination” (1969, p. 186). The key constituents of Rogers’s structural model of personality are presented Table 1.4 (Ewen, 2003). It can be concluded that, according to phenomenologists, human behavior is best explained by means of what a person can do with it (Mischel & Mischel, 1973). Although the phenomenological (and, broadly speaking, humanistic) approach imposes an inherent difficulty on researchers of human personality, as it requires them to accept that human behavior is not predictable or controllable, it continues to grow in popularity, because of its association with positive psychology (cf. Snyder & Lopez, 2002).

1.2.4 Cognitive Social Learning Approaches The cognitive view of an individual is deeply rooted in the philosophical framework created by Rychlak (1968). According to the framework, an individual is equipped

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with some distinctive features, including self-concepts, phenomenal fields, lifelines, and personal constructs. Individuals’ environmental experience can be linked to their search for meaning, especially through active reflection, which may result in volitional action. Similar views can be found in Kelly’s (1963) personal construct theory, which differs considerably from other personality theories since it refutes the existence of identical constructs for individuals. Also, it supports the claim that individuals resemble scientists in the way they handle construct change. Other major assumptions incorporated in Kelly’s (1991) paradigm involve: . psychological channelization of an individual’s personal processes which serve event anticipation; . construction corollary—anticipating events by means of constructing their replications; . individuality corollary—individual variation in terms of event construction; . organization corollary—individuals’ evolution is convenience-driven, but convenience concerns event anticipation; . dichotomy corollary—the composition of an individual’s construction system of a finite number of dichotomous constructs; . choice corollary—an individual’s choice of one of the dichotomous alternatives, which ensures a better systematic elaboration; . range corollary—equivalence of a construct for the anticipation of a limited number of events; . experience corollary—the variation in an individual’s construction system caused by construing replications of events; . modulation corollary—the limitation in the variety of an individual’s construction system caused by the permeability of the ranges of convenience; . fragmentation corollary—the inferential incompatibility of construction systems employed by an individual; . commonality corollary—the similarity in experience construction between individuals; . sociality corollary—the scope of co-construing the construction processes among individuals belonging to the same society. It is not merely the existence of a vast number of personal constructs that makes the theory truly complex. Another factor contributing to its intricacy is the dynamic nature of constructs, which impedes their validation. Moreover, Kelly (1963, 1991) emphasizes the necessity of accounting for the role of emotion in construct change and asserts that, when confronted with all their emotions, individuals need to adapt to the development of these constructs. A procedure which consists of five steps is repeated every time a construct changes, and involves the phases of anticipation and hypothesis formation, investment in the event, encounter with the event, confirmation or disconfirmation of hypothesis, and constructive revision. Table 1.5 includes a brief description of the emotional factor in construct change. Advocating for the cognitive approach, Cervone (2004) posits that any personality assessment needs to:

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Table 1.5 The origin of emotions in construct change (based on Kelly, 1963, p. 114) Emotion

Cause

Anxiety

Recognition of the occurrence of events outside the range of convenience and the construct system

Hostility

Failure of an individual’s prediction of their construct system accompanied by attempts to enforce its recognition by others

Threat and fear

External changes of the core construct system

Guilt, shame, embarrassment

Perception of the self in the core constructs

Confidence, pride

Awareness of the validation of an individual’s core constructs

Humor

Realizing that more interpretations of the same construct are possible

Love

Awareness of the concordance between our own and somebody else’s construct system

. consider the disparity between individuals’ internal structures and general behavioral tendencies; . account for individuals’ systems which determine their actions; . distinguish between psychological and physiological systems; . allow for each individual’s uniqueness; and . never ignore the context in which it happens. Schultz and Schultz (2005) also stress that it is individuals’ interpretation of the events they experience rather than the events themselves that matter for their development. This is closely related to viewing the self-concept as dynamic and interpretive, and acknowledging that it actually mediates the most crucial intrapersonal processes, such as information processing, affective states, and motivation as well as a number of interpersonal processes that are crucial to L2 learning social perception, choice of situation, interaction strategy or reaction to feedback, to name but a few (Markus & Wurf, 1987). Overall, in the wake of the cognitive revolution, the perception of the self underwent a dramatic change as the construct ceased to be regarded as a monolith and became commonly considered to be multi-facet and dispersed. In contrast to the humanistic approach (cf. Rogers, 1981), the social cognitive approach recognizes three domains of the self, described by Higgins (1987) as: . the actual self, that is, the representation of the attributes that a person believes they have . the ideal self, that is, the representation of the attributes that they would like to have (e.g. hopes, aspirations, or wishes); . the ought self, that is, the representation of the attributes they believe they should have (e.g. sense of duty, obligations, responsibilities). Bandura’s (1977, 1986) social learning theory, already referred to in Sect. 1.2.2, may be regarded as an approach capitalizing on the insights from both behavioral and cognitive personality frameworks. The strongest link between behaviorists and social learning theorists consists in that they both emphasize the importance of

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learning, which social learning theorists even incorporate into the very construct of a human being. In other respects, as indicated by Bandura, “(c)onceptions of human behavior in terms of unidirectional personal determinism are just unsatisfying as those espousing unidirectional environmental determinism” (1986, pp. 22– 23). Instead, social learning theorists picture individuals as subject to the interplay between environmental factors, cognitive factors and other personal factors and believe that they can be modelled (Bandura, 1977, 1986). However, this is possible provided people pay attention to significant events, manage to retain relevant information through a representational system, convert the representations into appropriate actions of the primarily modelled behavior, and, finally, are presented with sufficient incentive so that the modelled action can actually be performed (Grusec, 1992). While some concerns exist over the reliability of the construct of the ideal self (Frank & Hiester, 1967), the ideal-actual self discrepancy has a huge potential as a measure of individuals’ adjustmental capacity and their overall self-regulation (Markus & Wurf, 1987). In the realm of FLL, the notion of multiple selves is central from the motivational perspective since, as suggested by Dörnyei and Csizér (2002), the whole concept of integrative motivation in FLL appears to be much more related to the basic integrative process (self identification) within an individual than to some largely abstract and metaphorical integration into the target language community. Various operationalization attempts have been made to account for the ideal and ought to selves and link them to self-regulatory, motivational processes (Dörnyei, 2005).

1.2.5 The Trait Approach One of the distinguishing features of the trait approach is its diligence in personality assessment and commitment to methodological excellence in measuring human personality traits. At the same time, the simplicity of reasoning of the trait approach is clearly its major asset confirmed by the clarity of the definitions of personality. For instance, Guilford (1959, p. 5) claimed that “(a)n individual’s personality is, (…) his unique pattern of traits”. According to Chamorro-Premuzik (2011), the main assumptions of the trait approach include: . consistency of behavioral, emotional and thought patterns; . belief in the internal nature of traits (though sometimes subject to debate); . limited number of personality traits (or dimensions) to be presented in a personality model; . quest for psychometric robustness of the created instruments. Schultz (1981) considers Allport to be the founder of the trait approach even though some of Allport’s conceptualizations of traits are fundamentally different from those developed by other trait theorists. Allport (1940, 1961) named the main techniques of psychological inquiry, including constitutional and physiological diagnosis, socio-cultural setting, membership and role, personal documents and case

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15

studies, self-appraisal, conduct sampling, ratings, tests and scales, projection, depth analysis, and synoptic procedures. Importantly, Schultz (1981) points out that Allport should not merely be associated with his belief in the deterministic role of traits, whose meaning he emphasized as a key to understanding different reactions to the same stimulus, but also remembered as the scholar who linked the study of personality with the interest in individual differences. Mischel et al. (2008) credit Allport with actually founding the field of personality psychology and expanding the scope of investigating individuals as opposed to analyzing its specific segments such as learning or memory without accounting for individual variation. In other words, Allport’s traits are dispositional and can be used to predict an individual’s behavior and performance. Allport’s definition of personality, which was coined after years of research, assumes that the concept should be understood as “the dynamic organization within the individual of those psychophysical systems that determine his characteristic and behavior and thought” (1961, p. 28). Considered by Allport (1940, 1961) to be constituents of human personality, traits are believed to be: . . . . . . . .

real, not merely nominal; general, in particular more generalized than a habit; dynamic, or, at least, determinative in behavior; established empirically; relatively independent from each other; not synonymous with values, virtues or any form of moral or social judgement; analyzable from either the individual’s or the society’s perspective; not always consistent with an individual’s behavior.

Allport’s (1961) framework for personality investigations assumes the existence of three categories of traits, depending on their intensity in an individual, that is, cardinal, or dominating (typically one per person), central (only a few of which exist in a person) and secondary (displayed relatively seldom). For example, authoritarianism could be considered a dominant personality feature, self-confidence, kindness, and gregariousness could be classified as central traits, and irritability could be classified as a secondary one. Within this framework, comparisons between individuals are possible, yet problematic due to the idiosyncratic (or, to use Allport’s language, idiographic) nature of individuals. According to Scheier and Carver (1992), some traits which occupy the central position in one person may be secondary in another and have no presence in yet another one. Gross (2009) takes a more extreme position and suggests that some traits are only characteristic of single individuals and even if the same trait label is used with reference to two individuals, its semantic interpretation may vary. The possibility of making personality-related comparisons among individuals remains one of the key areas of disagreements between the advocates of the idiographic approach and those who support the nomothetic stand. Some psychologists, such as Zuroff (1986), argue that Allport should not be considered a trait theorist because of his distinction between idiographic and nomothetic traits, as well as his commitment to approaching individuals with an emphasis on the recognition of their

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purposes or perceptions and respect for their individuality. Allport’s (1940, 1961) interest in individuals’ purposes is reflected in his assumption that the study of human personality cannot be separated from that of motivation. Commenting on an alternative hierarchical organization of personality traits, Gray (1999) links specific behaviors with traits and views them as the ground for drawing more general conclusions about individuals. Basing on Eysenck’s (1982) model, he explains specific behaviors as demonstrations of surface traits, which could then be organized into central traits. For example, a person who becomes easily involved in debates in which she defends unpopular stands, but also frequently expresses their opposing views in letters to the editors of the newspapers that they he or she reads, is likely to be argumentative (surface trait level). If the person also displays pugnacious and competitive behaviors, her central trait is likely to be aggressiveness. When approached from such a stance, the trait theory of personality may indeed be seen as attempting to provide a thorough description of personality composed of as few central (possibly non-redundant) traits as possible. Huffman (2008) lists three major criticisms of trait theories, which are the following: lack of explanation of the source of human personality traits and individual variation, insufficient specificity in explaining developmental tendencies of personality, and neglect of situational effects in personality assessment or attempts to predict people’s behavior. At the same time, trait theorists attempt to minimize these drawbacks and new theories of personality emerge in a dialectic manner.

1.3 The Five Factor Model of Personality It is the trait approach that underlies the methodology of the study seeking to link personality to the use of LLS described in Chap. 4. In spite of being the subject to a great deal of debate, the FFM (Costa & McCrae, 1985, 1992) can be referred to as a personality model of unique strength and predominance in psychology. Widiger (2017) suggests that the FFM largely owes its integrative character to the compatibility of its framework with the English lexicon used to describe traits, its adaptability for various personality theories, such as those of neurobiological, cognitive, or even psychodynamic origin, and a vast amount of empirical research which has been conducted in order to test its validity. The following subsections present the historical development of the model, describe its major theoretical assumptions, and attempt to thoroughly describe each of the ‘big’ five personality traits in terms of their heredity, development across human life, and their underlying facets.

1.3.1 Historical Perspective The development of the Five Factor Model of personality (Costa & McCrae, 1985, 1992) is traditionally linked with the rise of the trait approach in personality

1.3 The Five Factor Model of Personality

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psychology in the 1930s. Wiggins and Trapnell (1997) provide a brief outline of the development and use of a five-factor personality model, according to which the existence of five factors was first cited by Thurstone (1934), followed by a reference made by Allport and Odbert (1936). A number of different five-factor models later emerged over the decades in the works of such psychologists as Cattell (1943), Cronbach (1956), Guilford (1959), Eysenck (1960), Tupes and Christal (1961), Goldberg (1990), and, finally, Costa and McCrae (1985, 1992, 1995). Table 1.6 provides a selection of studies which are relevant to the development of the five-factor model of personality. Research into the validity and cultural universality of the Big Five model, as well as the stability of personality traits, has continued through the 1990s and in the twenty-first century, and selected findings are referred to on many occasions later in this book.

1.3.2 Major Theoretical Assumptions of the Five Factor Model Supporting the views expressed by Hjelle and Ziegler (1976), Costa and McCrae (2017) refer to a set of essential premises concerning human nature, which, as they claim, underlie the Five Factor Model of personality (Costa & McCrae, 1985, 1992). The model could also be described as resting on four major assumptions, which are as follows (Costa & McCrae, 2017): . knowability, that is, the belief that personality can be a valid scientific research area rather than merely a metaphysical entity; . variability, that is, the belief that human personalities are different but nevertheless can be studied in an attempt to account for possible universals; . proactivity, that is, people’s empowerment to behave in a certain way, juxtaposed with the kind of determinist view of individuals advocated by behaviorists; . reality, that is, the belief in the relationship between the manifested exemplifications of human behavior reported on questionnaires and the trait construct. Adopting the FFM (Costa & McCrae, 1985, 1992) also means accepting that personality attributes are continuous dimensions rather than discrete or categorical types, hierarchically ordered (with multiple layers of specificity), and that they cannot be easily structured. It can be assumed that the FFM (Costa & McCrae, 1985, 1992) is not merely a model, but also, in fact, a scientific concept, as it underlies a separate personality theory. This theory does not simply assume that a person’s individuality can be demonstrated in a variety of patterns of thoughts, feelings, and behaviors, but also recognizes the following tenets: . the initial assumption that individuals’ plans, goals, and schedules are influenced by their personality traits (Murray & Kluckhohn, 1953); . the premise that individuals have a conscious view of themselves, which is both cognitive and affective in nature (McCrae & Costa, 1988);

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Table 1.6 Outline of studies in the development of the FFM (based on Wiggins & Trapnell, 1997) Study

Findings

Thurstone (1934)

A study requesting participants to name 60 commonly used trait adjectives in describing people resulted in identifying five factors that account for the intercorrelations between the named traits

Allport and Odbert (1936)

Examination of trait-descriptive terms resulted in the classification of lexical items under the categories of personal traits, temporary states, social evaluations, and metaphorical terms

Cattell (1943)

4500 terms were arranged in 171 groups based on semantic similarity, from which 35 clusters were subsequently obtained to account for a “standard reduced personality sphere”, which was initially declared to have 12 underlying factors. Self-ratings, teammate ratings and staff-assessment ratings were used to provide data for 22 of the original 35 rating scales

Fiske (1949)

The first study of consistency of primary factors confirmed a high degree of consistency of factors among different raters

Cronbach and Meehl (1955)

Construct validity became part of the philosophy of science. Consequently, a stricter approach to test construction gave rise to strivings to excel personality tests contrary to the behaviorist perspective on the human person

Loevinger (1957)

The monograph Objective tests as instruments of psychological theory became a milestone in the history of psychometrics and test construction. References to introversion and neuroticism were made, but test responses were constructed as instances of behavior and dichotomous scales replaced Likert scales for fear of self-reports

Tupes and Christal (1958, 1961)

The investigation of 20 bipolar rating scales resulted in the emergence of a five-factor model built of extraversion, agreeableness, conscientiousness, emotional stability, and culture, four of which appear in the FFM (Costa & McCrae, 1985) A study of universality of the above five-factor model demonstrated a high stability of the five-factor solution across different samples and conditions (continued)

1.3 The Five Factor Model of Personality

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Table 1.6 (continued) Study

Findings

Norman (1963)

The rationale and procedures for developing a taxonomy of personality traits was scrutinized. Attention was also paid to such key issues as the generalizability and using peer ratings in order to improve

Cattell (1973)

Criticisms of the five-factor model centered around underscoring correlation matrices and the mechanical rotation of factors through clusters of surface variables

Goldberg (since 1981), Costa and McCrae (since 1985)

The search for universal dimensions in trait names and work on redeveloping a better instrument were resumed

. the recognition of an individual’s perception of themselves, which is coherent from their point of view, and consistent with their personality traits (McCrae & Costa, 1996); . the assumption that personality traits are accountable for “consistency and coherence in affect, behavior, cognition, and desire” (Wilt & Revelle, 2017, p. 57); . the belief in the endogenous origin of traits which are substantially heritable (Tellegen et al., 1988), reflected in the claim that all the Big Five traits are biologically determined (McCrae & Costa, 2008)1 ; . the acceptance of the developmental nature of traits, which are fully developed by about the age of 30 (Costa & McCrae, 1994); . the recognition of the hierarchical organization of traits, which consists in their specific order, from specific to broad dispositions, eventually generalized as the “big” five traits, that is, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness (Costa & McCrae, 1995). According to Costa and McCrae (2017), adaptations to the environment are influenced by both personality traits and earlier adaptations. Consequently, adaptations which fail to successfully match cultural values or individuals’ goals can be interpreted as maladjustments and linked to personality disorders. Adaptations vary throughout an individual’s life and can be affected by both changes to the environment and an individual’s conscious decisions. Human actions are believed by trait theorists to be subject to multiple determination, that is, they satisfy different needs connected with various traits. At the same time, human behavior is subject to external influences, which results in an interplay between individuals’ personality and their environment. In effect, the environment is constructed consistently with an individual’s personality traits and reciprocity, that is, influencing some element of the environment that influences an individual. Costa and McCrae (2017) claim that the dynamic processes can be universal in nature (that is, affect all people in a 1

Evolutionary psychologists suggest that traits can be viewed as strategies to meet adaptive challenges in the social environment (Nettle, 2005; Wilt & Revelle, 2015, 2017).

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similar manner), but they can also be affected by individual variation; the expression of some traits can be shaped by the expression of others. The FFM (Costa & McCrae, 1985, 1992) recognizes the duality principle, that is, the assumption that traits and trait indicators constitute two entirely different categories (or levels) and that trait indicators are characteristic adaptations but, at the same time, proxy measures of basic tendencies. As Costa and McCrae (2017) elucidate, “situations, behaviors, and explanations are some of the ingredients of indicators of heritable traits”2 (p. 25). Hence, it is possible to distinguish between dispositional states and personality traits, and, at the same time, draw a parallel between personality states, which can be understood as short-term, concrete and contextualized patterns of affect, behavior, condition, and desire (ABCD) (Wilt & Revelle, 2015), and personality traits, involving decontextualized ABCDs (Wilt & Revelle, 2017). However, Wilt and Revelle (2015, 2017) also suggest that personality traits can be described in the same way as personality states, which can lead to the conclusion that no need exists to design a separate framework of investigation of personality states. To recapitulate, the major postulates of the FFM (Costa & McCrae, 1985, 1992, 2017) are the following: . hierarchical organization of traits; . independence of adult personality from upbringing, cultural norms or historical conditions; . gradual stabilization of personality traits in adult individuals; . genetic influence on personality; . the relationship between personality and age; . the impact of one’s objective biography (that is, a persons’ factual life story, their successes and failures, struggles, or redemptions in the course of their lives); . the influence of brain pathology and pharmaceutical agents on personality; . the transcultural character of personality traits. Personality is believed by trait theorists to be identifiable across a vast number of cultures and amenable to investigation in cross-cultural contexts (McCrae & Allik, 2002). At the same time, the five-factor structure of Costa and McCrae’s Model (1985, 1992) has been challenged, particularly in the Asian context (Cheung et al., 2011). In order to account for cultural differences, adaptations of personality tests are needed which fulfil relevant goodness criteria for psychometric tests relating to cultural adjustment and hence it was the Polish adaptation of the NEO-FFI Inventory (Zawadzki et al., 2010) that was used in the study reported in Chap. 4.

2

The proponents of FFM do not offer a single explanation of the relationship between an individual’s traits and his or her behavior. Along with the ABCD framework, they present the conceptualization introduced by Yang et al. (2014), according to which traits can further be divided into situations in which trait-relevant behaviors take place and explanations for those behaviors.

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21

1.3.3 The ‘Big’ Five Personality Traits The present subsection deals with the description of the dispositions which constitute the elements of the FFM, that is, extraversion, openness to experience, agreeableness, conscientiousness, and neuroticism (Costa & McCrae, 1985, 1992). Each of them is defined and interpreted on the basis of its “capacity to render many stimuli functionally equivalent, and to initiate and guide equivalent (meaningfully consistent) forms of adaptive and expressive behavior” (Allport, 1961, p. 347). In addition, each trait is analyzed in terms of its underlying facets, accounted for in terms of its heredity, discussed in terms of its ABCDs (Wilt & Revelle, 2015, 2017), considered over people’s lifespan, reflected on from the angle of people’s objective biographies, and considered from the perspective of its potential impact on the language learning process.

1.3.3.1

Extraversion

Extraversion as a personality dimension was introduced into mainstream psychology by Jung (1921) (see Sect. 1.2.1), who described extraverts as more focused on the outer world, or, in other words, more engaged with it, whereas introverts as those focused more on their own inner mentality, or, to put it differently, drawn inward into thought. All major personality inventories, such as the Myers-Briggs Type Indicator (MBTI), (Myers & Briggs, 1976), Cattell’s Sixteen Personality Factor Questionnaire (16 PF) (Cattell, 1956), Eysenck’s Personality Inventory (Eysenck, 1964), and the Revised NEO-Personality Inventory (NEO-PI-R) (Costa & McCrae, 1992), include extraversion as a distinct personality domain. Trait theorists define extraversion as “the dimension of personality reflecting individual differences in the tendencies to experience and exhibit positive affect, assertive behavior, decisive thinking, and desires for social attention” (Wilt & Revelle, 2017, p. 57). They also list a number of characteristics of extraverts, such as being energetic, dominant, spontaneous and sociable, and juxtapose these with the typical characteristics of introverts, such as being lethargic, inhibited, reflective, and generally quiet. Highly extraverted individuals are also typically friendly, cordial, talkative, playful, optimistic and cheerful, and tend to seek stimulation, while their introverted counterparts are typically shy, reserved, deprived of optimism, and exhibit a strong preference to keep to themselves (Zawadzki et al., 2010). A number of frameworks exist which aim to scrutinize the hierarchical organization of extraversion. One of the predecessors of the FFM (Costa & McCrae, 1985, 1992), developed by Tupes and Christal (1961), includes the dimension of surgency, which is the equivalent of extraversion, built of the underlying traits of talkativeness, assertiveness, adventurousness, and exuberance. Indeed, the common process underlying both constructs is the disposition to engage in social behavior (McCrae & Costa, 1997a, 1977b). Eysenck et al. (1970) also put forward a model accounting for extraversion as a phenomenon that can be analyzed at four different

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levels of abstraction, including specific responses, which appear on single occasions (for instance, flirting with a specific person at a given party), habitual responses (for instance, behaving in a lively manner at different parties on various occasions), facetlevel constructs, (for instance, gregariousness), and the so-called general (broad) trait of extraversion. From this perspective, the constructs residing at lower levels (for instance, flirting behavior) are incorporated into only one higher level trait (that is, extraversion). While this proposal has some intuitive appeal, it is criticized for insufficient empirical support (Wilt & Revelle, 2017). Another controversial issue concerning the interpretation of extraversion is whether to include impulsivity as one of its lower-order features (Revelle, 1997). While scholars have tried to account for the degree of relevance of both concepts, empirical evidence indicates that although impulsivity and sensation-seeking do, to some extent, correspond to the conscientiousness scale, the latter is, in fact, more related to extraversion (Whiteside & Lynam, 2001). At the same time, the results of the study conducted by Quilty et al. (2014) suggest that sensation seeking is related, but not entirely explained by assertiveness or enthusiasm, both being aspects of extraversion. A great number of studies rely on the six-facet organization of extraversion put forward by Costa and McCrae (1992, 1995): . E1: warmth, involving friendliness and investing in others; . E2: gregariousness, understood as a preference for other people’s company over solitude; . E3: assertiveness, displayed in pushing others to get one’s way; . E4: activity, involving being energetic and vigorous; . E5: excitement seeking, or the willingness to feel joy through experiencing thrills; . E6: positive emotion, expressed in the ability to control positive mood. With regard to the heritable character of extraversion, findings from early longitudinal studies involving twins suggest that the levels of the trait are substantially heritable, but, at the same time, influenced by the environment, especially when treated as a way of responding to the environment (Scarr, 1969). The findings of numerous studies into extraversion in adult twins provide strong evidence for genetic endowment of the trait (Eaves et al., 1989). More recent studies have confirmed the links between the level of the trait and the genes responsible for dopamine production (Cohen et al., 2005), but at the same time have revealed that significant differences exist across groups of individuals living in different types of climate (Fischer et al., 2018). The ABCD framework (Wilt & Revelle, 2015) certainly contributes to a better understanding and a more accurate description of extraverts. According to Wilt and Revelle (2017), high levels of the trait extraversion can be linked to: . in terms of affect—positive emotions (at momentary, situational and trait levels), reinforced by the social perception that extraverts are effective in the pursuit of their goals;

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. in terms of behaviors, being bold, socially adept, and secure, entering a higher number of relationships than introverts, relying on stimulants relatively often, doing more exercise, talking more often, and using gestures; . in terms of cognition—involvement as a reaction to positive stimuli and avoidance of negative stimuli, relatively frequent favorable cognitions concerning social situations, multitasking (resulting from the ability to restrict distractions), and possible difficulties in the performance of tasks requiring persistence or sustained attention; . in terms of desires—rather high expectations for happiness related to goal completion, approach motivation (reward-orientation), relatively greater need for social contact, intimacy, and interdependence, strife for social status, and, often career in the social domain, and, finally, relatively greater demand for personal agency, but also a strong need for affiliation. Importantly, as pointed out by Siuta (2006), accounting for the characteristics, and, indeed, the ABCDs of introverts, might pose a challenge since in a number of respects, introverts ought not to be considered as merely the opposite of extraverts. A more appropriate understanding of introversion may, according to Siuta (2006), rest on the assumption that introverts do not possess some qualities which underlie extraversion rather than possess the opposite qualities. To exemplify, being withdrawn does not simply translate into being hostile, and a preference for solitude does not imply experiencing anxiety in social contacts. In terms of the developmental pattern for extraversion, evidence from large-scale studies exists according to which the levels of the trait decrease with age (McCrae et al., 2005). According to the results of the meta-analysis conducted by Terracciano et al. (2010), the level of the trait generally declines from the age of 30, but the tendency becomes more prominent after reaching the mid-50s. Related constructs, such as social vitality and social dominance, show partly similar lifespan patterns. The former tends to be more stable, with the most marked increase from adolescence to young adulthood, relative stability from the 20s to the 50s, and a decline in later years, while the latter exhibits a consistent increase from adolescence to the early 30s, followed by a two-decade stagnation period, and a gradual decline from the 50s on (Roberts et al., 2006). Lucas and Donnelan’s (2011) study confirmed the overall tendencies for extraversion on the basis of data from nationwide datasets from Germany and the UK and proved that the level of the trait is not really mediated by people’s occupation or gender. As far as an individual’s objective biography is concerned, apart from actually entering a higher number of relationships, greater job satisfaction, and even better performance at work, an extravert is more likely to involve more positive emotions in a story and to center the story around such key concepts as status, optimism, sociability, and activity. Extraverts are also more likely to share their memories with others, and, while doing so, they have a tendency to emphasize interpersonal trust (McLean & Pasupathi, 2006). In addition, from the perspective of an individual’s self-esteem, extraverts tend to show greater praise of themselves, which Crocker and Luhtanen (2003) refer to as a global evaluation of general worth as a person.

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1.3.3.2

Openness to Experience

Openness to experience, a term used interchangeably with openness, is defined by the proponents of the FFM as “the breadth, depth, and permeability of consciousness, and (…) the recurrent need to enlarge and examine experience” (McCrae & Costa, 1997a, p. 826). Highly open individuals are deeply interested in both their inner life and the outer world, they are creative, imaginative, intellectually curious, aesthetically sensitive, often unconventional, and inclined to question authority, whereas those whose levels of the trait are low exhibit conventional behavior, tend to hold conservative views, praise traditional values, and have more pragmatic interests (Zawadzki et al., 2010). From the psychometric standpoint, openness to experience comprises the following dimensions (Costa & McCrae, 1992, 1995): . . . . . .

O1: fantasy, which involves a wide imagination; O2: aesthetics, which manifests itself in a person’s appreciation of beauty; O3: feelings, represented in plethora of emotions that an individual experiences; O4: actions, which result from a person’s eagerness to try new things; O5: ideas, reflected in a person’s intellectual curiosity; O6: values, which are liberal in the case of an open person.

According to a more recent conceptualization of openness, proposed by Sutin (2017), the trait can be considered in terms of four dimensions: . its breadth, referring to the range of an individual’s interests (for example, the number and variability of one’s hobbies); . its depth, referring to the density of associations regarding particular ideas held by individuals, which can also be referred to as divergent thinking skills; . its permeability, referring to the malleability of mental boundaries, or, more broadly, the amount of differentiation in a wide spectrum of perspectives; . the motivation to actively engage in search for variety and/or novelty of experiences. In terms of the causes of openness, researchers generally agree that it is at least partly explained by genetic factors, similarly to the way that an individual’s general cognitive ability is (Riemann et al., 1997). Studies confirm the hereditary character of the trait; however, estimates of the contribution of genetic factors to an individual’s level of openness vary considerably, ranging from slightly over 20% (Power & Pluess, 2015) to nearly 50% (Larsen et al., 2013). When it comes to the ABCDs of openness to experience, it is possible to integrate the most relevant insights (Wilt & Revelle, 2017; Kaufman et al., 2013; Silvia & Christensen, 2020) and conclude that a high level of the trait primarily involves: . in terms of affect—extraordinary aesthetic and affective engagement (reflected in participating in activities related to, for example, music, dance, humor, theater and film), often linked to open individuals’ interest in arts and, consequently, being perceived as creative;

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. in terms of behaviors—a general tendency to engage in intellectually challenging tasks, greater probability of spending time with strangers, preference for being busy rather than “doing nothing,” reluctance to watch TV; . in terms of cognition—overall positive associations with intellect, cognitive construals including aesthetic and intellectual stimuli, and a positive relation to intellectual construals overall; . in terms of desires—seeking variety, longing for knowledge in general and intellectual development. Moreover, as reported by Costa and McCrae (1999), thanks to their curiosity, highly open individuals tend to travel a lot, pursue a great variety of hobbies, and demonstrate a good knowledge of foreign cuisine. Their vocational interests tend to be more diverse than those of people with low levels of the trait, and, interestingly, they develop friendships with people who share their tastes. Narrative studies of highly open individuals exhibit a high complexity of the narratives they provide. Interestingly, the level of openness also constitutes a valid predictor of success in presidential elections in the US, while also correlating significantly with maintaining high ethical standards at work (Ones et al., 2004). A considerable amount of research concerns the changeability of openness across individuals’ lifespans. It is commonly believed that adolescents and young adults tend to be relatively more open to experience than older individuals. However, it has been shown that openness to experience constitutes a differentiating factor as early as in childhood (Soto & John, 2014). From then on, it continues to increase in adolescence and young adulthood (Robins et al., 2001). Moreover, people’s educational choices can matter in the development of the trajectory of this trait. For instance, a study conducted among German university students indicated that the level of their openness to experience was significantly higher than their counterparts’ who chose vocational education (Lüdtke et al., 2011). It is still debatable when the level of openness starts declining, but many specialists agree that this happens after reaching the age of 60 (Roberts & Mroczek, 2008). Some vital characteristics of highly open individuals seem to be particularly relevant to learning and using additional languages. These include verbal fluency, a sense of humor, and being expressive (Sneed et al., 1998), as well as greater cognitive flexibility, which is demonstrated by storing, manipulating, and retrieving information with ease (Sutin, 2017). Consequently, it is logical to expect that both openness to experience and people’s greater need for cognition positively correspond with their use of LLS. Table 1.7 contains examples of language-related manifestations of openness to experience.

1.3.3.3

Agreeableness

Agreeableness is described by Graziano and Tobin (2017) as a synthetic measurement of the motivation to maintain positive relationships with others, and prioritizing interpersonal bonds over individual differences in social contacts and even in

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Table 1.7 Linguistic manifestations of openness to experience (based on Sutin, 2017) Study

Findings

Bates and Shieles (2003)

Open young adults tend to perform better on vocabulary and comprehension tasks

Noftle and Robins (2007) Open adolescents achieve better results in verbal sections of language aptitude tests Ayotte et al. (2009)

Open individuals are characterized with better executive functioning, which predisposes them to perform better on verbal fluency tasks

Sharp et al. (2010)

Open older adults show better verbal measures of cognition, such as analogies and synonyms

Ritchie et al. (2013)

Open individuals demonstrate better reading comprehension skills

thinking. A simpler definition, proposed by Haslam (2007), states that agreeableness is one of the “big” five personality factors which involves the disposition to be cooperative, interpersonally warm, and empathetic. According to another description provided by McCrae and Costa (2003), individuals who are highly detached tend to be critical, skeptical, try to push limits, express hostility more directly, and are more often reluctant to agree whereas highly agreeable individuals are relatively more sympathetic, considerate, warm, compassionate, likeable, and generous. The higher-order construct of agreeableness comprises the following lower-order traits (Costa & McCrae, 1992, 1995): . A1: trust, expressed in people’s positive assessment of others, their actions, and situations; . A2: straightforwardness, understood as directness and honesty in communication; . A3: altruism, involving concern for other people, selflessness, self-sacrifice, and generosity; . A4: compliance, expressed in avoiding conflict and using cooperative strategies to resolve it; . A5: modesty, related to individuals’ self-concept and being humble about oneself; . A6: tender-mindedness, described as people’s tendency to be sympathetic. Similarly to levels of other personality traits, the level of agreeableness is to a large extent genetically determined. It is most commonly associated with the so-called clock gene, largely determining individuals’ circadian rhythms, and, interestingly, high levels of the trait positively correlate to being a “morning person” (Terracciano et al., 2010). Also, variants of the DRD3 gene, expressed in the limbic system, have been shown to highly correlate with the levels of agreeableness (Kim et al., 2013). This said, it needs to be emphasized that evidence for the genetic endowment of the trait in question is not as strong as in the case of other traits. For instance, further research needs to be conducted to determine the degree to which externalizing problems as a manifestation of agreeableness is determined genetically (Tackett et al., 2019). Agreeableness remains one of least researched traits, also in the realm of L2 learning (Piechurska-Kuciel, 2020). Therefore, similarly to openness, to the best

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knowledge of the present authors, no uniform description of the ABCDs has been compiled for this trait. Yet, some observations about the ABCDs of agreeableness have been offered in the literature (cf. Wilt & Revelle, 2017, 2020), according to which a high level of the trait involves: . regarding affect—experiencing humility and being sensitive to others’, but also expressing affection relatively often to retain relationships; . regarding behaviors—honesty, rapid responses to cues exhibited by others, spending time with friends, involvement in situations requiring cooperation, and acquiring allies; . regarding cognition—favorable influence of a reassuring person on cognitive processes; . regarding desires—absence of willingness to deceive others. The levels of agreeableness tend to rise from early/middle childhood, decrease slightly before reaching adolescence, and then increase again until adulthood (Soto, 2016). The underlying facets of agreeableness show more complex patterns. As reported by Tackett et al (2019), agreeableness in childhood reflects willing compliance and low antagonism, while in adult age it is manifested more in empathetic and compassionate tendencies. Regarding lower-level traits, the level of altruism is known to increase in adolescence, but only in girls. At the same time, compliance decreases during adolescence and so does dominance, but, yet again, only in girls, while egocentrism and irritability are subject to hardly any change in pre-adolescence and adolescence (De Haan et al., 2017). As concluded by Tackett et al. (2019), developmental trends for higher-order agreeableness are likely to mask more complicated developmental patterns of the underlying facets. There is also some empirical evidence to suggest that changes in effortful control (that is, a self-regulatory temperament trait akin to conscientiousness) and agreeableness in later adolescence may promote increases in agreeableness-relevant behaviors such as prosociality (Alessandri et al., 2014; Caprara et al., 2012). When approached from the objective biography angle, a high level of agreeableness generally translates into compliance, and is realized in exercising deference to others, also in interpersonal conflicts (Costa & McCrae, 1999). Moreover, agreeable individuals exhibit more forgiving attitudes towards colleagues, friends, and partners, which, on the one hand, may prevent professional conflicts or breakups of relationships, but, on the other hand, makes many of them susceptible to manipulation (Graziano & Tobin, 2002). It is also worth considering the relationships between agreeableness and other semantically related characteristics, that is, empathy, prosocial behavior, and, to some degree, self-regulation. As far as empathy is concerned, high agreeableness scorers demonstrate a better developed skill of perspective-taking while not being affected by personal distress in case of witnessing others’ misfortunes. They have also been shown to behave more pro-socially (Graziano & Habashi, 2015). What is particularly relevant to language learning and learning situations in general, people who are more agreeable tend to show better self-regulation abilities, especially with regard to frustration management in social situations. The most

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relevant notion here is effortful control, which can be understood as the ability to suppress a dominant behavior (Graziano & Tobin, 2017). It is said to be a common characteristic of individuals who display high agreeableness. In school and university settings, fewer problems related to noncompliance or inattention are reported with children who are high in agreeableness (Laursen et al., 2002). The trait is thus likely to have a considerable impact on learners’ performance and participation in classroom activities.

1.3.3.4

Conscientiousness

Conscientiousness can be briefly described as a wide range of constructs that reflect the propensity to be self-controlled, responsible to others, hard-working, orderly, and rule-abiding (Jackson & Roberts, 2017). According to the psychological interpretation from the NEO-FFI manual (Zawadzki et al., 2010), highly conscientious individuals possess strong will, exhibit high levels of motivation and determination in goal completion, they are meticulous, punctual, considerate, and reliable, and tend to belong to achievers, although it may come at the expense of workaholism and endless pursuit for perfection. Similarly to other constituents of the FFM (Costa & McCrae, 1985, 1992), conscientiousness is hierarchically organized, and reflects relatively stable, automatic patterns of thoughts, feelings, and behaviors. A number of researchers distinguish between the proactive and inhibitory component of conscientiousness (Jackson et al., 2010; Roberts et al., 2005). Jackson and Roberts (2017) explain that the proactive component can be associated with the willingness to accomplish goals and attempts to perform well whereas the inhibitory component is related to responsibility, delayed gratification, and controlling one’s instincts or impulses. Table 1.8 presents an overview of the lower-order facets of conscientiousness compiled on the basis of various models. The problems encountered in comparing various frameworks for investigating conscientiousness primarily involve difficulties in replicating studies incorporating various underlying factors. A comprehensive list of characteristics that are ascribed Table 1.8 Alternative arrangements of the facets of conscientiousness Authors

Constituents

Roberts et al. (2005), DeYoung et al. (2007)

Industriousness and orderliness; empirical tests prove that this arrangement only caters for the proactive component of conscientiousness

Roberts et al. (2005), Jackson et al. (2010)

Achievement, self-control, and responsibility

Perugini and Gallucci (1997), Peabody and De Raad (2002)

Orderliness, industriousness (constituents of the proactive component), responsibility, and self-control (constituents of the inhibitory component)

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to conscientious individuals was put forward by Jackson et al. (2009), who adopt a four-facet hierarchical organization of conscientiousness. According to this stance, conscientious individuals can be described as follows: . people high in orderliness, who enjoy cleanliness and neatness, which can manifest itself in arranging belongings in an organized manner, but also drawing plans and striving to stick to them; . industrious individuals, who are basically hard-working and not easily discouraged by obstacles in achieving their goals, as well as able to cope with challenge and persevering; . highly responsible people, who easily adhere to rules and follow instructions, but at the same time they are more likely to keep promises or appointments; . possessing self-control as an inhibitory facet which determines their ability to refrain from immediate action, restricts their impulses, or helps them resist the urge of immediate gratification. By contrast, Costa and McCrae (1992, 1995) propose the model of conscientiousness which underlies the construction of the NEO-FFI (Costa & McCrae, 1992), comprising the following facets: . C1: competence, which can be explained as a sense of one own’s capability; . C2: orderliness, consisting in being neat and clean; . C3: dutifulness, associated with consistency in respecting principles and moral obligations; . C4: achievement striving, that is, high aspirations accompanied by focus on goal attainment; . C5: self-discipline, that is, one’s ability to carry out tasks despite obstacles or boredom; . C6: deliberation, which involves being thoughtful and reflective in decision making. Strong evidence exists which supports the genetic basis of conscientiousness as well as relevant lower-order traits, such as effortful control, self-control, and grit. For example, the comprehensive study investigating the characteristics of twins conducted by Takahashi et al (2021) confirmed that genetic correlations with the levels of the trait are stronger than non-shared environmental correlations, and while individual differences with respect to lower-order facets of conscientiousness are hard to identify, their overlap is largely attributable to genetic factors. Specifically, the KATNAL2 gene, responsible for producing brain proteins, seems to be particularly relevant to the level of the trait (De Moor et al., 2021). While no comprehensive description of the ABCDs of conscientiousness exists, it can be assumed on the basis of literature review that a high of level of the trait involves: . regarding affects—love of duty, willingness to abide rules;

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. regarding behaviors—dedication to obligations, expressed through, for example, spending time on education/in class, delay in the onset of inappropriate behaviors/persistence in appropriate behaviors, or involvement in chores; . regarding cognitions—involvement of moral issues in cognitive construals; . regarding desires—willingness to do well in the completion of tasks and achievement of goals. In terms of objective biography, highly conscientious people frequently make use of their leadership skills, and generally eagerly pursue their careers, which is one of the manifestations of striving for achievement (Costa & McCrae, 1999). They also plan meticulously and for long periods of time, organize support networks, and exhibit good technical expertise. Interestingly, the experience of parenthood does not mediate the developmental pattern of the trait (Neyer & Asendorpf, 2001). Numerous attempts have been made to trace the developmental pattern of conscientiousness. The trait has been reported to increase steadily until the age of 50, level off between the ages of 50 and 70, and decrease in old age (Lucas & Donnellan, 2011; Roberts & DelVecchio, 2000). The belief in the stable character of conscientiousness results in the assumption that an individual who scores high on this trait in childhood is expected to achieve a relatively higher score in adolescence and adulthood. These expectations are to a certain degree mediated by cultural differences (Yang et al., 1999), which are also responsible for at least a part of the variance in conscientiousness. Some psychologists point to the existence of the so-called conscientiousness paradox, as nationalities commonly regarded as highly conscientious, and also relatively better-off, such as the Japanese, have a tendency to lower their self-reported conscientiousness in comparison to other nationalities, a phenomenon which is influenced by respondents’ modesty and high demands concerning laboriousness (Chen, 2016; Meisenberg, 2015). More detailed patterns concerning the development of the four constituting facets of conscientiousness are presented below: . self-control and responsibility are reported to increase in young adulthood and in later stages of life (Jackson et al., 2009); . industriousness is subject to considerable fluctuations during young adulthood and generally increases during lifespan (Terracciano et al., 2010); . orderliness does not significantly change as individuals mature (Jackson et al., 2009); . impulse control is also partly responsible for the overall increase in conscientiousness (Jackson & Roberts, 2017). Conscientiousness plays a vital part in prognosticating people’s objective biographies, as it is one of the best predictors of academic success (Bratko et al., 2006) as well as underlies students’ better grades (Poropat, 2009). It also determines the level of students’ dedication to handling assignments and projects (Duckworth & Carlson, 2013), corresponds with students’ motivation to succeed in school performance (Capara et al., 2011), and ultimately determines successful transition from school to professional settings (Jackson & Roberts, 2017).

1.3 The Five Factor Model of Personality

31

As can be seen from the foregoing discussion, conscientiousness can exert a considerable influence on learners’ behavior, performance and attainment. It could also be expected that a high level of this trait is correlated with the employment of those learning strategies whose use requires relatively more effort and diligence. Moreover, the level of conscientiousness might mediate the link between learners’ motivation and their involvement in performing specific tasks, as well as affect the efficiency of managing the learning process. In other words, highly conscientious learners might be more likely to display greater willingness to take charge of the L2 learning process. Therefore, it could be expected that more conscientious learners may demonstrate greater responsibility and accountability as L2 learners, and their use of learning strategies could, potentially, be more frequent.

1.3.3.5

Neuroticism

Often referred to as negative affectivity or negative emotionality (Rothbart et al., 2001), neuroticism can be explained as a personality dimension involving emotional instability, proneness to experience negative emotions, vulnerability, and consistently low self-esteem (Haslam, 2007). It is said to reflect individual differences in tendencies toward negative affect, including sadness, anxiety, and anger, as well as individual responses to threat, frustration, or loss (Widiger, 2009). Individuals whose level of the trait is high are more susceptible to irrational ideas, less able to control their drives or cope with stress, worry excessively, and experience hostility or anger accompanied by lack of self-respect and embarrassment (Zawadzki et al., 2010). The FFM (Costa & McCrae, 1985, 1992) assumes the existence of six underlying facets of neuroticism, which are the following: . N1: anxiety, that is, proneness to feeling isolated and helpless in a hostile environment; . N2: angry hostility, that is, experiencing anger or frustration; . N3: depression, understood as a tendency to experience negative feelings such as sadness; . N4: self-consciousness, that is, a heightened sense of self-awareness, especially with respect to one’s drawbacks; . N5: vulnerability, that is, proneness to panic and experiencing stress; . N6: impulsiveness, that is, inability to control one’s urges. While neuroticism is substantially hereditable, with around half its variance explained by genetic influences (Lahey, 2009; Widiger, 2009), environmental factors prove to be equally important in determining its levels. At the same time, variation in the extent of neuroticism can be attributed to either non-shared or shared environmental factors, with the latter showing complex connections with genetic variation (Tackett & Lahey, 2017). On the basis of a review of the existing literature, it can be assumed that the ABCDs of neuroticism involve:

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. in terms of affect—experiencing stress beyond standard levels, . in terms of behaviors—spending time alone, watching TV, doing nothing, . in terms of cognitions—preference for quick generalizations of reactions to stressful or threatening environments, . in terms of desires—maintenance of leisure situations, The development of neuroticism shows complex patterns, but it is possible to trace slight increases of rank-order stability among both young and adult individuals (Roberts & DelVecchio, 2000). Also, the overall variability of an individual’s personality is associated with emotional lability, often considered to be a facet of neuroticism, if not its equivalent (Widiger, 2009). With reference to the objective biography of individuals scoring high on neuroticism, it is presumed that their tendency to experience dysphoric affect frequently gives rise to low achievement accompanied by feelings of guilt concerning, for example, the prestige of one’s profession (Costa & McCrae, 2009). Such situations often translate into self-actualized prophecies of leading oneself to failure as a result of failure anticipation rather than judgements based on one’s effort or competency (Carver et al, 1979). Although the manifestations of neuroticism which could affect educational performance are scarcely described in literature, studies which have dealt with general aspects of neuroticism can shed some light on predicting academic performance: . high neuroticism scorers show preferences for insufficient forms of coping, such as avoidance or disengaging attention (Bredemeier et al., 2011); . the cognitive response of individuals high in neuroticism to both negative and ambiguous stimuli is relatively higher than that of individuals lower in neuroticism (Hirsh & Inzlicht, 2008). Regarding the impact on academic success, studies indicate that a high level of neuroticism can result in learners’ low performance (Bhagat & Nayak, 2014), give rise to situational fears or anxiety (Hakimi et al., 2011), and even impede learners’ self-actualization (Duff et al., 2004). At the same time, assessing the impact of neuroticism on academic performance is not free from controversy, as one of the underlying facets of neuroticism, that is, anxiety, is known to take a range of forms (Seipp, 1991). Its two extreme manifestations, that is, debilitative and facilitative anxiety were distinguished by Alpert and Haber (1960), who also designed an instrument to measure both, that is the Anxiety Achievement Test. A study conducted by Carrier et al. (1984) indicated that debilitative anxiety impaired students’ performance in educational activities, such as note-taking, and subsequent tests, whereas facilitative anxiety did not significantly correlate with students’ educational performance.

1.4 Conclusion

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1.4 Conclusion Conceptualizations and frameworks for investigating personality vary in a lot of respects, including the constituents and even the very nature of the construct. It might appear that contradictions in understanding personality exist even within a given approach. For example, according to Allport (1961), it is dynamic, whereas it is described by Larsen et al. (2013) as organized and relatively enduring. At the same time, trait theorists tend to agree that personality can be seen as an intrinsic psychological structure, described by adjectives referring to personality traits centered around a certain limited number of dimensions (Piechurska-Kuciel, 2018). The extent to which personality determines people’s actions is debatable; however, a considerable proportion of researchers believe that it underlies human behavior, either in a deterministic manner, or, at least, by interacting with specific conditions (Ellis et al., 2009). It is logical to expect personality to affect virtually every domain of human existence, including learning styles, academic achievement (Komarraju et al., 2011), and LLS use (Oxford, 1986, 1990, 2011, 2017). Moreover, learners’ personalities are believed to interact with each other within each individual learner’s microsystem (Oxford, 2017). As is the case of any other complex construct, scholars need a framework of investigation to approach personality systematically and account for its measurement. Over the decades, the psychodynamic approach, the behavioral approach, the humanistic/phenomenological approach, and the trait approach, have shaped the con-temporary perception of personality. Within these approaches, numerous models have been developed so as to facilitate personality assessment. The advantages of the FFM (Costa & McCrae, 1985, 1992) consist in its relative simplicity in describing individuals (Costa & McCrae, 2017), and its potential across languages or cultures (Piechurska-Kuciel, 2018). At the same time, it should be stressed that the use of the FFM, as well as the NEO-FFI inventory (Costa & McCrae, 1992), may produce a bias towards analyzing personality in terms of its higher-order constituents rather than lower-order traits, and result in neglecting the role of such phenomena as language anxiety (Dörnyei & Ryan, 2015). This notwithstanding, the FFM was constructed with due scientific scrutiny recognized by a vast body of researchers (cf. Widiger, 2017) and even those who manifest a certain dose of skepticism towards it acknowledge that it was developed in a psychometrically appropriate manner (Dörnyei & Ryan, 2015). It enables cross-cultural and longitudinal comparisons and recognizes the genetic foundation of personality traits (Ellis et al., 2009). Its universal character has been confirmed across continents, and its popularity has expanded our knowledge of the determinants of human behavior in various areas of life, including L2 learning. Also, the application of the instruments developed on the basis of the model is likely to trigger reflection on the part of the learners who complete it. The present authors strongly believe that such reflection is likely to increase learners’ person knowledge, which involves understanding one’s own strengths and weaknesses (Oxford, 2011), and, in effect, make learners more active, better self-regulated, and more positive about language learning. This,

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in turn, enhances creativity and facilitates the FLL process (MacIntyre et al., 2016). The motivation behind the interest in learners’ personality traits is thus, to a large extent, generated by the conviction that self-awareness is an extremely desirable quality in L2 learning.

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Chapter 2

Language Learning Strategies

2.1 Introduction Thorough empirical investigations of LLS in the last several decades have, on the one hand, expanded the knowledge about learners’ characteristics, thoughts, behaviors, and desirable practices, which especially good language learners apply, but, on the other hand, made it more challenging to adopt a uniform view of how to best define or classify LLS. Moreover, some researchers have expressed reservations concerning the very notion of LLS, pointing to their allegedly insufficient theoretical framework or postulating alternative ways of accounting for learners’ actions taken in order to learn a foreign language (Dörnyei, 2005; Dörnyei & Ryan, 2015). At the same time, Ellis (2008) includes LLS as one of pillars of the framework for investigating individual learner differences, and Dro´zdział-Szelest (1997) sees LLS as a valid explanatory variable in investigating L2 achievement, stressing their relevance in defining the previously unaccounted for variance, which is certainly an important argument for including LLS as one of individual differences (IDs) in empirical inquiries. Despite some methodological shortcomings and theoretical disputes, a number of strategy researchers have persisted in conducting such empirical investigations, perhaps feeling obliged to strive to support learners and teachers with expert practical guidance (Gu, 2012). In an attempt to reflect on the progress made in strategy research, Oxford et al. (2014) identified key themes in their reflections on investigating LLS. These revolved around various psychological aspects of language learners, including, first of all, their self-regulation, but at the same time recognized the role of strategies in successful task completion and self-reflection. The present chapter attempts to address the afore-mentioned challenges in accounting for learners’ use of LLS. It opens with a historical overview of approaches that aims to provide a broad context for analyzing LLS. By accounting for the scope of findings and perspectives provided in the discussed studies, it is also intended as an argument for the legitimacy of the role of LLS in L2 learning. After anchoring LLS investigations in the so-called good language learner studies in Sect. 2.2, selected

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6_2

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early definitions of LLS are discussed in Sect. 2.3.1, followed by Sect. 2.3.2, dedicated to strategy features. An attempt to account for the status quo in strategy research in the present century is made in Sect. 2.3.3. Afterwards, an account of taxonomies, classifications, and categorizations of LLS is provided in Sect. 2.4. The following part of the present volume, that is, Sect. 2.5, addresses LLS through the prism of self-regulation (SR) and thus expands the macrocontext of strategy use. This includes a discussion of the psychological foundations of SR, reflections on its educational implications and, finally, elaborating on recent insights into the concept of selfregulated language learning (SRLL). Section 2.6 of the present chapter accounts for the variables affecting the use of LLS and individual differences (IDs) in strategy use, with the exception of personality, which is addressed in Chap. 3. Final conclusions regarding the status of the LLS construct are presented in Sect. 2.7.

2.2 Good Language Learner Studies With the onset of the humanistic approach, efforts to identify the characteristics which make some language learners more successful than others became more intense. For one thing, a number of researchers believed that expanding the scope of knowledge about learners’ inherent characteristics could contribute to more harmonious development of the learner. In addition, it was expected that at least part of the strategic repertoire of good language learners could be tailored to the specific needs and abilities of less successful learners (Griffiths, 2015). A number of researchers consider Rubin’s (1975) paper on good language learners to be “the initial spark for the language learning strategy field” (Oxford et al., 2014, p. 31). According to Rubin (1975), good language learners: . . . . . . . . . .

are not afraid to figure out meanings; skillfully manage information; focus on communication in language development; actively search for opportunities to apply new knowledge; are willing to integrate with other speakers of the target language; maintain motivation in the long run; are driven to communicate despite language shortcomings; are not limited by inhibitions; attend to forms and patterns; are aware of connections between meaning and structure.

In another pioneering analysis of good language learners, Stern (1975) placed special emphasis on the ways in which learners tackled the three problems that they encountered as beginners, that is, the disparity of language systems within the new target language, the code-communication dilemma, understood as the way in which a message is communicated by means of the imperfect linguistic system, and, finally, the choice on the part of the learner between adopting a more intuitive, or a more rational way of learning the target language. In Stern’s (1975) view, in

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order to address each of the three dilemmas, FL learners need to employ LLS. In spite of assuming that the L2 learning should involve both conscious use of LLS and unconscious mental processes, Stern (1975) hypothesized that it was possible to isolate specific techniques or strategies in a process of prolonged observation. A number of researchers have employed Stern’s (1975) paradigm to investigate the LLS employed by good learners. According to Cook (2008), it is beneficial for L2 teachers and researchers to exploit the LLS of good language learners and use them to train less successful learners to be more autonomous. This notwithstanding, no single, universal set of good LLS exists, since strategy use is influenced by a number of individual variables, and, at the same time, certain LLS are skill-specific (Griffiths, 2008, 2018). Also, as pointed out by Lesiak-Bielawska (2013), poor language learners’ strategies have received relatively little attention in SLA research, which is partly due to the fact that unsuccessful language learners might not be fully able to reflect on the LLS which they apply or, perhaps, to word their thoughts. This, indeed, constitutes a major limitation in LLS investigations, since virtually all studies into LLS rely on introspection as the main method of data collection.

2.3 The Construct of LLS Given the lack of consensus among strategy researchers, it seems that LLS have not been defined in a satisfactory way so far, and efforts to fully account for the concept are still being made (cf. Oxford, 2017). The major issues which underlie the lack of unanimity in addressing the notion of LLS include: . the legitimacy of LLS among IDs1 and their distinctiveness when compared with ordinary learning activities, (Dörnyei, 2005; Dörnyei & Ryan, 2015), and . their location (that is, mental or behavioral domain), size, degree of abstractness, and contextual setting of LLS, as indicated by Macaro (2006). The following subsection offers an overview of the definitions of LLS that have been proposed over the years as well as aims to explain how the understanding of the construct has evolved, particularly with regard to two the problematic areas mentioned above.

2.3.1 Early Definitions of LLS In the early years of interest in LLS, Rubin (1975, p. 43) described LLS as “the techniques or devices which a learner may use to acquire knowledge”, while Naiman et al., (1978, p. 4) regarded them as “more or less deliberate approaches, and more 1

Dörneyi and Ryan (2015) pointed out the ambiguity of strategies and opted for describing strategies as features of the learning process rather than an attribute of the language learner.

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specific techniques, i.e., observable forms of language learning behavior”. Tarone (1983, p. 67), in turn, defined them as attempts on the part of the learner “to develop linguistic and sociolinguistic competence in the target language—to incorporate these into one’s interlanguage competence”. A somewhat more complex description LLS was provided by Carver (1984), who defined them as “the overt or covert behavior, conscious or unconscious”, which he believed to stem from “higher level categories”, such as learning styles, understood as “learner’s preferences for ways of organizing his learning” (pp. 124–125). From this psychological perspective, strategies derive from studying, or, more generally, working habits and plans, and comprise a statement of objectives along with the assumed time frame, list of necessary materials, and techniques, and, finally, some methods of evaluation. As pointed out by Carver (1984), LLS use may be a function of both learner’s personality and situational factors. Indeed, strategy researchers have often approached LLS from the standpoint of educational psychology. For example, O’Malley et al. (1985) referred to Rigney’s (1978) and Dansereau’s (1985) explanations of LLS, and, consequently, defined them as “any set of operations or steps used by a learner that will facilitate the acquisition, storage, retrieval, or use of information” (p. 23). Such a description of LLS also resembles Bialystok’s (1983) definition, according to which, LLS are “activities in which the learner may engage for the purpose of improving target language competence” (p. 101). Inspired by Anderson’s (1983) adaptive control of thought theory, Chamot and O’Malley (1986) continued to advocate for the cognitive foundation of LLS, claiming that conscious and deliberate use of strategies leads to the development of declarative knowledge, which can become procedural knowledge through practice, but then it ceases to be to strategic and becomes autonomous. Much of what is known about LLS can surely be attributed to Oxford, who for many years has been spearheading research in this area. Although Oxford’s views have evolved over time, her belief in the benefits of studying LLS and expectations of the potential of LLS as a predictor of foreign language performance and proficiency, as well as skill development, have persisted. In one of her earliest papers on LLS, Oxford (1986) referred to Weinstein and Rogers’s (1985, p. 3) definition of learning strategies, according to which they can be understood as “cognitions or behaviors that a learner engages in during learning that are intended to influence the encoding process so as to facilitate the acquisition, retention, and retrieval of new knowledge”. Oxford (1986) juxtaposed LLS with teaching techniques and instructional strategies and explained the difference by linking LLS to learners’ autonomous choices. Wenden (1986) provided a number of more detailed descriptions of LLS. First, she explained the construct as language learning behaviors that learners actively engage in so as to learn and regulate the learning of a second language, thus classifying LLS as behaviors rather than mental actions, yet recognizing the component of volition (that is, learners acting as agents). Wenden (1986) also assumed that LLS involve strategic knowledge, which can be investigated when learners are asked to reflect on their learning process. According to Wenden (1986), efficient LLS use requires a certain amount of awareness of personal factors which facilitate and impede L2 learning, and depends on the recognition of one’s own competence as a language user. Thus,

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LLS use strongly depends on learners’ beliefs and raising learners’ awareness of LLS is likely to help them diagnose their language problems, reflect on achievement, and even handle feelings. Learners should therefore be empowered to be in charge of their L2 learning process. In terms of assigning LLS to a particular domain of human activity, a number of researchers, at least initially, perceived LLS as a cognitive construct. Among them, Chaudron (1988) described LLS as “cognitive operations that learners apply both in the classroom and in other learning situations” (p. 109) and pointed to the disparity between the two settings. Similarly, Chamot and O’Malley (1986), referred to LLS as “conscious processes and techniques that facilitate the acquisition and retention of new skills and concepts” (p. 15) and asserted that LLS use stems from learners’ attempts to facilitate the learning process with reference to both, language, and content learning. The definitions of LLS coined by other researchers, such as Tarone (1981, 1983) and Bialystok (1983), emphasized the role of LLS in the communication process, and signaled the role of strategies in developing communicative competence. Tarone (1983) considered LLS to represent attempts on the part of the learner “to develop linguistic and sociolinguistic competence in the target language—to incorporate these into one’s interlanguage competence” (p. 67). She also suggested that the distinction between learning and communication strategies only depended on the primary purpose of their use. Another attempt to distinguish between LLS and communication strategies was made by Bialystok (1983), who claimed that a particular strategy could be used for different purposes, and be characterized by a different degree of control, and a certain level of consciousness.

2.3.2 Strategy Features Oxford’s (1990) book Language learning strategies: What every teacher should know constituted a milestone in the study of LLS since it set out a thorough framework for investigating them as an ID in a scientific manner. The work is deeply rooted in the principles of humanistic psychology, which is reflected in the references made by Oxford (1990) to LLS as “steps taken by the students to enhance their own learning”, “tools for active, self-directed involvement, which is essential for developing communicative competence”, and “the way students learn a wide range of subjects” (pp. 1–2). With regard to notion of communicative competence (Hymes, 1972), Nyikos and Oxford (1993) suggested expanding the strategic component of communicative competence, included in Canale and Swain’s (1980) model. Nyikos and Oxford (1993) pointed out that strategic competence, understood as the competence in using LLS, “fosters competence in grammatical, discourse, sociolinguistic, and psycholinguistic areas” (p. 11), both in instructional and naturalistic settings. Moreover, Oxford (1990) also clarified the term input by expanding it beyond the language system that the learner is exposed to and incorporating in it the “variety of student and teacher characteristics, such as intelligence, sex, personality, general learning or

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teaching style, previous experience, motivation, attitudes, and so on” (p. 5), along with a number of societal and institutional factors. All the above considerations are reflected in another definition of LLS proposed by Oxford (1990), according to which “learning strategies are specific actions taken by the learner to make learning easier, faster, more enjoyable, more self-directed, more effective, and more transferrable to new situations” (p. 8). From the early years of interest in LLS, researchers have attempted to propose the characteristics which facilitate their understanding as a scientific construct. These, according to Oxford and her co-workers (Nyikos & Oxford, 1993; Oxford, 1990), include: . contribution to communicative competence and learners’ self-direction as the underlying goals of their training and use; . expansion of teacher’s role in L2 instruction as a requirement for their introduction and training; . orientation towards problem-solving; . learners’ agency; . holistic treatment of the learner’s person, that is, inclusion of various dimensions of language learning, not merely connected with cognition; . variation in the scope and level of influence on learner’s performance and achievement (direct versus indirect); . variation in their visibility to the observer; . multidimensionality, resulting from the fact that learning as such is multidimensional; . synergism, which is manifested in the advantages of using strategy chains; . scientifically confirmed demonstrability. A number of the above characteristics were recognized by Ellis (1994, 2008), including the use of reference to both general approaches and specific actions, problem orientation, awareness of LLS, the mental and behavioral dimension of LLS, and variation in strategy use stemming from the variety of language learning tasks. At the same time, Ellis (1994, 2008) referred to the following, additional features of LLS: . involvement of both linguistic and non-linguistic behavior; . potential for linguistic strategy use in both L1 and L2; . indirect and direct contribution of LLS to the learning process, consisting in either providing language learners with the data on L2, which they can process, or addressing specific areas of target language (TL) competence. In an early paper, Cohen (1995) addressed the issue of conscious strategy use by referring to Schmidt’s (1995) distinction between focal and peripheral attention. He concluded that if a learning behavior was totally unconscious, that is, if the learner could not answer the question what they had been just doing, their behavior should be treated as a process rather than a strategy. He also referred to Ellis’s claim (1994) that strategies that become proceduralized may not be accessible for verbal description by learners. Cohen (1995) specifically linked LLS use to the completion of certain

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tasks, which a well-functioning strategy repertoire can foster. Unlike Oxford (1990, 2011, 2017), Cohen (1995, 1998, 2003, 2014) drew a distinction between language learning strategies and language use strategies. While he linked the first category exclusively to the educational context, he further divided language use strategies into retrieval strategies, rehearsal strategies, cover strategies, and communication strategies. Moreover, with respect to the latter, Cohen (1995) further distinguished between language performance strategies and communication strategies, proposing that language performance strategies include cognitive processing strategies, strategies for solidifying newly acquired language patterns, and strategies for determining the amount of cognitive energy to expend. By contrast, he considered communication strategies to be strategies that are used in conveying messages. At the same time, he acknowledged the existence of some overlap between learning and communication strategies.

2.3.3 Recent Approaches to Conceptualizing LLS After the dissonance in understanding the strategy concept became more evident, some researchers attempted to name the major problem areas in accounting for LLS (Cohen, 1998, 2003; Dörnyei, 2005; Griffiths, 2004, 2018; Griffiths & Oxford, 2014; Gu, 2012; Liang, 2009; Macaro, 2006; Oxford, 2017; Pawlak, 2021; Pawlak & Oxford, 2018; Rubin, 2008). These areas could be summarized under the following headings: (1) (2) (3) (4) (5) (6) (7) (8)

the conscious/subconscious dilemma of strategy use; the features of LLS, such as their location, and degree of abstractness; the contextual setting of strategies among other IDs, learning goals, and tasks; strategy chains and internal relationships between particular LLS; the relationships between LLS and plans and processes; the correspondence between LLS and motivation; references to cognitive styles and learning styles; the inclusion of language skills in the strategy model.

Addressing the problems of the size and scope of LLS, Cohen (2003) refers to LLS as “conscious or semi-conscious thoughts and behaviors used by learners with the explicit goal of improving their knowledge and understanding of a target language” (p. 280). Referring to Wenden’s (1986) definition of LLS, Griffiths (2004) points out that some LLS can be observed directly, but some could also be inferred from language learners’ behavior. According to Macaro (2006), the existence of a number of definitions of LLS does not facilitate finding the answer to the dilemma of the cognitive/behavioral nature of LLs and while situating the strategy concept within the framework of cognitive theory implies accepting the assumption that strategies are a cognitive constructs, they cannot be restricted to the mental dimension since they actually include overt activities. In Macaro’s (2006) view, the breadth of LLS definitions corresponds with the scope of problems that one is likely to encounter

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making attempts to identify the area of human activity responsible for LLS. At the same time, the semantic proximity of such notions as strategies, operations, routines, processes, procedures, actions, tactics, techniques, plans, or steps seriously impedes the interpretation of the concept of strategies. Moreover, LLS need to be accounted for in context, which includes the purpose they serve, as well as the particular task and situation, and they are consciously employed by language learners. These views are reflected in Macaro’s (2006) three assumptions about the nature of LLS: . the description of LLS needs to involve three aspects, that is the goal, the situational component, and that of mental action; . the effectiveness of LLS depends on their use for particular tasks and the operation of various processes; . the constructs which cannot be used as synonyms of LLS include language learning processes, styles, plans, and actions which happen automatically. A number of other researchers have also referred to the dilemmas addressed by Macaro (2006). For example, White (2008) describes LLS as “the operations or processes which are consciously selected and employed by the learner to learn the TL or facilitate a language task” (p. 9), adding that language learners choose them from a variety of options, and their decisions are influenced by both the dynamic environment, and their goals in learning and/or using the target language. White (2008) also emphasizes the importance of exploring LLS in order to gain insights into independent learning, noticing considerable potential in the impact of the findings from strategy research on the enhancement of the language learning process, both inside and outside the language classroom, stressing their particular relevance to distance and online language education. Countering the criticism of allegedly insufficient scientific rigor underlying the LLS concept (cf. Dörnyei, 2005; Dörnyei & Skehan, 2003; Macaro, 2006). Griffiths (2013) provides a thorough description of the origins and the features of LLS and relevant notions, such as target language and speakers of other languages. In Griffith’s (2008, 2013) view, LLS need to be seen as active, conscious, chosen, purposeful, regulatory, and learning-focused. Oxford (2011, 2017) emphasizes the role of volition in learners’ use of LLS, indicating that deliberateness could actually serve as the criterion for distinguishing between strategies (consciously employed) and skills (automatically exercised and demonstrated). Oxford’s (2011, 2017) updated list of LLS features includes the following characteristics: . consciousness in strategy use, involving awareness, attention, intention, and effort (cf. Schmidt, 1995); . facilitative character of LLS, which consists in making the learning process easier, more enjoyable, and/or more effective; . potential to take the form of different tactics, work in different contexts, and be used for a variety of purposes; . inclusion of a number of aspects of the learner as a human person, such as, for example, cognition, metacognition, affect, etc.;

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. condition of joint use of a number of strategies (that is, strategy chains) as a premise for successful self-regulation in strategy use; . adaptability and transferability across a number of situational contexts. Griffiths and Oxford (2014) consider the status quo in strategy research in the twenty-first century, taking into account the lack of consensus across defining the strategy concept, the relationship between LLS use and learners’ proficiency, some theoretical underpinnings, categorization issues, contextual relevance of LLS, their teachability, research methodology, and techniques of analysis. When it comes to the existence of multiple definitions of LLS, describing strategies as learning behaviors, tactics, or techniques, Griffiths and Oxford (2014) express their conviction that efforts to unify and consolidate the beliefs about the source and nature of LLS should be maintained so as to enable more fruitful investigations of the concept. Commenting on the nature of LLS, the researchers suggest that LLS ought to be considered a cognitive construct, involving the processing and acting upon information. However, such processing is not limited to behavioristic “machine-like” production of output, since it involves generating rules, learning from errors, developing interlanguage, creating schemata, and employing metacognition. The following statement aptly summarizes Griffiths and Oxford’s (2014, p. 2) views on LLS: Strategies are theoretically multifaceted, and although the need for a sound theoretical base for the purpose of meaningful research is acknowledged, perhaps we should also be careful that attempts at clarification do not oversimplify and thereby reduce the richness and predictive potential of a phenomenon which is by its nature extremely complex.

In another attempt to account for the complexity of the LLS construct, Cohen (2014) defines language learner strategies as “thoughts and actions, consciously chosen and operationalized by language learners, to assist them in carrying out a multiplicity of tasks from the very onset of learning to the most advanced levels of target-language performance” (p. 7). The construct thus encompasses both language learning and language use strategies, where the former are understood as LLS employed when learning a language material for the first time, while the latter are seen as referring to strategies for using the TL material previously encountered in the learning process. On the one hand, maintaining the differentiation between learning and use distinguishes Cohen from other strategy researchers (cf. Griffiths, 2003, 2008, 2013, 2018; Oxford, 1990, 2011, 2017). On the other hand, Cohen’s (2014) claim that strategy use is conscious and his recognition of the role of context in strategy use across different proficiency levels are shared by a great number of strategy researchers who consider LLS as one of the pillars of learners’ self-regulation (Griffiths, 2003, 2008, 2013; Oxford, 1990, 2011, 2017). The debate over the strategy construct is far from being resolved and proposals of advancements in research into LLS continue to be proposed (Pawlak, 2021; Thomas et al., 2022). As pointed out by Oxford (2017), the core areas which are still being discussed include the diversity of LLS, their purposefulness, their consciousness, the mode of their use, contextuality, teachability, and the nomenclature of addressing LLS. These are discussed in the present chapter, in Sect. 2.5.3, dedicated to selfregulated language learning.

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2.4 Classifications of LLS The classifications, categorizations, typologies, and taxonomies2 of LLS have evolved along with the development of the strategy concept (cf. Pawlak, 2021). Initially, they tended to be more of ad hoc collections of labels, created in order to account for the strategies recognized in early strategy studies, such as practicing, monitoring, and inferencing. With time, the scope of identified strategies became considerably wider, which led to the creation of more thorough classifications, typologies, and taxonomies (Dro´zdział-Szelest, 1997). The following subsections provide an overview of the most influential classifications of LLS in chronological order.

2.4.1 Rubin’s (1981) Classification of LLS Basing on her analysis of cognitive processes in L2 learning, Rubin (1981) groups LLS into two major categories: (1) LLS directly contributing to learning, including: . asking for clarification or verification of problematic words or expressions; . monitoring, various aspects of linguistic correctness, esp. through selfcorrection; . memorization of new elements of the target language, through associations; . guessing and inductive inferencing, consisting in using linguistic clues to interpret meaning or ‘discover’ the rules of the target language; . deductive reasoning, comprising the search for target language patterns; . L2 practice, through which learners experiment and make use of the acquired knowledge of the target language, and (2) LLS indirectly contributing to learning, including: . looking for and creating opportunities for practice, such as engaging in conversation with native speakers; . compensating for missing chunks of language, for instance using synonyms, circumlocutions, cognates, or even gestures, collectively described as production tricks.

2

Mapping the scope of LLS poses a challenge not merely because of the scope of strategy research, but also due to a variety of co-existing approaches which researchers have adopted when attempting to distinguish between various strategies. For this reason, scholars have resorted to categorizations consisting in recognizing, differentiating, and understanding ideas which are grouped for specific purposes (Cohen & Lefebvre, 2005), classifications, that is, ordering entities into groups of classes on the basis of their similarity in order to achieve within-group homogeneity and between-group heterogeneity (Bailey, 1994), or taxonomies, that is, empirically derived groupings, aimed to introduce structure into a body of facts, and build a unified and homogeneous view of a particular domain (Chandra & Tumanyan, 2005).

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With time it has become evident that Rubin’s (1981) classification of LLS mainly accounted for cognitive strategies. At the same time, the LLS included under the indirect label bear resemblance to Oxford’s (1990) metacognitive and compensation strategies while clarification/verification strategies in the direct group are interactive in nature, and thus can be related to the social category of LLS in Oxford’s (1990) model (see Sect. 2.4.3).

2.4.2 LLS Classification by O’Malley et al. (1985) Following Brown’s (1982) scheme, O’Malley et al. (1985) classification of LLS encompasses three main categories: metacognitive strategies, cognitive strategies, and social mediation strategies. Metacognitive LLS in the framework include advance organizers, defined by O’Malley et al. (1985) as comprehensive previews of the organizing concept or principle in an anticipated learning activity, directing attention to learning tasks, selecting or focusing on specific aspects of language, selfmanagement, consisting in creating favorable learning conditions, advance preparation, involving both planning and rehearsing; self-monitoring, connected with striving for accuracy, and manifesting in self-correction and situational appropriateness; scheduling production consciously after reception, self-evaluation, referring to both, one’s progress and accuracy, and different ways of self-reinforcement. According to O’Malley et al. (1985), the group of cognitive LLS encompasses repetition, involving imitation of model input, and silent rehearsal, resourcing, consisting in the use of target language materials, directing physical response to physical actions as in giving orders, translation, grouping, based on attributes, various types of note-taking, deduction with reference to target language rules, recombination through manipulating L2 chunks in order to create larger sequences, imagery, or visualizing new elements of the target language, auditory representation, involving the retention of target language sounds, key word strategy, requiring the use of a familiar word which somehow resembles the word to be learnt, using context for embedding newly learnt words, elaboration, consisting in relating new information to previously learnt concepts, transfer, involving the use of previously acquired knowledge to deal with a new task, inferencing, applied in order to handle new language items, predict content, or compensate for missing information, and asking for clarification. When it comes to social mediation LLS, O’Malley et al. (1985) briefly explain them as working with other language learners in order to obtain information or, more specifically, feedback on one’s performance, as well as providing or benefiting from modelling a language activity.

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2.4.3 Oxford’s (1986, 1989/1990) Early Taxonomies of LLS Oxford’s (1986) taxonomy of LLS attempts to account for learners’ efforts to develop all four language macroskills. It is descriptive rather than prescriptive in nature, available in two versions, simplified or expanded, and designed to be used by professionals (teachers, researchers, etc.) and L2 learners. Capitalizing on Rubin’s (1981) work, Oxford (1986) divides LLS into two major categories, that is direct (primary) and indirect (support) strategies, which she explains in the following way. Direct LLS are employed to operate directly on L2 learning material and include L1 to L2 strategies, such as translation, interpretation, transfer, contrastive analysis, and analogy, inferencing strategies, consisting in attempts to comprehend the meaning of L2 words of phrases, emphasis or summary strategies, such as note taking, various forms of outlining, summarizing, highlighting, or using context-signaling devices, clarification or verification strategies, resourcing, consisting in skillful use of materials, such as dictionaries or recordings, formal practice strategies, such as rule generation and/or revision, rule search and/or application, exercising, generalization, deductive reasoning, analysis, practice, repetition, imitation, and noticing patterns, functional practice strategies, such as, for example, recombination, naturalistic practice, L2 self-talk, or L2 games, communication strategies, such as, for instance attempts to maintain communication in L2 or making use of available information,3 mnemonic strategies, such as preparing lists, dealing with them, e.g. breaking lists into smaller lists, assigning attributes to parts of lists, using acronyms, loci, flashcards, relating L2 entities to situations or contexts, mechanical tricks, rhyming, using auditory associations, imagery, keyword techniques, elaboration, physical response, phonological aids, rote learning, silent rehearsal, or learning a whole passage. According to Oxford (1986), indirect LLS are employed in order to develop an appropriate attitude, handle various constraints in the learning process, such as tiredness, boredom, or distractions, etc. They facilitate learning in a number of ways, and involve, in particular, general study strategies, such as organizing work and the learning environment, planning and goal setting LLS, referring to both the language learning process and particular tasks, attention-enhancing LLS, such as advance organizers, or focusing on L2 input; self-management LLS, involving learners’ monitoring, assessment, evaluation, estimation, diagnosis, prescription, and reinforcement, social cooperation LLS, such as clarification requests or asking questions in general: creating practice opportunities, cultural orientation towards the L2 society and history, and, finally, affective LLS, such as, for example searching for incentives, reduction of anxiety, and ways of improving perseverance. Oxford (1986) also differentiates between cognitive and metacognitive LLS. The former fall into the category of direct LLS, whereas the latter represent indirect LLS. Cognitive LLS involve adjustments made by language learners to the learning material in order to support retention or enhance learning, whereas metacognitive 3

Communicative strategies were excluded from the strategy taxonomy in later papers (Ehrman & Oxford, 1990; Oxford, 1990) as the label tended to be misused and the tactics under the label specifically referred to compensation strategies (cf. Tarone, 1981, 1983).

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LLS entail reflection on language learning, knowledge about it, and increase in the ability to regulate one’s own learning. Another distinction is made between syntactic and semantic LLS. Although both of them are examples of cognitive LLS, syntactic LLS focus on function words, affixes, and some content words, whereas semantic strategies require the use of contextual cues which can be found in learners’ environments. A number of other strategy categories are recognized in the taxonomy, such as formal versus functional practicing (cf. Bialystok, 1981), certain affective strategies, and some LLS specifically dedicated to processing texts in the target language. Moreover, as Oxford (1986) claims, the distinctions between the above categories may become blurred in practice since learners may apply some strategies in either a direct or indirect manner. For example, social strategies are recognized as a separate group of LLS, but not classified as either direct or indirect strategies. In an attempt to simplify the taxonomy discussed above, Oxford (1989a, 1990) introduced another functional classification of LLS, and ordered them into six basic categories: . cognitive strategies, focused on the target language itself, such as reasoning, analysis, note taking, as well as both functional and formal practice, all of which can all be classified as direct LLS; . memory strategies, helping learners store and retrieve relevant information; . compensation strategies, employed by learners to deal with insufficient knowledge of the L2, e.g. inferencing or circumlocution; . metacognitive strategies, used to plan and evaluate their learning and execute control of the learning process; . affective strategies, aiding learners in managing their emotions, attitudes, and motivation; . social strategies, relying on cooperating with others. According to a later interpretation by Ehrman and Oxford (1990), memory, cognitive, and compensation strategies can be classified as direct strategies, while metacognitive strategies, affective, and social strategies as indirect strategies. In her milestone publication, Oxford (1990) presents a more thorough version of the previously described taxonomy. Each of the subcategories (19 strategy sets) can be expanded into particular strategies, 62 in total. For example, the cognitive strategy of practicing includes repeating, formally practicing with sounds and writing systems, recognizing and using formulas and patterns, recombining, and practicing naturalistically, whereas the memory strategy of applying images and sounds can take the form of using imagery, semantic mapping, using keywords, or representing sounds in memory. While a certain dose of overlap in LLS classifications is inevitable, and it may prove difficult to classify a strategy as either structured reviewing or repeating, in Oxford’s (1990) view, this can be explained by the fact that strategies work in chains, that is, combinations of mutually supportive strategies, rather than in isolation. An example of a strategy chain or cluster might involve dividing the learning content (e.g. a set of professional papers in FL) into manageable sections and allocating time for these, finding related content in one’s mother tongue, skimming for gist and/or thoroughly, highlighting challenging vocabulary and checking it in a

58 Table 2.1 Examples of LLS based on the SILL ver. 7.0 (Oxford, 1990)

2 Language Learning Strategies Strategy scale

Subcategories

Memory strategies

Creating mental linkages Applying images and sounds Reviewing Employing action, for example, through physical response Practicing

Cognitive strategies

Receiving and sending messages Analyzing and reasoning Creating structure for input and output

Compensation strategies

Making guesses Overcoming limitations in speaking and writing Centering one’s learning

Metacognitive strategies

Arranging and planning learning Evaluating learning Lowering one’s anxiety

Affective strategies

Self-encouragement Taking one’s “emotional temperature” Asking questions

Social strategies

Cooperating with others Empathizing with others

dictionary and/or using context to infer the meaning of some words or phrases, and summarizing the content (Oxford, 2003). Table 2.1 illustrates Oxford’s (1990) division of LLS into subcategories. According to Oxford (1990), memory strategies are employed in order to help learners store and retrieve information which they need to communicate. They are also applied when information used in the communication process needs to be moved from the fact level to the skill level. This may take the form of matching different elements, such as, for example, assigning verbal labels to mental images of words or phrases. Cognitive strategies constitute a relatively heterogeneous set; however, as reported by Oxford (1990), they all serve the purpose of manipulating or transforming the target language by, for example, analyzing and reasoning or creating structure for input and output. Compensation strategies are vital whenever the language learner encounters difficulties caused by shortages of knowledge, either trying to understand or communicate something. Metacognitive strategies provide their users with the opportunity to order and coordinate the process of their own learning. They enable language learners to avoid information overload through planning and organizing the learning process as well as various tactics of maintaining focus. Also,

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since metacognitive strategies include seeking opportunities for practice, their use considerably affects the amount of target language input that the language learner is exposed to as well as translating into an efficient use of opportunities to interact in the target FL. Affective strategies are connected with learners’ management of emotions, attitudes, motivations, and even the values which they believe in as they influence learners’ self-esteem, the degree of inhibition which they experience in learning or using the target language, and their tolerance for ambiguity. Oxford (1990) stresses the importance of teachers’ role in creating a facilitative atmosphere in the classroom and, in this way, assisting the learner in their search for the sense of efficacy. Finally, social strategies are an inevitable ingredient in successful language learners’ repertoire, since not only do more proficient interlocutors provide learners with opportunities for practice, but they also serve as a source of input. Moreover, other L2 users can serve as instructors or experts in charge of correcting learners’ mistakes or errors and even attempt to consciously work on the areas which, in their view, need guidance or improvement.

2.4.4 Macaro’s (2001, 2007, 2018) Classifications of LLS Macaro (2001) suggests that LLS should be mapped on two continua based on the direct–indirect and conscious-subconscious dichotomies. Regarding the former continuum, LLS may be seen as “either directly at the interface with the processes involved in perception, decoding, processing, storage and retrieval [o]r, (…) indirectly involved with language, functioning as mechanisms which oversee cognitive strategies via planning, monitoring and evaluating for effectiveness” (Macaro, 2004, p. 7). Concerning the latter dichotomy, Macaro (2001, 2006) draws a distinction for learning activities on the basis of whether they are subject to an individual’s control. The LLS which he views as relatively more indirect and subconscious include: . . . . .

linking L2 words to mental images; inferring meaning from close context; grouping vocabulary items into lexical categories; storing L2 chunks in short-term memory before analyzing them; referring to gist while attempting to understand details of meaning. The LLS that can be placed in the central part of the continuum include:

. . . .

reflecting on the similarity of L2 and L1 words; repetition of new words or phrases; memorizing new language items; providing answers (in one’s mind) to questions asked to other students. Finally, the following LLS are classified as relatively more direct and conscious:

. making mental associations with objects/ shapes of words in writing; . asking for clarification;

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. practicing with peers (that is, acting out dialogues); . relaxation strategies employed in order to prevent being overwhelmed by a task. Macaro’s (2001, 2004, 2006) attempt to situate LLS on continua in order to account for their complexity allows certain flexibility, and, at the same time, strives to link research into LLS to the practice of L2 learning and teaching. In his subsequent LLS typologies, Macaro (2007, 2018) adopts a more contextualized, skill- and subsystem-based approach. In a more recent publication, Macaro (2018) suggests that investigating LLS employed in listening should be approached from different angles as listening to the teacher varies considerably from listening to audio materials, primarily since the latter is often followed by activities aimed to boost learners’ range of structures and FL vocabulary. Examples of LLS employed when listening to audiovisual materials include: . . . . . . .

various types of noticing (concerning words, word parts, word positions, etc.); various types of repetition (loudly, silently, in one’s thoughts, mechanical coping); organizing vocabulary in various forms (lists, flashcards); creating vocabulary exercises; linking new vocabulary to graphic images; creating associations, for example, through making sentences; recording techniques relating to various modalities.

As can be seen, the taxonomies of LLS proposed by Macaro (2001, 2007, 2018) are grounded in the practice of L2 learning and teaching and can easily be translated into learning activities, both inside, and outside the language classroom.

2.4.5 Griffith’s (2013) Taxonomy of LLS Admitting that strategy classification remains an area of controversy among researchers, Griffiths (2013) suggested a simple taxonomy of LLS consisting of five major categories: . cognitive strategies, central to the taxonomy since they are directly connected to the material to be learnt, such as learning vocabulary encountered in a text; . affective strategies, employed in order to control feelings and emotions, such as attempting to relax or rewarding one’s good performance; . social strategies, applied in order to manage interaction with others, such as arranging to meet with other L2 users; . memory strategies, used in order to remember the target material, such as writing down selected words or phrases in order to memorize them; . metacognitive strategies, involving the control, management, and regulation of the learning process, such checking requirements. The above taxonomy is functional in nature since it accounts for the purposes for which LLS are employed rather than considering them across specific language

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skills or subsystems. To a large extent, it reflects Oxford’s (1990) classification of LLS even though the distinction between memory and cognitive strategies, still present in the classification put forward by Griffiths (2013) has been criticized (cf. Cohen & Dörnyei, 2002; LoCastro, 1994). One respect in which the classification differs from its predecessor developed by Oxford (1990) is the lack of recognition of compensation strategies as a separate category, predominantly due to their proximity to communication, rather than learning, strategies.

2.4.6 Cohen’s (1998, 2014) Typologies of LLS Cohen’s (2014) view of LLS categories confirms that some crucial discrepancies among strategy researchers have never been eradicated. Firstly, the distinction between language learning and language use is still present in his classification, and, secondly, communication strategies are discussed as a category of language use strategies.4 In order to explain the distinction between language learning and language use strategies, both of which represent language learner strategies, Cohen (2014) provides examples of both and provides a typology of language use strategies employed by language learners in order to improve their command of the target language. Referring to the category of language learning strategies, Cohen (2014) mentions: . identifying, distinguishing, and grouping target language chunks; . repeated contact with the target language, including solitary rehearsal; . memory strategies, which include repetition and mnemonics. These categories partly correspond to the groups included in Oxford’s (1990, 2011) taxonomies, and focus on the cognitive and metacognitive aspects of LLS; however, the affective and social dimensions of L2 learning seem to be unaccounted for. When escribing language use strategies, Cohen (2014) identifies four subsets of these strategic devices: . retrieval strategies, consisting in accessing the language material stored in memory; . rehearsal strategies, through the use of which learners engage in various types of practice; . coping strategies, comprising compensatory strategies, allowing learners to cope with gaps in their TL knowledge, and cover strategies, employed by them to create the impression that they have control over the learning material and; . communication strategies, which are employed in order to convey meaningful messages in speech or writing despite potential knowledge gaps, further divided into: 4

Cohen (2014: 16) admits that communication strategies may or may not have impact on learning.

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– – – – – –

intralingual strategies, such as overgeneralization of target language rules; interlingual strategies, such as transfer from L1 to L2; topic avoidance or abandonment; message reduction; code switching; paraphrasing, for instance, through the use of synonyms or circumlocutions.

Cohen (2014) also indicates that LLS could be classified by skills, functions, proficiency levels, and, finally, specific cultures and languages, and distinguishes a number of subcategories with respect to the first two factors. Considering the possible categories of strategies with regard to skill development, Cohen (2014) does not suggest that LLS differ regarding the development of each of the four basic macro skills, but also assumes that learners could employ specific vocabulary and translation strategies across the four skills as well as relying on LLS while developing their TL grammar. Commenting on the possible functional division of LLS, he refers to Chamot’s (1987) and Oxford’s (1990, 2011) categories of LLS and agrees that LLS could be classified as metacognitive, cognitive, affective from a functional point of view, yet, at the same time, persists in distinguishing between language learning and language use strategies. At the same time, citing the example of monitoring and evaluation strategies, commonly classified under the metacognitive label, Cohen (2014) points out that certain strategy categories could overlap, and their use might depend on specific language tasks.

2.4.7 Oxford’s (2011, 2017) Classification of LLS In her strategic-self regulation (S2 R) Model, Oxford (2011, 2017) does not merely suggest a theoretical and contextual framework for the investigation of LLS, but also sheds new light on their classification. Oxford (2017) argues that LLS ought not to be rigidly assigned to merely a single functional category since this could result in oversimplification of not only the roles LLS play in L2 development, but also the strategy construct as such.5 Caution should also be exercised when distinguishing between LLS on the basis of their skill-dependence6 as not only are some traditional skill divisions viewed as irrelevant nowadays, but also the same strategy can serve different purposes even when considered for a single skill, and, may be accompanied by a set of other, less evident, strategies. Instead, a more flexible approach is recommended, manifesting itself in, for instance Oxford’s (1990, 2011, 2017) refusal to divide strategies used by L2 learners into language learning and language 5

The examples that Oxford (2017) provides include using analysing to regulate emotions, manage motivation, or deal with sociocultural issues and attitudes, and thus going beyond its cognitive dimension, and qualifying summarising texts, reconceptualising words, or skipping examples in a text as either cognitive or metacognitive strategies, depending on the researcher’s interpretation. 6 For example, reasoning is traditionally associated with developing receptive skills rather than productive skills (Oxford, 2017).

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use strategies. Unlike Cohen (1998, 2014), Oxford (2017) points out that the distinction between learning and use is not only rejected by educational psychologists, but it is also not recognized by institutions responsible for establishing and implementing language policies, such as the Council of Europe. The S2 R Model assumes that the organization of strategies could, in fact, be simplified to include four main categories of strategies, that is, cognitive, motivational, social, and affective strategies, corresponding to three relevant meta- categories. Initially considered by Oxford (2011) to be a subcategory of affective strategies, motivational strategies were distinguished as a separate group in Oxford’s (2017) most recent taxonomy. The S2 R model constitutes a response to the appeals for treating the language learner holistically, and consequently, the division of strategies is functional, so as to account for each aspect of the human being. Each dimension of strategies is “supervised” by the relevant meta- dimension built of eight strategies which empower learners so that they become in charge of their learning process. As Oxford (2017) explains, “(m)etastrategies, by virtue of their executive-control and management function, help the learner know whether and how to deploy a given strategy and aid in determining whether the strategy is working or has worked as intended” (p. 146). According to Oxford (2017), metastrategies include: . paying attention, for instance, noticing the markers of politeness in L2; . planning, for example, arranging to study at home; . organizing learning and obtaining resources, for instance, through using dictionaries to find additional information on encountered L2 structures; . monitoring and evaluating, for example, checking one’s own understanding while reading a piece of text. According to Oxford (2011, 2017), cognitive LLS are believed to support memory processes, such as remembering and processing information as well as facilitating the application of newly acquired knowledge. They include: . using senses to understand and remember, such as, for example, analyzing visual clues that accompany texts or recordings; . activating knowledge, for instance, brainstorming specific vocabulary; . reasoning, for example, through making deductions about L2 grammar rules; . conceptualizing with details, for example, breaking complex words into smaller components; . conceptualizing broadly, by, for instance, drawing semantic maps; . going beyond the immediate data, by, for example, using headings or topic sentences in reading comprehension. Oxford first S2 R Model (2011) proposes a distinction between two general strategy sets in the affective domain: activating supportive emotions, beliefs, and attitudes, and motivational strategies, later considered a separate category of LLS. The affective category is expanded upon in Oxford’s most recent version of the S2 R Model (2017) by including five additional families of emotional self-regulation strategies, initially introduced by Gross (2014). Oxford (2011) points out that that activating supportive emotions might also be manifested through providing oneself with encouragement,

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such as self-talk, before performing a language task. Ultimately, Oxford (2017) lists the following strategy sets, believed to help learners deal with emotions and optimize their beliefs and attitudes, and, in the long run, maintain their motivation to learn, under the affective label: . selecting the situation to influence emotions, such as, for example, avoiding unpleasant classmates; . modifying external situations to control emotions, by, for example, using and manipulating objects so as to encourage positive emotions; . deploying attention to control emotions, by, for instance, managing distractions; . changing cognitive appraisals of situations to shape emotions by modifying one’s own judgement of pace, progress, or achievements in learning L2; . modulating emotional responses, by, for example, attempting to relax; . making meaning as a means of handling emotions through valuing positive experiences in L2 learning. According to Oxford (2017), the three LLS in the sociocultural-interactive domain include: . interacting to learn and communicate, such as, for example, studying for tests in pairs or groups; . overcoming knowledge gaps in communicating, such as, for example, using circumlocutions in presentations; . dealing with sociocultural contexts and identities, such as, for instance, figuring out the expected amount of silence in turn taking. In short, the sociocultural-interactive dimension of LLS corresponds to two categories previously distinguished by Oxford (1989a, 1989b, 1990), namely, compensation, and social strategies. The decision to conflate them into a single dimension seems legitimate as compensating for missing elements of the TL frequently takes place during interaction with other L2 users. Furthermore, sociocultural-interactive strategies are expected to assist learners in their attempts to make use of the target language in various contexts, but also to facilitate the use of the language whenever the learners’ level of competence is not sufficient to allow satisfactory expression. Also, learners might resort to this category when encountering temporary problems, such as not being able to remember a word or expression which they need to use. Finally, as Oxford (2011) suggests, some learners actually like studying together, and hence might typically choose to prepare for a test in pairs or even groups. Motivational LLS constitute the final functional category distinguished by Oxford (2011, 2017), who describes them as entailing the learner’s self-regulation of motivation and volition and lists the following motivational strategy sets: . self-consequating, by, for instance, implementing a system of punishments and rewards for oneself; . using positive self-talk and positive self-image, such as preparation for delivering a presentation in L2;

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. using defensive pessimism, by, for example, providing oneself with the explanation that it is impossible to do well; . enhancing learning, for instance, through making learning a play or a game; . controlling attributions, such as, for example, not accepting blame for uncontrollable factors that cause failure. To summarize, Oxford’s (2011, 2017) classifications of LLS constitute interesting alternatives not only to her earlier taxonomies (1986, 1989a, 1989b, 1990), but also to other categorizations of LLS. The employed nomenclature remains general enough to classify particular tactics into one of the labelled categories of strategies. Moreover, the taxonomy is set in a theoretical and systematic framework, which, on the one hand, reflects the contemporary expectation to recognize the complexity of the learner, but, on the other hand, makes it possible to incorporate such concepts as strategy chains or task-specificity, and does not deprive strategy researchers of the option to analyze strategies across skills or other variables. Perhaps most importantly, the “old” categories suggested by Oxford (1986, 1989a, 1989b, 1990) easily fit in with the new labels, which certainly facilitates comparisons across strategy studies conducted at different times. It could be concluded that strategy researchers are aware of the lack of consensus regarding not merely the definition of LLS, but also their organization across skills, functions, skills, subsystems, or even various groups of learners. Responding to this problem, Griffiths (2013) recommends avoiding existing strategy classifications and insists on grouping strategies based on the data gathered in a particular study. Such a proposal, although it is methodologically grounded, does not constitute a systematic solution, and it seems that a general expectation exists that researchers devise a more consistent set of categories that could be applied more widely (Griffiths & Oxford, 2014). Indeed, the issue of the subjectivity of strategy categories has been explored for a long time. For example, Oxford and Cohen (1992) address this issue and attributed it to a variety of epistemological beliefs and diverse inclinations of strategy researchers. To illustrate this point, Oxford and Cohen (1992) provide three examples of LLS which may be classified in different ways: . asking questions for clarification or verification, which various researchers classify as either a social or cognitive strategy; . monitoring one’s errors, which may be regarded as a cognitive or metacognitive strategy; . seeking practice opportunities, which is believed to be as a metacognitive or social strategy. More recently, a tendency has emerged among strategy researchers to avoid divisions of LLS into clear-cut categories. Supporters of the tendency include Griffiths (2013), Oxford (2017), and Cohen (2014), who seem to agree that rigid classification frameworks may impede a full understanding of the strategy construct, as they are likely to fail to account for multiple functions of LLS. Domain-specific classifications referring to specific L2 skills and subsystems or aspects of L2 learning such as learning its culture, may, indeed, constitute a valid alternative, since they are much

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more likely to account for “distinctive strategies and constellations thereof that aid the mastery of each domain, with the effect that it may become impossible to devise successful strategic intervention” (Pawlak, 2021, p. 824).

2.5 LLS and the Concept of Self-regulation The present section constitutes an attempt to account for self-regulation (SR) processes which guide language learners and relate them to LLS. First, a brief definitional description of SR is provided from the perspective of the model of limited resources (Baumeister & Alquist, 2009), and the distinction between SR and selfcontrol (SC) is explained. Second, a number of psychological perspectives on the phenomenon are presented, which can be grouped into four categories, suggested by Forgas et al. (2009), including motivational processes, goal-oriented behavior, affective and cognitive processes, and, finally, social and interpersonal processes. Third, an attempt is made to account for self-regulated learning (SRL) from a theoretical perspective, and some leading frameworks for SRL are elaborated on, which is followed by a review of studies into SRL. Finally, self-regulated language learning (SRLL) is discussed, which involves a presentation of SRLL models and a synthesis of selected research findings.

2.5.1 Theoretical Assumptions and Models of Self-regulated Learning (SRL) One major reason for educational researchers’ interest in SR is the assumption that it positively affects academic performance. According to Baumeister and Alquist (2009): (1) trait self-control significantly predicts grade-point average (GPA); (2) trait self-control is a better predictor of GPA than IQ; (3) individuals characterized by relatively high levels of SR could be expected to have fewer absences at school or university, choose more competitive programs of studies, and dedicate more time to homework while spending less time watching TV. The present section aims to provide support for these assertions by addressing relevant empirical investigations. Prior to that, however, the relevant theoretical background is provided in order to consider SRL as a scientific construct. Schunk and Zimmerman (1994) define self-regulation as “the process whereby students activate and sustain cognitions, behaviors, and affects, which are systematically oriented toward attainment of their goals” (p. 309). Although the definition might not seem complex, approaching self-regulation remains a challenging task at the explanatory

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level. A number of models have been created in order to account for the complexity of the notion. Boekaerts (1997) assumes that two types of SR could be distinguished: cognitive SR and motivational SR. According to the researcher, cognitive SR involves the use of cognitive regulatory strategies on the part of the learner, such as creating mental representations of learning goals, designing action plans, or monitoring one’s progress goal achievement. By contrast, motivational SR involves the use of motivational regulatory strategies, such as creating mental representations of one’s own behavioral intentions, linking intentions to action plans, being persistent in implementing and pursuing these plans in spite of potential problems, as well as disengaging action plans and behavioral intentions. Cognitive regulatory strategies empower the learner to orchestrate the use of cognitive strategies, such as paying attention selectively, decoding, rehearsing, elaborating, structuring, thinking of questions, activating and applying rules, uptake, and repair in case of making mistakes, and finally, proceduralizing skills. On the other hand, motivational strategies orchestrated by motivational regulatory strategies include creating the learning intention in the learner, managing one’s negative emotions and limiting the stressors in learning, applying prospective and retrospective attributions, or even limiting effort. Both types of strategies are connected to domain-specific knowledge, involving conceptual and procedural knowledge in the content domain as well as metacognitive knowledge shaped by motivational beliefs. Boekaerts (1997) specifically insists on considering metacognitive knowledge as a learner’s prior knowledge, which is viewed as one of the basic components of SR, allowing comprehension, monitoring, and assessment of both conceptual and procedural knowledge of a given domain. Focusing particularly on goal orientation, the framework proposed by Pintrich (2000) is based on several important assumptions. Firstly, according to the cognitive perspective on SRL, learners are believed to actively construct goals and meanings, and choose strategies employed to attain them. Secondly, they are also expected to be able to monitor, control and, moreover, regulate, at least some aspects of their own cognition, motivation, and behavior. Thirdly, the framework presumes the existence of certain goals, criteria, or standards, which are considered as desirable by learners. Finally, self-regulated activities are considered to be mediators between learners’ IDs and contextual characteristics. A comprehensive model based on the four above assumptions assumes that SRL can be analyzed in four phases, including (1) Forethought, planning, and activation, (2) Monitoring, (3) Control, and (4) Reaction and reflection. Four areas of affect/motivation, behavior, cognition, and context need to be considered at each of the above stages.7 Specifically, in Phase 1, goals are adopted, and tasks are planned along with the dedicated time and effort necessary for their accomplishment. Judgements are made about self-efficacy, task difficulty, and task value. Phase 2 involves monitoring cognition, motivation, and affect, as well as any changes in the context of task conditions, and requires self-observation. Phase 3 consists in the 7

These areas bear a close resemblance to the ABCDs of personality, which include affects, cognitions, behaviors, and desires (Wilt & Revelle, 2017), and are discussed in Chap. 1.

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selection of relevant cognitive and motivational strategies, and effort management, as well as introducing any necessary amendments to the pursued tasks. Finally, Phase 4 comprises making judgements regarding learners’ own cognitive abilities, affective reactions, behavior, task, and context for its completion, and forming relevant attributions. The universal character of the presented model can certainly be regarded as its advantage. Moreover, the model also constitutes a valid attempt to account for the interplay between the contextual characteristics of the task, and the learner IDs, thus allowing for the inclusion of learners’ strategic knowledge and learning strategy skills as well as other variables that significantly impact learning and achievement in considering SRL. Referring to the way that information is acquired and organized by learners, Weinstein et al. (2000) argue that learning strategies can be applied to various types of tasks, both simple ones, such as memorization, and more complex ones, such as those involving conceptual learning. Depending on the perceived complexity of the task, learners might resort to different strategies, such as rehearsal strategies, elaboration strategies, organizational strategies, affective strategies, and support strategies. More recent definitions of SRL remain consistent with the already discussed ones. For example, according Kostons et al. (2012), SRL is “an active, constructive process in which learners plan, monitor, and control their own learning process” that “can occur at different levels, from learners controlling how they engage in studying a given task or whether they want to restudy it (…) to learners controlling what information they want to study” (p. 1). SRL can also be conceptualized in terms of three processes, namely, goal setting, goal operating, and goal monitoring. Importantly, implicit theories of SR could be valid predictors of distinct self-regulatory processes, and therefore, also of goal achievement, while incremental theories could serve as significant predictors of goal setting (operationalized as performance and learning goals), goal operating (both helpless- and mastery-oriented strategies), and goal monitoring (expectations versus negative emotions) (cf. Burnette et al., 2013). Finally, it should be pointed out that the contemporary SR models, such as the one proposed by Zimmerman and Kitsantas (2014), have often considered SR as referring to processes in the cognitive, emotional, and behavioral sphere, which are also the frequently addressed dimensions of SR in L2 learning (Dörnyei & Ryan, 2015; Gregersen & MacIntyre, 2014; Oxford, 2011, 2017).

2.5.2 Selected Studies Investigating SRL Since the present book focuses on the relationships between personality traits and LLS employed by university students and given the fact that SR in learning develops relatively late (cf. Bruin & van Gog, 2012), the scope of the overview is limited

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to studies investigating SR in the case of adults and adolescents.8 At the same time, investigations of SR require references to earlier developmental stages, since evidence exists that SR largely depends on early attachment experiences (see Drake et al., 2014). A number of researchers have emphasized the crucial role of goal orientation in SRL. Studies conducted by Pintrich and Van De Groot (1990), and Pintrich and Garcia (1991) indicated that students who developed mastery orientation used cognitive strategies, such as elaboration, and organization, relatively more frequently, and were more likely to process information more deeply than those who failed to develop such orientation. Similarly, the study undertaken by Wolters (1999) proved that goal orientation was the strongest predictor of cognitive strategy use (explaining 25% of variance) and regulatory strategy use (accounting for 35% of variance in selfregulation). Thiede et al. (2003) conducted a study of the impact of metacognitive monitoring on the comprehension and learning of texts in a group of 66 psychology students. It was found that SR could be enhanced by simply asking students to generate key words before testing them on reading comprehension. Also, those students required to generate key words were able to select pieces to re-read more accurately. The best results concerning both SR and ultimate reading comprehension test scores were obtained by the group in which generating key words was delayed by reading other, irrelevant texts. In a longitudinal experiment, Sitzman and Ely (2010) aimed to link prompting SR to learning outcomes and attrition from training. Involving a sample of 479 adults participating in a voluntary Microsoft Excel course consisting of four consecutive modules, each finishing with a multiple choice test, the study proved that prompting SR through asking questions (continuous or delayed prompts) increased learning, reduced attrition, and overall, exerted a more powerful influence on a subsequent self-regulatory activity than performance in a previous activity. Also, delayed and continuous prompting resulted in participants’ allocation of greater amounts of time on task. At the same time, continuous prompts were efficient in maintaining a relatively high level of SR irrespective of trainees’ performance in a previous module. Overall, attrition turned out to be significantly lower among trainees who were continuously reminded to reflect on their learning, and the effect of prompting SR on learning was exclusively mediated by the amount of time trainees spent on task. A study of 148 college graduates was undertaken by Strunk and Steele (2011) in order to investigate the relationships between SR, self-handicapping, and procrastination. The instruments used in the study included two scales of the Motivated Strategies for Learning Questionnaire, developed by Pintrich and De Groot (1990): the self-regulation and the self-handicapping subscales. SR was found to be a statistically significant predictor of academic procrastination and at the same time it solely

8

It needs to be granted, though, that de Bruin and van Gog (2012) also claim that “(w)hen metacognitive instruction takes into account a number of design principles, accuracy of metacognitive processes in children can equal that of adults” (p. 45).

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explained the variation in self-efficacy.9 Although some overlap was uncovered between SR and self-handicapping, the researchers suggested that both constructs could be applied in studies explaining procrastination. At the same time, no significant differences were found across genders on any investigated variables. Pieschl et al. (2012) assessed the monitoring and SR in a group of 119 undergraduate college students. The participants were asked to complete a task-specific questionnaire and their learning behavior was observed in the hypertext learning environment on genetic fingerprinting by means of log-file analysis. The researchers concluded that although the participants’ behavior implied the adaptation of efficient learning strategies for three tasks of various level of difficulty, their log files indicated better adaptation to task demands than the self-reported measures. Also, it was suggested that a certain degree of dissociation might exist between explicit reflection and direct indicators of monitoring and SR. Kostons et al. (2012) carried out two experiments in groups of 80 and 90 secondary school students. Seeking to evaluate the effects of observing modelled self-assessment and task selection on the development of language skills, the researchers also found out that improvement in self-assessment and task selection skills could enhance the effectiveness of self-regulated learning. Participants learnt about heredity, did a pre-test and post-test on relevant problems, rated their mental effort according to a scale developed by Paas (1993), engaged in self-assessment, which was later confronted with their test scores in both, the pre-test and the posttest, and selected upcoming tasks, which differed in complexity and level of support. As regards self-assessment, it turned out that participants who were given a chance to observe self-assessment modelling examples and task-selection modelling examples displayed significantly better self-assessment accuracy. At the same time, no statistically significant differences were found between the two groups exposed to the two different ways of modelling. The results of the study demonstrated that both self-assessment and task selection skills could be trained, either through modelling or through explanations and practice. The findings also indicated that self-regulated learning could, indeed, be developed through training. Zimmerman and Kitsantas (2014) set out to investigate the relationships between 507 high school students’ self-discipline, SR, and their academic achievement, operationalized as GPA and Virginia Standards of Learning (VSOL), categorizing scores into three main levels: pass advanced, pass proficient, and fail. Their study involved the application of a multi-method, multi-source array of questionnaires. Self-discipline was measured by the scales previously used by Duckworth and Seligman (2005, 2006) to assess the construct, and the Eysenck Junior Questionnaire Impulsivity Subscale (Eysenck et al., 1984), while the measurement of selfregulation relied on the Self-control Rating Scale (Tangney et al., 2004). SR was assessed by means of the Motivated Strategies for Learning Questionnaire (MLSQ; Pintrich, 1991), the Self-Efficacy Learning Form (SELF; Zimmerman & Kitsantas, 2007), and the Perceived Responsibility for Learning Scale (PRLS; Zimmerman & 9

Strunk and Steele (2011) therefore advocated for using the term self-efficacy for self-regulation, as earlier suggested by Klassen et al. (2008).

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Kitsantas, 2005). According to the results of hierarchical regression, the combined composite of SD and SR accounted for more than 69% of variance in GPA, and the inclusion of SD as an independent variable improved the prediction by 5%. When tested separately, SD only accounted for 10% of GPA variance. The two composites also accounted for 42% of VSOL variance. Confirmatory factor analysis proved that the two variables, although moderately correlated, loaded on two separate factors rather than one, common latent factor. Lauriola et al. (2015) investigated the relationships between SR and epistemic curiosity (EC), which they measured applying the interest (I) and deprivation (D) subscales, both of them consisting of 5 items on a four-point trait scale, developed by Litman and Mussel (2013). Two studies were conducted in groups of 151 Italians (group 1) and 218 Americans and 56 Germans (group 2). Seeking to trace the monitoring and control processes that accompany individuals in their attempts to achieve higher levels of knowledge and proficiency, the researchers also applied several instruments designed to measure SR: the Emotion Regulation Questionnaire (ERQ; Balzarotti et al., 2010), the Elaboration on Potential Outcomes Scale (EPO; Nenkov et al., 2008), and a scale to assess participants’ risk-taking behavior (RT-18; De Haan et al., 2011). All questionnaires were administered in participants’ native languages. The results of the first study indicated that D-type EC significantly correlated with expressive suppression and generation/evaluation constituents of emotion regulation, while no significant relationship was detected with regard to I-type EC. Instead, I-type EC correlated significantly with positive focus on results, which made the researchers conclude that I-type EC involves being optimistic about making discoveries. In the second study, I-type EC correlated positively with fun seeking, which was interpreted as a proof of the importance of searching for joy in learning. At the same time, impulse control and punishment sensitivity were found to significantly influence D-type EC, which was interpreted as evidence that moderately intense emotional states are favorable for concentration and prolonged intellectual activity. Finally, insights into the kind of processing that is involved in self-regulated learning were provided by Winne (2011, 2018). Since it is generally accepted that it is deep processing that ensures greater knowledge gains and makes knowledge sustainable, the researcher decided to employ the levels-sensitive approach in his investigations of self-regulated learning. Winne’s (2018) model assumes that selfregulated learning consists of four phases, including surveying task conditions, setting goals and planning, engaging in the task, and designing adaptations for subsequent tasks. The main implication from Winne’s considerations was that selfregulated learning should not be automatically classified as deep processing. Instead, according to Winne (2018), “it is processing more complex—deeper—information about a different topic, namely processes for learning” (p. 9).

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2.5.3 Self-regulated Language Learning (SRLL) Although it is difficult to deny that research into LLS has contributed to advances in L2 education, as was already mentioned in the present chapter, studies of LLS have received considerable criticism due to the alleged insufficient reliability and validity, and the purported definitional and classificational fuzziness of LLS as a scientific construct (cf. Dörnyei, 2005; Dörnyei & Ryan, 2015; Skehan, 1989). Apart from numerous efforts to bring order into the realm of LLS, which have produced even more definitions and classifications, attempts have been made to reshape the concept of a strategic language learner, and account for strategy use in the context of SR. One example of such an attempt is the construction of a framework for motivational strategies by Dörnyei (2001). According to Dörnyei (2001), the five major classes of self-motivating strategies include: . commitment control strategies, assisting learners in the pursuit of their original goal, such as thinking of positive outcomes, incentives, or rewards, or anticipating the consequences of failure in goal attainment; . metacognitive control strategies, employed by learners in order to handle concentration issues, such as procrastination or distractors, such as, for instance, getting rid of disturbing classmates; . satiation control strategies, applied by learners in order to fight boredom and add excitement to the learning task, such as changing the characters in a role-play; . emotion control strategies, assisting learners in managing their moods and, emotions as well as managing disruptive emotional states, such as engaging in breathing exercises, yoga, or resorting to relaxing visualizations; . environmental control strategies, employed to dispose of unwelcome environmental influences and make the best possible use of positive environmental settings, such as choosing an air-conditioned library to study rather than a hot room. A number of researchers claim that Dörnyei’s (2005) model of SR and the learning strategy use models should not be treated as incompatible since they allow us to account for two various aspects of L2 learning. This point of view is supported by Gao (2007), according to whom, the apparently contradictory models could in fact allow researchers to address two aspects of language learning: SR could be compared to the initial driving forces while strategy use would then represent the outcome of their operation. Other LLS experts, such as Rose (2012), even point out that the model of motivation control could be subject to similar definitional fuzziness and insufficient theoretical base as the formerly criticized functional classifications of LLS. They also argue that discarding the LLS construct might be compared to throwing LLS out of the bathwater, thus implying that research into L2 learning would suffer if efforts to investigate LLS were to cease. It is therefore surprising that some papers which discuss the relationships between LLS and SR advocate replacing the strategy framework with the SR framework. In the Rose’s (2012) view, such a shift of focus could only result in an incomplete picture of L2 learning. At the same time, research

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into LLS, both within the “old” and the “new” paradigm, continues to yield results which are useful and inspiring for everyday teaching and learning practice in the area of FLL (Pawlak, 2021; Pawlak & Oxford, 2018; Przybył & Urba´nska, 2020; Rose et al., 2018). It needs to be emphasized that SRLL involves the development, use as well as successful management and adaptation of LLS. In order to illustrate the connection, Oxford (2017) refers to numerous examples of both theoretical and empirical investigations, such as the works of Zimmerman and Martinez-Pons’s (1986), who elaborated on the use of self-regulated learning strategies by successful students, or Winne and Perry’s (2000), who investigated the way that self-regulated students addressed potential problems in the learning process. Introduced by Oxford (2011), the Strategic Self-Regulation (S2 R) Model for Language Learning constitutes a bridge between studies of SR in psychology, including the domain-specific findings of educational psychologists referred to earlier in the present chapter, and studies into LLS, carried out by language educators and applied linguists, and discussed in Sects. 2.1, 2.2, and 2.3. However, central to the model is the modified definition of LLS in which Oxford (2017, p. 79) aims to identify the prototypical factors of strategies: L2 learning strategies are complex, dynamic thoughts and actions, selected and used by learners with some degree of consciousness in specific contexts in order to regulate multiple aspects of themselves (such as cognitive, emotional, and social) for the purpose of (a) accomplishing language tasks; (b) improving language performance or use; and/or (c) enhancing long-term proficiency. Strategies are mentally guided but may also have physical and therefore observable manifestations. Learners often use strategies flexibly and creatively; combine them in various ways, such as strategy clusters or strategy chains; and orchestrate them to meet learning needs. Strategies are teachable. Learners in their contexts decide which strategies to use. Appropriateness of strategies depends on multiple personal and contextual factors.

The relevance of strategies to SRL can specifically be inferred from their features, elaborated on by Oxford (2011) and discussed in Sect. 2.3.2 of the present chapter. The organization of the model is simplified since each strategy category is accompanied by a parallel set of metastrategies. Oxford (2017) emphasizes that these sets do not vary between each other, but obviously the strategies are dimension-specific. Basically, the distinction between strategies and metastrategies consists in the supervisory function of the latter. Oxford (2011, p. 14) describes them as “crucial mental processes or tools” employed by language learners in order to control and manage the use of strategies from each strategy dimension. Referred to as executive functions, the metastrategies are described by Oxford (2017, p. 218) as supporting the learner in choosing whether or not to use a particular strategy and evaluating its performance through paying attention, planning, organizing learning and obtaining resources, and monitoring and evaluating. It is also explicitly asserted by Oxford (2011, 2017) that metastrategies can only be successfully set in motion after a learner has accessed his or her metaknowledge. Originally defined by Oxford (2011, p. 289) as “knowledge underlying the use of metastrategies that enables a learner to learn more effectively”, the concept can be analyzed with resect to six dimensions Oxford (2011, 2017):

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. person knowledge, involving the understanding of the characteristics of language learners, such as their preferred learning and cognitive style, elements of SWOT analysis, as well as learning goals; . group or culture knowledge, that is, learners’ awareness of the cultural norms and expectations in both their L1 and L2 culture; . task knowledge, consisting in the right understanding of the demands imposed by a given language learning task; . whole-process knowledge, going beyond the above and concerning learners’ interest in L2 learning success, which requires thinking about future aims and outcomes; . strategy knowledge, regarding learners’ familiarity with LLS, and involving both direct and indirect strategies; . conditional knowledge, which orchestrates the application of all other five types of metaknowledge, thus enabling learners to use all the previous types of knowledge (in other words, enables the learner to use the previous types of knowledge). Equipped with necessary metaknowlege, and making efficient use of LLS, a self-regulated language learner is thus likely to develop a range of useful qualities, including, as suggested by Oxford (2011, 2017), focus on learning goals by controlling different aspects of learning, ability to regulate their own cognitive and affective states, as well as observable behavior, and learning conditions, control over one’s learning beliefs, ability to link elements of declarative knowledge to procedural (automatic) knowledge, ability to choose between a number of strategies on the basis of their appropriateness regarding their goals, needs, context, learning styles and other individual variables, resistance to overreliance on a single strategy in various contexts, awareness of the relationships between strategy use and performance and language learning success, self-efficacy, and a greater overall sense of agency and autonomy. To summarize, as advocated by Oxford (2011, pp. 40–41), the S2 R model attempts to synthesize the findings of three scientific traditions within which research into LLS has been conducted, that is, the psychological, social-cognitive, and sociocultural tradition. It caters for an appropriate balance between the above dimensions, not showing preference of any of them and widens the meta- dimension of strategic competence by not limiting it to metacognition (metastrategies may be accessed at different levels, that is, the task level, and the whole-process level). It also distinguishes between deep processing and surface strategies, postulating the special role of deep processing, exhibits potential for ordinary, and crisis-like situations for using LLS, recognizes the findings of neuroscience, and includes references to a number of techniques for strategy development and assessment. Last, but not least, it is not overwhelmingly complex, comprising 19 strategies in total, but at the same time allows for in-depth analysis of strategy use at the level of particular tactics, and presents strategy chains. The complex relationships between the constructs of learner autonomy, agency and SRL certainly require an explanation. According to Oxford (2017), while each of these constructs is volitional in nature, agency and autonomy are relatively

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general notions, whereas accounts of SR focus into a greater extent on more specific processes. On the one hand, without the sense of agency, language learners are unlikely to employ any LLS or initiate any goal-oriented actions, but, on the other hand, as pointed out by Williams et al. (2015), strategic knowledge is one of the pillars of agency. Also, a number of researchers, such as Wenden (1991), Cotterall (1995), Oxford (1999), Micho´nska-Stadnik (2008), and Griffiths (2013) view LLS as an important element of learner autonomy. At the same time, it also remains true that, as pointed out by Oxford (2003), whereas autonomy results in strategy use, autonomy also capitalizes on strategy use. In order to account for the relationships among learner autonomy, strategy use, and SRL Oxford (1999, 2011, 2017) employed Vygotsky’s (1978, 1986) zone of proximal development theory. In Oxford’s (1999) view, the aim of learning consists in the creation of “an independent, self-regulated, problem-solving individual” (p. 111), and the process needs the support of “the more capable others”, described by Vygotsky (1978, 1986) as “scaffolding”. Such scaffolding assists learners in transition through their ZPD, which is a representation of the distance between what a learner knows and can do unsupported and what he or she could achieve once provided with adequate support. Of course, this transition can be enhanced by efficient strategy use.

2.5.4 Empirical Investigations of SRLL There are quite a few studies that have attempted to explore self-regulation in L2 learning. On the basis of Zimmerman’s (2002) self-regulation model, Studenska (2011) developed the Foreign Language Learning Self-regulation Difficulty Inventory (FLLSDI) to measure SR difficulty reported with regard to three basic stages of learning: planning, performing, and evaluation. Conducted in a group of 380 Polish learners of English as a foreign language, Studenska’s (2011) study was designed to investigate differences in SR difficulty in learning English as a foreign language across genders and educational levels (primary/lower-secondary/upper-secondary). Principal component analysis allowed identification of four aspects of SR, reflecting the four scales of the FLLSDI, that is (1) difficulty in choosing goals, ways, and conditions for learning, (2) difficulty in planning, organizing, and implementing learning, (3) difficulty in motivational and emotional control, and (4) difficulty in reflecting and making changes. Significant main effects were detected for gender regarding three dependent variables: general foreign language learning self-regulation difficulty (a combination of the four above scales), as well as scales (3) and (4) mentioned above. Specifically, the female participants were found to experience less difficulty in planning; however, when analyzed separately for each educational level, the differences only proved significant for primary and lower secondary school students. Evaluation of difficulties in self-regulated learning behavior also differed across genders as twelve types of behavior were ranked more difficult by the male participants of the study. Specifically, men found devoting time for independent learning, looking for people and materials that could help, planning learning in distant future, using

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various ways of learning, putting learning plans into practice (scale 2), increasing one’s willingness to learn, continuing learning instead of engaging in more pleasant activities, avoiding distracters, taking advantage of one’s dispositions (scale 3), and making changes to learning when necessary, identifying causes in one’s learning results (scale 4) significantly more difficult than women. Also, the impact of the educational level on planning, organizing, and implementing learning turned out to be significant, with a growing, linear trend being observed from primary to upper secondary school. Sampson (2012) made a number of suggestions on how to foster SR in the language learning classroom after investigating the relationship between learners’ self-images, socially-possible self-images, and language learning motivation during a 15-week course of English. The participants of the study included 34 female Japanese students at the Faculty of International Communication. The study was grounded in the view of motivation in terms of the framework by Dörnyei and Ushioda’s (2009) motivational self system, and thus involved the ideal L2 self, the ought-to L2 self, and L2 learning Experience. Three major research questions were considered while the three-cycle action research took place: (1) Whether collecting information about learners’ visions of their L2-selves would facilitate the development of more motivating lessons, (2) What self-conception-building lesson elements might motivate students, and (3) How do the participants perceive the change in their L2-self-image. Data was collected from a free-writing task in which the participants described the best possible Englishself, learning journal entries preceded with prior instruction, and after participating in activities expected to foster goal achievement strategies. Overall, on conducting qualitative analysis of participants’ expectations and reflections, Sampson (2012) came to the conclusion that the evolution of the L2-self enhanced a more self-centered approach to learning English. Also, numerous connections between the learners’ ought-to selves and refined ideal-self-images were observed. Although the participants were representatives of a collectivist culture, they were able to provide comprehensive conceptualizations of the selves, and actively reflected on the effort required to meet their individual goals. It was inferred that ensuring a student-centered learning environment could, indeed, improve learners’ focus on their learning outcomes in general. A qualitative study of SR in learning the Japanese written characters, Kanji, was conducted by Rose and Harbon (2013). Twelve volunteers, students of Kanji courses at university, participated in a series of 10 interviews throughout the academic year. The interview questions were constructed on the basis of the study carried out by Tseng et al. (2006) and modified after an earlier pilot. Most of the topics which were selected for analysis corresponded to the five major classes of self-motivating strategies described by (Dörnyei, 2001); however, additional themes emerged, including goals, procrastination, boredom and interest, stress, and, finally, the learning environment. Participants’ SRL was assessed by the interviewers in order to present a synthetic picture of extremely well self-regulated learners, typical cases, and extremely low cases of self-regulation. Instruction in the Kanji classes was focused on character list learning rather than improving the overall reading process and classes

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did not assist students in developing their comprehension skills in reading authentic materials. Regarding commitment control and goal-setting challenges, goal attainment proved more difficult for relatively more advanced learners,10 which was due to the degree of difficulty of the set goal, and the amount of material to be studied. Moreover, the most advanced learners goal attainment was linked to both future education and future employment, which enhanced the overall pressure and stress. At the same time, the relatively less proficient learners concentrated on short-term and more easily manageable goals, whose attainment was only assessed in the classroom. A limited proportion of advanced Kanji learners attempted to handle commitment control through regular self-study tasks, which resulted in clearer goal management and increased confidence.11 Learners, especially the more advanced ones, also reported experiencing numerous negative emotions while pursuing their kanji learning goals, including frustration and defeatism, and had to deal with negative selfthoughts. Some of the most advanced learners even considered goal abandonment and changing their future career plans because of the experienced problems. Difficulties were also reported with reference to satiation control, as both increasing boredom and decreasing satisfaction were reported by the more proficient participants of the study. Some students were successful in dealing with satiation issues by employing the strategy of self-rewarding after completing smaller portions of tasks whereas in one case it was simultaneous participation in learning Kanji and physical exercise that helped the student overcome boredom. Also, boredom was successfully dealt with by altering environmental settings, which led Rose and Harbon (2013) to conclude that environmental control as such might not be a separate strategy, but a means to an end. On the basis of the findings, it was advocated that Kanji teachers should support students’ motivation not only through inclusion of more authentic materials in the classroom, but also through systematic support in self-regulation related problems, such as breaking learning goals into manageable tasks, indicating connections between the material learnt and the Japanese culture and everyday reality, reflecting on progress, and assisting students in taking emotional control of the learning process. Although based on the traditional LLS paradigm and strategy classification reflected in Oxford’s (1990) SILL ver. 7.0, the case study conducted by Véliz (2012) did manage to provide a number of interesting insights into SRLL, especially with regard to the interrelationships between motivation and strategy use. By conducting semi-structured interviews with two third-year students participating in teacher-training phonetics courses, the researcher aimed to verify whether both direct and indirect strategies resulted in pronunciation improvement, and investigated the strategies applied in pursuit of native-like accent, the extent to which the participants referred to formal instruction in the learning process, and, finally, the relevance of motivation in learners’ attempts to attain native-like accent. On the one hand,

10

The most advanced learners aimed to review and study between 1000 and 2000 Kanji characters. Rose and Harbon (2013) mention that similar conclusions were reached by Bandura and Schunk (1981) and Dörnyei (2001).

11

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certain similarities were observed, such as increased use of indirect strategies, especially metacognitive strategies, which served the purpose of centering, arranging, and planning learning. Specifically, the investigated individuals reported participating in a preparatory course or doing “pronunciation research,” which encompassed activities such as monolingual, and pronunciation dictionary use, but also looking for contextual use of words and phrases on YouTube. On the other hand, differences were observed regarding social strategy use, which was in fact mediated by learners’ personal characteristics in order to boost SRL. The learner who was more reserved and withdrawn at the thought of making contact with native speakers of English would not engage in practicing the language actively, whereas the learner who was more open and outgoing tended to look for opportunities to engage in conversations. Adopting appropriate indirect strategies did not merely result in a more effective application of direct strategies, such as creating mental images of new phonetic utterances, or engaging in routine practice tasks, such as repetition of new words and phrases, but also had a positive effect on learners’ motivation. Veliz (2012) concluded that a similar degree of autonomy was developed by both learners through the use of different, well-adjusted strategies and both of them benefited considerably from their positive perception of their educational attainment. Several attempts have been made to develop an instrument for SR measurement, both for selected aspects of language learning, such as vocabulary, and for SRLL in general. The Self-Regulating Capacity in English Language Learning (SRClang) was developed and examined with regard to its psychometric properties by Liu and Lee (2015). Over 500 high school students from East Asia completed the questionnaire in order to provide data on the instrument item-model fit, response category use, appropriateness for item difficulty level, reliability, and dimensionality. Based on the Self-Regulating Capacity in Vocabulary Learning (SRVoc) scale (Tseng et al., 2006), Liu and Lee’s (2015) questionnaire originally consisted of 27 items, three of which were subsequently removed due to their unsatisfactory fit to the model. The differences in the maximum and minimum values between person trait scores and item difficulties suggest that the scale might be not comprehensive enough to investigate extremely-well/poorly self-regulated learners. At the same time, the employed reliability measure, which was Pearson separation reliability estimate, indicated that the instrument could be used so as tool to differentiate between individuals. In turn, the analysis of goodness criteria for psychometric tests conducted for the instrument indicated that the developed items might not constitute a single dimension of selfregulation in L2 learning. In other words, creating an instrument to measure language learners’ overall SR remains one of the challenges that SR researchers still face. Ziegler (2015) investigated the efficiency of using the SRCVoc scale introduced by Tseng et al. (2006) in predicting learners’ motivational characteristics through the prism of SR. Conducted in a group of 572 Saxon learners of English (grades 4–9), his study revealed that whereas the SRCVoc significantly predicted all the scales of SRL measured by the MSLQ (Pintrich et al., 1991), effect sizes ranged from small for the three scales of test anxiety, control beliefs, and extrinsic goal orientation to medium for the scales of academic self-efficacy, intrinsic goal orientation, and task value. The study revealed that applying the SRCVoc did not produce overall satisfactory results

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with regard to measuring learners’ overall capacity for SRL. According to Ziegler (2015, p. 646), the questionnaire can serve as a “measure of the strategic behaviors characteristic of the performance phase of the self-regulated learning cycle”. In an attempt to explore self-regulated LLS employed by FLL in writing, Teng and Zhang (2016) developed and validated the Writing Strategies for Self-Regulated Learning Questionnaire (WSSRLQ) in order to provide insights into language learners’ cognitive and metacognitive processes, as well as their social and motivational behaviors. Their study was conducted in a group of 790 Chinese university students learning English as a foreign language, and involved three major phases: item generating, pilot study, and psychometric evaluation. The final version of the 7-point Likert scale questionnaire consisted of 40 items that were divided into 9 subscales: goal-oriented monitoring and evaluating (GME), idea planning (IP), peer learning (PL), feedback handling (FH), interest enhancement (IE), emotional control (EC), motivational self-talk (MST), text processing (TP), and course memory (CM). The results of confirmatory factor analysis indicated an acceptable model fit for the 40-item, 9-factor construct, with significant parameter estimates, robust reliability of each of the subscale, and statistically significant correlations between the subscales. In particular, goal-oriented monitoring and evaluating strategies were strongly correlated with peer learning and interest enhancement, which did not only confirm that LLS work in chains, as suggested by Oxford (2003), but also indicates that learners aware of the need to monitoring their task goals are also more likely to regulate their social behavior and manage their intrinsic motivation to control their involvement in L2 writing tasks. It was observed that the model of SR as a hierarchical construct built of 9 strategies produced the best fit. Also, the four strategies belonging to the realms of motivation and metacognition, that is, idea planning, goal-oriented monitoring and evaluating, motivational self-talk, and interest enhancement, had the largest loadings on SR, which proves the essential importance of planning and metacognition in the self-regulated development of writing skills in L2, and supports the sociocognitive view on the processes underlying SRL. Rose et al. (2018) conducted a systematic review of studies of LLS conducted after Tseng et al. (2006) appealed for replacing the traditional strategy paradigm with SR-based research. Designed to identify adaptations in strategy studies, the review also took into account the ways of theorizing LLS, research instruments, and the methodologies underlying the analyzed studies. Three major categories of studies were identified by Rose et al. (2018): . studies adopting SR and SRL as the construct essential to their research framework; . studies allowing contributions from SR, but still within the traditional strategy paradigm; . studies aimed to develop new instruments, and investigating the link between strategic learning and yet other theories. One of the advantages of the first category of studies, advocated by Dörnyei (2005), is that SR has already been a well-established construct in psychology, and adopting

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the paradigm would thus result in resorting to apparently more sophisticated or efficient tools of investigation framed within methodologies with a long-standing tradition. The second category of studies, certainly recognizing the tradition of strategy research, does not only manage to respond to methodological criticisms, but also shows promising areas for generating even more knowledge about the learner, such as investigating the context of strategy use and the importance of the language task. Also, studies such as that conducted by Ardasheva and Tretter (2013) have proved that empirical investigations based on Oxford’s (1990) SILL can still be successfully adapted and become valid, culturally-specific ways of analyzing strategic learning. Finally, there are many researchers who adopt Gao’s (2007) standpoint, according to which strategy and SR researchers explore different facets of the same process, and may prove to be of complimentary, rather than substitute nature. This has led to the emergence of hybrid models, such as Oxford’s (2011, 2017) S2 R model, which have already been used as foundations for new research instruments dedicated to the measurement of LLS use (cf. Habók & Magyar, 2018). In the concluding article to the special volume of Studies in Second Language Learning and Teaching, dedicated entirely to strategy research, Pawlak and Oxford (2018) discuss the potential directions of research into LLS, addressed the emerging methodological challenges of such research, and appeal for increasing its focus on pedagogical implications. They stress that both types of studies into LLS, those of quantitative nature, adopting a macro-perspective and involving large groups of learners, and those investigating the strategy use by individuals or in small groups of learners, could contribute profoundly to a better understanding of the intricate nature of LLS. They also lend support to earlier calls for taking a holistic view in LLS studies, exploring LLS use in specific learning situations, learning targets, and not in isolation from individual learner characteristics (Griffiths & Cansiz, 2015). Therefore, Pawlak and Oxford (2018) argue that future research should focus on strategy use in learning the culture of the target language, differences in strategy repertoires in the development of following foreign languages, and, finally, selfregulation in L2 learning. They also believe that looking into the well-established concept (LLS) from a new perspective (SR) could, in fact, shed new light on strategy use. Consequently, Pawlak and Oxford (2018) call for empirical studies that would provide insights into how strategy use contributes to the development of language learners’ SR, from the behavioral, emotional, and motivational perspective. At the same time, they criticize the idea of replacing the strategy research paradigm with the SR paradigm, and subscribe to the Gao’s (2007) standpoint, according to which researchers of LLS and SRLL investigate the same process from different angles.

2.6 Variables Affecting LLS Use As emphasized by Cohen (1998, 2014), the strategic character of L2 learners’ conscious choices in the process of L2 development could only pertain to the given learner who makes them. In an attempt to account for the idiosyncratic nature of LLS

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use, the present book aims to account for strategy application not merely from the microcontext perspective of strategy use, but also addresses the strategy user in a more systematic way through considering a number of possible influences of IDs of various origin and character in this respect. Since the construct of LLS is extremely broad and defies a clear-cut classification as either behavioral or cognitive (cf. Micho´nskaStadnik, 2008), it is necessary to capitalize on the insights provided from multiple perspectives. Although the factors influencing learners’ strategic choices could be categorized as individual, group/population-specific, or contextual (cf. Cohen & Macaro, 2007; Oxford & Nyikos, 1989, Pawlak, 2011b), the considerations of the interactions between each of the analyzed IDs and strategy use in the present section do not reflect this organization. This notwithstanding, they attempt to elaborate on the complex network of relationships which build the macrocontext of strategy use. This involves the impact of such factors as, among others, the language being learnt, the language learning experience, IDs such as age, and gender. Moreover, strategy use can also be mediated by learners’ beliefs, learning styles or language aptitude. Certain implications arise from learning a TL in a specific L1 cultural background and instructional settings. Attention should also be paid to the importance of the microcontext of strategy use, that is, the language task, determining learners’ strategic choices. Finally, considerable variation in LLS use exists among learners who differ in terms of attainment. It could be argued that the context of strategy use can be analyzed from at least two various perspectives, including the micro- perspective of certain specific strategies employed in order to handle a specific language task, and the macro- perspective, in which case more general patterns are explored. The latter allows researchers to investigate the intricate relationships between LLS and other IDs, such as learning styles, motivation, language aptitude, or affective factors. These all are known to create bundles of factors which certainly influence strategy use (cf. Pawlak, 2021b; Pawlak & Oxford, 2018). In the words of Griffiths (2015, p. 432): We have learnt that strategies are important, and that successful learners have a large repertoire of different types of strategies that they use frequently. But strategies are not the whole answer, and the strategies that are chosen and which are effective depend on the context, the learning goal, and the learner’s own unique set of individual characteristics.

Indeed, in order to fully understand the choice and use of LLS, it is inevitable to pay attention to other aspects of individual variation among language learners. The interaction between LLS and other IDs has been addressed and investigated by strategy researchers since the early years of interest in strategy use. Rubin (1975) listed a number of IDs which she expected to influence the use of strategies, such as a learner’s age, the context of using the target language, individual learning styles, or cultural differences. Oxford and Nyikos (1989) provide a synthetic list of factors report by strategy researchers as essential determinants of learners’ strategic choices and categorize them as either learner variables or situational variables, while Pawlak (2011b) groups the factors affecting strategy choices and use under three major labels, including individual, contextual, and group variables. On the basis of the three proposals, the following list of variables mediating LLS use could be formulated:

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. . . . . . . . .

the language being learnt; language learning experience; national origin, culture, and instructional settings; age; gender; learners’ beliefs and attitudes12 ; learning styles; language aptitude; a number of motivational variables, including the dynamic changes in their motivational intensity, as well as their learning goals (also referred to as motivational orientation) and learners’ career orientation; . learners’ attainment; . specific requirements of the performed language tasks; . personality.13 Adopting the above list of factors influencing strategy use as a starting point, the following subsections seek to explore their connection to learners’ choice and use of LLS. The overview of theoretical standpoints is supplemented with examples of empirical investigations so as to provide evidence of how various IDs might impact learners’ selection and application of LLS. Given the fact that personality is the main focus of this book, it is discussed separately in Chap. 3.

2.6.1 The Language Learnt It seems obvious that the specificity of the TL exerts a powerful influence on the way it is learnt, as reported by Oxford and Nyikos (1989), Grenfell and Harris (1999), Pawlak (2011b), Grainger (2012), Oxford and Gkonou (2018). First of all, the availability of a given L2 to the learner can vary, even though globalization and the Internet make virtually all languages more accessible. Some languages, such as English, enjoy a more privileged (or dominant) position, and hence, the learner does not have to strenuously look for L2 input. Also, as pointed out by Harmer (2001), it is possible to learn an L2 in different settings, that is, in countries where the language is spoken as a first language, in countries where the language is spoken as a second, and sometimes also, official language, and, finally, in places where the language is recognized as important considering, for instance, its cultural or economic impact. Moreover, even in the specific case of learning English, essential differences exist regarding the accessibility of both educational and authentic materials comparing American, British, or 12

According to Oxford and Nyikos (1989), learners’ attitudes are, in fact, a composite of affective variables, which also include their personality. Since personality cannot really be analyzed in terms of an affective variable, regardless of the framework chosen in order to investigate it, it is considered as a separate factor. 13 Oxford and Nyikos (1989) distinguish between the so-called personality characteristics, or, longterm traits, and general personality types, measured by the MBTI (Myers & Briggs, 1976).

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Australian, and other resources, and the availability of dedicated learning resources is asymmetric, with the British ELT industry enjoying the dominant position on a number of European markets. Secondly, if a language learner makes an independent choice as to which L2 they want to study, their choice may be motivated not merely by practical or instrumental reasons, but also by their fondness of a certain culture which they associate the language with. For instance, one could prefer German rather than English because of their penchant for orderliness, Spanish or Italian because of the appeal of their prosodic features, and French or Latin because of their attraction to high culture. Consequently, learners willing to master different languages may favor different strategies, such as, for example, LLS that require planning and good organizational skills, participation in authentic communication with L2 speakers, or increasing the input by watching cultural programs or films in L2. Also, as indicated by Grenfell and Harris (1999), progression in reaching attainment targets by language learners depends on the type and form of the language being learnt, its style, degree of grammatical sophistication, the language learning content, familiarity with the TL, encompassing, among others, its relative degree of unpredictability and the possibility and/or need for improvisation, level of support possible to obtain from visual clues, cognates, gestures, or written clues. Clearly, these features can be accounted for in both interlingual and intra-lingual comparisons, and even related to the differences between learning a language as such and learning a language for specific purposes. Finally, accounting for the language learnt from a broad perspective also involves referring to the developmental stage of a particular L2 teaching methodology. In the case of certain languages, learning and teaching resources might be relatively scarce, the level of pedagogical competence of providers of materials and course instructors could be relatively lower, and, consequently, the range of available methods, techniques, and strategies to learn these languages, could be much narrower. Examples of studies referred to below are provided to illustrate the influence of the (chosen) TL on learners’ strategy repertoire and usage. According to the results of two studies reported by O’Malley and Chamot (1990), learners of Spanish and Russian use cognitive strategies slightly less often than learners of English. Conducted in groups of 70 EFL high school students, 67 highschool learners of Spanish, and 34 college students of Russian, the comparison across the language being learnt revealed that learners of Spanish and Russian also used metacognitive strategies relatively less frequently and hardly ever resorted to social or affective strategies. Some strategies, such as memorization of longer pieces of text, were only applied by the learners of Russian, confirming earlier findings reported by Chamot (1987), according to which learners of Russian demonstrated greater overall scope of strategy use than learners of Spanish. The results also lend support to the outcomes of Politzer’s (1983) study, comparing the learning behaviors in a group of 90 university students learning French, German, or Spanish as a foreign language, according to which learners of Spanish tended to engage in relatively fewer behaviors which were expected by the researcher to boost their overall learning attainment14 in 14

Politzer (1983) investigated three types of students’ self-reported behaviours, including general behaviours, classroom behaviours, and interactions with others.

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comparison to learners of French or German. Additionally, Politzer’s (1983) study demonstrated that learners of German and Spanish tended to be relatively more oriented towards social interaction and increasing their TL input. It needs to be pointed out that the identified differences in strategies could also have reflected differences in instructional practices. Schmidt and Watanabe’s (2001) comparative study conducted in a group of more than 2000 students of Mandarin Chinese, Tagalog Filipino, French, Japanese and Spanish revealed a number of ways in which L2 can affect LLS choice. The analysis of variance in learners’ motivation and strategy use across target languages proved that the investigated learners of Filipino were the most frequent strategy users, followed by learners of Spanish, while learners of Mandarin Chinese used strategies significantly less frequently than learners of the remaining languages. Regarding the use of particular strategy categories, the learners of French and Filipino were the most frequent users of cognitive strategies, which were relatively last frequently used by learners of Japanese. Social strategies were relatively more often used by learners of Filipino and Spanish, while being less popular with learners of Chinese. Students of Filipino also outperformed all other students in the use of strategies consisting in efficient use of study skills and coping strategies. Finally, from the motivational perspective, it turned out that the learners of Spanish were principally interested in satisfying the language requirements of the university curriculum. Thus, they were characterized by relatively lower intrinsic motivation and they reported to be less willing to participate actively in activities which required increased effort. Being the least frequent strategy users in Schmidt and Watanabe’s (2001) study, the learners of Mandarin Chinese were at the same time the most self-confident, they were the greatest believers in their own aptitude, and they were the least anxious, which can be linked to the reported personal, “heritage” link to Chinese. The learners of Japanese were similar with respect to their self-reported connection to the heritage language. At the same time, the learners of Japanese also acknowledged the difficulty of learning Kanji and had relatively low attainment-related expectations. This combination of characteristics had a number of implications for their learning behaviors, which generally reflected the traditional pedagogical focus on grammar, vocabulary, reading, and writing. Similar findings were revealed by Rose and Harbon (2013), who investigated the motivational strategies of kanji learners, a study that was described in more detail in the section dedicated to self-regulation in L2 learning. Finally, Schmidt and Watanabe (2001) also observed that the learners of Filipino exhibited both high social motivation, which allowed them to embrace innovative activities, such as using authentic materials, and made their learning more goal-oriented in general. Overall, this empirical investigation may serve as valid evidence that the TL itself can influence the choice and use of LLS.

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2.6.2 Language Learning Experience According to Wilczy´nska (1999), each time an act of learning happens, an individual pays attention to the new concept, manages to remember and comprehend it, reflects on it, and imagines it in his or her own, personalized context. Logically, increased length of exposure to both the TL and TL instruction is likely to boost the volume and diversity of learners’ strategy repertoire (Ehrman & Oxford, 1990; Oxford & Nyikos, 1989; Pawlak, 2011a). At the same time, the length of the L2 learning experience is likely to increase awareness of the efficiency of strategy use, thus perhaps limiting the range of the applied strategies to those that the learner regards as potent or useful (Williams et al., 2015). As pointed out by Wenden (1991), language learners gradually acquire strategic knowledge and make decisions which LLS they continue using, and which ones they abandon, thus developing a resource file on strategic knowledge. Additionally, they develop knowledge of linguistic tasks regarding the resources that are required for task completion and the possible ways in which a given task can be accomplished. According to Wenden (1991), L2 learners also develop a resource file on task knowledge, and even a resource file on the nature of communication. The threads of the relationships between LLS use and language learning experience are thus complex, as they are interwoven with the impact of learners’ increasing proficiency and instruction in strategy use. Leaver et al. (2005) explain it in the following way: Every so often, you should evaluate the learning strategies you are using. Some of them may be no longer useful because you have learned new ones or because you have reached a level of proficiency where they no longer help and you need to develop new ones. For example, at lower levels you may need to look up some words in a dictionary or guess their meaning from context. At higher levels, however, you might be able to figure out their meaning based on the meaning of their roots, your knowledge of word formation and/or comparison with vocabulary that you already know (p. 60).

Also, according to Williams et al. (2015), learners who have studied more than one L2 are likely to compare experiences across languages and form TL-specific self-concepts. Several studies have addressed the interplay between language learning experience and strategy repertoire. To start with, after investigating a group of 275 Turkish students of English with Oxford’s (1990) SILL (ver. 7.0), Uztosun (2014) arrived at a number of interesting conclusions regarding the links between learners’ educational backgrounds, their language learning experience, and strategy use. The participants of the study belonged to three categories: 38% attended preparatory (“year 0”) courses, 34% were first grade students, and 28% were second grade students. Overall, participants favored compensation, metacognitive, and social strategies, which lent support to previous findings concerning strategic preferences of Turkish students revealed by Yılmaz (2010). The most frequent strategies included paying attention to the interlocutor, asking the interlocutor to slow down/repeat, and using a different word/phrase with a similar meaning. Social strategies were used relatively more often by the least experienced learners, which could imply that the “year 0” students

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might require more assistance from course instructors in L2 learning—a conclusion also reached by Magogwe and Oliver (2007), who investigated the LLS of Batswana EFL. At the same time, limited dependence on cognitive strategies might be somewhat worrying, especially in a group of English majors. It also indicates that learners need more task-specific training in LLS use. Pawlak and Kiermasz (2018) conducted a study which provided a number of insights into the intrapersonal differences in strategy use with reference to L2 (English) and L3 (that is, Spanish, German, French, Italian, Russian, Dutch, and Polish), and the possibility of strategy transfer across different languages. Involving the use of a Polish adaptation of the SILL (Oxford, 1990) and a series of semistructured interviews, the study was designed to compare overall strategy use with regard to the languages in question and identify the dominant patterns in L2 and L3 strategies. Overall, the reported strategy use was significantly more frequent in L2 learning than in L3 learning. The differences were the most striking for memory, metacognitive, and social strategies, which were at the same time the only categories where strategy use could be interpreted as high for learning L2. Additionally, individual variation in strategy use was considerably higher in the case of L3, which confirms the essential role of individual learning experience in strategy use. The analysis of qualitative data confirmed the close relationship between learning experience and the level of proficiency. Differences in learners’ strategic choices reflected in the analysis of quantitative data were also attributed to the disparity of proficiency levels for L2 and L3. The strategies favored in L3 were associated with lower-level strategies, such as looking for cognates in L1, relying on gestures, or creating associations with images or sounds. Hence, it could be argued that the study also indicated that the interaction between strategy use and language learning experience could be mediated by the level of linguistic competence in any of the languages in question.

2.6.3 Cultural Variables It is hard to deny the impact of learners’ national origin and culture when analyzing the factors potentially influencing strategy choice. Firstly, as indicated by Pawlak (2011a), educational models differ across borders and hence learners are exposed to different kinds of instruction depending on the country where they receive education. Secondly, some cultures favor more individualistic behaviors while others, such as a great deal of Eastern countries, train the individual mainly to become a useful part of a society. This, in turn, may also result in some of their desires and needs being unattended to, and, possibly, some strategic choices being unrecognized, or, from a different perspective, never become familiar to the learners. It could also be argued that the instructional materials that language learners are exposed to reflect not only a certain philosophy of language as such or L2 learning, but also some underlying values. As pointed out by Canagarajah (1999), these values might stand in contrast to the learners’ own values and result in learners’ adaptation of strategies preventing them from feeling culturally or linguistically dominated, such as drawing

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pictures on the margins of the course books. Also, as observed by Oxford (1989a), the understanding of what language learning consists in differs across cultures and consequently so does the curriculum. The curriculum might or might not involve elements of strategy instruction, and the degree of emphasis on learner autonomy in it might differ considerably. For example, in the Australian, American and Central and Western European context, the conviction that strategy training could encourage the development of L2 skills is generally rather firm, a belief that has been expressed by a vast number of researchers, such as O’Malley and Chamot (1990), Grenfell and Harris (1999), Taylor et al. (2006) or Griffiths (2013, 2018). While according to some researchers, such as Hoff and Paige (2008), some LLS could not only be teachable, but also universal, and learners, once trained, could make use of them regardless of their cultural background, the odds are that in some countries L2 learners might never be exposed to them due to differences in instructional settings. In Poland, for instance, evaluation procedures might reflect some relatively old methodological assumptions, resulting in a bias in strategy use towards more traditional strategies, such as memorization or repetition, and a neglect of metacognitive, affective, social and more sophisticated cognitive strategies (cf. Przybył, 2016; Pawlak & Kiermasz, 2018). Overall, researchers seem to agree that learners’ identities need to be accounted for in studies of LLS and that LLS repertoire should be inclusive of strategies for cultural acclimatization, identity-stretching, or managing power relationships in different learning situations (cf. Lee & Oxford, 2008). At the same time, doubts have been raised whether learners’ L1 national culture and origin could be considered as strong predictors of strategy use. In fact, the studies conducted by Griffiths’s (2003) and Grainger (1997, 2012) indicate that learners’ culture should not be interpreted as a barrier to language learning. Early studies addressing the impact of learners’ nationality and cultural background on LLS use, such as those conducted by Politzer (1983), Politzer and McGroarty (1985), and O’Malley et al. (1985), indicate that rote learning and mnemonic strategies are typically favored by oriental learners as those learners might be less responsive to training, even if teacher-centered. The final claim is also supported by Usuki (2000), who identified psychological barriers which were partly to blame for the lack of success in effective adoption of LLS by Japanese students, allegedly too passive in order to make use of some strategies. Commenting on the results of a study investigating the use of strategies by 73 Japanese female college learners of English, Takeuchi (1993) linked participants’ preference for some learning strategies, such as writing notes, avoiding word-by-word translation, analyzing words or paying attention over other strategies, such as asking questions, using flashcards, looking for opportunities to use English, or writing down one’s feelings in a diary), to the learners’ cultural beliefs and shared values. More recently, Magogwe and Oliver (2007) addressed the issue of cultural variation in LLS use after investigating 480 Batswana learners of English strategic choices. It was reported that compensation strategies were the least frequently used among the six strategy categories of the SILL (Oxford, 1990) and the findings were consistent across the examined levels of education, from primary school to university and attributed to the cultural background of the learners. Grainger (2012) analyzed the

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differences in strategy use among nearly 200 learners of Japanese in the Australian context. Significant differences were found at item level for nearly 17% of all the investigated items, and it was concluded that native Australians were able to concentrate more and made conscious efforts to think in Japanese more than non-Australian learners with Asian backgrounds.

2.6.4 Age The role of age in learners’ strategic choices remains debatable as, similarly to the other IDs described in this section, its influence is believed to be interwoven with the impact of other variables, such as language learning experience, level of proficiency, or learners’ beliefs.15 Dakowska (2005) reflects on five aspects of L2 learners’ development with reference to age: . the state of their cognitive system, with implications for learners’ attention span, their ability to manage their learning process, use memory strategies, and the cognitive load they can successfully handle in terms of not merely linguistic parameters, such as vocabulary acquisition, but also in terms of their ability to think in abstract terms, use symbols, or visualize concepts; . communicative accomplishment, which is mediated by the degree to which the learner can adopt his or her interlocutor’s perspective, be goal-oriented, or process conversational feedback; . linguistic development, demonstrated in the length of utterances, produced in both L1 and L2, stage of syntactic or phonological acquisition, as well as metaknowledge; . social growth, involving the development of a sense of identity and cooperative behaviors, but also the ability to follow rules; . emotional development, involving in the first place the ability to control one’s emotions. Clearly, given the above premises, the development of an L2 by those who already speak other languages differs considerably from the development that takes place in children who are only beginning to speak their L1 and at the same time encounter another language. In general, there seems to be a clash of at least two contradictory views regarding age. On the one hand, the conviction that younger learners are somehow superior to older learners seems to be quite common and is often supported with real-life examples, referred to by Griffiths (2008) as anecdotal evidence. On the other hand, at least with reference to LLS, a number of researchers tend to agree that older learners can choose from a wider spectrum of strategies and, as strategies are at least initially employed consciously, they can choose more appropriately. 15

According to Stern (1992), the combination of the two variables, age and learners’ beliefs, may be of critical importance, as some adult learners might not even make any efforts to learn, for example, the pronunciation of the target language, only due to their conviction of being “too old”.

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According to Oxford (1986), and Ehrman and Oxford (1989), older learners are also more likely to use “more sophisticated” strategies. Indeed, as reported by Rohwer and Bean (1973), and Pressley and Levin (1977), language learners become more skilled at applying certain strategies as they get older, or as they progress from one developmental stage to another. Also, according to the results of the study conducted by Pressley and Levin (1977), older learners perform significantly better in using memorization strategies. More recent studies conducted by Griffiths (2003, 2013) have failed to confirm the existence of a simple, linear relationship between learners’ age and their use of LLS. The data for the first study was collected by Griffiths (2003) from 26 students of a private language school in Auckland, New Zealand, through the administration of the SILL (ver. 7.0, Oxford, 1990) and semi-structured interviews. The aim of the study was to examine whether older language learners (specifically more than 40 years old) were less successful at language development than younger learners, and, should it be the case, identify the factors responsible. The interviews revealed that although age did influence the learners’ strategy use and development of language skills in English, it was primarily a matter of attitude and, partly, the difficulties that the learners had to face, which were not directly related to the learning process. The fact that two learners of the same age (41) progressed at very different rates and the frequency of their strategy use differed considerably was largely due to their beliefs. Specifically, the less successful learner was convinced that she was not able to learn more efficiently because of her age and the overwhelming problems with her children, while the successful learner claimed that he put his whole heart in the learning process and actively explored new strategies, including some very unconventional ones. The difficulties encountered by the 64-year-old learner were of cultural and social nature rather than due to his age. He reported resorting to some strategies, such as spending more time with his notebook instead of engaging in conversations with his classmates, which he developed as defense mechanisms to combat anxiety and self-respect problems. Overall, the findings were supported by Griffith’s (2013) later quantitative study of 348 learners of English as a foreign language aged 14–62, which also provided a number of interesting findings concerning the meaning of age in strategy application. The learners were divided into two groups: 172 younger learners (14–23 years old) and 176 older learners (24–64 years old). In general, younger learners tended to attend slightly more advanced classes than older learners; however, both groups were characterized by the same frequency of strategy use which was estimated at 3.2, a medium frequency according to Oxford (1990).

2.6.5 Gender While the existence of gender-related differences with respect to learner language, L2 development processes, and strategy use has been generally acknowledged (Ehrman & Oxford, 1988; Green & Oxford, 1995; Oxford & Nyikos, 1989), the impact of gender as an ID is intertwined with that of other related factors, such as

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learners’ career choices, cultural background, or the culture of the countries where the TL is spoken. Even the classification of gender as an ID is not as clear-cut as it might seem. Ellis (1994, 2008) considers sex or gender, as a social factor influencing second language acquisition, while Morgan and Clarke (2011) view gender as a primarily demographic domain being part of the broader concept of a learner’s identity. According to the outcomes of Gass and Varonis’s (1986) investigation of the impact of gender of LLS use, female language learners could be expected to achieve better results in tests and become more proficient than their male counterparts in the same classrooms as well as employ more positive attitudes and deal with language tasks differently from men. At the same time, another finding of the study links learners’ gender to the type of interaction that they typically get involved in. In short, Gass and Varoni (1986) claim that women mostly use TL to gain more input whereas men do that so as to provide output. A number of studies have addressed the impact of gender on learners’ strategic choices, regarding both the overall range of the strategy repertoire, the general frequency of strategy use, and the strategy categories favored across genders. Oxford et al. (1988) sought to explain the causes of differences in strategy use across genders and aimed to account for the interpretation of the impact of gender on strategy use as an independent variable. Overall, the analysis of LLS use across genders revealed that the female participants used a wider range of LLS with regard four categories: general study, functional practice (understood as authentic language use), searching for and communicating meaning, and self-management strategies. Such results were attributed to women’s overtly more social orientation and their different (traditionally deemed better) use of verbal skills. The finding was supported by the results of Green and Oxford’s (1995) study of Puerto-Rican students, although the frequencies of strategy use for both genders could be classified within the same interval (medium strategy use) when interpreted according to Oxford’s (1990) guidelines. Green and Oxford’s (1995) study also revealed that women significantly outperformed men in the use of memory, metacognitive, affective, and social strategies, while men tended to use TV and watch films in order to learn English.16 The study conducted by Oxford et al. (1988) provided evidence that female learners used conversation/input elicitation strategies significantly more often than male learners, which was attributed to women’s desire for social approval, greater compliance with existing social norms, and the allegedly greater verbal ability. Overall, perhaps apart from the last conclusion, the beliefs about gender differences in strategy use have not altered considerably until present. More recent publications dedicated to the impact of gender on the variation in strategy use, such as the chapter by Nyikos (2008) tend to represent the view that women generally exhibit more frequent use of strategies for authentic language use, communicating meaning, self-management, as well as social, affective LLS, and strategy use in general.

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Green and Oxford (1995) related this finding to the tendencies which they had observed in TV programs, which were, at they claimed, dominated by shows preferred by men, such as broadcasts of sport events or action films.

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All of this having been said, some studies have not confirmed any relationship between gender and strategy use. For instance, in her study aimed to examine the patterns of strategy use, Griffiths (2003) set out to identify the variation in reported strategy use regarding a number of IDs, including gender. Conducted with a group of 348 mostly Asian participants in English courses at different levels (A1-C2) in an Australian language school, the research project was based on the use of the SILL (Oxford, 1990) and did not reveal significant differences across genders, either in general, or with respect to any particular level. In a more recent study, Hakan et al. (2015) found in the case of a group of 120 undergraduate Turkish learners of English that significant differences in the frequency of strategy use between the male and female participants existed only with regard to compensation strategies that were used more frequently by men.

2.6.6 Learners’ Beliefs According to Dörnyei and Ryan (2015), since their introduction into the L2 literature by Horwitz (1985), language learning beliefs have gained considerable prominence in studies of L2 development because of their anticipated impact on both learning behaviors and learners’ performance. It could be argued that some beliefs, such as those about language learning and beliefs about self, underlie self-regulation processes in L2 learning (Winne, 2011, 2018; Zimmerman, 2000). For instance, learners who feel more empowered and possess a stronger conviction of their agency in the language learning process could simply be expected to be more active in their search for LLS, as well as in the process of selecting the right LLS for a particular task. Benson and Lor (1999) refer to the role of learners’ beliefs in that respect by describing them as “cognitive resources on which students draw to make sense of and cope with specific content and contexts of learning” (p. 462). From a practical point of view, language learning beliefs can determine the choice of a specific language course or be the reason for leaving the country if an individual wants to immerse in the L2 environment. Therefore, learners’ beliefs do constitute an important determinant of strategic choices, a particularly intricate one at the same time. For example, according to Pelligrino (1998), learners’ favorable perceptions of L2 learning abroad could lead to their prioritization of learning abroad over studying in the classroom in one’s own country. Among several studies linking the use of LLS to L2 learners’ beliefs, Yang’s (1999) investigation conducted in a group of over 500 university EFL students in Taiwan certainly deserves attention because of its results. It was found that language learners’ epistemological beliefs had a major impact on their use of functional practice strategies, whereas beliefs about the value and nature of learning spoken English considerably influenced the use of formal oral-practice LLS. What was striking was that some beliefs, such as those concerning the necessity to practice speaking English if possible, and those regarding making mistakes in free speech, may actually have

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been regarded as mutually conflicting, and, consequently, result in insufficient coordination in LLS use. At the same time, in Yang’s (1999) view, the relationship between language learning beliefs and strategy use is likely to be cyclical, and appropriate employment of LLS may not merely foster language attainment, but also result in adaptations in learners’ self-perception of their language proficiency and, in effect, benefit their motivation. The outcomes of more recent study conducted by Suwanarak (2012) in a group of over 200 university graduates in Thailand suggest that both beliefs about language learning and strategy use can be linked to learning attainment. The analysis revealed that while a vast majority of the informants of the study viewed themselves as unsuccessful learners, those who had a more optimistic perspective on their achievement were, at the same time, frequent LLS users. Moreover, some beliefs were found to either facilitate or block the employment of certain LLS categories. For instance, learners’ beliefs concerning their self-efficacy and confidence in learning English as a foreign language positively correlated the reported use of with social and practical learning strategies. These results confirm Zimmerman’s (2000) contention, according to which learners’ beliefs have a considerable impact on their self-regulatory capacity.

2.6.7 Learning Styles According to Dörnyei and Ryan (2015), learning styles (LS) can be described as different ways in which people learn, chosen to make learning more effective. While there are certainly methodological criticisms concerning the very core of the concept of LS, such as those voiced by Coffield et al. (2005), the potential promise that L2 instruction could be matched to learners’ preferences is alluring (cf. Dörnyei & Ryan, 2015; Griffiths, 2012). At the beginning of the present century, Oxford (2003) appealed for more studies investigating the relationship between styles and strategies, expressing the belief that “(t)he more that teachers know about their students’ style preferences, the more effectively they can orient their L2 instruction, as well as the strategy teaching that can be interwoven into language instruction, matched to those style preferences” (p. 16). The multitude of the categorical labels that have emerged over the years of research into LS have certainly added up to the complexity of the construct. Dörnyei and Ryan (2015) adapted the map of learning styles introduced by Coffield et al. (2004), and distinguished between the following categories of LS: . physiologically-based LS, including the visual, auditory, kinesthetic, and tactile modalities, introduced by Dunn et al. (1975); . LS based on learners’ cognitive structure, introduced by Riding and Cheema (1991); . LS based on personality types, introduced by Myers and Briggs (1976); . “flexibly stable” learning preferences, first investigated by Kolb (1984); . LS understood as approaches, strategies, or orientations, initially investigated by Entwistle (1990).

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In an attempt to illustrate the distinction between LS and LLS, Oxford (1989a) referred to LS as general problem-solving tendencies and pointed out that they could directly affect specific learning behaviors, including strategy use. A similar distinction was made by Carson and Longhini (2002), who inferred from their diary study in immersion settings that LS are generally more consistent than LLS. At the same time, Harris (2001) hypothesized that only through the use of certain LLS can some learners discover how to make the most of their learning style. A number of studies have confirmed the relationship between the two variables. In a qualitative empirical investigation, Stevick (1989) conducted a series of interviews with seven randomly selected L2 learners. He categorized them as an intuitive learner, a formal learner, an informal learner, an imaginative learner, an active learner, a deliberate learner, and a self -aware learner. Each of the learners was eager to reflect on their learning styles and preferences, which was interpreted as a quality of good language learners. Stevick (1989) found a number of differences in the use of metacognitive strategies among those seven learners who showed various learning style preferences. In general, it was found that the strategic devices resorted to when learning the target language were adjusted by the learners to fit the modality they favored. Specifically, some of the learners preferred engaging in social conversations with a list of linguistic aims in mind, others devised their one own phonetic transcription, while one specific learner was “mechanically” oriented, which was demonstrated in his fondness of drills and production of charts. In general, the study confirmed the correspondence between learners’ general perceptual and learning preferences and the LLS which they employed. Finally, it was also pointed out that learners preferred a specific style relying on their strengths rather than attempting to eradicate their weaknesses. An analysis of an advanced learner’s diary was conducted by Ma and Oxford (2014) in order to account for the interaction between LS and LLS used in listening and speaking in English. The insights of the diarist-researcher entered in the learning diary for 85 days resulted in a corpus of 18 entries, and more than 13 thousand words in total. Reflections were entered in the form of in-class notes, involving the use of key words, and retrospective descriptions of learning sessions in class or plans for future learning. For the reflective, introverted, visual, and environmentally-sensitive learner, the tailor-made strategy repertoire was efficient if it included note-taking during lectures (a form of surviving in the mainly auditory learning environment), establishing communicative goals and attempting to accomplish them through stretching the introvert style, as well as making efforts to rely more on intuition. Overall, it was concluded that any language learner should at least attempt to account for the advantages and disadvantages of their own learning style through the application of metacognitive strategies. A belief was also expressed according to which learners who engage in that kind of reflection can take charge of their own self-regulation.

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2.6.8 Language Aptitude Although instruments designed to measure language aptitude (LA) include items that imply the use of task-specific strategies, such as inferencing, conceptualizing narrowly or conceptualizing broadly, the very notion of LA remains debatable. For example, Richards (2015) defines language aptitude as merely “(t)he theory that some people have a special aptitude for second language learning, and are better able to reorganize grammatical relations, master pronunciation, and learn words more easily” (p. 741). On the other hand, the tradition of exploring the role of LA has been well established for the simple reason that it has commonly been recognized as a strong predictor of academic success in general (cf. Dörnyei, 2005; Dörnyei & Ryan, 2015; Gregersen & MacIntyre, 2014; Ranta, 2008). Empirical evidence for these claims was provided, for example, by Ehrman and Oxford (1995), who found significant correlations between language aptitude and the rate of language learning and attainment. At the same time, studies linking LA and LLS use are scarce, and in those few that have been conducted both LA and LLS are typically treated as predictors of skill development (cf. Winke, 2013). Similarly to LLS, LA could be approached from a specific task perspective, which was suggested by Robinson (2002) and Ranta (2008), who are in favor of measuring the effect of LA on learners’ performance in specific instructional activities rather than in general. According to Gregresen and MacIntyre (2014), aptitude could also be analyzed with regard to the ability of learners’ noticing the gap between the correct and the incorrect, a concept introduced by Schmidt (1990) and elaborated on further by Robinson (2002), or memory for contingent speech, investigated by Ranta (2008). Furthermore, according Skehan (2002), aptitude could be analyzed with respect to four stages of SLA: noticing, patterning, controlling, and lexicalizing. The direct link between these stages and strategy use seems quite obvious, as noticing requires paying attention (that is, a cognitive strategy) while patterning involves analyzing, processing and making generalizations, for instance, through conceptualizing broadly (that is, a cognitive strategy yet again). Lexicalizing, in turn, involves gathering a certain collection of expressions that can be accessed quickly, which could easily be used whenever compensation strategies are employed to support communicative processes in the face of difficulties with retrieving L2 elements. Dörnyei and Ryan (2015) point to new developments in assessing LA and provide an example of an alternative tool for LA measurement, that is the Cognitive Ability for Novelty in Acquisition of Language (CANAL-FT), introduced by Grigorenko et al. (2000). The CANAL-FT test consists of five tasks: (1) Learning meanings of neologisms from context, (2) Understanding the meaning of passages, (3) Continuous paired-associate learning, (4) Sentential inference, and (5) Learning language rules. These tasks directly correspond to five processes present in learning an artificial language (Dörnyei & Ryan, 2015; Grigorenko et al., 2000), that is (1) selective encoding, (2) Accidental encoding, (3) Selective comparison, (4) Selective transfer, and (5) Selective combination as well the stages of acquisition proposed by Skehan (2002) and require language learners to employ specific LLS. According to Dörnyei

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and Ryan (2015), selective encoding, involves selecting relevant information, and requires learners to employ cognitive strategies, such as paying attention. Accidental encoding relies on the use of context and thus requires learners to conceptualize broadly. Selective comparison consists in selecting old information for future tasks in order to enhance learning. This, in turn, might require learners to use metacognitive strategies, such as planning and orchestrating the learning process. Selective transfer involves applying inferred rules in new context. Finally, selective combination, consists in synthesizing relevant pieces of information. It could be concluded that the processes investigated by the CANAL-FT (Grigorenko et al., 2000), imply a relationship between LA and LLS use.

2.6.9 Motivation Motivational differences among individuals learning additional languages are certainly reflected in their selection of LLS. Obviously, these reasons may be related to other, previously discussed, variables affecting learners’ strategic choices. As pointed out by Gregersen and MacIntyre (2014), although the importance of motivation in L2 learning is commonly acknowledged, multiple perspectives exist on how it works and where it originates from. The definitions of motivation offered by applied linguists are perhaps not mutually exclusive, but they tend to stress different aspects of the notion. For example, Ellis (2008) refers to motivation as “the effort that learners put in learning an L2 as a result of their need to desire to learn it” (p. 972), while Gass and Selinker (2008) describe it as “(t)he characteristic that provides the incentive for learning” (p. 520). Williams et al. (2015) warn that it might be misleading to link motivation as an ID with the core verb, motivate, from which it derives, as this could result in a bias in interpreting motivation as merely an external entity. Indeed, the results of early research into the impact of motivation on learning achievement, conducted by McGroarty (1988), indicate that lack of motivation could impede progress in L2 learning and negatively affect educational achievement even if learners are provided with state-of-the-art instruction. It is thus reasonable to consider the characteristics of a motivated language learner, which, according to Gardner (2013) include having a goal, making efforts and being willing to achieve it, adopting favorable attitudes pursuing it, being persistent, focused and attentive, making attributions about success and failure. It appears that each of these characteristics requires the use of certain strategies. For example, pursuing an educational objective requires the use of metacognitive strategies, such as planning or organizing one’s learning, being willing to achieve one’s educational goal can be fostered with the use of affective strategies, and, finally, making efforts can take place by application of virtually any learning strategy. Elaborating on good language learners’ characteristics, Griffiths (2008) describes their strategic behavior as goal-oriented and purposeful, which is certainly linked to their being motivated. What seems much more challenging for applied linguists and language educators is accounting for the sources of motivation. While it is not

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the focus of the present book, it should be noted that adopting a certain theoretical perspective, such as the social psychological approach (Gardner, 2010), or the dynamic perspective of motivation, introduced by Dörnyei and Otto (1998), certainly influences not only the beliefs that a given researcher holds about motivation, but also the impact of such views on empirical investigations of this the links between motivation and LLS use. For the purpose of the present considerations, Gardner’s (2013) list of the characteristics of a motivated learner is used as a basis for linking motivation and LLS use. At the same time, the dynamic perspective is closely connected to SRLL, discussed in Sect. 2.5. It could be argued that the relationships between LLS and motivation are mutual since, as pointed out by Harris (2001), learners “are more likely to persist if they feel the outcome of their learning is not predetermined and they have some control over it” and “(s)trategies can play an important part in giving them that sense of control and changing their perceptions of themselves” (p. 16). As asserted by Macaro (2006), motivation might stem from learners’ use of metacognitive strategies of selfassessment and reflecting on one’s progress, hence making the interaction between motivation and LLS more complex. Oxford (2017) even specifically distinguishes a separate category of motivational LLS that learners employ to maintain enthusiasm and interest in improving their L2 skills. Although the dual nature of the relationship between LLS and motivation was recognized in the early days of strategy research (cf. Oxford & Nyikos, 1989), the present chapter considers LLS as a dependent variable influenced by other learner IDs, and, consequently, the perspective of motivational impact on strategy use has been adopted. Moving on to empirical evidence, the study conducted by Oxford and Nyikos (1989) in a group of 1200 American university students learning five different L2s confirmed the intuitive assumption of the positive relationship between the level of learners’ motivation and the frequency of strategy use. The research instruments involved a 121-question version of the SILL (Oxford, 1990), and a background questionnaire which was intended to provide information about participants’ gender, language learning experience, the type of language course (elective versus obligatory), as well as self-perceptions of motivation and language proficiency. Overall, the learners who perceived themselves as relatively more motivated used LLS significantly more often. Motivation also turned out to significantly affect the following LLS factors: . formal, rule-related practice strategies, involving the use of knowledge about language structures, making cross-linguistic comparisons, generating and revising rules, or analyzing words; . functional practice strategies, involving various forms of practicing outside the classroom, such as seeing films in the TL, making contact with native speakers, and imitating them, initiating conversations in TL, or using authentic materials; . general study strategies, consisting in planning and organizing the learning process, ignoring distractions, and time management;

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. conversational input elicitation strategies, including guessing meaning from context, or asking the interlocutor to speak slowly or act as a pronunciation role-model. Pawlak’s (2012) mixed-method study of the dynamic aspects of motivation provides a number of insights into the impact of learners’ levels of motivation on their use of LLS. Evidence comes from a longitudinal study of 28 Polish upper secondary school students who were learning English as part of their curriculum. Data was obtained from observation during regular lessons, a 42-item, 6-point Likert-scale questionnaire designed to assess motivation, based on earlier instruments designed by Ryan (2005), Taguchi et al. (2009), and Csizér and Kormos (2009), and a series of 11 interviews with the investigated learners. With regard to LLS use, it was observed that the learners who recognized the role of English, had relatively more specific future goals, were at the same time eager to dedicate more time and effort to boosting their competence. This involved a considerable number of metacognitive, metasocial, and metamotivational LLS at work as the learners tended to increase exposure to English through participation in additional lessons, searching for additional resources, using the Internet reading books, or listening to English music. Conversely, learners whose motivation and educational achievement in English were rather low displayed little interest in making the learning of English a more selfdirected, voluntary, and, perhaps, most importantly, enjoyable experience. It was also found that students who planned in the long run and who were prone to the impact of their ideal language self were also much more active, in their quest for well-suited, tailor-made strategies, both enjoyable and efficient, and certainly going far beyond the scope of school requirements. The qualities of these learners strongly correspond to the markers of high SR levels (see Sect. 2.5).

2.6.10 Language Learning Attainment The interest in LLS is obviously connected with the strong belief of strategy enthusiasts that the use of LLS can boost learners’ performance and attainment,17 and their conviction that both L2 performance and attainment can be improved by strategy training.18 Already referred to in the present dissertation, Rubin’s (1975) and Stern’s 17

Language attainment is probably the most comprehensive term that refers to L2 learners’ achievement, and learning or improving skills, which could be operationalized as performance in specific tests, as suggested by Pawlak (2008), or quantified by self-assessment or CEFR level. Obviously, the term itself denotes a certain degree of ambiguity, which can impede investigating the relationships between language learning strategies and language attainment. This remains particularly relevant from the contemporary perspective of LLS investigations (cf. Pawlak, 2021), especially in the light of criticisms of CEFR scales for insufficient validity (Wisniewski, 2018). 18 Strategy researchers’ belief in the benefits of strategy use led to the arrival of a number of guidebooks for both language learners and course instructors to accelerate the acquisition of the target language, which were later assessed in terms of efficiency. To mention just one example, Cohen (2005) conducted a comprehensive study of a group of language learners and course instructors in

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(1975) papers provided an impetus for subsequent research in this respect. In general, two perspectives could be distinguished in studies of the relationships between LLS use and L2 achievement. On the one hand, a number of researchers have tended to link the use of LLS to learners’ performance or attainment, operationalized as specific achievement or performance tests, or evaluated according to certain criteria. In retrospect, these attempts appear to have aimed to prove the overall usefulness of LLS, and their contribution as an explanatory variable in accounting for educational achievement in L2 learning. Studies within this paradigm are referred to as paradigm one studies later in this subsection. On the other hand, a number of researchers have investigated variation in the use of LLS by learners at different levels of proficiency with the use of specific LLS. Studies within this paradigm are referred to as paradigm two studies in later parts of the present subsection. It could thus be argued that a thorough description of the relationships between learners’ proficiency and their strategies should take into account both perspectives, since, as signaled by Halbach (2000), Kamper et al. (2003), and Pawlak (2008), the correlational nature of the relationship between strategy use and learners’ proficiency precludes making any assumptions concerning the role of strategies in boosting learners’ proficiency. At the same time, Oxford’s (2003) attempt to explain the ambiguous nature of the relationship through a reference to its spiral (mutual) nature lends support to Vygotsky’s (1978, 1986) views concerning the cumulative nature of learning embedded in his theory of social constructivism. According to a number of theoretical and empirical paradigm one studies, frequent LLS users are typically more proficient learners. Starting with Rubin’s (1975) and Stern’s (1975) observations, research into LLS has resulted in the discovery of a plethora of relationships between strategy use and TL proficiency. Referring to earlier findings by O’Malley and Chamot (1990), Oxford (1990, 1996), and Wenden and Rubin (1987), Oxford (1999) asserts that successful language learning is typically associated with the use of a larger number of LLS, their wider range, and overall greater effectiveness in their use, as well as their better suitability for particular task demands. Table 2.2 provides more detailed information on the procedures employed in investigating the relationships between strategy use and proficiency level obtained in studies drawing on the SILL (Oxford, 1986, 1990). The findings of selected studies using the techniques listed in Table 2.2 are briefly summarized below. In order to avoid information overload, the selection is limited to studies investigating learning English as L2, and thus it does not include any references to the strategies employed by native speakers of English learning other languages. . In a study of 141 young adult students with various L1s, Phillips (1991) found that the mid-proficient learners demonstrated higher strategy use than low-proficiency or high-proficiency learners.

order to assess the impact of expanding learners’ LLS repertoires and provide instruction in strategy training and use.

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Table 2.2 Types of investigations of links between strategies and proficiency (based on Oxford, 1999) Procedure

Aim of application

Multiple regression

Determining what percentage of language proficiency can be predicted by the frequency of strategy use

Correlation

Calculating the strength and direction of the relationship between the frequency of strategy use and measures of proficiency

Analyses of variance

Percentages of variance of language proficiency determined by the frequency of strategy use (ANOVA) or strategy use and other variables (MANOVA)

. In a study of 78 Japanese female college students carried out by Takeuchi (1993), 58% of variance in learners’ proficiency, measured by CELT test scores, was explained by eight LLS. . In a study of 374 Puerto Rican university students, Green and Oxford (1995) found linear relationships between ELSAT test scores and four out of six strategy scales, that is, compensatory, cognitive, metacognitive, and social strategies. . A study conducted by Oxford and Ehrman (1995) among 262 adult learners of English employed in the US Foreign Service Institute indicated a weak, but significant correlation between the use of cognitive LLS and learners’ speaking proficiency, operationalized as end-of-term ratings. . In a study of 305 South African speakers of Afrikaans, conducted by Dreyer and Oxford (1996), 46% of all variance was explained by the use of LLS (as measured by the SILL), with metacognitive LLS being the best predictor of learners’ proficiency, followed by social and affective LLS; the correlation coefficient calculated in canonical correlation analysis amounted to 0.73; . In her comprehensive investigation of patterns of strategy use, Griffiths (2003) identified significant relationships between the applied strategies and course level, managing to select nineteen “plus” strategies, distinguishing advanced learners from others. Conducted in a group of 384 students of various nationalities, aged 14–64, attending courses in a language school, the study sought to trace patterns of strategy use across different proficiency levels, identified by Oxford Placement Test (OPT; Allan, 1995) as well as an oral interview by an experienced language teacher; the learners participated in a strategy awareness raising activity or a course in study skills, which were both expected to orient learners more towards strategy use. The study confirmed that advanced learners used strategies significantly more often than elementary students. ANOVA showed that more than 10% of variance in learners’ proficiency was determined by their use of these nineteen strategies. The eight critical groups of strategies involved: interaction with others, vocabulary learning strategies, reading strategies, ambiguity tolerance strategies, strategies related to language systems, strategies employed to manage feelings and emotions, managing one’s own learning, and strategies allowing learners to utilize available resources.

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. Investigating the impact of lexical inferencing strategies on second language reading proficiency, Parel (2004) found that reading comprehension skills in English as L2 may be improved by the acquisition of the meanings of the most productive affixes of English, which was aided by instruction in principles of morphological analysis. . Studying the used by Batswana learners of English in order to handle the problem of learners’ relatively low fluency in English and their poor performance in English examinations in tertiary education, Magogwe and Oliver (2007) provided support for the claim that the relationship between proficiency and strategy use may largely depend on the type of strategy employed; they did not find any statistically significant relationships between learners’ proficiency and their use of LLS, but at the same time, they observed that learners’ willingness to use metacognitive strategies increased considerably in secondary and tertiary education. . The results of a study of 77 full-time Slovenian students of the University of Ljubljana conducted by Jurkoviˇc (2010) indicated that few beneficial effects could be expected from explicit strategy training; at the same time, the researcher suggested that one of the reasons for this situation could have been the heterogeneous nature of the group. Learners varied considerably regarding their initial L2 proficiency, and strategy training did not account for the differences in strategies used by lower level and higher-level students. . Conducted in a group of 868 Hungarian lower secondary school students (aged 11 and 14) in order to examine the relationships between LLS, learners’ proficiency level and their L2 grades, Habók and Magyar’s (2018) study revealed moderate, significant correlations between overall LLS use and learners’ grades in L2; however, the results showed no clear tendencies for the investigated scales of LLS, pointing to the conclusion that efficient LLS use is largely idiographic. Although the results of the above studies are characterized by a certain degree of inconsistency, the general conclusion which arises from the above overview reflects that made by Oxford and Ehrman (1995, p. 69), according to whom successful language learners manage a wide repertoire of LLS which they are able to apply accordingly to the particular task demands, the learning material, the individual’s personality, proficiency level and stage of learning. The body of paradigm two research dedicated to the investigation of the role of learners’ proficiency in their choice of their strategic repertoire seems somewhat limited in comparison to the plethora of studies drawing on paradigm one. Some researchers that have followed the second paradigm have simply investigated the frequencies of overall strategy use or the use of certain categories of strategies (such as the scales included in the SILL) among learners grouped according to their proficiency level, while others, such as Gregersen et al. (2001) or Lai (2009), have attempted to trace patterns in LLS use. In the case of paradigm two studies, an attempt can be made to analyze LLS as a variable explained by learners’ level of proficiency. A number of interesting perspectives on the use of LLS by Chilean students, varying in terms of both TL proficiency and attainment in their English studies, were addressed in a pilot study conducted by Gregersen et al. (2001). The empirical

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investigation focused on the differences in LLS use between good and poor learners (as indicated by a panel of professors) and between first-year and fourth-year students. The following findings were reported: . regarding memory strategies, good learners outperformed poor learners in their use in the first year; however, the situation was reversed in the fourth year; this implies that memory strategies could be more naturally used by lower-level learners in order to help them expand their vocabulary range, whereas among more proficient learners, emphasis is more frequently put on acquisition rather than learning. . the use of cognitive strategies remained consistently more frequent among good learners than among poor learners throughout the period of studies, and the difference in cognitive strategy use in the fourth year exceeded the difference in the first year; . the frequency of use of compensation strategies did not vary among good and poor students in the first year; however, these strategies were relatively more frequently used by poor students in year four, which implies that excessive use of compensation strategies could possibly hinder the process of L2 learning; . good language learners outperformed poor language learners in the use of metacognitive strategies and the efficiency gap in the fourth year exceeds the one among first year students; the scholars concluded that strategies such as planning, organizing, or evaluation, are crucial to learning L2; . interesting insights were obtained regarding learners’ use of affective strategies, which, as it turned out, were more frequently employed by poor learners rather than by good learners, which could imply that the need to use affective strategies may only arise when learners are experiencing difficulties or feel uncomfortable, but might also be linked to potential problems with the wording of the questions in the scale; . the use of social strategies remained consistently higher among good students than among poor students and the tendency did not change over the time of studies. In order to investigate the patterns of LLS use, Lai (2009) conducted a study in a group of 418 students participating in the Freshman English for Non-Majors (FENM) program at Tunghai University in Taiwan. The level of proficiency in English turned out to have a significant impact on participants’ choice of LLS. More proficient learners used LLS significantly more often than less proficient ones, showed a preference for different groups of strategies, with metacognitive and cognitive strategies being the domain of proficient students, and memory strategies being the domain of less proficient users. The distinguishing strategies of good (and thus proficient) language learners mainly involved arranging and planning one’s learning, and making good use of one’s reasoning and analytical skills, as well as practicing pronunciation and speaking. Attempting to explain the differences in strategy application by good and poor Iranian students, Gerami and Baighlou (2011) examined a group of 200 students from two universities and measured their declared strategy application according to self-reported frequencies in the SILL. These students were divided into three groups

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according to their TOEFL scores, that is, high-level (top 27% of scores), mid-level, and low-level students (bottom 27% of scores). Not only did the analysis indicate considerable differences in general strategy use in favor of good students, but it also provided interesting insights into the patterns of strategy application. Specifically, high level students preferred metacognitive strategies and deep cognitive strategies. By contrast, poor students preferred surface structure cognitive strategies, such as saying or writing new words in English several times, or looking for similar words in their native language. The results of the study confirmed the utmost importance of planning and organizing one’s own learning. Based on a similar rationale, a study of 140 Turkish students of English conducted by Yılmaz (2010) indicated that the students who were classified as “good” on the basis of their cumulative average of grades in English subjects significantly outperformed “poor” students with regard to affective strategy use. This was attributed to their better ability to encourage themselves to store and retrieve information more efficiently and lower their anxiety. Another study which set out to identify the LLS serving as markers of good language learners was conducted by Salahshour et al. (2013) in a group of 60 high school students. It confirmed the considerable role of metacognitive strategies, which were used significantly more often by high-proficiency learners than low-proficiency learners. In an attempt to elicit the strategies of effective language learners, Wong and Nunan (2011) studied the strategies of 110 Hong Kong undergraduate students, 33 of whom were “poor” learners, graded “E” or “F” on the Hong Kong Examinations and Assessment Authority “Use of English Examination”, and 77 of whom were “more effective” learners, graded “A”. The five most popular strategies among the “more effective” students included: learning by watching/listening to native speakers, learning English words by seeing them, watching TV in English, learning in class by conversation, and learning new words willingly. At the same time, the strategies favored by the “less effective” students involved: listening to error correction done by the teacher, learning English words by seeing them, using the teacher’s help to discuss one’s own interest, having one’s own textbook, and learning new English words by doing something. Overall, merely one strategy proved to be favored by both categories of students: learning English words by seeing them. This strategy could be executed in a number of ways, which could differ considerably by the two categories of learners. All the strategies favored by the “more efficient” participants seemed to require relatively more involvement than those employed more frequently by the “less efficient” learners. Those employed by the “less efficient” learners also appeared to be relatively more passive, perhaps with the exception of learning by doing. It might thus be concluded that, as signaled in earlier research conducted by Nunan (1997), successful learners are more at ease, more in charge, and more communicatively oriented than their unsuccessful counterparts. Researching relationships between strategy use and the proficiency level of first year Thai university students, Kunasaraphan (2015) was interested in finding patterns of the use of both direct and indirect strategies, as well as their dependence on participants’ level. Unlike previous studies of Thai students, such as those conducted by Khamkhien (2010) or Anugkakul and Yordchim (2014), Kunasaraphan (2015)

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found that Thai students used indirect LLS relatively more frequently than direct LLS. The linear relationship between the general use of LLS and learners’ proficiency levels was confirmed. A significantly higher frequency of metacognitive strategy use was also found for students whose proficiency level was higher (that is, learners’ level of proficiency was determined by means of a Thai SSRUIC test, and an interview, as either basic, intermediate, or advanced). On the other hand, lower-level students used memory strategies significantly more often than higher level students. Kunasaraphan (2015) also expressed the belief that it is possible to promote LLS typically chosen by high-achievement students among low-achievement students, and therefore influence their attainment. The particular role of self-regulation and orchestration of one’s own learning, along with the essential role of efforts on the part of the learners made in order to increase exposure to English were shown to be of vital importance in the study conducted by Lee and Heinz (2016). The participants were enrolled in translation and interpretation courses at a Korean university and the aim was to elicit the LLS employed by advanced learners. Although it was emphasized that the participants were not typical EFL learners and the results could not be generalized, their findings match the overall picture of high-proficiency learners, and confirm the critical importance of LLS from the cognitive and metacognitive domains. Numerous researchers have attempted to capture the complex relationships between LLS and proficiency by including more variables in their studies. For example, in a study already referred to in the present section, Habók and Magyar (2018) set out to analyze the differences between relatively more and less proficient learners of English in terms of strategy preferences. While some of these differences between students characterized by different levels of language proficiency turned out to be statistically significant, showing an overall preference for metacognitive strategies, and a shift from memory and affective strategies to cognitive strategies among relatively more proficient learners, the results remain ambiguous due to the fact that the informants were not merely different in terms of proficiency, but also in terms of age. Consequently, it is not clear whether the observed differences could be attributed to the learners’ increasing proficiency in English, their cognitive development connected with the process of growing or, perhaps, both. Habók and Magyar’s (2018) constitutes a good example of how challenging it might be to capture the complex relationships between LLS and language attainment, proficiency, and educational achievement. First of all, some researchers do attempt to distinguish between the three categories. Of course, it is possible to operationalize each of the three as different variables. For instance, one could equate language attainment with endof-term evaluation of learners’ performance, learners’ proficiency as their CEFR level, and educational achievement as grade/mark average, but it remains true that each of them can constitute a measure of progress that learners make in L2 development. Secondly, the age factor poses a serious challenge in any analysis of the developmental patterns in strategy use. The ceteris paribus condition is hard to meet in comparative research investigating the strategies of learners who differ in their level of proficiency, especially when juxtaposing groups of students from primary or secondary schools. It needs to be remembered that, as indicated by Singleton

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and Le´sniewska (2012), age constitutes an essential individual characteristic, which can considerably affect learners’ performance and attainment. Thus, any comparison across groups of learners whose ages are different, especially those at different developmental stages, could be biased. Another difficulty consists in the already mentioned correlational nature of the relationship between LLS and TL attainment that was addressed by most studies. Commenting on the issue of investigating the links between LLS and target language attainment, Pawlak (2011a) suggests that the cause-and-effect relationship between strategies should be embraced rather than feared, and calls for context-based investigations of learners’ strategic competence which would allow more in-depth analysis of successful strategy use, account for the fit to a particular language task or the influence of other IDs, such as learning styles.

2.6.11 Language Learning Task While it appears quite obvious that the type and specifics of a language task to be performed by language learners exert an influence on their strategy choice, the nature of the influence remains complex. More specifically, learners making strategic choices may take into account immediate language tasks, but also forthcoming language tasks, and even anticipated language tasks or situations in general. For example, learners might rely on contextual clues when dealing with unknown vocabulary in a reading comprehension task in a progress test, but at the same time, they could frequently check the meaning of unknown words or phrases in an online dictionary when doing the same task at home. The interaction between LLS and the language task has been already referred to in the present book in introducing the LLS concept (Sect. 2.3.2). In brief, as Oxford (1990, 2011, 2017) emphasizes, it is generally believed that the overall purpose of LLS is to facilitate the completion of specific language tasks. Some strategy researchers, such as White (2008) or Cohen (2014), have even further emphasized the importance of the language task by including it in the definition of LLS. Others, such as Bialystok and Fröhlich (1978), and Cohen (1995) have stressed the necessity to refer to specific language tasks when judging the efficiency of LLS. Finally, it is commonly believed that the variety of language tasks exerts a direct influence on the variation in strategy use, as indicated, for example, by Ellis (1994) or Pineda (2010). The belief expressed by Oxford et al. (2004) that research into task-based strategy investigations should be complimentary to research into strategy use as such rather than replace it appears to be relatively common. For example, Rubin (2008) perceives effective learning as dependent on the use of LLS in terms of accomplishing specific language tasks rather than claiming that learners should be aware of the existence of certain LLS as such. Also, it appears that the overall usefulness of some strategies is greater that of other strategies with respect to tasks requiring the use of particular modalities. Bialystok (1981) specifically suggests that self-monitoring might be more frequently used in writing tasks than in speaking tasks.

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As pointed out by Oxford (1989b, 1990), LLS can be transferred across tasks. In Anderson’s (2000) view, this can happen provided there is a sufficient degree of similarity between the tasks, such as the necessity to employ certain specific language patterns. According to Cohen (2003), successful learners select and adjust their LLS as they progress in performing a task. For instance, in reading comprehension, they might approach the task initially using the strategies for finding the main idea of a text, such as reviewing headings and subheadings quickly in order to comprehend the organization of a written passage, but they are likely to replace them with strategies for making inferences from the text, such as noticing key adjectives in order to identify the writer’s attitude and distinguish between facts and opinions. Good language learners are also likely to apply different LLS for summarizing the text, such as making marginal notes or converting detailed points of a summary into more general points. Among a plethora of various factors which mediate the use of LLS, the task which the learner has to complete is one that is frequently external to the learner i.e., because it is related to assignment from a language course instructor or requirement created by the conditions of learning the language in a foreign environment, thus going beyond the level of skills. For example, writing a postcard differs considerably from writing a report ordered by a superior. As explained by Oxford et al. (2004), “task-based strategy assessment seeks to anchor strategy use within the context of a particular language task, thus allowing for a more detailed, more contextualized analysis of L2 strategy use” (p. 2). In their in-depth analysis of the role of the language task in the application of various types of LLS, Oxford et al. (2004) lists three major perspectives: . the perspective of a duty to fulfil; . the perspective of a segment of curriculum, which, in turn, is reflected as a stage in the organization of the teaching and learning process as well as a checkpoint in the assessment of L2 outcomes; . the perspective of the application of tasks as communicative activities or accuracyoriented activities. Obviously, performing a certain task may be connected with more than one perspective, and, similarly, a number of task categories can be distinguished, which might show a considerable overlap, such as, for example, role-plays, simulations, problem-solving, decision-making, sharing experiences. A number of dimensions of tasks exist, all of which have the in-built component of external origin. Oxford et al. (2004) draw attention to the following: . goals (convergent or divergent), related to systematic elements of the target language or a language function; . the level of risk, determining the level of stress which a language learner may encounter performing it; . timing, which can be defined or not; . input, which can take different forms, and vary in terms of comprehensibility;

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. materials and settings, which constitute the input, and vary with reference to their relevance and suitability; . output, which varies in terms of complexity and reflects the level of understanding the task, the operating cognitive processes which underlie performance, and learners’ aptitude; . the level of TL skill (that is, any of the four macro language skills or their combination, which results in an integrated use of language skills) and the key aspect of communicative competence addressed by the task; . complexity, resulting from the involvement of certain cognitive processes and the degree of its familiarity to the learner; . the expected mode of interaction (for instance, verbal or non-verbal); . planning, whose extent may differ depending on the learner’s use of metacognitive strategies and the emphasis on accuracy and spontaneity in the completion of a particular task; . amount of strategic control on the part of the learner, which strategy researchers believe can facilitate the completion of a number of L2 tasks; . learner-specific factors, such as personality traits, motivation, dominant learning style, language anxiety or preferences connected with the role to be adapted in group work; . teacher-related factors, such as teaching beliefs and preference for certain classroom techniques. All these factors are connected with the degree of difficulty, which Skehan (1996) considers with respect to three issues, including linguistic complexity, cognitive complexity and communicative stress. Oxford et al. (2004) also refer to Pica’s (1993) conditions that need to be met so that a task enables learners to develop their strategic competence through negotiation of meaning (that is, efforts made by interactants to anticipate and solve communication breakdowns). These include, most importantly, the information gap that interlocutors need to fill and the need to supply the missing information through communication. More recent findings referring to the importance of the language task in empirical investigations of learning strategies are listed below: . Elgort and Warren (2014) suggest that in vocabulary tasks learners should be able to employ more explicit task strategies, such as mnemonics or other higher-order cognitive strategies; they also link fluent language use with fast and accurate processing of word forms and retrieval of their meanings. . Uhrig’s (2015) conclusions from a case study of learners performing a series of reading comprehension tasks supported Cohen’s (2003) and Dörnyei’s (2005) assumptions about the influence of students’ learning style on their choice of strategies which are relevant to particular tasks. . According to Varasteh et al. (2016), learners who attribute relatively greater value to the performed language task are also relatively more frequent deep strategy users and, hence, achieve greater self-regulation.

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Although the importance of the language task in determining learners’ strategic choices is quite obvious and the framework for investigating task-based language learning and teaching has long been in existence (cf. Ellis, 2003; Willis, 2021), strategy researchers seem to prefer the functional approach, which corresponds to the early taxonomy of LLS developed by Oxford (1990). The links between LLS and language tasks are indeed complex, due to the involvement of a number of variables in their mutual interaction. As shown above, strategies can be accounted for with reference not merely to their functions, but also to the four skills, and even language areas, such as grammar or vocabulary. Perhaps the need for a new framework for investigating LLS in the context of task performance should thus be preferred.

2.7 Conclusion The growing level of awareness about the complexity of the strategy construct has not discouraged researchers from investigating the use of LLS and relevant variables. On the one hand, it remains true that factors such as the lack of consensus concerning the very name of the strategy ID (language learning strategies vs. language learner strategies), the co-existence of a multitude of strategy definitions, and the partly contradictory insights about strategy features can all exacerbate the challenge of arriving at some ultimate conclusions concerning the role of LLS in L2 development. On the other hand, the dissemination of insights into the ways of using LLS, the patterns of their use, and the influence of a number of IDs on strategy use have all influenced the way that LLS are investigated. Originally, mostly accounted for from the functional and quantitative perspective, LLS have become a construct that is investigated in relation not merely to skills, functions, aspects of language such as grammar or vocabulary, and other learner IDs, also in context of particular tasks, and as a pillar of learners’ self-regulation (cf. Oxford, 2017; Oxford & Amerstorfer, 2018). Perhaps the final conclusion which arises from the issues discussed in the present chapter will partly echo the view present in Oxford’s (2017) second book on LLS as part of learners’ self-regulation. It seems that, given all the complexity and ambiguity which relate to the strategy construct, definite and arbitrary judgements should best be avoided when addressing the scope of work and efficiency of strategy research. A trend to investigate LLS in context has clearly emerged and it is only a matter of time before new research results can be analyzed and conclusions can be summarized and generalized. It is already clear, though, that the context for analyzing LLS involves both the micro- and the macro-environment of strategy use, the former consisting in the use of LLS with reference to particular language tasks, and the latter requiring the inclusion of a whole range of learners’ individual characteristics. The present chapter has attempted to illustrate the intricate relationships between LLS and a number of other learner characteristics. Its final section, which contains a review of selected studies into LLS in recent years, certainly supports the conviction that strategy research should continue, there is no need to stick to a single paradigm, and, perhaps most importantly, the breadth of perspectives into the choice and use

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of strategies constitutes much more of an advantage than a drawback, as pointed out by Pawlak and Oxford (2018). It would thus be unwise to abandon strategy research as new insights which contribute to a more holistic picture of the strategy user continue to appear as results of studies largely relying on the traditional methodology, including the use of the SILL (Oxford, 1990). It is only a matter of time before the directions of future research, such as those indicated by Pawlak and Oxford (2018), including studies of the impact of learners’ emotions on strategy use or cross-linguistic influences in strategy application, will start being pursued by SLA researchers and provide fresh insights into LLS use and its effects.

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Taguchi, T., Magidand, M., & Papi, M. (2009). The L2 motivational self system among Japanese, Chinese and Iranian learners of English: A comparative study. In Z. Dörnyei & E. Ushioda (Eds.), Motivation, language identity and the L2 self (pp. 66–97). Multilingual Matters. Takeuchi, O. (1993). Language learning strategies and their relationship to achievement in English as a foreign language. Language Laboratory, 30, 17–34. Tangney, J. P., Baumeister, R., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271–324. Tarone, E. (1981). Some thoughts on the notion of communication strategy. TESOL Quarterly, 15, 285–295. Tarone, E. (1983). On the variability of interlanguage systems. Applied Linguistics, 4, 142–164. Taylor, A., Stevens, J. R., & William, A. J. (2006). The effects of explicit reading strategy training on L2 reading comprehension: A meta-analysis. In L. Ortega & J. M. Norris (Eds.), Synthesizing research on language learning and teaching (pp. 213–244). John Benjamins Publishing. Teng, L. S., & Zhang, L. J. (2016). A questionnaire-based validation of multidimensional models of self-regulated learning strategies. The Modern Language Journal, 100, 674–701. https://doi. org/10.1111/modl.12339 Thiede, K. W., Anderson, M., & Therriault, D. (2003). Accuracy of metacognitive monitoring affects learning of texts. Journal of Educational Psychology, 95, 66–73. Thomas, N., Rose, H., Cohen, A. D., Gao, X. A., Sasaki, A., & Hernandez-Gonzalez, T. (2022). The third wind of language learning strategies research. Language Teaching, 55, 417–421. https://doi. org/10.1017/S0261444822000015 Tseng, W. T., Dörney, Z., & Schmitt, N. (2006). A new approach to assessing strategic learning: The case of self-regulation in vocabulary acquisition. Applied Linguistics, 27, 78–102. Uhrig, K. (2015). Learning styles and strategies for language use in the context of academic reading tasks. System, 50, 21–31. https://doi.org/10.1016/j.system.2015.02.002 Usuki, M. (2000). Promoting learner autonomy: Learning from the Japanese language learners’ perspectives. ERIC Clearinghouse on Language and Linguistics. Uztosun, M. S. (2014). The impact of language learning experience on language learner strategy use in Turkish EFL context. International Journal on New Trends in Education and Their Implications, 5, 157–168. Varasteh, H., Ghanizadeh, A., & Akbari, O. (2016). The role of task value, effort-regulation, and ambiguity tolerance in predicting EFL learners’ test anxiety, learning strategies, and language achievement. Psychological Studies, 61, 2–12. https://doi.org/10.1007/s12646-015-0351-5 Véliz, M. C. (2012). Language learning strategies (LLSs) and L2 motivation associated with L2 pronunciation. Literatura y Lingüística, 25, 193–220. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. MIT Press. Vygotsky, L. S. (1986). Thought and language. MIT Press. Weinstein, C. E., Husman, J., & Dierking, D. R. (2000). Self-regulation interventions with a focus on language learning strategies. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 727–747). Elsevier Inc. Weinstein, C., & Rogers, B. (1985). Comprehension monitoring: The neglected learning strategy. Journal of Developmental Education, 9, 619–629. Wenden, A. L., & Rubin, J. (1987). Learner strategies in language learning. Prentice Hall International. Wenden, A. L. (1991). Learner strategies for learner autonomy: Planning and implementing learner training for language learners. Prentice Hall. Wenden, A. L. (1986). Helping language learners think about learning. ELT Journal, 40, 3–12. White, C. (2008). Language learning strategies in independent language learning: An overview. In S. Hurd & T. Lewis (Eds.), Language learning strategies in independent settings (pp. 3–24). Multilingual Matters. Wilczy´nska, W. (1999). Uczy´c si˛e czy by´c nauczanym? O autonomii w przyswajaniu j˛ezyka obcego [To learn or to be taught? About autonomy in foreign language acquisition]. PWN.

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Chapter 3

Research into the Role of Personality in L2 Learning

3.1 Introduction Two options for organizing the review of studies investigating the role of personality in L2 learning seem particularly appealing: linking the studies to the research paradigms discussed in Chap. 1 or classifying them according to the aspect of L2 learning which they have sought to investigate. While the former option appears alluring because of its structural appeal, it is not really feasible for two main reasons. Firstly, a discrepancy exists between the vast body of research based on psychometric inventories, such as the MBTI (Myers & Briggs, 1976) or the NEO-FFI (Costa & McCrae, 1992), and experimental research within the behavioral, humanistic, and cognitive frameworks, which is virtually non-existent. Secondly, among the studies dedicated to various aspects of personality, relatively few emphasize their explicit links to specific personality theory. For instance, frequently based on the Foreign Language Anxiety Scale (FLAS; Horwitz et al., 1986), studies into foreign language anxiety (cf. Zhang, 2019) rarely explain whether they subscribe to the psychodynamic construct of anxiety (Freud, 1923) or one of the trait models in which this ID factor is an underlying construct of neuroticism (cf. Cattell & Scheier, 1961; Costa & McCrae, 1992). Finally, since a comprehensive overview of studies investigating the impact of each of the “big” five personality traits on SLA is provided in the seminal work by Piechurska-Kuciel (2020), centering the overview around specific personality traits would not provide a substantial contribution to the existing literature. The present authors accept the view expressed by MacIntyre et al. (2007), according to which “(p)ersonality traits impinge on behavior in context, helping to shape our adaptation to that context. To emphasize the person by situation interactions, then, is to shift the focus onto the fit between the demands of language learning and the personality of the student” (p. 289). Therefore, the problem-centered approach is adopted in the present chapter. Accordingly, the studies investigating the role of personality in L2 learning and overviewed below have been grouped into the following categories: L2 use and performance, L2 attainment, specific L2 skills, L2 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6_3

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anxiety, L2 willingness to communicate (WTC), L2-related attitudes and emotions and, the use of LLS, an area which is directly relevant to the research project reported in the remainder of the book. The authors believe that such an approach is consistent with the perspective provided by Dewaele (2022), and makes it viable to account for the impact of both higher-order and lower-order personality traits on SLA and L2 performance as well as investigate the effect of specific psychological variables in specific situations or tasks. Due to space limitations, the overview is confined to studies conducted in the present century, except for the study conducted by Ehrman and Oxford (1989), focused on adult and adolescent learners, and selective. Reviews of earlier studies can be found, for example, in Krashen (1981) or Leino (1972), and an early model of personality as a variable in SLA is discussed by Lalonde and Gardner (1984). The following sections of the present chapter focus on the relationships between personality and L2 use in different contexts (Sect. 3.2), the links between personality and L2 attainment (Sect. 3.3), the role of personality in the development of specific L2 skills (Sect. 3.4), the impact of personality on various affective factors involved in L2 learning (Sect. 3.5) and the links between personality and LLs use (Sect. 3.6). Section 3.7 synthesizes the most essential findings reported in the previous sections.

3.2 Personality and L2 Use in Different Contexts A number of studies have explored the impact of personality on various aspects of L2 use. The empirical investigation conducted by Oya et al. (2004) in a group of 73 Japanese EFL learners sought to shed light on links between personality and performance in an oral test operationalized in terms of oral fluency, accuracy, complexity as well as global impression of the examiners evaluating students’ performance. The test battery included the Maudsley Personality Test (Jensen, 1958), based on Eysenck’s (1959) model of personality developed within the trait approach, the Spielberger State and Trait Anxiety Inventory (Spielberger, 1962), and a story-telling task, adapted from Wechsler’s Adult Intelligence Scale (Wechsler, 1955), employed in order to evaluate different aspects of participants’ oral performance. It was reported that no fluency, accuracy, or complexity measure significantly correlated with learners’ personality traits. At the same time, the analysis indicated that global impression of participants’ oral performance showed a significant, positive, moderate correlation with learners’ extraversion. Also, there was a significant, negative, weak correlation between learners’ state anxiety and clause rate accuracy. It was concluded that it was worth cultivating or encouraging those aspects of an extravert’s profile which could add up to an overall positive impression in spoken communication. In their thorough study of the effect of extraversion on oral performance in L2, Van Daele et al. (2006) measured the personality traits of 25 Dutch learners of French and English on the basis of their responses to the EPQ (Eysenck & Eysenck, 1975). The choice of the instrument was dictated by the preference for including a

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single dimension of psychoticism rather than dealing with agreeableness and conscientiousness separately, as well as subscribing to the reticulo-cortex arousal as the neurological explanation of extraversion (Eysenck & Eysenck, 1967). On the basis of previous studies (for instance, Dewaele & Furnham, 1999), it was expected that introverts could outperform extraverts in formal settings because of greater mental concentration ability It was also anticipated that the area in which introverts would perform better was explicit learning ability and, conversely, they would be inferior to extraverts with respect to communicative skills. Van Daele et al. (2006) were primarily interested in the effects of extraversion on the level of oral fluency, complexity and accuracy in learners L1 (Dutch), and in English, and French, learnt as foreign languages. It turned out that the measure of lexical complexity, Guiraud’s Index (Guiraud, 1959), significantly correlated with the extraversion variable. In other words, extraverts demonstrated greater lexical complexity than introverts. At the same time, no correlations were revealed between the level of extraversion and learners’ fluency, syntactic complexity or lexical and grammatical accuracy, which the researchers attributed to the specificity of research settings (that is, relaxing rather than stressful) and to the psychological characteristics of the investigated learners (that is, relatively high average extraversion scores). Ockey (2009) examined the effect of learners’ personalities on other test-takers in a group oral exam, investigating the influence of assertiveness, an underlying facet of extraversion in the FFM (Costa & McCrae, 1992). The study was conducted in a group of 113 Japanese first-year students of English, whose personality measurement involved administering the NEO-Personality Inventory Revised (NEO-PI-R; Costa & McCrae, 1992). According to the results of the study, assertive participants received higher scores than expected once grouped with non-assertive candidates, and lower scores than expected once grouped with only assertive candidates. Consequently, a recommendation was made to include guidance for evaluators on how to assess candidates in the context of a particular group and assign scores unbiased by comparisons with the performance of other group members. The role of assertiveness was re-examined by Ockey (2011) in an investigation of 360 Japanese first-year university students and augmented with insights into the impact of learners’ self-consciousness on their oral ability. The research instruments included an adaptation of the NEO-PI-R (Costa & McCrae, 1992), and the L2 Group Oral Discussion Test (Ockey, 2009). Self-consciousness was defined as the degree to which individuals experience shame, embarrassment, and social anxiety when present in a group of people, while assertiveness was explained as freedom from hesitation and assuming the function of a group leader, also regarding conversation (Costa & McCrae, 1992). Ockey (2011) hypothesized that assertiveness could facilitate L2 learning, whereas self-consciousness could be seen as an obstacle. The results of the study indicated that assertiveness was indeed predictive of oral L2 performance; however, self-consciousness was not. Moreover, covariance analysis revealed that the subconstructs of L2 oral ability were also explained by assertiveness to some degree. It was concluded that non-assertive learners could be at a disadvantage in their attempts to learn English if not assisted in building their strategy repertoires.

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Hajimohammadi and Makundan (2011) investigated the impact of Iranian students’ personalities on their performance in a writing self-correction task. The study relied on the self-reports of 120 pre-intermediate EFL learners, all of whom were female, gathered by means of the Nelson English Language Test (NELT; Fowler & Coe, 1977), and the Eysenck Personality Questionnaire (EPQ; Eysenck & Eysenck, 1975). Statistically significant differences were revealed in the effectiveness of various types of corrective feedback, and training EFL learners in self-correction influenced their subsequent performance to a greater extent than traditional top-down explicit correction offered by the instructor. No evidence was reported to confirm any significant relationship between learners’ personality traits and their progress in EFL writing. In a study focusing on the communicative aspect of EFL use, O˙za´nska-Ponikwia and Dewaele (2012) investigated the link between immigrants’ personality and the amount of interaction in EFL outside the language classroom. Subscribing to the trait approach, personality measurement was based on two instruments, the OCEAN test of personality developed by the researchers and the Trait Emotional Intelligence Questionnaire (TEIQ, Petrides & Furnham, 2003). Conducted in a group of 102 Polish adults, the study revealed that openness to experience and self-esteem constituted two significant predictors of perceived L2 achievement and correlated with the frequency of using EFL. Openness to experience was found to explain more than 7% of the variance in self-reported L2 use. At the same time, participants’ self-perceived L2 proficiency positively correlated with their levels of agreeableness, openness to experience, and empathy. Although the study was not conducted in a classroom setting, its results provide evidence for an important role of openness to experience as a trait which triggers L2 use in general. Another study which focused on immigrants, but was conducted in the L2 classroom, was conducted by Ramírez-Esparza et al. (2012) in a group 700 immigrants. It addressed the socio-interactive behaviors of the adult learners, and how they corresponded to their extravert/introvert personalities manifested in their classroom performance measured in qualitative observational analyses. Learners’ sociointeractive behaviors were coded into five category clusters, including learner’s language learning tasks, resources, engagement, personality (only regarding extra/introversion), and interaction. Importantly, they were also linked to the learners’ educational background. The results of the study revealed that low-education learners displayed more introvert behaviors and achieved significantly lower test scores. In particular, introversion also significantly correlated with taking up the novice role, but the tendency decreased along with an increase in learning experience. In a study focused on various aspects of perception and expression of emotions in L2 English, more thoroughly discussed in (Sect. 3.4), O˙za´nska-Ponikwia (2013) explored several relationships linking the reported frequency of L2 use by 137 Polish immigrant EFL learners and their emotional intelligence (EI), established on the basis of their responses to Petrides and Furnham’s (2003) TEIQ. It was found that the use of English in various social situations, such as talking to relatives, or relying on it at work, positively correlated with several EI traits, including self-esteem, stress management, adaptability, and well-being as well as participants’ global EI levels.

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The impact of the personality traits of 164 Taiwanese learners on their English use on Facebook (EUF) and test achievement was investigated by Kao and Craigie (2014). Learners’ personality was established on the basis of an adaptation of the Big Five Inventory (John et al., 1991), whereas EUF was assessed on the basis of participants’ answers to the English Usage on Facebook Inventory for Language Learning (EUFILL; Kao & Craigie, 2014). Test achievement was operationalized as informants’ results in the General English Test. It turned out that extraversion moderately correlated with the frequency of EUF and conscientiousness showed a weak relationship with it, which was attributed by the researchers to the willingness of relatively more conscientious learners to actively engage in the search for online resources facilitating language learning. In the case of neuroticism, the relationship with EUF was weak and negative. No significant results were reported in terms of the levels of openness to experience. Also, highly neurotic participants’ scores were significantly worse than the results of respondents characterized by low or middle levels of the trait, which could likely be attributed to the situational anxiety they experienced. Liang and Kelsen (2018) investigated the influence of personality and motivation on oral presentation performance in a group of 257 Chinese undergraduate students learning ESP at various colleges. Participants’ personality traits were measured on the basis of their responses to the Chinese version of the Big Factor Inventory (BFI; Benet-Martinez & John, 1998; John et al., 1991), while their performance on oral presentations was assessed on the basis of peer rating conducted in teams of 3–6. The final research instrument employed in the study was the Collaborative Inquirybased Project Questionnaire (CIPQ; Chow & Law, 2005), which offered insights into the participants’ motivation in the context of FLL. The students’ performance in oral presentations significantly correlated with their levels of extraversion, and the trait also turned out to be the strongest predictor of learners’ performance in oral presentations. These results led to the conclusion that extraverted students performed well in oral communication and that, especially in the case of lower-level learners, extraverted personalities can compensate for shortages in English language ability.

3.3 Personality and L2 Attainment Several studies have aimed to address the impact of personality on of L2 attainment, operationalized in various way. The growing need to order and typify individual learner variables in L2 learning was addressed in the study conducted by Onwuegbuzie et al. (2000), who considered the influence of cooperativeness, competitiveness, individualism, and locus of control on learners’ attainment in an investigation of 184 students from US universities enrolled in L2 courses in courses in Spanish, French, German, or Japanese. Personality variables were used as one of four groups of predictors of L2 achievement in the study; however, the investigation also incorporated measures of foreign language anxiety, perceived intellectual ability, perceived scholastic competence, and perceived self-worth, all four of which can be classified

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as affective variables. The battery of tests consisted of the Foreign Language Anxiety Scale (Horwitz et al., 1986), the Self-Perception Profile (Neemann & Harter, 1986), the Social Interdependence Scale (Johnson & Norem-Hebeisen, 1979), the Academic Locus of Control Scale (Trice, 1985), and the Study Habits Inventory (Jones & Slate, 1992). The results of the study indicated that two of the variables investigated by the researchers in the personality group, that is, individualism and cooperativeness, significantly correlated with L2 achievement; however, the strength of these correlations was weak. At the same time, more than one third of the variance in language achievement was explained by five variables, including cooperativeness, one of the lower-order personality variables. In a large-scale investigation of 500 distance learners of French, Hurd (2006) examined the links between the perception of the language learning experience and personality self-perception at The Open University (UK). Overall, one of the aims of the study consisted in establishing the set of personality traits which could facilitate the accomplishment of online language courses. On the basis on an initial assumption that distance learners should have a relatively high degree of self-regulation, an attempt was made to link the degree of self-regulation with learners’ self-reported personality traits. The research instruments included two questionnaires consisting of lists of personality adjectives in which the participants were asked to indicate those which they deemed helpful in distance language learning and those that they considered to be their own characteristics as well as a set of interviews and think-aloud verbal protocols. On the basis of the insights from the data provided by the participants, a rank of personality features facilitating distance language learning was established. It included 17 characteristics, the most frequently mentioned of which, reported at the beginning and at the end of the course, included being motivated, enthusiastic, persistent, systematic, and self-confident. The set of the above adjectives was only slightly different in informants’ self-descriptions as language learners. While motivation, enthusiasm, and persistence continued to occupy positions 1–3, communicativeness and independent mindedness were reported as self-characteristics ranked 4 and 5 in the initial study. In a quantitative study relying on 89 Flemish learners’ responses to the abbreviated Eysenck Personality Questionnaire (EPQr, Eysenck et al., 1985) and the FLCAS (Horwitz et al., 1986), Dewaele (2007) traced the relationships between language learners’ personality characteristics and their grades in foreign language courses. While no significant effects were found for the three higher-order traits of extraversion, psychoticism, and neuroticism, the study revealed that language learners characterized by high levels of LA obtained significantly lower grades in the L2 and L3. At the same time, strong, positive correlations existed between grades obtained by the participants of the study in courses of multiple languages. The results indicate that while personality cannot simply be used as a predictor of language learning attainment, experiencing LA might not be context-dependent but, rather, result from enduring predispositions. Ehrman’s (2008) study conducted in a group of adult advanced learners of Chinese, French, German, Hebrew, Indonesian, Italian, Korean, Lao, Portuguese, Russian, Spanish, Swedish, and Turkish, aimed to account for the psychological profile of

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good language learners on the basis of participants’ responses to an adapted MBTI (Myers et al., 1998). The respondents were selected from the database of more than 3,000 records of the Foreign Service Institute (FSI) on the basis of the results of the FSI oral proficiency interview, which incorporated speaking, interactive listening, and interactive reading tests. Intuition1 was found to be the distinguishing quality of high achievers in L2, which was linked to the propensity of intuitive language learners to concentrate on meaning and their ability to respond to change, consisting in identifying patterns in the language learnt and making associations. Also, it was pointed out that being intuitive involved a high degree of receptiveness to peripheral learning, manifesting itself, for instance, in the ability to adapt to unfamiliar ways of speaking in the language learnt, or acquiring native-like ways of self-expression. Among intuitive learners, high achievers turned out to exhibit a preference for thinking rather than feeling, which was attributed to their pursuit of excellence, requiring goal setting skills and a certain degree of self-regulation, especially in self-assessment and self-monitoring. In a study accounting for predictors of near-native ability in L2, conducted in a group of young adults (18–29 years of age), Doughty et al. (2010) initially incorporated tolerance of ambiguity (TOA) among a number of factors that could possibly impinge on language ability. Defined as “the ability to keep contradictory or incomplete input in memory” (p. 18), TOA was assessed on the basis of participants’ responses on a scale developed on the basis of earlier works investigating the construct (Budner, 1962; Norton, 1975; Webster & Kruglanski, 1994). While the items extracted from three instruments measuring TOA were all correlated, and all loaded on the same factor, the trustworthiness of participants’ self-reports was called into question due to their performance on the lie scale. Consequently, while TOA was found to be a significant predictor of L2 ability, the researchers argued that a new, behavioral instrument assessing TA should be developed and ultimately decided to remove TOA from the battery measuring L2 ability. Khodaddy and Zabihi (2011) explored the relationships between the school achievement of 419 students majoring in English or Persian, their cultural and social background, and their personality characteristics using their grade point averages (GPAs), various measures of learners’ social background, as well as the Persian adaptation of the NEO-FFI (Costa & McCrae, 1992). A significant difference in GPAs existed between English and Persian majors along with significant differences in income levels in their families. With regard to personality traits, openness to experience turned out to be a positive correlate of English learners’ GPAs, which was attributed to the benefits of being more open to both the language and culture of the TL, and, possibly, relying on a wider repertoire of strategies employed in the learning process. At the same time, the relationship between English learners’ conscientiousness and their GPAs was not confirmed. The findings provide support for the assumption that language learning is a distinctive area of education, in which

1

This dimension in the post-Jungian personality framework has been found to significantly correlate with the level of openness to experience in the FFM Model (McCrae & Costa, 1989).

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it is openness to experience rather than conscientiousness that can be viewed as a predictor of attainment. In a study into the role of personality as a predictor of L2 proficiency, Ghapanchi et al. (2011) investigated the relationship between 141 Iranian EFL university students’ levels of personality traits, determined on the basis of the Transparent Bipolar Inventory (Goldberg, 1992), and participants’ self-rating of their listening, speaking, reading, and writing skills. In order to account for the impact of motivational variables on L2 proficiency, the researchers also relied on Papi’s (2010) framework for investigating the L2 motivational self system. Overall, it was found that the levels of two personality traits, extraversion and openness to experience, exerted a significant impact on learners’ self-rated L2 (English) proficiency. At the same time, the amount of variance in self-reported L2 proficiency was considerably higher in a regression model incorporating motivational variables than in the model exclusively relying on learners’ personality traits as explanatory variables. Kao (2012) explored the relationships between 137 Taiwanese students’ personality traits, measured by the Chinese adaptation of the Big Five Inventory (John et al., 1991), their feeling of loneliness, established on the basis of their responses to the UCLA Loneliness Scale (Russell et al., 1980), and their EFL scores in the National University Entrance Examination. Three statistically significant findings were reported with respect to participants’ personality traits. The levels of conscientiousness and agreeableness positively correlated with EFL achievement while neuroticism turned out to be its negative correlate. Learners’ scores in the EFL test were also significantly and negatively affected by their experience of loneliness, which was attributed to the scarcity of social interaction, including interaction with other language learners, experienced by students reporting loneliness. Already referred to in Sect. 3.2, the study conducted by O˙za´nska-Ponikwia (2013) also resulted in the identification of some major personal characteristics correlating with participants’ self-perceived proficiency level in EFL. Among them, constructs investigated by the Perception and Expression of Emotions in the L1 and L2 instrument, developed for the purpose of the study, involved change of attitudes toward L2, expression of emotions in English, and L2 dominance. Additionally, participants’ openness to experience and agreeableness were measured on the basis of informants’ responses to the IPIP (Goldberg et al., 2006), and related to their selfperceived proficiency in English. It was concluded that EFL immigrant learners who perceived themselves as proficient tended to be friendly, cooperative, imaginative, creative, and eager to engage in cultural and educational experiences. The links between self-rated proficiency, FLCA, determined on the basis of responses to the FLCAS (Horwitz et al., 1986) and second language tolerance of ambiguity (SLTA), assessed on the basis of Second Language Tolerance of Ambiguity Scale (SLTAS; Ely, 1995), were investigated by Dewaele and Shan Ip (2013) in a study of 73 Chinese adolescent and adult EFL learners. The results of statistical analyses revealed that both FLCA and SLTA were valid predictors of self-rated proficiency, accounting for more than a half of the observed variance. At the same time, it needs to be pointed out that both explanatory variables were largely intercorrelated. Overall, it was suggested that low levels of FCLA and high levels of SLTA might

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boost L2 learners’ confidence as well as positively impact their curiosity and interest in the language learnt, which, in turn, might facilitate language achievement. In a study conducted in a group of 128 undergraduate students of linguistics, Novikova et al. (2020) sought to establish the relationship between participants’ personality traits, assessed on the basis of the Russian adaptation of the NEO-FFI (Costa & McCrae, 1992), and FL achievement in English, measured on the basis end-of-semester grades and the Foreign Language Proficiency Scale (FLPS). The FLPS was developed by the researchers for the purpose of the study, in an attempt to account for EFL skills of listening, reading, writing, and speaking, but at the same assessing the range of learners’ vocabulary, communicativeness, and pronunciation. Based on the outcomes of regression analysis, conscientiousness turned out to be the sole significant predictor of L2 proficiency among the “big” five personality traits. Interestingly, the areas of assessment on which learners’ levels of conscientiousness were found to have an impact included not only the total score and diligence, but also creativity. Even though TL attainment should be carefully distinguished from language learning aptitude (LLA), or a flair for learning additional languages, it also makes sense to mention here the study by Biedro´n (2011) which explored the relationships between personality traits, measured by the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 1998), LLA, measured by the Modern Language Aptitude Test (MLAT; Carroll & Sapon, 2002), and the Language Ability Test (LAT; Wojtowicz, 2006). The results of the analysis of the data collected from two groups of participants, 44 gifted, and 46 non-gifted students, cast new light on personality as a predictor of LLA. On the one hand, no statistically significant differences in the levels of the “big” five personality traits were detected between the two groups, but, on the other hand, a number of statistically significant correlations were revealed between the level of personality traits and participants’ language aptitude in the group of 46 non-gifted learners. These correlations indicated a moderate relationship between the subcategory of the MLAT referred to as grammar and vocabulary, and openness to experience and negative, moderate correlations between two MLAT constituents, that is, number learning and paired associates, and the level of neuroticism. Apart from that, multiple regression indicated that a number of personality traits were in fact valid predictors of L2 aptitude. Openness to experience was the strongest positive predictor, whereas extraversion affected L2 aptitude negatively. The other personality traits exerted an influence on language aptitude with regard to specific components of MLAT and LAT: it was positive for conscientiousness, and negative for neuroticism.

3.4 Personality and Specific L2 Skills Some SLA researchers have also attempted to determine links between personality traits and the mastery of different TL skills. Among such skills, the most emphasis has been placed on the extent to which personality affects learners’ speaking. Such

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a situation results from the historically well-established position of the extraversion/introversion dimension in personality models (Freud, 1923), the importance attached to it in contemporary mainstream personality research paradigms (Costa & McCrae, 1992; Myers & Briggs, 1976; Widiger (Ed.), 2017), and the involvement of speaking-related characteristics as the underlying traits of the E/I dimension in trait theorists’ models of personality (Costa & McCrae, 1985, 1992; Eysenck & Eysenck, 1967). Dewaele and Furnham (2000) examined the effect of extraversion and, possibly, its correlates, such as short-term memory and stress resistance, on individual variation in speech production of 25 Flemish learners of French. The level of the trait was measured by the Eysenck Personality Inventory (EPI; Eysenck & Eysenck, 1964) while speech production was analyzed in both stressful and non-stressful situations (that is, oral exam settings and neutral settings, respectively). Statistically significant, positive correlations with the level of extraversion were found for the constructs of implicit speech style and speech rates in both types of settings, while negative correlations were detected for lexical richness and the proportion of the ‘er’ utterance in the exam situation only. This was attributed to the difficulties which introverts might experience in trying to maintain the level of automaticity of speech production in stressful conditions involving being tested or observed. It was suggested that under those circumstances introverts were forced to rely more on working memory, which was likely overloaded. Also, their choice of a more explicit speech style resulted in an intensified search for relatively infrequent lemmas and, consequently, led to the overburdening of their cognitive resources as well as impaired their speech fluency. In another study investigating EFL learners’ speaking skills, Khany and Ghoreyshi (2013) explored the links between 217 adolescent and adult Iranian students’ personality traits, established on the basis of their responses to the Big Five Inventory (John et al., 1991) and their foreign language speaking confidence (FLSC), measured by means of the Foreign Language Speaking Confidence Scale (FLSCS; Apple, 2011) and incorporating six dimensions of foreign language classroom speaking anxiety, perceived foreign language speaking self-competence, desire to speak English, past English classroom experiences, current English classroom perception, and perceived social value of speaking English. According to the outcomes of statistical analyses, all personality trait levels were found to be significant predictors of participants’ FLSC. While the levels of four out of five traits, that is, extraversion, openness, conscientiousness, and agreeableness, positively corresponded with participants’ FLSC, neuroticism was found to be a negative correlate. Extraversion proved to be the strongest FLSC predictor, which was attributed to extraverts’ propensity to engage in classroom tasks resembling social activities. While investigating the impact of learners’ personality characteristics on their oral performance has been a relatively popular research area, studies investigating the influence of personality on the other L2 skills have been relatively scarce. In one of them, Fayyaz and Kamal (2011) investigated the relationships between Pakistani learners’ metacognitive listening skills and their personality traits in two phases, including a pilot study and a main study using amended personality measurements. The main study was conducted in a group of over 300 students and involved the

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use of the Metacognitive Awareness Listening Questionnaire (MALQ, Vandergrift et al., 2006) and a Pakistani adaptation of the NEO-FFI (Costa & Mccrae, 1992) for personality measurement. Its main purpose consisted in providing insights into the affective domain of listening comprehension as an L2 skill. Overall, total MALQ scores showed a significant negative correlation with neuroticism scores while the relationship between listening performance and extraversion, openness to experience, and conscientiousness levels turned out to be positive. The researchers speculated that improving language learners’ self-perceptions could result in boosting their listening performance, and the importance of the listening skill should be emphasized, particularly in times of a ubiquitous emphasis on developing L2 learners’ speaking skills. In an innovative study into college learners’ of English performance in EFL writing, He (2019) investigated the predictive power of lower-level personality traits, established on the basis of the Personality Facet Scale (PFS; Soto & John, 2009). On the basis of personality self-reports gathered from 201 English majors and the evaluation of their essays, based on a six-category rubric involving content, organization, style/quality expressions, language use, mechanics, and length of text (He et al., 2013), it was found that two facets of conscientiousness, that is, self-discipline and order, and one facet of extraversion, that is, activity, significantly predicted participants’ performance in writing tasks. These findings were attributed to the relevance of the three characteristics to learners’ ability to regulate their writing efforts and systematize their writing tasks as well as the positive impact of high levels of conscientiousness on academic achievement in general (cf. Dörnyei & Ryan, 2015; Jackson & Roberts, 2017). While the study conducted by Jackson and Park (2020) also addressed the relationships between EFL writing and learners’ personality, the researchers expanded the design of their investigation by incorporating the construct of SR in writing as well as accounting for the trait and state perspectives on personality. Data were collected from 645 Japanese university students majoring in English, Asian languages, and international communication. The research instruments included a writing-oriented adaptation of Tseng et al.’s (2006) SRCVOC, encompassing six SR subscales of controlling commitment, metacognition, satiation, emotions, and the learning environment, items measuring participants’ conscientiousness and neuroticism, extracted from DeYoung et al.’s (2007) conceptualization of the Big-Five Model, and a selfreported writing ability scale. Statistical analysis showed that conscientiousness significantly contributed to learners’ SR in writing while neuroticism was found to have a negative impact on it. The levels of the conscientiousness and neuroticism were also found to affect learners’ self-reported writing ability in a positive and negative manner, respectively. The results of the study definitely support the claim that L2 writing is a skill whose development substantially depends on both learners’ personal characteristics and their ability to self-regulate.

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3.5 Personality and Affective Variables A considerable body of research into the role of personality in SLA has explored the relationship between individuals’ traits and various affective aspects involved in L2 learning, such as FLA or communicative anxiety (CA). This is not really surprising since, as aptly pointed out by Piechurska-Kuciel (2018, p. 193), “(t)he language learning experience (…) threatens the learner’s ego, and requires a great deal of personal investment, concentration, patience, and active involvement”. In one study into the effects of trait EI on FLA, conducted in a group of 464 multilinguals, Dewaele et al. (2008) investigated how the constituents of EI affected L2 learners in five situations, including oral communication with friends, colleagues, strangers, on the phone, and in public. EI was assessed on the basis of participants’ answers to the Trait Emotional Intelligence Questionnaire–Short Form (TEIQueSF; Petrides & Furnham, 2006), and the Bilingualism and Emotion Questionnaire (BEQ; Dewaele & Pavlenko, 2001-2003) while FLA was assessed on the basis of participants’ self-reported anxiety levels under specific circumstances of speaking in different languages, different types of interlocutors, and in different situations. The study revealed that high levels of trait EI correlated with significantly lower FLA reports. In a study conducted in a group of 148 adult language learners of multiple languages, Dewaele (2013) sought to establish links between participants’ personality traits, measured by the revised version of the Eysenck Personality Questionnaire (EPQr; Eysenck et al., 1985), and language anxiety, determined on the basis of responses to the FLCAS (Horwitz et al., 1986). Language anxiety (LA) was found to significantly correlate with participants’ levels of neuroticism, but the correlation was negative, which means that more emotionally stable informants of the study experienced LA to a lesser degree. Overall, FLCA and neuroticism shared between 9 and 25% of variance. Also, since strong, significant correlations were detected between LA levels in multiple languages, it was assumed that LA levels remain relatively stable across languages. In the study already referred to earlier in this chapter (see Sect. 3.2), O˙za´nskaPonikwia (2013) explored the relationships between the personality traits Polish EFL learners living in the UK and Ireland, their perceptions and expression of emotions in L1 (Polish) and L2 (English), and their trait emotional intelligence. The levels of the “big” five personality traits were measured on the basis of informants’ responses to the IPIP (Goldberg et al., 2006), while their levels of emotional intelligence were established on the basis of their responses to Petrides and Furnham’s (2003) TEIQ. The assessment of perception and expression of emotions in L1 and L2 relied on a research instrument constructed for the purpose of the study and incorporating eight dimensions: change of attitudes towards the L2, difficulties in the perception and expression of emotions in L2, feeling different when using L2, L2 use, expression of emotions in L2, expression of emotions in L1, L2 dominance, and L1 dominance. In terms of the relationships between participants’ personality traits and their perception and expression of emotions in L1 and L2, statistically significant, positive correlations

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were detected between their levels of extraversion/openness on the one hand and feeling different when using L2 as well as the actual L2 use on the other hand, and their levels of agreeableness and feeling were different when using L2. At the same time, the levels of neuroticism turned out to be a significant, negative correlate of informants’ difficulties in the perception and expression of emotions in L2 as well as their expression of emotions in L1. Additionally, numerous statistically significant correlations were found between the subscales of the TEIQ (Petrides & Furnnham, 2003), and the subscales of perception and expression of emotions in the L1 and L2 (O˙za´nska-Ponikwia, 2013). It was concluded that sociable and emotionally skilled individuals could have a flair for noticing even relatively subtle changes in personality and behavior when using L2, which, in turn, might make them more aware of their own linguistic repertoires. Shao et al. (2013) explored the links between 500 Chinese students’ EI, measured by the Trait Emotional Intelligence Questionnaire–Short Form (TEIQue– SF; Petrides & Furnham, 2006), their LA, measured by the FLCAS (Horwitz et al., 1986), their achievement in English, determined on the basis of the results of the College English Test, and their self-rated proficiency in English. Statistically significant, positive correlations were detected between EI and achievement measured by the CET, and EI and self-rated proficiency while statistically significant, negative correlations were revealed between FLA and achievement as well as self-rated proficiency. Also, statistically significant, yet weak, mediating effects of FLA were revealed, both between EI and English achievement and between EI and informants’ self-rated English proficiency. These results certainly testify to the relevance of learners’ personal characteristics for L2 learning. Attempts have also been made to link personality traits to other affective variables in FLL, such as attitudes or beliefs held by L2 learners about the learning process or willingness to communicate (WTC) in L2. In one of them, Pourfeiz (2015) examined the relationships between 157 Turkish students’ of English self-reported global personality traits, measured by the International Personality Item Pool (IPIP; Goldberg et al., 2006) and their attitudes towards L2 learning, assessed by means of the Attitudes towards Foreign Language Learning inventory (A-FLL; Vandewaetere & Desmet, 2009). The study yielded a number of conclusive results. Not only were statistically significant, positive correlations found between the levels of the “big” five personality traits and attitudes towards L2 learning, but also significant relationships were detected between the cognitive, affective/evaluative, behavioral, and personality components of A-FLL and the five personality traits. Openness to experience turned out to be the strongest predictor of the cognitive component, while emotional stability, agreeableness and openness to experience accounted for a large proportion of variance of the behavioral/personality component. Also, conscientiousness, agreeableness, emotional stability and openness to experience were all significant predictors of the affective/evaluative component. Specifically, the lower the level of emotional stability was, the more challenging it became for the participants to feel positive about learning L2 English and the more likely they were to succumb to anxiety.

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The qualitative study conducted in a group of 10 learners of English studying in the USA by Coker and Mihai (2017) provided a number of interesting personality-related insights regarding L2 learners’ attitudes and forms of interaction with L2 teachers and other course participants. Measured by the ENNEAGRAM (Riso & Hudson, 1996), personality was found to strongly influence how participants interacted with each other and with their teacher. Type 1 learners, labeled perfectionists, stayed focused on the goal, but also preferred secure situations and structured activities. Type 2 learners, referred to as helpers, were eager participants in group activities and enjoyed helping others. Type 3 participants, called achievers, pursued their aim to succeed in learning the language, but also demonstrated leadership skills. Finally, Type 4 learners, known as leaders, felt responsible for other members of the group and disapproved of any manifestations of laziness of other group members. Two recommendations were made on the basis of the results. Firstly, it was emphasized that L2 teachers need to create an environment where each student could actually benefit from their personal characteristics. Secondly, the awareness of their own weaknesses, which could be referred to as person knowledge (see Sect. 2.5.2), helped the participants understand their reactions in different learning situations, but also equipped them with the ability to improve their study habits. With respect to willingness to communicate, Oz (2014) examined the links between this construct and personality traits on the basis of self-reports of 168 preservice 168 EFL. Two instruments were used, that is, the Willingness to Communicate Scale (WTCS) (McCroskey & Richmond, 1987), and the International Personality Item Pool (IPIP, Goldberg et al., 2006). The results indicated a moderate correlation between the desire to talk to strangers and learners’ self-reported extraversion, as well as statistically significant, positive correlations between extraversion (a strong relationship), agreeableness (a moderate relationship), and openness to experience (a weak relationship) and WTC. Also, agreeableness was found to moderately correlate with educational achievement. The results of the study differed significantly for male and female participants for two personality dimensions, that is, emotional stability and agreeableness. It can be inferred on the basis of the findings that students who are open, sociable, and person-oriented as well as friendly, curious, and creative are more likely to communicate in English. In a qualitative study examining EI within the context of positive psychology interventions, Gregersen et al. (2014) sought to account for the role of EI and combined insights from a learner and teacher perspective. Basing on Salovey et al.’s (2002) EI model, the researchers analyzed participants’ EI in terms of its four dimensions, that is emotion perception and expression, emotional facilitation of thought, emotional understanding, and emotional management. Qualitative analysis was largely based on insights from two participants characterized by the most pronounced movement toward attaining their possible future L2 selves. It was suggested that understanding how to make use of EI by any participant of the language learning process required the ability to engage in in-depth analysis of emotional experiences, inside and outside the classroom. Also, strategic ordering of learning activities encouraged the participants to savor their good experiences as well as triggering learning optimism.

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Finally, emotional awareness turned out to be essential in facilitating participants’ understanding of their own emotions and emotional self-regulation. In a study conducted in a group of 348 Arabic learners of English, Dewaele and Saraj (2015) explored the relationships between informants’ LA, measured by means of the Arabic Foreign Language Anxiety Questionnaire (AFLAQ; Al-Saraj, 2014), and their levels of cultural empathy, open-mindedness, social initiative, emotional stability, and flexibility, established on the basis of the Multicultural Personality Questionnaire-Short Form (MPQ-SF; Van der Zee et al., 2013). According to the outcomes, self-perceived proficiency in oral English and self-reported frequency of the use of English were valid predictors of LA, accounting for over a third of the observed variance. Also, two of the investigated traits, that is, emotional stability and social initiative, were found to explain 20% of the variance in LA. In short, relatively more proficient participants tended to be less anxious and relatively more neurotic, whereas more introverted participants reported experiencing greater language anxiety. Gargalianou et al. (2016) conducted a study into L2 anxiety in specific business contexts, in order to account for the differences in LA levels among learners varying in terms of the levels of personality traits. Data collected from 320 Dutch adults learning English as L2 were obtained from the responses to the FLCAS (Horwitz et al., 1986), and the HEXACO Personality Inventory-Revised (HEXACO-PI-R; Lee & Ashton, 2004), distinguishing six personality traits of emotionality, conscientiousness, extraversion, agreeableness, openness to experience, and honesty/humility. The latter tool was primarily chosen for its refinement of the emotionality factor. Statistically significant, positive correlations were revealed between participants’ LA and their levels of emotionality and conscientiousness, while a negative, significant correlation was detected between LA and extraversion. Also, gender was found to be a variable mediating the relationship between LA and personality, with female participants being significantly more emotional and conscientious. The outcomes of the study were partly attributed to the conceptual framework of emotionality in the HEXACO PI-R (Lee & Ashton, 2004) since emotionality incorporates, among other underlying facets, trait anxiety. Therefore, the results also partly corroborate Dewaele’s (2013) study, linking LA to trait neuroticism. In a study of over 500 Polish adolescents and young adults, Piechurska-Kuciel (2018) investigated the role of openness to experience in shaping WTC in L2 learning. The level of the trait was measured by means of a 20-item constituent scale of the IPIP (Goldberg, 1990) while participants’ WTC was tapped into by the Willingness to Communicate in the Classroom Scale (MacIntyre et al., 2001), consisting of four subscales dedicated to specific language skills. The results of the study confirmed the hypothesized positive relationship between both constructs as well as a negative relationship between the level of openness to experience and the level of language anxiety, as indicated by the employed regression model. Also, the participants who were relatively more open, tended to get significantly better final grades in EFL courses. It was also concluded that students who were relatively less open to experience might encounter more difficulties when attempting to tackle linguistic idiosyncrasies, communicative shifts, and ambiguity involved in L2 learning processes,

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which, in turn, makes them susceptible to experiencing tensions and feelings of insecurity. Vural (2019) investigated 1845 Turkish university students majoring in English linguistics and literature and ELT in an attempt to explore the link between personality traits, assessed on the basis of the Big Five Inventory (John et al., 1991) and FLA, established on the basis of participants’ responses to the FLCAS (Horwitz et al., 1986). A number of statistically significant correlations were reported, including the negative relationships between LA and the levels of extraversion, openness and conscientiousness, and positive correlations between LA and the levels of agreeableness and neuroticism. Also, apart from openness, all the traits were significant predictors of FLA, positive in the case of agreeableness and neuroticism, and negative in the case of extraversion and conscientiousness. It was suggested that students with high levels of extraversion might develop better strategies for coping with LA by stabilizing their emotions as well as cooperating and empathizing with others and, particularly when accompanied by high levels of openness, positively affect language learners’ confidence and self-esteem. In a similar, yet comparative, study conducted in two groups of 270 Moroccan and 257 Koreans undergraduate students of various faculties learning English as L2, Babakhouya (2019) investigated personality traits, measured by means of the IPIP (Goldberg, 1999), as predictors of foreign language speaking anxiety (FLSA), assessed on the basis of informants’ responses to 18 items extracted from the FLCAS (Horwitz et al., 1986). Statistical analyses indicated that low levels of openness and high levels of neuroticism were the strongest predictors of FLSA in both groups of participants. The researcher concluded that investigating students’ personal characteristics might actually prove substantial support in predicting anxiety issues. In a large-scale study into foreign language enjoyment (FLE) and foreign language anxiety (FLA), Dewaele and MacIntyre (2019) looked for links between the two constructs and 750 language learners’ multicultural personality traits. Participants were students of English, French, Spanish, German, and Japanese, most of whom studied in Europe. The informants’ personal characteristics were assessed on the basis of their responses to the Multicultural Personality Questionnaire (MPQ, Van der Zee et al., 2013), designed to measure five personality dimensions relevant to multicultural success, that is, cultural empathy, open-mindedness, social initiative, emotional stability, and flexibility. Enjoyment was measured through participants’ responses to ten items selected from the Foreign Language Enjoyment Questionnaire (Dewaele & MacIntyre, 2014), while anxiety was tapped into by means of eight items extracted from the FLCAS (Horwitz et al., 1986). Quantitative analysis was supplemented with the students’ accounts of enjoyable episodes in FL classes and descriptions of episodes which in their view resulted in situational anxiety. Correlational analyses confirmed that FLE and FLCA were separate dimensions, but it was also inferred from multiple regression analyses that while FLE was mostly predicted by teacher-related variables, FLCA largely depended on informants’ levels of emotional stability. Consequently, it was concluded that FLE was more context-dependent than FLCA, and suggested that FL instructors should focus on facilitating FLE rather than attempting to counteract FLCA.

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Similar results were obtained by Šafranj and Zivlak (2019), who carried out a study into the effects of the “big” five personality traits, measured by means of the IPIP (Goldberg, 1999), and fear of negative evaluation, assessed by the short version of the Fear of Negative Evaluation Scale (FONES; Leary, 1983), on FLA, determined on the basis of responses to the FLCAS (Horwitz et al., 1986). Based on insights from 296 English for specific purposes (ESP) students of engineering, statistical analyses revealed that both general FLA and its three subcomponents of communication apprehension, fear of feedback by peers and teachers, and fear of language tests were significantly predicted by participants’ levels of neuroticism. At the same time, it was found that high levels of conscientiousness had a significant impact on the level of communication apprehension. This finding was linked to the concerns experienced by highly conscientious individuals willing to make a positive impression on others through, for instance, demonstrating knowledge in the language classroom. A mixed-methods study exploring the links between 768 secondary- and tertiarylevel European EFL learners’ trait EI and positive and negative emotions in first and foreign language classes was conducted by Resnik and Dewaele (2020). The research instruments included the adapted the Trait Emotional Intelligence Questionnaire— Short Form (TEIQue-SF; Petrides, 2009) a set of 20 items extracted from the Foreign Language Enjoyment Scale (Dewaele & MacIntyre, 2014) as well as 8 items extracted from the FLCAS (Horwitz et al., 1986). LE and LA turned out to be negatively correlated, and, at the same time, higher levels of EI were linked to higher levels of enjoyment in EFL classes as well as lower LA. It was concluded that while L2 learners were likely to experience both positive and negative emotions in class, their performance in class largely depended on their EI. The outcomes of the study were later corroborated by another empirical investigation conducted by Resnik and Dewaele (2021) in a group of 510 students learning EFL in online language courses.

3.6 Personality and the Use of LLS Given the main focus of the present volume, the most relevant to the research project reported in the subsequent chapter are studies that have sought explore the relationship between different facets of personality and the use of LLS. Before a selective overview of the existing empirical evidence is offered several observations of general nature are in order. First, it should be pointed out that empirical investigations of this kind are still few and far between, which dictates that any revealed patterns and relationships should be viewed with considerable circumspection. Second, researchers have employed sometimes quite disparate instruments to collect data on both L2 learners’ personality traits and their reported use of LLS, which precludes making definitive interpretations or generalizations. Third, relatively few, more recent studies have adopted the FFM (Costa & McCrae, 1985, 1992) as basis for establishing personality traits, with previous research typically opting for the MBTI (Myers & Briggs, 1976). Fourth, in the majority of cases, Oxford’s (1990) SILL was used to tap into the

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use of strategies, with more recent conceptualizations of the construct in terms of the complex dynamic systems theory (CDST) and self-regulation (Oxford, 2017) largely being ignored. Fifth, the bulk of research striving to link personality of LLS use has focused on the role of the extraversion/introversion dimension giving considerably less attention to other personality factors. Sixth, to the best knowledge of the present authors, no attempt has been made thus far to identify clusters of personality factors and LLS that would allow identification of distinct learner profiles, which surely speaks to the novelty of the study described later in this book. In an early study, Ehrman and Oxford (1989) used the long version of the SILL and the MBTI to collect data on personality traits (psychological types) and strategy use from 78 adult learners with different professional backgrounds and attending different language courses. The analysis showed, among other things, that extraverts were more likely than introverts to resort to affective strategies as well as strategic devices based on visualization, whereas introverts reported searching for and communicating meaning more frequently. Several other interesting findings were reported: intuitive learners more often fell back on authentic L2 use and affective strategies than sensing learners; at the same time, judgers reported more frequent use of general strategies (for instance, previewing lessons) than perceivers, who manifested a tendency to use LLS for searching for and expressing meaning. The same data collection instruments or adaptations thereof were later employed in a number of other studies, such as those undertaken by, for example, Wakamoto (2000), Bielska (2006), Sharp (2008), Chen and Hung (2012), or Zhou and Intaraprasert (2015). The study conducted by Wakamoto’s (2000) involved 254 junior college students in Japan who were majoring in English. It was revealed that extraversion correlated with functional practice strategies, such as those applied to enhance accuracy with respect to grammar and pronunciation, and socio-affective strategies, whereas no such relationships were uncovered in the case of introversion. Participants of the empirical investigation carried out by Bielska (2006) were 381 Polish secondary school L2 English learners. The most important findings were as follows: extraverts reported using some specific metacognitive, affective and social LLS more frequently than introverts; learners representing the feeling type tended to employ social strategies more often than those characterized by the thinking type; and students of the judging type superseded those of the perceiving type in overall strategy use. Sharp (2008) investigated the link between personality and the application of LLS among 100 undergraduate students in Hong Kong. Correlational analyses showed that introversion was negatively related to the reported use of social strategies and positively related to the use of cognitive strategies in this context. These findings failed to be corroborated in a more recent study undertaken by Chen and Hung (2012) among 364 senior high school learners of L2 English in Taiwan. This is because in this case extraverts proved to be more frequent users of all the six categories of strategies included in the SILL than introverts. Similar tendencies were reported by Zhou and Intaraprasert (2015) among 863 Chinese English majors in a teacher training program. More specifically, extraverted participants reported using metacognitive, cognitive, affective and social strategies more often than introverts.

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In addition, students representing the judging type proved to be more frequent users of some strategic devices than those characterized by the perceiving type. There are also empirical investigations that have relied on alternative measures of personality and in some cases also LLS use, looking at strategic learning with respect to specific areas of L2, such as particular L2 skills, and also embracing the concept of self-regulation. For example, Liyanage and Bartlett (2013) used the Eysenck Personality Questionnaire (Eysenck et al., 1985) and the SILL to collect data from 948 secondary school students learning English in Sri Lanka. The analysis showed that extraversion and introversion constituted the strongest predictors of preferences concerning strategy use, in particular for learners characterized by low neuroticism. This tendency was the most pronounced in the employment of metacognitive strategies in the course of speaking and listening. In another study, Alibakhshi et al. (2017) tapped the personality of 100 university students in Iran with the help of Goldberg’s (1993) Big Five Inventory and, yet again, measured the employment of LLS by means of the SILL. The main results were as follows: neuroticism negatively predicted the use of metacognitive and memory strategies, extraversion was positively related to the use of metacognitive LLS, and conscientiousness predicted reliance on compensation strategies. Relying on self-reports from 58 adolescent and young adult EFL learners from Indonesia, Noprianto (2017) explored differences in LLS use between extraverts and introverts. LLS use was assessed on the basis of the English Language Learning Strategy Inventory (ELLSI; Griffiths, 2003) while participants’ levels of extra- and introversion were measured by means of the Introversion Scale (Richmond & McCroskey, 1998). While no significant differences in the frequency of LLS use were reported in statistical analyses between extraverted and introverted participants, they exhibited various strategic preferences. To be more specific, participants in both categories most frequently relied on learning from mistakes and learning from their course instructor, introverts preferred learning from dictionaries, whereas extraverts were more inclined to learn English through watching TV. He (2019) investigated relationships among personality, writing strategy use and writing performance in the case 201 Taiwanese college-level learners of English. The data were collected by means of the Personality Facet Scale (Soto & John, 2009), the Writing Strategy Scale (Peñuelas, 2012) and argumentative essays written by participants. They established a structural model in which five strategy types and six facets of personality predicted writing performance, nine personality facets positively or negatively predicted the use of at least one strategy type, and five types of strategy mediated the link between the nine personality facets and performance on essay writing. Jackson and Park (2020), in turn, used structural equation modelling, visualization and interviews to examine relationships between self-regulation in writing, on the one hand, and consciousness and neuroticism, on the other, among 645 Japanese university students. Using the scales of ten aspects of the Big Five (DeYoung et al., 2007), the researchers demonstrated that self-regulation was positively predicted by consciousness and negatively by neuroticism. Moreover, the two personality traits were shown to fluctuate over the period of 15 weeks.

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In view of the way in which personality was conceptualized and tapped into in the research project reported in this book, of particular relevance are studies that have adopted the big five model of personality and used some version of the NEO-PI or NEO-FFI to collect the necessary data. Admittedly, such empirical investigations are few and far between. For example, Fazeli (2011) used the Persian translation of the NEO-FFI and the SILL with 213 female English majors in Iran to shed light on the link between personality traits and strategy use. Significant, negative correlations were reported between the level of neuroticism and four types of LLS, that is, metacognitive, cognitive, memory and social. Using the same sample of participants and the same tools, Fazeli (2012) later provided evidence for a positive relationship between agreeableness and the use of compensation strategies. In another study, Ghyasi et al. (2013) employed the NEO-FFI to examine the role of personality in mediating the use of self-regulatory strategies, measured by means of the Motivated Strategies for Learning Questionnaire (Pintrich et al., 1993), among 231 university students of English in Iran. The analysis yielded the following outcomes: neuroticism was a positive predictor of rehearsal and a negative predictor of help-seeking strategies; extraversion was positively related to self-regulatory based on elaboration, peer learning and help-seeking; openness to experience positively predicted reliance on elaboration, time management and study environment; and consciousness was positively linked to time and study management LLS. Worth mentioning is also the research project conducted by Obralic and Mulalic (2017) among 70 students of the International University of Sarajevo. Using a revised version of the NEO-FFI and the SILL, they provided evidence for a positive correlation between agreeableness and the use of affective strategies. As can be seen from this brief overview of studies that have attempted to illuminate the link between personality traits and LLS use, the empirical evidence in this respect is scarce, patchy, contradictory, inconclusive and thus very difficult to interpret. Such a situation is related not only to the relatively small number of relevant studies but is also the corollary of different measures of personality factors, researchers’ preference for focusing on some of them to the detriment of others, reliance on different tools to gather information on LLS, which depend on the conceptualization of the constructs as such, the application of different types of analyses as well as the way in which the results of such analyses are presented and discussed. For this reason, there is an urgent need to further illuminate the intricate relationship between personality traits and LLS use in different contexts as well as to try to identify distinct learner profiles in this respect, a goal that the study reported in the following chapter seeks to attain.

3.7 Conclusion The aim of the present chapter was to provide a brief, selective overview of studies that have sought to shed light on the link between personality and different aspects of L2 learning. In an attempt to summarize the findings related to the impact of personality on FLL, Dörnyei and Ryan (2015) conclude that:

3.7 Conclusion

139

(1) Conscientiousness and openness to experience appear to be the two best predictors of academic achievement, and the impact of the latter trait is complex as it can facilitate critical thinking, but at the same time impede the ‘required’ acquisition of knowledge; (2) Extraversion correlates negatively with attainment measures because of its inherent distractibility; (3) Neuroticism tends to impede academic achievement since, in a sense, it includes anxiety. While the above recap does, to some extent, capture the impact of personality on FLL, it does not fully account for the influence of the traits on specific aspects of the language learning process. With regard to conscientiousness, high levels of the trait might not merely contribute to more effective L2 learning, but also negatively affect such aspects of this process as goal pursuit or psychological adjustment due to conscientious individuals’ proneness to persist too long at specific tasks and goals (Spielman et al., 2022). When it comes to the relevance of openness for L2 learning, its impact expands far beyond facilitating critical thinking and impeding the compliance in accepting the transfer of knowledge. As McCrae and Costa (1997, p. 838) aptly point out, “(t)olerance of ambiguity, emotional ambivalence, and perceptual synesthesia are all hallmarks of the open person”. Examples of studies into TA and EI referred to in the present chapter definitely confirm the special status of this trait among IDs facilitating L2 learning. As regards extraversion, the effect of the trait expands far beyond making language learners prone to distractions in formal settings. Investigations of the influence of extraversion on various aspects of L2 learning discussed in the present chapter have confirmed its facilitative role in the context of performance in communication-oriented tasks as well its positive impact on learners’ willingness to look for opportunities to benefit from increased TL input as well as engage in interaction in that language. Finally, when it comes to neuroticism, whereas consensus among researchers seems to exist about the overly negative impact of the trait on L2 attainment and various aspects of L2 performance, some studies, including several mentioned in the present chapter, have failed to confirm the statistical significance of such findings. It would appear that, as argued by Dewaele (2022), over the time, researchers have overall gained a better understanding of psychological variables affecting L2 learning, but at the same time, due to a vast number of inconclusive results concerning specific personality dimensions, have also been forced to adjust their expectations about the explanatory power of both, higher, and lower order traits. This largely pertains to studies dedicated to examining the correspondence between LLS use and language learners’ personal characteristics. On the one hand, some relationships, particularly those shedding light on the influence of extra- or introversion on LLS use have been revealed. On the other hand, some traits, such as neuroticism or agreeableness need to be studied in much more detail as the results of studies attempting to explain their impact have largely been inconclusive. One such attempt has been made by the authors of the present volume in their study, discussed in Chaps. 4 and 5, which aimed to account for the interplay between personality traits and LLS use by

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university students by looking at them as clusters of relatively homogenous language learners.

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Chapter 4

Methodology of the Research Project

4.1 Introduction The preceding three chapters have provided insights into different conceptualizations of personality and the changing approaches to the study of LLS as well as discussing empirical investigations that have explored the role of personality factors in L2 learning and teaching. As indicated at the end of Chap. 3, empirical investigations into the role of personality in the choice and use of LLS are still relatively scarce, selective in nature, and rely on diverse data collection tools, all of which precludes definitive conclusions in this area. The present chapter offers the description of the methodology of the research project, which starts with an outline of the procedures and results of the pilot study (Sect. 4.2). Its findings are presented as a basis for elaborating on relevant implications for the rationale and design of the main study, discussed in Sect. 4.3, which starts with formulating the research questions (RQs), contains a detailed description of the participants of the main study and the research instruments. Both inventories used in the pilot study and in the main study, that is, the Polish adaptation of the SILL ver. 7.0 (Oxford, 1990) and the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992, Zawadzki et al., 2010), are evaluated in terms of the fulfilment of goodness criteria for psychometric tests including, most importantly, their objectivity, standardization, validity, and reliability. Next, the data collection process is briefly described. In the final part of Sect. 4.3, the analytical procedures employed in the data analyses intended to provide answers to the RQs are discussed. Regarding quantitative insights, this involves discussing the choice of descriptive and inferential statistics used in accounting for the personality profiles of the informants and their reported strategy use as well as providing an outline of the clustering techniques applied to identify relatively homogenous groups of participants. With respect to qualitative insights obtained in a series of semi-structured interviews, the main assumptions and major stages of thematic analysis (TA) are outlined. Section 4.4 provides final conclusions on the methodology of the study discussed in the present book. It should be stressed at this juncture that the findings reported in the present chapter are part of a larger research project investigating the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6_4

147

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4 Methodology of the Research Project

relationships between tertiary language learners’ personality traits and their use of LLS (cf. Przybył & Pawlak, under review).

4.2 Pilot Study The pilot study was conducted in order to assess the potential of using the Polish adaptation of the NEO-FFI (Zawadzki et al., 2010) along with the Polish adaptation of the SILL ver. 7.0 (Oxford, 1990) for investigating the relationships between language learners’ personality traits and their choices of LLS.1 The research tools were verified in terms of their fulfilment of the goodness criteria applied in psychometric research, including objectivity, standardization, reliability, validity, normalization and accuracy of adaptation (Hornowska, 2007). Moreover, it was expected that the results of the pilot study would at least partly reveal the relationships between the characteristics of the participants and their choice of particular LLS.

4.2.1 Participants, Data Collection, and Research Instruments Participants of the pilot study included 50 undergraduate students of management and finance learning English as L2 as part of their curriculum, aged 20–43 (M = 24.5), 80% of whom were women. The students had been familiarized with the purpose of the study, encouraged to provide honest answers, and told that no correct or expected answers existed. Participation in the study was voluntary and the administration of the questionnaires had been approved by relevant university authorities. The informants were asked to complete pen-and-paper questionnaires of Polish adaptations of the SILL ver. 7.0 (Oxford, 1990), and the Polish adaptation of NEOFFI (Zawadzki et al., 2010). The adaptation of the SILL ver. 7.0 (Oxford, 1990) included modifications which had been introduced in order account for strategies available in the second decade of twenty-first century, yet unavailable back in the 1990s when the SILL was constructed. The following modifications were introduced: • item 15, originally worded I watch English language TV shows spoken in English or go to movies spoken in English was altered in order to account for a greater variety of English input to which learners could obtain exposure, predominantly online, and paraphrased into I watch English TV programs and films; • item 17, originally worded I write notes, messages, letters, or reports in English, was also redesigned in order to allow for a wider number of options available, such as text messages, emails, blogs, etc., and thus changed into I write notes, messages, letters, or other forms in English. 1

Both instruments are introduced in Sect. 4.2.2 and discussed in detail in Sect. 4.4.3.

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149

In order to explore the internal consistency of the adapted SILL ver. 7.0 (Oxford, 1990), Cronbach’s alpha reliability coefficients (α) were calculated for each LLS scale (i.e., memory, cognitive, compensation, metacognitive, affective, and social strategies). The values of the coefficients are presented in Table 4.1. As can be seen from the table, three LLS scales, cognitive, metacognitive, and social LLS, were characterized by acceptable values of the α coefficient (α > 0.7; Kline, 2000). The alpha value for memory strategy scale was just slightly lower than 0.7 and it could be expected that the value may increase in the main study as a consequence of the rise in the number of participants. At the same time, the compensation LLS scale, and the affective LLS scale, were characterized by Cronbach’s alpha values amounting to 0.53 and 0.27 respectively, which indicates low internal consistency of these subscales. In order to increase the reliability of the two problematic scales in the main study, additional questions were introduced into each after their evaluation by a panel of judges (Brzezi´nski & Maruszewski, 1978; Lawshe, 1975). The judges were all experienced EFL academic teachers. On the basis of their approval, five additional items were added to the original SILL ver. 7.0 (Oxford, 1990). They are presented in Table 4.2 and the improvements to the reliability of both scales concerned, resulting from including extra items in the adapted version of the SILL, are presented in Sect. 4.3.3, dedicated to the research instruments employed in the main study. Table 4.1 Cronbach’s alpha values for strategy scales Scale and abbreviation

No. of items

Cronbach’s alpha

Memory strategies

9

0.63

Cognitive strategies

14

0.80

Metacognitive strategies

9

0.86

Compensation strategies

6

0.53

Social strategies

6

0.74

Affective strategies

6

0.27

Table 4.2 Items approved by experts that were added to the Polish adaptation of the SILL (Oxford, 1990) Question Scale

Item

C7

Compensation strategies I refrain from using online dictionaries or translators while communicating on the Internet

C8

Compensation strategies I draw a word which I cannot remember in English

E7

Affective strategies

I use emoticons when I write in English

E8

Affective strategies

I share my feelings about learning or using English on an Internet blog or on social portals

E9

Affective strategies

I try to perceive my English teacher in a positive way

150 Table 4.3 Cronbach’s alpha values for personality dimensions

4 Methodology of the Research Project Scale and abbreviation

No. of items Cronbach’s alpha

Neuroticism (N)

12

0.86

Extraversion (E)

12

0.65

Openness to Experience (O) 12

0.60

Agreeableness (A)

12

0.79

Conscientiousness (C)

12

0.72

The procedure applied to examine the internal consistency of the personality scales included in the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010) reflected the measurement for LLS scales. Thus, Cronbach’s alpha reliability coefficients (α) were calculated for each personality scale of neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. The values of the coefficients are presented in Table 4.3. As can be seen from the table, the values of Cronbach’s alpha coefficients all amounted to 0.6 or more. While the value typically reported as satisfactory amounts to 0.7, it has been acknowledged that for small samples (N < 300), the value of the coefficient might not reach 0.7 due to its dependence on the number of participants (Cortina, 1993; Kline, 2000). Moreover, since the NEO-FFI (Costa & McCrae, 1992) is a standardized psychological test, modifications consisting in introducing additional items cannot be implemented since they could affect the overall structure of the inventory and result in an uneven split of questionnaire into the “big” five personality scales. Consequently, no modifications were made in the case of the personality questionnaire, and it was expected that with a sample size larger than 700, planned for the main study, the reliability coefficients for personality scales would reach or exceed the value of 0.7. In order to account for the validity of the Polish adaptation of the SILL ver. 7.0 (Oxford, 1990), item-scale Pearson correlation coefficients were calculated,2 and the significance of these correlations was the first premise to consider a given item as valid. Three items turned out not to correlate significantly with the subscales of LLS to which they belonged. These were the following: • memory strategy 6 (I use flashcards to remember new English words); • cognitive strategy 12 (I find the meaning of an English word by dividing it into parts that I understand); • affective strategy 5 (I write down my feelings in a language learning diary). One reason for the absence of statistically significant item-scale correlations in the case of the three items listed above could be the corollary of the relative obsolescence of the LLS which the items represent. Yet, while this could arguably indicate validity concerns, the items were ultimately not excluded from the battery of tests intended 2

The results of the Shapiro–Wilk test confirmed that the distribution of each of the LLS scales did not vary significantly from normal distribution (p < 0.05 adjusted by the Bonferroni correction; df = 49).

4.2 Pilot Study

151

to be used in the main study for two reasons. Firstly, the results could have been affected by a relatively small sample of informants (N = 49). Secondly, while it is by all means feasible to exclude items from statistical analysis at later stages, removing them from prior to the administration of the main study could result in a loss of data (Kline, 2000). Examining the validity of the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010) reflected the procedure for the adaptation of the SILL ver. 7.0 (Oxford, 1990).3 Item-scale Pearson correlation coefficients were calculated for each of the ‘big’ five personality domains. The following items did not significantly correlate with their subscales: • • • •

E2 (It is easy to make me laugh); E3 (I am not particularly careless); O1 (I do not like wasting time on dreams); A9 (I am tough and relentless towards others).

In spite of possible validity concerns, on the grounds presented above, including relative inflexibility in adapting standardized psychological tests and a possibility of introducing amendments at later stages, the above items were ultimately kept in the battery of tests administered in the main study.

4.2.2 Preliminary Findings and Implications for the Main Study Although the pilot study was mainly conducted in order to verify the rationale for the main study, with a particular focus on the examination of the data collection instruments to be used in that study, some findings concerning the frequency of LLS use and the level of personality traits were also revealed. To start with, the reported LLS use and the levels of personality traits were computed for each participant. In compliance with the guidelines from the SILL Profile of Results (Oxford, 1990) and the manual for the NEO-FFI (Zawadzki et al., 2010), this involved calculating mean values for LLS scales and sums for personality scales. Participants’ scores in terms of LLS use were interpreted according to the guidelines provided in the SILL Profile of Results (Oxford, 1990), according to which values below 2.5 should be understood as rare LLS use, values exceeding 3.5 should be understood as frequent LLS use, and values in between should be interpreted as average LLS use. Participants’ levels of personality traits were interpreted according to norms for Poles presented in the NEO-FFI manual (Zawadzki et al., 2010), according to which the levels of traits belonging to stens 1–3 should be perceived as low, those belonging to stens 4–6 should be perceived as medium, and those falling in the final range of stens 7–10 should be interpreted as high. 3

The results of the Shapiro–Wilk test confirmed that the distribution of each of the personality scales did not vary significantly from normal distribution.

152 Table 4.4 Descriptive statistics in the pilot study for LLS

4 Methodology of the Research Project Scale

Median (Md)

Range

Memory strategies (Mem)

2.47

2.22

Cognitive strategies (Cog)

2.79

2.71

Compensation strategies (Cps)

3.17

2.50

Metacognitive strategies (Mcg)

3.00

2.67

Affective strategies (Aff)

2.49

2.33

Social strategies (Soc)

3.17

2.67

GULLS

2.81

1.66

Afterwards, descriptive statistics were computed. The selection of the measures of central tendency and measures of dispersion was dictated by the results of normality tests, run for the “big” five personality scales of neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness (Costa & McCrae, 1992) and the six LLS scales of memory, cognitive, compensation, metacognitive, affective, and social strategies (Oxford, 1990). These tests revealed that the distribution of data did not significantly differ from normal distribution for personality scales (p < 0.05 adjusted by the Bonferroni correction; df = 2), but at the same time, it differed significantly from normal distribution for two LLS scales, that is, memory and metacognitive strategies (p < 0.05 adjusted by the Bonferroni correction; df = 2). Consequently, median and range values are reported for LLS scales while mean values accompanied with the values of standard deviation (SD) are reported for personality scales. Table 4.4. contains the descriptive statistics computed for LLS scales. In the final row, the frequency of participants’ general use of language learning strategies (GULLS) is reported, calculated as a mean, overall use of LLS in all the six categories. On the whole, according to the SILL Profile of Results (Oxford, 1990), while the frequency of LLS use in general (GULLS) could be described as medium, the frequencies reported by participants in specific LLS categories ranged from rare (memory strategies and affective strategies) to medium (cognitive strategies, compensation strategies, metacognitive strategies, and social strategies). The participants most frequently relied on compensation and social strategies (Md values of 3.17 in both cases). Among specific individual LLS, the investigated language learners most frequently employed the social strategy, SILL item 45, If I do not understand something in English, I ask the other person to slow down (Md = 5) as well as three cognitive strategies, SILL item 10, I say or write new English words several times, SILL item 18, I first skim an English passage (read it quickly) then go back and read carefully and SILL item 22, I try not to translate word-for-word, three compensation LLS, SILL item 24, To understand unfamiliar English words, I make guesses and SILL item 25, When I can’t think of a word during a conversation in English, I use gestures and SILL item 29, If I can’t think of an English word, I use a word or phrase that means the same thing, three metacognitive LLS, SILL item 31, I notice my English mistakes and use that information to help me do better and SILL item

4.2 Pilot Study Table 4.5 Descriptive statistics in the pilot study for personality scales

153 Scale

Mean

SD

Neuroticism

22.92

8.85

Extraversion

30.65

5.25

Openness to experience

25.90

5.00

Agreeableness

30.24

6.41

Conscientiousness

32.80

5.39

32, I pay attention when someone is speaking English, and SILL item 33, I try to find out how to be a better learner of English, one affective LLS, SILL item 40, I encourage myself to speak English even when I am afraid of making a mistake and one more social LLS, SILL item 47, I practice English with other students (Md = 4). At the same time, the least frequently employed LLS included two memory LLS, that is, SILL item 5, I use rhymes to remember new English words and SILL item 6, I use flashcards to remember new English words and one affective LLS, SILL item 43, I write down my feelings in a language learning diary. Overall, participants’ preference for compensation and social LLS could indicates that they were not overwhelmed by insufficient range of mastered vocabulary and, at the same time, eager to learn from each other and from other people, possibly inside or outside the EFL classroom. It could also be concluded that the investigated learners exhibited no clear preference for direct or indirect LLS. Table 4.5 presents the descriptive statistics concerning the levels of participants’ personality traits. As can be seen from the table, no high (stens 7–10) or low (stens1–3) levels of personality traits were observed for the investigated sample of students considering the mean scores of personality traits. When interpreted according to the norms for particular ages and genders, the mean values all fell into the average category, which, according to the manual description (Zawadzki et al., 2010) could be summarized in the following way: • in terms of neuroticism, the participants of the pilot study were well-balanced, and occasionally experienced anger, grief or feel guilty; • in terms of extraversion, the participants of the pilot study were fairly sociable, displaying a preference for entering into social interactions with others on some occasions, but, at the same time, showing a preference for privacy and intimacy on other occasions; • in terms of openness to experience, the participants of the pilot study proved to be balanced in their readiness to explore new ideas and reliance on traditional values; • in terms of agreeableness, the participants of the pilot study were typically nice and friendly, but sometimes exhibited competitive behaviors; • in terms of conscientiousness, the participants did show some organization of their goals and lifetime ambitions, but, at the same time, were not likely to strive for them at all price.

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4 Methodology of the Research Project

4.3 The Design of the Main Study In order to comply with contemporary standards of methodological data triangulation (Oxford, 2017; Pawlak, 2010; Wi´sniewska, 2014), the main study was designed as a mixed-method empirical investigation, relying on a combination of quantitative and qualitative methodologies. It was expected that its quantitative part would provide information about the correspondence between university students’ personality traits and their use of LLS. More specifically, through the use of statistical procedures, an attempt was made to identify relatively homogenous clusters of learners on the basis of their self-reported strategy use and the levels of their personality traits. At the same time, qualitative data obtained from semi-structured interviews were expected to provide contextual insights into the possible impact of learners’ personality on LLS use in particular language tasks and with reference to specific language subsystems, such as grammar or vocabulary. As stressed by Oxford (2017), only by gathering data from both types of studies does research into LLS stand the chance of accounting for the complexity of the strategy construct and the role of LLS in language learning.

4.3.1 Research Questions Although numerous studies have investigated factors that influence the choice and use of LLS (see Sect. 2.6), research into the role of personality traits as determinants of LLS use is scant and limited in many ways (see Sect. 3.5). Aiming to fill this research gap, the present empirical investigation sought to link LLS use to learners’ personality traits by addressing the following research questions: 1. What are the general characteristics of tertiary learners of English at Polish universities in terms of their reported LLS use? 2. What are the general characteristics of tertiary learners of English at Polish universities in terms of their personality traits? 3. What clusters of participants can be identified on the basis of the levels of their “big” five personality traits and reported LLS use?

4.3.2 Participants The participants were 742 students from two universities in a major Polish city: 608 (81.9%) studied at a state-run university ranking among the best in Poland and 134 (18.1%) studied at a private university, mostly operating in the sector of economic and business education. EFL courses were part of their curriculum at both universities. The cohort comprised 454 female participants (61.2%), 282 male participants (38%) and 6 participants who did not indicate any of the above genders (0.8%). All the informants were young adults, aged 18–29 (M = 20.7, SD = 1.49). In terms of their

4.3 The Design of the Main Study

155

level of attainment in English, determined on the basis of placement tests conducted at both universities prior to learners’ enrolment to specific groups, 38 (5.1%) were A1 + learners, 253 (34.1%) were A2 learners, 162 (21.8%) were B1 learners, and 289 (39%) were B2 learners. They studied at various university faculties, 134 of them (18.1%) were students of the Faculty of Finance and Banking (all from the private university), 77 (10.4%) of them studied law and administration, 59 (8%) studied history, 59 (8%) studied theology, 55 (7.4%) studied maths or IT, 50 (6.7%) studied modern languages, 45 (6%) studied physics, 44 of them (5.9%) studied geography and geology, 44 (5.9%) were students of educational studies, 41 (5.5%) studied biology, 39 (5.3%) studied social sciences, 39 (5.3%) studied chemistry, 29 (3.9%) studied political sciences or journalism, and 27 (3.6%) studied Polish or classical philology. Importantly, the number of students in both cohorts, the one from the state university, and the one from the private university, met the requirements for minimum sample sizes (cf. Brzezi´nski, 2004).4 Therefore, the results of the study may be regarded as representative of the populations of undergraduate EFL learners at both universities. 19 students participated in the qualitative part of the study, 16 of whom were female, and 3 of whom were male. These participants all volunteered to take part in the semi-structured interviews discussed in Sect. 4.3.3.3.

4.3.3 Research Instruments In order to collect data for the quantitative part of the study, participants were asked to complete two adaptations of the psychometric tests, that is, the Polish adaptation of SILL ver. 7.0 (Oxford, 1990), and the adaptation of the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010). The choice of research instruments was determined by analyzing the degree of meeting the goodness criteria by the instruments used in the pilot study as well as findings from another study based on the use of alternative tool for personality measurement (Przybył, 2016). Due to the doubts concerning the internal consistency and validity of the Ten-Item Personality Inventory (TIPI; Sorokowska et al., 2014), the NEO-FFI (Costa & McCrae, 1992) was used in the study. Also, on the basis of the conclusions from the pilot study, the compensation scale, and the affective scale of the SILL ver. 7.0 were expanded in an attempt to improve their reliability (see Sect. 4.2.2). The following Sects. 4.3.3.1 and 4.3.3.2, discuss the research instruments which were used for the purpose of exploring the relationships between LLS and learners’ personalities. Section 4.3.3.3 discusses the 4

N=

P(1−P) e2 Z2

+ P(1−P) N

N=

P(1−P) e2 Z2

+ P(1−P) N

, where the following symbols represent:

n—minimal sample size; P—estimated fraction (assumed to be 0.5 if there is no information); e—acceptable sampling error, amounting to 0.04; Z—value resulting from the assumed confidence interval; for the assumed confidence interval equal to 0.95, Z = 1.96; N—population size.

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4 Methodology of the Research Project

design of the interview which was used in the qualitative part of the research project in order to triangulate the data obtained in the quantitative part.

4.3.3.1

SILL ver. 7.0

The SILL ver. 7.0 is one of a number of questionnaires developed by Oxford in order to measure the frequency of LLS use among L2 learners (Oxford, 1990). Despite a barrage of criticisms, researchers have continued using adaptations of the questionnaire in order to identify and explore LLS in various contexts (Amerstorfer, 2018; Del Ángel Castillo & Gallardo Córdova, 2014; Griffiths, 2008; Kayao˘glu, 2013; Liang, 2009; Pineda, 2010). Version 7.0 consists of 50 questions on a Likertscale ranging from 1 (never or almost never) to 5 (almost always or always). The major advantages of the instrument, that is, its systematic and easily comprehensible structural design, and user-friendliness from the perspective of language learners, instructors, and researchers are believed to be the main reasons behind its utmost popularity in LLS research (Amerstorfer, 2018). The six scales of the SILL ver. 7.0 are presented in Table 4.6. As a result of the changes aiming to improve the reliability of two of the scales, that is, the compensation LLS scale and the affective LLS scale, discussed in Sect. 4.1, the number of items in the Polish adaptation exceeds the number of items in the original inventory. For each scale the number of items in the Polish adaptation of the questionnaire is provided before and after modifications based on the results of the pilot study (see Sect. 4.2.1). Since the SILL ver. 7.0 (Oxford, 1990) is, from a psychometric point of view, a test that accounts for the description of individual differences between language learners (Stuart-Hamilton, 2007), the degree to which it fulfils the goodness criteria needs to be analyzed. Oxford (1986) herself also considers the SILL a psychometric test and therefore it is important to determine both the reliability and validity of the tool before developing the final version of the questionnaire. In terms of objectivity, the inventory is most likely to produce the same results for any two raters (“blind” diagnosis test), since it is also equipped with a simple marking scheme (Oxford, 1990). Also, the scoring procedure is described in a simple manner in order to minimize the risk of miscalculating the score. As regards standardization, the questionnaire is accompanied by a set of instructions which appears in its initial part. Basing on the instructions, one can infer that the questionnaire can be used for both individual and group studies. Consequently, it can be employed as both a self-assessment tool for learners who are willing to reflect on the way that they learn English as L2 and for comparisons between learners, and across groups. Time limit is not specified; however, a comment on the questionnaire states that it takes no more than 30 min to complete. Finally, the section SILL Profile of Results (Oxford, 1990) offers a key to understanding the scores, their graphic representation, and an explanation of what the averages mean. Detailed interpretations are provided with cut-off points indicating low, average, and high LLS use. Another measure which accounts for the degree to which a psychometric inventory fulfils the goodness criteria is its validity. According to Messick (1994), “(v)alidity

4.3 The Design of the Main Study

157

Table 4.6 SILL ver. 7.0 scales (based on Oxford, 1990) Scale Description Mem Deal with storing and retrieving information

No. of items (original) No. of items (adapted) 6

6

Cog

Involve manipulation/transformation of 14 the language in some direct way, e.g. through reasoning, analysis, note taking, and both functional practice in naturalistic settings and formal practice with sounds and structures

14

Cps

Handle lack of/insufficient knowledge and thus include guessing while listening or reading, using synonyms or circumlocution while speaking or writing

6

7

Mcg

Aim to enable the learner to control the learning process through centring, arranging, planning, and evaluating their learning

9

9

Soc

Include interactions with other people which facilitate language learning

6

6

Aff

Help learners manage their emotions, attitudes, and seriously influence learners’ motivation

6

9

is an overall evaluative judgment of the degree to which empirical evidence and theoretical rationales support the adequacy and appropriateness of interpretations and actions based on test scores or other modes of assessment” (p. 6). Apart from face validity, that is, an estimate whether a test measures what it subjectively appears to measure to the person taking the test (Anastasi & Urbina, 1997), three main constituents of validity tend to be distinguished throughout most of the second half of the previous century: • content validity, that is, “the degree to which elements of an assessment instrument are relevant to and representative of the targeted construct for a particular assessment purpose” (Haynes et al., 1995, p. 238); • criterion validity, which comprises the concurrent and predictive validity of a research instrument5 ; • construct validity, which Messick (1990, p. 7) describes as “the degree to which certain explanatory concepts or constructs account for performance on the test”. At the end of the century, however, the validity of a psychometric instrument started to be more frequently viewed as an integral, unified concept, with six distinguishable 5

According to the Standards for Educational & Psychological Testing (2014), concurrent validity reflects only the status quo in a particular research area at a particular time, whereas predictive validity can serve as a comparison between the measure and the outcome assessed at a later time.

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4 Methodology of the Research Project

aspects, that is, its content, substantive processes, score structure, generalizability, external relationships, and testing consequences (Messick, 1989, 1990, 1994, 1998). For the purpose of verifying the face validity of the instrument, Oxford (1990) investigated the classificatory agreement between two independent raters “blindly” matching the SILL items with LLS enlisted in a strategy taxonomy. The inter-rater agreement coefficient amounted to 0.95, which could be treated as an indicator of satisfactory face validity. As far as the content validity of the questionnaire is concerned, its connection with success in L2 learning or with measures of L2 proficiency and other similar instruments have been assessed by various researchers. A number of studies can be quoted to confirm the relationship. One example is the study conducted by Green and Oxford (1995), where 78% of variance in language proficiency was explained by the SILL. While the validity of measuring LLS by the SILL (Oxford, 1990) has been challenged (Dörnyei, 2005, 2009; Skehan, 1991), confirmatory factor analysis conducted by Hsiao and Oxford (2002) proved that the 50-item SILL showed most the most consistent fit with learners’ strategy use. Two procedures were employed to evaluate the validity of the SILL ver. 7.0 (Oxford, 1990) in the present study. First, bivariate item-scale Spearman correlation coefficients were calculated for each item of the questionnaire. This procedure was repeated for all the LLS scales, that is, memory, cognitive, compensation, metacognitive, affective, and social LLS. In order to be regarded as valid, the items needed to significantly correlate with specific scales (p < 0.05/x, where x marks the number of parallel correlations, as required by the Bonferroni correction). Second, the values of these correlations were juxtaposed with the critical values for the Spearman correlation (p < 0.05/x; df = 2). According to the results of the analysis, each item of the adapted SILL ver. 7.0 could be regarded as valid. The values of the item-scale correlations for all the items from the SILL inventory are presented in Appendix A. With reference to the reliability of the SILL ver. 7.0, Cronbach’s alpha coefficients measuring the internal consistency of its scales were calculated for memory, cognitive, compensation, metacognitive, affective, and social LLS. In line with the insights from the pilot study (see Sect. 4.2), additional items were added to the scales of compensation and affective LLS in order to improve their reliability. As can be seen in Table 4.7, Cronbach’s alpha values improved after expanding the scales of compensation strategies and affective strategies as the values of the coefficients increased from 0.625 to 0.631, and 0.408 to 0.60, respectively. Such improvements notwithstanding, while these increases certainly marked improvement in the reliability of both scales, the values fell short of reaching the golden standard for Cronbach’s alpha coefficient, that is 0.76

Cortina (1993) suggests the following interpretation of Cronbach’s alpha value: α < 0.5—unacceptable internal consistency; 0.5 ≤ α < 0.6—poor internal consistency; 0.6 ≤ α < 0.7—questionable internal consistency; 0.7 ≤ α < 0.8—acceptable internal consistency; 0.8 ≤ α < 0.9—good internal consistency; 0.9 ≤ α—excellent internal consistency.

6

4.3 The Design of the Main Study Table 4.7 Reliability of the adapted SILL ver. 7.0 scales

4.3.3.2

Scale

159 Cronbach’s alpha—original scale

Cronbach’s alpha—expanded scale

Memory LLS

0.610

N/A

Cognitive LLS

0.803

N/A

Compensation LLS

0.625

0.631

Metacognitive LLS

0.830

N/A

Social LLS

0.704

N/A

Affective LLS

0.408

0.600

NEO-FFI

Recommended by the Polish Psychological Association for both research and clinical purposes (Zawadzki et al., 2010), the NEO-FFI (Costa & McCrae, 1992) is an inventory designed to measure an individual’s personality in five bipolar dimensions corresponding with the Five Factor Model (FFM) of personality developed by Costa and McCrae (1985, 1992). As argued in Chap.1, the FFM has two major advantages over alternative models. Firstly, it is said to measure different personality traits without the danger of their overlapping, and, secondly, the traits included in the model display a considerable level of consistency in interviews, descriptions and when observed (Schacter et al., 2012). Costa and McCrae’s (1992) NEO-FFI includes 60 items, dedicated to the measurement of the “big” five personality scales, that is, openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism, each of which is tapped into by means of 12 items. Respondents choose their answers on a 5-point Likert scale by indicating to what degree they agree or disagree with a particular statement (1 = strongly disagree; 5 = strongly agree). The scales of the questionnaire are described in Table 4.8. Similarly to the SILL ver. 7.0 (Oxford, 1990), as a psychometric test, the NEOFFI (Costa & McCrae, 1992) also needs to fulfil six goodness criteria: it needs to be objective, standardized, valid, reliable, interpreted according to norms, and adapted to the specific characteristics of a local population (Hornowska, 2007). First of all, the NEO-FFI inventory (Costa & McCrae, 1992; Zawadzki et al., 2010) can be called “standardized”. To start with, general rules for testing are included in the manual, which enables the researcher to conduct the test in the same manner every time there is a need to repeat it. Moreover, the instructions specify that the questionnaire can be used in group research as well as individual assessment, define the time limit, contain a marking scheme, as well as suggesting that the data should be collected in a pen-and-paper mode. Also, the manual defines how to calculate, code, check, and register test scores as well as providing the norms that should be adhered to. In order to allow for comparisons between individuals of the same gender and within specific age groups (15–19; 20–29; 30–39; 40–49; 50–80), test-takers’ raw scores are commonly recounted as sten scores in research and clinical practice. The psychometric interpretation of sten scores assumes that the sten scores 1–3 should

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4 Methodology of the Research Project

Table 4.8 NEO-FFI scales (adapted from Zawadzki et al., 2010) Personality trait

Definition

Examples of manifestations

Openness

A personality trait which describes an individual’s tendency to search for and value experiences, as well as tolerance of new concepts and cognitive curiosity

Excitement aroused by reading poetry or contemplating a work of art, interest in the nature of the universe and human nature

Conscientiousness

A personality trait which describes the degree of an individual’s organization, perseverance, and their motivation to achieve goals, or, in other words, an individual’s attitude to work

Clearly set objectives, working systematically, being perceived as a reliable worker

Extraversion

A personality trait which characterizes the quality and amount of social interaction, as well as the level of an individual’s activity and their ability to experience positive emotions

Willingness to be surrounded by people, being cheerful and full of life

Agreeableness

A personality trait which describes an Considered to be cold and shrewd, individual’s attitude to other people, being able to manipulate others in or, in other words, their interpersonal order to get what one wants orientation resulting in altruism / antagonism in thoughts, feelings, and actions

Neuroticism

A personality trait which reflects one’s ability of emotional adaptation or lack of emotional stability, expressed through experiencing negative emotions, such as fear, confusion, dissatisfaction, anger, feeling of guilt, and sensitivity to psychological stress

Feeling tense or anxious, feeling helpless, feeling dependent on others in solving problems

be interpreted as low, sten scores 4–6 should be interpreted as medium, and sten scores 7–10 should be regarded as high. Referential norms are provided in Appendix C of the Polish adaptation of the NEO-FFI (Zawadzki et al., 2010). For all these reasons, the Polish adaptation of the NEO-FFI inventory (Costa & McCrae, 1992; Zawadzki et al., 2010) may be seen as both standardized and objective since the risk of interpreting the same result in a different way by different researchers is virtually non-existent. The validity of the Polish adaptation of NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010) was assessed in a similar manner to the validity of the SILL ver. 7.0 (Oxford, 1990; see Sect. 4.2.3.1). First, bivariate item-scale Spearman correlation coefficients were calculated for each item of the questionnaire. This procedure was repeated for all the NEO-FFI scales. In order to be regarded as valid, the items needed to significantly correlate with their scales (p < 0.0042; value adjusted by the

4.3 The Design of the Main Study Table 4.9 Reliability of personality scales

Scale

161 Cronbach’s alpha

Openness to experience

0.68

Conscientiousness

0.72

Extraversion

0.80

Agreeableness

0.75

Neuroticism

0.86

Bonferroni correction7 ). Second, the values of these correlations were juxtaposed with the critical values for the Spearman correlation (p < 0.0042; df = 2). According to the results of the analysis, each item of the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010) could be regarded as valid. The values of the item-scale correlations for all the items from the NEO-FFI items are presented in Appendix B. In order to assess the reliability of the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992, Zawadzki et al., 2010), the values of the Cronbach’s alpha coefficients were calculated. As can be seen in Table 4.9, all the coefficient values were acceptable, with the value being slightly lower than 0.7 only in the case of openness to experience.

4.3.3.3

Semi-structured Interviews

In order to provide further insights into the links between university students’ personality traits and their use of LLS, semi-structured interviews were conducted with 19 participants from the quantitative phase of the study who volunteered to take part in this stage of data collection. The choice of the format of the interview was determined by the necessity to allow for a wide range of topics including the emergence of unexpected themes (Richards, 2009). It was expected that resorting to interviews as a data collection method would result in greater contextualization of the research findings through engaging participants in conversations, and letting them interpret their own experience (Schultze & Avital, 2011). As aptly pointed out by Braun et al., (2022, p. 441), each such interview can be seen as “a product of the specific set of circumstances, of time, place, persons, and many other factors, that come together in a particular moment”. An interview guide was prepared in advance in compliance with the guidelines for the design of semi-structured interviews (Friedman, 2012), such as relying on the use of open-ended questions, avoiding either leading or complex questions, and intending to maximize the comprehensibility of the questions to interviewees. The interview guide contained an introductory section, prompting the participants to generally reflect on the EFL experience, a section developed in order to gain insights into 7

The value 0.0042 was obtained by dividing the significance level of 0.05 by 12, which is the number of items in each personality subscale of neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness in the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010).

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the students’ LLS repertoires, a part encompassing questions relating to personality, and a final section, designed in order to provide interviewees with an opportunity to consider the relevance of strategic metaknowledge in learning EFL. The most extensive section, dedicated to LLS repertoires, was designed with the aim to illuminate how interviewees tended to use LLS with regard to specific subcomponents of English and in development of specific TL skills. At the same time, an attempt was made to account for multiple dimensions of LLS by referring to different aspects of the L2 learning process. In the section addressing the role of personality in learning EFL, the informants were asked to reflect on the possible influences of their characteristics on the language learning process as well as appraise their impact. A complete interview guide is attached to the present volume as Appendix C.

4.3.4 Data Collection With respect to the SILL ver. 7.0 (Oxford, 1990) and NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010), data collection took place in multiple EFL classrooms at 14 different faculties, 13 at the state-run university, and 1 at the private university. Prior to distributing the questionnaires, consent had been granted from the deans of the faculties involved. Through a random selection of a pool of EFL instructors, the choice of participants of the quantitative part of the study was random. In each EFL class where the questionnaires were administered, the students were informed about the purpose of the study and granted full confidentiality. They were also informed that participation in the study was voluntary and that they could withdraw from it at any time. Only after the participants had given their consent, were they asked to fill in the pen-and-paper versions of both questionnaires. Additionally, they were requested to supply information concerning their age, gender, work experience, place of residence, level of language attainment on the basis of the university placement test, and their field of studies. While no time limit was set for the completion of the questionnaires, on the whole, it did not exceed 40 min. Regarding the collection of the qualitative data, 19 students responded to the email sent through the university mailing system, volunteering to take part in a semi-structured interview. The interviews were conducted in Polish, at either of the two universities. Upon participants’ consent, they were recorded digitally on a mobile device and transcribed. Their length ranged from 20 to 40 min.

4.3.5 Analytical Procedures 4.3.5.1

Quantitative Procedures

The distributions of the “big” five personality trait levels of openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism as well as the scales

4.3 The Design of the Main Study

163

of memory, cognitive, metacognitive, compensation, affective and social LLS were tested for normality with Shapiro–Wilk test. Each time, H0 assumed that the a given distribution did not significantly differ from normal whereas H1 assumed it was significantly different from normal (p < 0.05). Normality test results are summarized in Table 4.10. In order to answer RQs1 and 2 and provide insights into participants’ characteristics in terms of their personality traits and reported LLS use, basic statistical parameters were reported, including measures of dispersion and measures of central tendency. This involved computing the values of the mean, median, standard deviation and percentiles. Prior to that, mean values of LLS use in each of the investigated categories were calculated for each participant and supplemented with the value of GULLS (see Sect. 4.2.2). For personality scales, it was also necessary to compute new variables for reversed items and, afterwards, calculate sums accounting for personality trait levels in each participant of the study. The descriptive statistics for personality traits were first calculated holistically for all participants, and then across age groups and genders so as to allow for a psychometric interpretation of the findings and classify the raw results as low, medium, and high (Costa & McCrae, 1992, Zawadzki et al., 2010). It needs to be emphasized that while raw scores ensure greater accuracy in correlational analysis, relying on the psychometric interpretation of the test scores is inevitable since the same raw score could not only be interpreted differently across genders, but also for participants varying with respect to age (Anastasi & Urbina, 1997). Referential norms for the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992) are provided in Appendix C of the manual (Zawadzki et al, 2010). In order to answer RQ 3, an attempt was made to group the participants according to their personality trait levels and their reported LLS use. This was done by means of cluster analysis, which serves the purpose of classifying data and, subsequently, Table 4.10 Shapiro–Wilk test results for LLS and personality scales Scale

W

p value

Normality

Memory strategies

0.993

0.014

Different from normal distribution

Cognitive strategies

0.995

0.064

Normally distributed

Compensation strategies

0.993

0.010

Different from normal distribution

Metacognitive strategies

0.995

0.053

Normally distributed

Affective strategies

0.987

< 0.001

Different from normal distribution

Sociocultural strategies

0.992

0.004

Different from normal distribution

GULLS—mean

0.998

0.854

Normally distributed

Openness to experience

0.992

0.007

Different from normal distribution

Conscientiousness

0.995

0.112

Normally distributed

Extraversion

0.995

0.072

Normally distributed

Agreeableness

0.987

< 0.001

Different from normal distribution

Neuroticism

0.995

0.092

Normally distributed

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4 Methodology of the Research Project

conducting discriminative analysis. Landau and Everitt (2004) differentiate between two types of clustering techniques, that is: • agglomerative hierarchical techniques, which consist in combining individuals who are “closest” (that is, most similar) to each other and, afterwards, combining them with other individuals, who are closest to them, by means of applying either complete or average linkage for defining inter-group distance; • k-means clustering, which divides a set of data into k clusters (k being a number established by the investigator), based on a measure of distance between cases, such as Euclidean distance, with the overall aim to minimize the variability within clusters while maximizing it between clusters. Importantly, the SPSS software, which was used in data analysis, offers a third option of cluster analysis, capitalizing on the advantages of both hierarchical and nonhierarchical analysis. TwoStep cluster analysis allows researchers to reveal natural groupings within large datasets and its main advantages involve the possibility of creating clusters from both categorical and continuous variables, its appropriateness for large datasets, and, finally, the inclusion of both continuous and categorical variables as foundations for the clusters. That final property of TwoStep clustering was crucial for creating profiles of L2 learners based on the levels of their personality traits and reported LLS use since it allowed the inclusion of LLS attributes as ordinal variables (that is, low, medium, and high reported strategy use) corresponding to Oxford’s (1990) SILL Profile of Results, the division of participants into infrequent, average, and frequent LLS users involved the acknowledgement of the following cut-off points: • for infrequent LLS users—mean LLS use lower than 2.5; • for average LLS users—mean LLS use between 2.5 and 3.4; • for frequent LLS users—mean LLS use higher than 3.5. The other clustering technique applied in the study, that is k-means clustering, relied on Ward’s method (Ward & Hook, 1963) to minimize the total within-cluster variance, and Euclidean distance as a measure of distance between the analyzed cases of learners. Cluster membership was saved as a separate variable in order to expand the range of characteristics for each respondent. Due to discrepancies in the range of values between personality scales and strategy scales (the former ranging from 0 to 40 as sums, the latter ranging from 0 to 5 as mean values), the data were standardized and new, standardized variables were created. Participants were then reanalyzed in terms of the differences in their levels of personality traits and the frequency of using LLS (both in general and with respect to particular scales) and the differences between clusters were tested for significance. On the basis of the findings of both types of the cluster analysis, learner profiles were created which were subsequently used in the discussion of the correspondence between language learners’ personality traits and their strategic choices. The assessment of the model of clustering was demonstrated in a figure. Conclusions were drawn about individuals’ membership in the obtained clusters and, subsequently, the results of the clustering

4.3 The Design of the Main Study

165

procedure were referred to from various theoretical perspectives in the discussion section. As explained in the initial part of the present section, some of the datasets analyzed in the study were characterized by distributions which significantly differed from what is viewed as normal distribution (p < 0.05 adjusted by the Bonferroni correction for multiple tests). Therefore, investigating the significance of differences in terms of participants’ levels of personality traits and reported LLS use across the obtained clusters of language learners required the use of the Kruskal–Wallis test. According to Brown (1988), the Kruskal–Wallis test may be treated as an extension of the Mann–Whitney U test applicable to comparisons across more than two means if all groups are random samples from their respective populations and the assumption of their independence among samples is met. The null hypothesis, H0 , assumed that the mean ranks of the investigated LLS and personality were the same across the analyzed clusters while H1 assumed that they were not. Mann–Whitney tests were applied as post-hoc tests in order to ascertain which pairs differed significantly from one another across the clusters. Importantly, the Bonferroni correction was applied to the significance values obtained from the series of Mann–Whitney tests.

4.3.5.2

Qualitative Procedures

TA (Braun & Clarke, 2006; Braun et al., 2022) was used to interpret the qualitative data collected in a series of 19 semi-structured interviews (see Sect. 4.3.3.3 for a description of this tool). The analysis fell into the categories of reflexive and, primarily, deductive. It may be seen as reflexive in the sense that when conducting it, the present researchers were fully cognizant of the need to make analytical decisions, the necessity to question and query their initial assumption, and the requirement for their active participation in the processes of theme identification and retrieval (cf. Braun & Clarke, 2019). At the same time, the analysis may be regarded as deductive since a series of concepts, ideas, and topics, pertaining to both personality traits and the use of LLS, were used in the process of data coding and interpretation (Braun & Clarke, 2012). However, while the deductive approach seemed inevitable in the specific case of the present investigation, since both the codes and the themes naturally derived from a plethora of studies into human personality and LLS, the semantic content of the data was not marginalized. Importantly, it was expected that given the advantage of the intimate familiarity between the interviewer and the interviewees (Delamont et al., 2010), no effects such as social desirability bias or self-deception should occur. The six-phase process for data engagement, coding and theme development reflected the framework put forward by Braun and Clarke (2006; Braun et al., 2022) and consisted of (1) becoming familiar with the data through a preliminary marking of ideas for coding and transcription of verbal data and writing familiarization notes; (2) systematic data coding;

166

(3) (4) (5) (6)

4 Methodology of the Research Project

generating initial themes; searching for, developing and reviewing themes; defining, refining, and naming themes; producing the report.

Following Braun and Clarke’s (2012) guidelines for the above stages of TA, Stage 1 involved immersing in the data by listening to the recorded interviews and reading the transcripts as well as note-taking through annotating the transcripts and highlighting text passages particularly from the angle of the research questions. Stage 2 consisted in implementing codes as constituents of later analysis with the aim to provide labels for participants’ use of LLS, their personality traits, and the possible impact of personality traits on strategy use. While a large proportion of the codes were descriptive or semantic, some of them could at the same time be labelled as latent or interpretative. Examples of such codes were the personality traits, some of which participants explicitly referred to. Stage 3 primarily entailed shifting from codes to themes in order to formulate the answers to the research questions. The themes were generated in the process of active construction. Stage 4 responded to the necessity of reinvestigating the themes developed in the previous stage by confirming their status as themes as opposed to merely codes, examining their usefulness in answering the research questions, setting their boundaries, and, finally, analysing the amount of the data supporting the themes in terms of their sufficiency and coherence. Stage 5 resulted in developing the final themes, which were intended to have a singular focus, be related, but not overlapping, and, at the same time, directly address the research questions. Finally, Stage 6 comprised writing up the findings of the TA in the form of a coherent story with meaningfully and logically connected themes related to both research questions.

4.4 Conclusion The present chapter was intended to account for the rationale, design, and methods of investigation applied in the empirical study of the relationships between the level of the participants’ personality traits and frequency and types of the LLS which they employed in learning English. The original idea behind the research project consisted in developing a methodology that would cater for the advantages of both the idiographic approach and the nomothetic approach towards investigating the differences in LLS use across groups of learners varying in terms of their personality trait levels. Consequently, the main study was planned as a mixed-method empirical investigation. The data collection tools were also piloted to ensure their validity and reliability. Moreover, particular attention was given to selecting a representative sample of students so that results of the study could be generalized across the populations of at least the two universities where the study was conducted. Both instruments employed in the quantitative part of the study, the SILL ver. 7.0 (Oxford, 1990) and the NEO-FFI (Costa & McCrae, 1992), have a long-established

References

167

tradition in personality investigations and studies exploring LLS. A vital part of the chapter was dedicated to the investigation of how both instruments complied with the goodness criteria for psychometric tests (Hornowska, 2007) as well as research instruments applied in investigating L2 learning (Dörneyi, 2003). In spite of the conscientious planning and administration of the study, it was impossible to resolve all the problems that eventually emerged in its implementation. Specifically, concerns might arise about the insufficient reliability of the affective strategies scale of the SILL. In spite of the steps taken to improve its internal consistency, it remained relatively low. Conducted for the purpose of data and method triangulation (Wi´sniewska, 2014), the semi-structured interviews with the participants were analyzed according to the framework suggested by Braun and Clarke (2006, 2012, 2019, 2021). In line with the recent calls for increased rigor in qualitative research (Thomas et al., 2022), the interviews relied on thematic analysis of learners’ insights into their use of LLS and its possible links to their personality traits. Attention was paid to how LLS were used in specific contexts and by specific learners so as to allow for accounting for the language learning process as a personal experience (the why and how of strategy use) (Pawlak, 2021; Pawlak & Oxford, 2018; Thomas et al., 2022).

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Chapter 5

Findings of the Research Project

5.1 Introduction Whereas some of the studies referred to in Chap. 3 of the present volume have indeed examined the correspondence between LLS use and L2 learners’ personality traits, only a limited proportion of them have attempted to account for the role of personality in strategy use by approaching personality as a constellation of traits rather than investigating the impact of particular characteristics. Without doubt, research assessing the impact of specific personal qualities on such aspects of L2 learning as TL attainment or broadly understood L2 performance can be valid, empirically grounded, and useful. This having been said, language learners can also be investigated as individuals who are unique not merely because of their traits but also combinations of these traits (Piechurska-Kuciel, 2020). Such a perspective appears particularly enticing since, while it remains nomothetic in nature, in a way it also responds to Allport’s (1961) calls for the use of “within-person”, idiographic methods in investigations of personality. In this vein, the research project discussed in this chapter aimed to account for the correspondence between LLS use and clusters of personality traits. Attempting to answer RQs 1 and 2, the initial part of the present chapter contains a thorough description of the participants in terms of their reported use of LLS and personality trait levels (Sect. 5.2). Section 5.3 is intended to answer RQ 3 and examines the possibility of extracting relatively homogenous clusters of L2 learners on the basis of their self-reported strategy use and their personality-related characteristics. Thus, it presents the results of quantitative and qualitative analysis described in Chap. 4. While the former is based on two independent clustering techniques, that is, hierarchical analysis and k-means analysis, the latter primarily involves deductive TA. The findings of the study are discussed and referred to relevant findings in the field in Sect. 5.4. This is followed by a concluding section (Sect. 5.5).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6_5

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5 Findings of the Research Project

Table 5.1 Descriptive statistics for LLS scales LLS scales Memory Cognitive Compensation Meta-cognitive Affective Social GULLS M

2.56

2.93

3.25

2.91

2.54

3.03

2.84

Md

2.56

2.93

3.17

2.89

2.56

3.00

2.85

SD

0.58

0.61

0.64

0.73

0.52

0.75

0.48

Percentiles 25

2.11

2.50

2.83

2.44

2.11

2.50

50

2.56

2.93

3.17

2.89

2.56

3.85

75

2.89

3.29

3.67

3.44

2.89

3.17

% of infrequent strategy users1

39.7

19.6

9.1

23.8

41.3

21.1

13.6

% of frequent strategy users2

5.2

19.1

39.4

22.4

4.1

29.9

10.8

5.2 Participants’ Reports of LLS Use and Personality Traits 5.2.1 LLS Use Any attempt to account for the links between learners’ personality traits and their use of LLS requires a preliminary characterization of the involved variables in terms their central tendency and dispersion. Table 5.1 contains the descriptive statistics for the six strategy scales of memory, cognitive, metacognitive, compensation, affective, and social LLS, as well as for the mean overall frequency of LLS use, operationalized as GULLS. Specifically, for each category, the mean and median values are provided, followed by the value of standard deviation SD, and means for each of the three quartiles. The final two rows contain percentages of participants who can be described as infrequent and frequent LLS users according to the SILL Profile of Results (Oxford, 1990). As can be seen from the table, 13.6% of participants could be classified as infrequent strategy users, whose SILL averages did not exceed the value 2.5, a vast majority of 75.6% of students were characterized by medium strategy use, with average scores ranging from 2.5 to 3.4, and 10.8% of participants were frequent strategy users, whose SILL scores exceeded the value 3.5. It was observed that the students showed a preference for two categories of LLS, compensation and social strategies, whose mean frequencies both exceeded 3.00. Both types of LLS from the cognitive dimension, 1

Oxford’s (1990, p. 300) key to understanding the averages assumes mean frequencies below 2.4 to be low. 2 Oxford’s (1990, p. 300) key to understanding the averages assumes mean frequencies above 3.5 to be high.

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173

cognitive and metacognitive strategies, were applied with moderate frequency (mean values approximating 3.00). The participants were not particularly fond of two categories of LLS, memory and affective strategies, whose mean frequency values only slightly exceeded the value 2.5, being the lower band of the interval of mean (average) strategy use according to Oxford’s (1990) SILL Profile of Results. According to the guidelines included in this document, the aggregate values of frequencies regarding both the general use of language learning strategies (GULLS) fell within the medium range of strategy use. For three LLS scales, the proportions of frequent strategy users were slightly lower than the proportions of rare strategy users with the differences amounting to 2.8% with regard to GULLS, 5% with regard to cognitive strategies, and 1.4% with regard to metacognitive strategies. The contrast was much starker with reference to memory strategies, which were frequently used by only 5.2% of the students, but rarely used by more than 39%, and affective strategies, which were infrequently used by more than 40% of the entire sample, but frequently used by only about 4%. Conversely, frequent strategy users were considerably more numerous than infrequent strategy users with regard to the categories of compensation strategies and social strategies, with differences amounting to 30.3% and 8.7% of the students, respectively. Two values of SD were relatively high, that is, the SD for the social scale (nearly 0.75) and the SD for the metacognitive scale (more than 0.73), which indicates considerable differences in the use of these two categories of LLS among the participants. Within the two most favored categories of LLS, that is, compensation and social, three specific strategies were reported to be used particularly frequently, and the relevant average values could be described as high according to Oxford’s (1990. p. 300) SILL Profile of Results. They were as follows: . When I do not understand, I ask the speaker to slow down, repeat, or clarify what was said (social strategy; M = 3.97); . When I cannot think of the correct expression to say or write, I find a different way to express the idea; for example, I use a synonym or describe the idea (compensation strategy; M = 3.96); . When I cannot understand all the words I read or hear, I guess the general meaning by using any clue I can find, for example, clues from the context or situation (compensation strategy; M = 3.56). Other LLS whose frequencies of use were high included one cognitive strategy and one affective strategy: . I say or write new English words several times (cognitive strategy; M = 3.56); . I try to have a positive image of my English teacher (affective strategy; M = 4.03).3 No metacognitive strategies exceeded the lower band of the high strategy use interval. However, the mean values of three specific LLS in this category were relatively high: 3

The question was introduced after consulting a panel of experts (see Sect. 4.2.1).

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. I notice my English mistakes and use that information to help me do better (M = 3.30); . I pay attention when someone is speaking English (M = 3.33); . I think about my progress in English (M = 3.27). As far as memory strategies are concerned, none of them were used frequently. The most popular strategy was I remembering new English words or phrases by remembering their location on the page, on the board, or on a street sign (M = 3.12). This was also the only strategy for which the value representing its reported frequency of use exceeded 3.0. The LLS whose frequencies of use could be described as low according to Oxford (1990) included three belonging to the affective domain, two representing memory use, and three strategies which each belonged to a separate category: . I keep a private diary or journal where I write my feelings about language learning (affective; M = 1.19) . I talk to someone I trust about my attitudes and feelings concerning the language learning process (affective; M = 1.93); . I share my feelings about learning and/or using English by writing a blog or using social media (affective; M = 1.45); . I use rhyming to remember the sound of the new word in my mind (affective; M = 1.68); . I initiate conversations in the new language (cognitive; M = 2.65); . I draw the meaning of an English word that I cannot remember (compensation; M = 1.45); . I arrange my schedule to study and practice the new language consistently, not just when there is the pressure of a test (metacognitive; M = 2.40). As clearly demonstrated above, affective LLS turned out to be the least employed strategy category. This finding is discussed in detail in Sect. 5.5.1 where possible explanations for this finding are presented.

5.2.2 Personality Traits As already mentioned, in order to be interpretable, descriptive statistics for personality scales need to be calculated across genders and within specific age ranges. Therefore, descriptive statistics for raw personality scores were tabulated so as to reflect the procedure for strategy scales, but a valid interpretation of personality scores required data splitting across genders and the prescribed age intervals (Zawadzki et al., 2010). Table 5.2 contains descriptive statistics for raw personality values of the ‘big’ five personality traits. Tables 5.3, 5.4, 5.5 and 5.6 present descriptive statistics for the levels of the “big” five personality traits for women aged 18 and 19, men aged 18 and 18, women aged 20–29, and men aged 20–29. The final column in each table is the standard ten (sten)

5.2 Participants’ Reports of LLS Use and Personality Traits

175

Table 5.2 Descriptive statistics for personality scales—raw scores Scale

Neuroticism

Extraversion

Openness to experience

Agreeableness

Conscientiousness

M

24.83

28.17

29.30

28.42

29.68

Md

25

28

29

29

30

SD

7.78

7.16

6.24

6.37

7.90

score that an individual would achieve if their trait intensity was equal to the mean value for the specific group (for instance, interpreted for a man, aged 20–29). It was expected that the mean values should correspond with the hypothetical values of stens 5 or 6, that is, the middle of the sten scale, as it is typically true for data sets whose distributions do not considerably differ from normal (cf. Hornowska, 2007). Regarding the group of women aged 18 and 19, all mean values for openness to experience and extraversion would be interpreted as sten 5 values, and the mean Table 5.3 Descriptive statistics for personality scales—women aged 18 and 19 Personality trait

M

Md

SD

Sten

Neuroticism

26.04

26.5

7.40

6

Extraversion

28.76

28

6.93

5

Openness to experience

30.25

29

6.28

6

Agreeableness

29.42

30

6.13

6

Conscientiousness

29.47

30

7.40

6

Table 5.4 Descriptive statistics for personality scales—men aged 18 and 19 Personality trait

M

Md

SD

Sten

Neuroticism

24.74

25

9.34

6

Extraversion

25.92

27

6.31

5

Openness to experience

27.84

26

6.89

5

Agreeableness

25.60

26

6.66

5

Conscientiousness

29.11

28

8.84

6

Table 5.5 Descriptive statistics for personality scales—women aged 20–29 Personality trait

M

Md

SD

Sten

Neuroticism

25.65

26

7.58

5

Extraversion

28.57

29

6.96

6

Openness to experience

29.45

29

6.24

6

Agreeableness

29.06

29

6.36

5

Conscientiousness

30.74

31

7.97

6

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5 Findings of the Research Project

Table 5.6 Descriptive statistics for personality scales—men aged 20–29 Personality trait

M

Md

SD

Sten

Neuroticism

22.79

23

7.49

6

Extraversion

27.94

28

7.63

5

Openness to experience

28.90

29

6.09

6

Agreeableness

27.78

28

6.27

5

Conscientiousness

28.52

29

7.56

5

values for conscientiousness, agreeableness, and neuroticism would be interpreted sten 6 values. Relevant data are presented in Table 5.3. As far as the male participants aged 18 and 19 were concerned, the mean scores of personality trait levels also corresponded with the ranges of central stens, 5 and 6. Interpreted for a single individual, the mean values for openness to experience, extraversion, and agreeableness would be diagnosed as sten 5 values, whereas the mean values for conscientiousness and neuroticism, would be diagnosed as sten 6 values. Detailed information is provided in Table 5.4. With reference to the female participants aged 20–29, the mean scores of personality trait levels interpreted as individual values would be interpreted as stens 5 and 6, too. More specifically, the mean values for openness to experience, conscientiousness, and extraversion would be diagnosed as sten 5 values, while the mean values for agreeableness and neuroticism would be diagnosed as sten 6 values. Table 5.5 contains relevant information. Finally, the values of trait intensity for men aged 20–29 could also corresponded to mid sten scores in terms of their psychological interpretation. The levels of the particular “big” traits would correspond to sten 6 for openness to experience, conscientiousness, and extraversion, and sten 5 for agreeableness and neuroticism. Table 5.6 presents relevant data. Overall, when confronted with norms for Polish men and women in appropriate age groups, all the mean values of the levels of the “big” five personality traits would represent sten 5 or sten 6 values. This means that no mean value for any personality trait lay in the extreme, upper (7–10) or lower (1–3) range of the sten scale, and thus the trait intensity could be rated as reflecting the levels for the majority of the Polish population (Zawadzki et al., 2010).

5.3 Participants’ Profiles In order to provide the answer to RQ3, clustering techniques described in Sect. 4.2.4 were employed. By applying the two-step clustering technique, initial pre-clusters of learners were distinguished, which were afterwards used to create a categorical variable, cluster membership, in the hierarchical analysis. The obtained results were

5.3 Participants’ Profiles

177

then compared with the results of the k-means non-hierarchical clustering procedure in order to triangulate both groups of findings. Along with the GULLS levels entered as ordinal values, 1 (low use), 2 (medium use), and 3 (frequent use), the input variables in cluster analysis included the levels of the four personality traits whose levels turned out to be statistically significant determinants of LLS use in a different study (Przybył & Pawlak, under review): openness to experience, extraversion, conscientiousness, and neuroticism. The following subsections report the results of two-step cluster analysis, k-means cluster analysis, and findings from a series of semi-structured interviews.

5.3.1 Results of Two-Step Cluster Analysis Based on calculating the log-likelihood distance measure, the use of the algorithm described in Sect. 4.3.5.1 resulted in the emergence of three clusters of learners, closely corresponding to their SILL Profile of Results (Oxford, 1990), that is, distinguishing between infrequent, average, and frequent LLS use. Although the clusters of frequent and infrequent strategy users (3 and 1) were less numerous than the cluster of average strategy users, the model fit was fair, as illustrated in Fig. 5.1. Table 5.7 contains preliminary information concerning cluster distribution, including the number of learners included in each cluster, and the percentage of the entire sample. Members of Cluster 1 were infrequent strategy users, whose GULLS scores amounted to 2.4 or less, characterized by the lowest levels of openness to experience, extraversion, agreeableness and conscientiousness, and the highest level of Model Summary Algorithm

TwoStep

Inputs

5

Clusters

3

Cluster Quality

Poor -1.0

-0.5

0.0

Fair

Good

0.5

Silhouette measure of cohesion and separation Fig. 5.1 Two-step cluster model summary

1.0

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5 Findings of the Research Project

Table 5.7 Cluster distribution

N Cluster

% of the entire sample (%)

1—Infrequent LLS users

123

25.9

2—Average LLS users

319

67.2

3—Frequent LLS users

33

6.9

Combined Excluded cases

475

100.0

267

neuroticism in comparison to the other groups. They constituted approximately 26% of all participants assigned to clusters. Members of Cluster 2, that is, approximately, two thirds of all the informants assigned to clusters, were average strategy users, whose mean GULLS values ranged from 2.5 to 3.4, characterized by medium levels of neuroticism, openness to experience, extraversion, and conscientiousness in comparison to members of clusters 1 and 3. Finally, members of Cluster 3 were frequent strategy users whose GULLS scores amounted to 3.5 and above, but at the same time also highly open to experience, relatively more extravert, and slightly more conscientious than members of the remaining clusters. They were also characterized by the lowest levels of neuroticism. They constituted 7.5% of all the participants assigned to specific clusters. Overall, the quality of the clusters obtained through the application of the two-step cluster algorithm could be described as fair, with the coefficient of silhouette measure of cohesion and separation amounting to 0.4.4 Table 5.8 contains the values of the centroids for the four personality traits known to significantly impact LLS use (see Sect. 5.1) across GULLS categories, that is, openness to experience, extraversion, conscientiousness, and neuroticism. As indicated by the results of the Kruskal–Wallis test (see Sect. 4.3.5.1 for the description of the procedure), the differences in the levels of openness and extraversion, were found to be statistically significant across the three identified clusters (p < 0.05; value adjusted by the Bonferroni correction for multiple tests) while they were not statistically significant concerning participants’ levels of agreeableness, conscientiousness and neuroticism. The Mann–Whitney post-hoc tests revealed that members of Cluster 3, that is, frequent LLS users, were significantly more extravert than members of Clusters 1 and 2, that is, infrequent and average LLS users respectively. An even more prominent tendency was observed regarding the levels of openness to experience. Members of Cluster 1, who were infrequent LLS users, were significantly less open to experience than members of Clusters 2 and 3. Members of Cluster 3, that is, frequent strategy users, were significantly more open to experience 4

A coefficient of 0.5 or above indicates a good cluster quality, while a coefficient below 0.3 indicates a poor one.

SD

6.09

6.02

29.81

33.97

2

3

32.12

28.33

26.86 7.79

7.15

7.30 30.93

30.57

28.27 8.70

8.23

6.98

SD

M

6.23

27.23

M

M

SD

Conscientiousness

Openness to experience Extraversion

1

Cluster

Table 5.8 Distribution of personality trait level across clusters of learners

23.51

24.69

24.80

M

Neuroticism

7.97

7.76

8.08

SD

29.45

28.80

27.77

M

Agreeableness

7.15

6.52

5.91

SD

5.3 Participants’ Profiles 179

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5 Findings of the Research Project

than members of Clusters 1 and 2. Members of Cluster 2, that is, average LLS users, were significantly more open to experience than members of Cluster 1, that is, rare LLS users.

5.3.2 Results of k-means Cluster Analysis The final stage of quantitative analysis involved conducting non-hierarchical clustering with the use of the k-means procedure. It involved determining a fixed number of clusters, which was set as three, basing on the previous findings from two-step cluster analysis. Respondents were clustered according to the level of their personality traits as well as the frequencies of using each of the six strategy scales. The maximum number of iterations was set as 10, and cluster membership was set as a separate variable in order to expand the range of characteristics for each respondent. Due to discrepancies in the range of values between personality scales and strategy scales (the former ranging from 0 to 48 as sums while the latter ranging from 1 to 5 as mean values), the data were standardized and new, standardized variables were created. The distances between clusters were determined through iteration and classification and computed using simple Euclidean distance. Eventually, three clusters were isolated which included 212, 255, and 198 students. These clusters were marked as Q1, Q2, and Q3, and they directly corresponded to groups of infrequent, average, and frequent LLS users. Data for 77 students had to be discarded from the analysis since their personality traits or frequency of LLS use did not center around the centroid values in the three clusters. The ratio of the biggest cluster size to the smallest cluster size amounted to 1.29, which signaled a good model fit (ratio value less than 2.0). The descriptive statistics for each cluster are presented in Table 5.9. The categories taken into account include all six strategy scales, the aggregated strategy frequency of use (GULLS) and all the levels of all of the “big” five personality traits. For each category, the mean value (M) is shown across the isolated clusters along with the value of the standard deviation (SD). For the sake of clarity, the lowest values of the means per category are marked in red, medium values are marked in yellow, and the highest values are marked in green. The superscript letters a, b, and c serve as significance markers of differences across clusters. Different letters for any pair of clusters indicate that significant differences (p < 0.05) exist between the two compared clusters in the specific case of a given variable.5 As can be seen from the table, the participants belonging to Q1 were infrequent strategy users whose level of openness to experience tended to be significantly lower than the level of the trait which characterized the members of the other clusters. They 5

In order to account for the significance of the differences across clusters, the Kruskal–Wallis test, since for some of the investigated scales data distributions were significantly different from normal. The Mann–Whitney test was applied as the post-hoc in order to account for the significance in all the analysed pairs of comparisons. Significance values have been adjusted by the Bonferroni correction for multiple tests (see Sect. 4.3.5.1).

5.4 Semi-structured Interviews

181

Table 5.9 Centroids for final clusters Variable Memory strategies Cognitive strategies Compensation strategies Metacognitive strategies Affective strategies Social strategies GULLS_mean Neuroticism Openness to Experience Conscientiousness Extraversion Agreeableness

Q1 (N = 212) M SD 2.09a 0.47 2.32 a 0.38 2.75 a 0.55 2.24 a 0.49 2.19 a 0.39 2.41 a 0.56 2.39 a 0.26 23.83 a 9.07 25.31 a 5.97 28.64 a 6.70 27.18 a 7.13 28.42 a 6.01

Q2 (N = 255) M SD 2.54 b 0.44 3.03 b 0.41 3.36 b 0.51 2.97 b 0.50 2.54 b 0.42 3.10 b 0.53 2.98 b 0.20 24.57 ab 8.56 28.11 b 5.90 27.38 a 7.35 25.89 a 6.41 26.98 a 6.37

Q3 (N =198) M SD 3.04 c 0.42 3.41 c 0.49 3.63 c 0.57 3.55 c 0.58 2.93 c 0.47 3.64 c 0.60 3.41 c 0.30 22.03 ac 8.82 31.36 c 6.44 33.26 b 7.69 31.96 b 6.57 30.61 b 5.97

employed all categories of LLS significantly less frequently than the members of the other clusters. At the same time, their level of neuroticism was significantly lower than the level which characterized the members of Q2. The levels of conscientiousness, agreeableness and extraversion centered around values which were significantly lower than those characterizing Q3. The members of Q3 applied all categories of LLS significantly more often than members of the two remaining clusters. They were also significantly more open, extravert, conscientious, and agreeable, but less neurotic in comparison to their counterparts from the other clusters. Overall, a consistent pattern was observed in the use of all categories of LLS and the levels of openness to experience and neuroticism. With respect to the former trait, a positive relationship was observed between its level and the frequency of use of LLS in general and all their categories. With regard to the latter, a negative relationship was revealed. When it comes to the levels of the remaining traits, that is, conscientiousness, extraversion, and agreeableness, the results of the Kruskal–Wallis test indicated that the most frequent strategy users were also significantly more conscientious, extravert, and agreeable than members of the two remaining clusters. At the same time, members of Q1 tended to be more conscientious, extraverted, and agreeable than members of Q2.

5.4 Semi-structured Interviews As already mentioned in Sect. 4.3.5.2, the semi-structured interviews were conducted to ensure methodological triangulation (Wi´sniewska, 2014) and they were expected to shed further light on the link between participants’ personality characteristics and their use of LLS thanks to incorporating both the emic and etic perspectives as well as embracing the main tenet of qualitative research, which consists in paying sufficient attention to the role of context (cf. Friedman, 2012). In terms of the interviewed

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5 Findings of the Research Project

learners’ strategy repertoires, a number of observations could be made. To start with, memory strategies were frequently referred to as a tool that the students used less willingly and only if they thought that their employment was inevitable, and a more effective alternative was unavailable. Some statements which exemplify this view are as follows6 : I only memorize things when I learn for school. I only memorize business words which I find impossible to understand. Learning by heart doesn’t work for me in the long run because I need emotion to remember something.

These comments also demonstrated a strong link between the volitional and emotional correlates of the participants’ motivation to use specific LLS. Specifically, memory LLS were employed as a “last resort” in situations when the students almost felt coerced into learning. It was also found that such strategies were drawn upon by relatively less proficient learners, and employed in order to learn specialist vocabulary, but also grammar rules and specific forms of words. One learner reported “learning tenses by heart”, by which she meant learning both the rules of the use of tenses and learning irregular verb forms. When it comes to the use of cognitive strategies, a number of students paid attention to new vocabulary and/or structures which they encountered on various occasions. Some of them, particularly those who were characterized by a relatively high level of proficiency (B1 or above) kept track of lexical items which they encountered while watching series or films, listening to podcasts, or reading articles or various types of Internet posts. One such interviewee commented: “I like learning vocabulary items which I accidentally encounter in scientific articles”. Others referred to getting to know vocabulary in a natural way through exposure rather than learning it from books. The use of the above cognitive LLS was obviously orchestrated by the employment of metacognitive LLS as many of the participants reported actively creating opportunities through which, as some of them believed, they “immersed into language”. These opportunities primarily included exposure to various types of English input, such as books, films, articles or podcasts. The use of social strategies was commonly referred to in the interviews. Different types of social LLS were mentioned, such as studying in pairs or groups and practicing with native speakers. Relatively less proficient learners also reported working with private language tutors so as to prepare for tests or pass the final certificate exam at university. It was evident that motivational differences existed between more and less proficient learners in the use of social LLS. While the former relied on social LLS because they treated interacting in English as a natural part of the FLL process, the latter did it largely for instrumental reasons, that is, to increase their chances of passing the oral part of the certificate exam or even to persuade themselves that they did something to support themselves in getting credit in the L2 course. The distinction was evident in comments as “I am eager to be in the natural environment where English is spoken” (a more proficient learner) and “I even decided to hire a 6

All the excerpts were translated by the researchers.

5.4 Semi-structured Interviews

183

private tutor because I know I will not pass the exam in English if I don’t do something about it” (a less proficient student who had in fact failed the university EFL course once). Clearly, the use of social strategies was, again, subject to the influence of meta-social LLS, whose use mainly consisted in finding opportunities to interact in English. Examples of such practices, predominantly mentioned by higher-level learners, included cooperating with classmates when preparing for tests as well as joining online gaming groups and various types of Internet forums with English speakers from all over the world. One of the most surprising findings of the interviews was that although a number of the students were able to identify their emotions which accompanied them in learning English, none of them really admitted to trying to manage them in any way. Several more proficient participants reported the emotion of joy when learning English, which mostly pertained to the circumstances of engaging in spontaneous interaction with other speakers of English and/or delving into a topic of interest by extensive reading or watching videos. At the same time, less proficient learners frequently referred to the language learning experience as a struggle and expressed their fear concerning the attainment of the goals they set. This finding was relevant to both instrumental goals, such as passing the exam in English, and more abstract goals, such as becoming fluent in English. No participant made a reference to how he or she handled their emotions involved in learning English. This implies that the use of affective LLS could be scarce, but the use of meta-affective LLS could pose an even greater difficulty to university-level L2 learners. When it comes to the correspondence between LLS and personality traits, the analysis of data lent support to the findings described in the preceding sections. First of all, some learners who were highly open to experience and attributed a particular role to openness reported using a wide range of LLS. Their willingness to explore new strategies could be, perhaps, best described with the words of one of the participants: “It’s difficult to learn a language if you’re narrow-minded, unwilling to try new things or you just think that you already know everything”. On the other hand, a student whose level of openness was diagnosed as low acknowledged: “I know what helps me and I don’t look for other ways to study because what I do seems to be working”. Also, a number of the metacognitive and cognitive strategies reported by the highly open learners required their users to dedicate a considerable amount of time in the long run. For instance, this was probably the case of watching English films or reading books in English. One student confessed: “I’m really addicted to watching films in English” while another one commented: “If it wasn’t for English, I wouldn’t be able to do half the things I do. I mean, mainly entertainment”. A tendency which supported the conclusions from the k-means analysis of the interaction between LLS and personality traits consisted in highly extraverted students’ preference for social strategies. Declaring their willingness to learn through interaction with others, they appreciated the benefits of both learning together (for instance, revising for tests, checking each other’s answers) and participating in conversations in English with foreigners. Some of them established long-term friendships with foreigners and specifically referred to them as pen-pals. Others referred to the satisfaction they experienced when engaging in real-life conversations rather

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5 Findings of the Research Project

than classroom activities imitating genuine communication. Another reported benefit of social learning consisted in receiving immediate feedback both on one’s overall command of English and with reference to its specific issues required for successful communication. A number of participants reflected on the advantages of being a conscientious language learner. However, while quite a few interviewees did refer to the trait and its underlying facets, such as being systematic or persistent, no clear correspondence could be established between its level and participants’ preference for any category of LLS. Relatively more advanced learners (B1, B2) tended to refer to the impact of openness to experience or its underlying traits. Secondly, many of them insisted that they preferred learning in groups because of their extraverted personality or believed that they could easily engage into conversations with foreigners because socializing with other speakers of English did not pose a difficulty for them. On the other hand, the participants who were not extraverted still managed to prevent learning English from becoming a solitary experience. Some of them claimed that it was easier for them to apply instant messengers rather than use English in face-to-face conversations. Others indicated their preference for practicing with their friends or classmates of their own choice rather over interacting with strangers. In one specific case, an introverted person explained that while she tended to opt for learning on her own, but did not really mind, and in fact enjoyed getting a chance to prove herself when travelling to the US and talking to Americans. Finally, whereas a number of learners reflected on the importance of being conscientious in learning English, their self-perception in this respect was extremely critical. Some of them did not hesitate to call themselves lazy and wished they had been more determined in their efforts to master the TL. Nevertheless, it needs to be emphasized that, according to the results of the cluster analysis, while a specific combination of traits can indeed result in a more frequent (and possibly more efficient) use of LLS, exceptions to the rule are common, as illustrated by the number of cases beyond clusters.

5.5 Discussion The present section aims to discuss the results of the study by referring them to previous research findings as well as the theoretical foundations of the LLS construct (Oxford, 1990, 2011, 2017) and the trait theory of personality (Allport, 1961; Costa & McCrae, 1985, 1992; Eysenck & Eysenck, 1967, 1975; Goldberg et al., 2006). Following the order of the RQs, Sects. 5.1 and 5.2 are dedicated to participants’ characteristics in terms of LLS use and their personality traits while Sect. 5.3 addresses the issue of participants’ profiles established on the basis of their reports of LLS use and their personality trait levels.

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5.5.1 Participants’ Use of LLS The students demonstrated consistent patterns with respect to the reported frequency of LLS use. Participants’ overall preference for social and compensation strategies indicates that they tended to rely on collaboration and were not easily discouraged from learning or using English even when they had to cope with scarce resources as L2 users. This was reflected in the most frequent use of two strategies: When I do not understand, I ask the speaker to slow down, repeat, or clarify what was said and When I cannot think of the correct expression to say or write, I find a different way to express the idea; for example I use a synonym or describe the idea. Similar findings were reported by Yang (1993), who investigated a group of 500 Taiwanese students. At the same time, the results obtained by Magogwe and Oliver (2007) in a study of Batswana students were considerably different, which signals the relevance of learners’ cultural background and the mainstream ELT methodologies in their countries for their strategic choices. Specifically, in Poland there has been a shift in focus from accuracy to fluency in terms of the (upper) secondary7 school-leaving exam criteria and therefore more learners might place a premium on conveying meaning even if they do not know a specific word or phrase or lack appropriate structures. The least frequently used strategies were affective strategies, which, again, might be due to cultural reasons. In an earlier study conducted in another group of Polish students of English, it was found that learners used affective strategies the least frequently, which was attributed to their lack of familiarity with strategies involving reward rather than punishment (Przybył, 2016). The affective domain of LLS remained blatantly neglected by the participants of the present study, as approximately 40% turned out to be infrequent users of such LLS. In particular, the students tended to avoid sharing their feelings about learning English. Moreover, reflecting on one’s feelings about learning English was underappreciated by the students with regard to both spoken and written communication. To some extent, these findings stand in contrast to those relating to the popularity of social strategies among the participants. However, the use of social strategies does not require students to manage emotions or reflect on their beliefs about L2 learning or relevant attitudes, while the use of affective strategies certainly does. The difficulties experienced by language learners in the use and orchestration of affective strategies might therefore boil down to the lack of recognition of the role of affect and self-reflection in L2 learning rather than their unwillingness to share their feelings as such. In other words, it appears that the act of sharing one’s emotions with others is considerably more challenging whenever one’s own feelings about their language self are at stake. At the same 7

The Polish educational system has recently been reorganized. At the time when data were collected, everyone was required to attend a 6-year primary school and a 3-year lower secondary school. Afterwards, they could choose between an upper secondary school or a modern technical school if they wanted to go to college or university. However, in 2019 lower secondary schools ceased to exist while primary schools were extended to eight years. Consequently, upper secondary schools became secondary schools.

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time, frameworks which conceptualize affect are scarce, and both EFL teachers and researchers are not typically educated in this area and thus may have to rely on intuition. While emotional well-being has been proven to correlate with language proficiency in studies involving large samples of language learners (cf. Ehrman & Oxford, 1995; Piechurska-Kuciel, 2008), it is hard to disagree with the view expressed by K˛ebłowska (2012) that applied linguists have often neglected the area. Indeed, a number of handbooks of L2 learning do not include any consideration of the role of affect or merely provide an explanation of Krashen’s (1981) concept of the affective filter (cf. Doughty & Long, 2003). Also, whereas adopting a certain framework for investigating emotions is inevitable, the current status quo rejects both behavior-only and cognition-only-based visions of emotions (cf. Panksepp, 2008). This view is at least partly shared by Dörnyei (2009), according to whom emotions are inseparable from cognitive appraisals as the latter perform not only a cognitive, but also an evaluative and interpretative function. To make matters even more complex, emotions have recently been viewed as a developmental phenomenon, constructed by individuals on the basis of their idiosyncratic experiences, and subject to both physiological and environmental influences (Barrett, 2017). In terms of participants’ reported use of direct (that is, memory, cognitive, and compensation) and indirect (that is, metacognitive, affective, and social) LLS (cf. Oxford, 1990, 2011, 2017), several conclusions could be drawn. On the one hand, since most of the LLS used the least frequently were indirect strategies, it could be argued that participants of the study experienced difficulty in self-regulating the process of language learning (cf. Oxford, 2017; Przybył & Chudak, 2022). At the same time, it could be argued that the students did not exhibit any clear preference for either direct or indirect LLS, which would then be an indication of a healthy balance between mental processing of the target language and overall management of the learning process. Overall, it could be concluded that the participants exhibited a preference for LLS which allowed them to overcome L2 deficiencies and handle potential problems that they could encounter when communicating in the target language.

5.5.2 Participants’ Personality Traits As indicated in the manual for the Polish adaptation of the NEO-FFI (Zawadzki et al., 2010), interpreting the scores should be psychometric and the psychological in nature. In terms of the former, referring the mean scores calculated for women aged 18–19, men aged 18–19, women aged 20–29, and men aged 20–29 (see Sect. 5.2.2) to group-specific norms each time revealed that the levels of participants’ personality traits corresponded to stens 5 and 6. In other words, the scores could be seen as average and typical for one third of the overall population of Poles in each of the analyzed age groups (Zawadzki et al., 2010). This notwithstanding, the levels of each of the “big” five personality traits within each and every age- and gender-specific

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category reported by some of the participants of the study fell into the categories of low and high, which was reflected in the SD values. Relying on the psychometric interpretation, the psychological interpretation of the NEO-FFI scores incorporates two aspects (Costa & McCrae, 1992; Zawadzki et al, 2010). Frequently referred to as psychological profiling, the first one pertains to a detailed characteristic of an individual in terms of some of their qualities and making inferences about others. At the same time, labelled as functional interpretation, the second involves assigning meaning to specific trait levels, particularly regarding the way in which individuals respond to the environment. A brief psychological interpretation of scores within stens 5 and 6 is provided below on the basis of the account brought by Zawadzki et al. (2010). . Regarding neuroticism, the majority of the participants were generally calm and well-balanced, but sometimes experienced feelings such as anger, grief, or guilt; . In terms of the level of extraversion, participants’ level of social activity was fairly average, with signs of preference for both establishing contacts with others on the one hand and keeping a certain dose of privacy on the other hand; . The average level of agreeableness indicated that the participants generally displayed cooperative orientation, but at the same time, did sometimes enjoy rivalry; . The mid sten value of the level of conscientiousness could be interpreted as indicating having clear targets in life on the one hand but no orientation towards reaching them at all price on the other hand; . The average level of openness to experience could be understood as a marker of being fairly practical and down to earth but not deprived of unconventional interests or pursuits, and consequently, maintaining a balance between tradition and novelty. It needs to be emphasized that the above interpretation only serves as an example and it does not necessarily apply whenever a particular score characterizing a participant in terms of any of the “big” five traits falls in the range of stens 1–3 or 7–10.

5.5.3 Clusters of Language Learners Distinguished by LLS Use and Personality Traits As pointed out by Piechurska-Kuciel (2020), the process of L2 learning is subject to idiosyncratic modifications on the part of the language learners which result not merely from the influence of each of their personality traits but also the impact of their unique combinations. Aiming to identify clusters of L2 learners formed on the basis of their personality traits and reported frequencies of LLS application, the final part of the study generated empirical evidence that could partly be interpreted as a confirmation of findings in the fields of educational psychology and the psychology

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of the language learner (Williams et al., 2015; MacIntyre et al., 2016). However, at the same time, it also expanded the perception of the L2 learners by taking into account all their “big” five personality dimensions and complete strategy repertoires. The members of the three clusters extracted in k-means analysis differed significantly in virtually all aspects which were analyzed. In particular, the members of Cluster 3 applied all categories of LLS significantly more frequently and were significantly more open to experience, extravert, conscientious and agreeable than members of the two other clusters, but also less neurotic than members of Cluster 2. Also, no significant differences in the level of neuroticism existed between members of Cluster 1 and Cluster 3. These findings imply that personality traits could work in a complimentary rather than substitutive manner. In other words, the fact that a given language learner is a frequent strategy user might result from a combination of being relatively open to experience and conscientious rather than being either open or conscientious. Moreover, according to the results of the k-means analysis, frequent strategy users were also typically relatively more extravert and more agreeable than an average or infrequent strategy users. Relating the assumptions presented above to former studies poses a challenge as, traditionally, the profiles of L2 learners did not use to be constructed on the basis of the levels of actual personality traits and rarely, if ever, on the basis of reported use of LLS. Instead, embracing the perspective of psychological determinism, numerous researchers have made efforts to account for the psychological profiles of good language learners (Dewaele, 2022). Indeed, references have been made to the right set of qualities which could benefit L2 attainment. Accounting for the role of trait clusters in FLL, Piechurska-Kuciel (2020) referred to them as the right stuff and concluded that “superior L2 learning and performance might be associated with a personality profile characterized by a combination of at least moderate levels of extraversion, openness to experience, agreeableness and conscientiousness along with lower levels of neuroticism” (p. 167). This stance is, to some extent, corroborated by the outcomes of the present study, according to which frequent LLS users were typically more extraverted, open, agreeable, and conscientious than infrequent and average LLS users. In retrospect, both empirical findings and speculations concerning the impact of some underlying facets of the “big” five personality traits have been present in publications on FLL for at least several decades. The results of the present study lend partial support to Jankowski’s (1973) views, according to which imagination (a component of openness to experience) and ability to concentrate (a component of conscientiousness) are both likely to facilitate L2 learning and people’s imaginative capacity can be linked to their efficiency at remembering details along with the ability to plan the learning process (a metacognitive strategy). Moreover, such a combination of characteristics could prevent learners from experiencing fatigue or boredom and losing concentration. Findings concerning the levels of each of the “big” five personality traits characterizing frequent LLS users’ may be related to earlier studies into the impact of each of these traits. They lend support to empirical investigations which revealed the correlation between extraversion and the use of socio-affective LLS (Bielska, 2006; Ehrman & Oxford, 1989; Wakamoto, 2000) as well as those which provided evidence

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for the beneficial impact of extraversion on the use of LLS in general (Chen & Hung, 2012; Zhou & Intraprasent, 2015). At the same time, they remain in stark contrast with the results of Sharp’s (2008) study, according to which the use of cognitive LLS was positively related to introversion. Concerning the negative impact of high levels of neuroticism on LLS use, the results of the present study correspond to the findings reported by Alibakhshi et al. (2017), Fazeli (2011), and Liyanage and Bartlett (2013). At the same time, the negative relationship between the levels of neuroticism and language learners’ use of social and compensation strategies corroborates the outcomes of the study conducted by Ghyasi et al. (2013), which revealed that highly neurotic language learners typically abstain from help seeking in the process of L2 learning. To some extent, the present study also supports the outcomes of earlier investigations into the impact of agreeableness on the application of LLS, particularly with respect to affective (cf. Obralic & Muralic, 2017) and compensation strategies (cf. Fazeli, 2011). Similarly, when it comes to the impact of conscientiousness, the results of both the quantitative and the qualitative analysis reported in the present chapter point to its impact on better orchestration of LLS overall and correspond to previous research linking the level of the trait to the use of time management as well as metacognitive and cognitive LLS (Ghyasi et al., 2013). The most clear-cut findings of the present study pertain to the positive impact of openness to experience on LLS use and thus lend support to earlier investigations which viewed it as a desirable trait, particularly for university students (Gray & Watson, 2002). Statistically significant differences were, indeed, found with respect to the level of openness between frequent, average, and rare strategy users with respect to all the strategy categories as well as overall strategy use. This highlights the importance of openness in tertiary language education and once again supports the distinction between the predictors of academic performance and achievement in tertiary education in general and those regarding foreign languages. Along with the results of previous studies linking the level of openness and its underlying traits to variables which contribute to success in L2 development, such as language aptitude (Tyszkowa, 1990) or willingness to communicate (Piechurska-Kuciel, 2018), the findings of the present empirical investigation rank openness as the most vital trait in L2 learning. In addition, the role of openness in aiding the mastery of foreign languages can be understood more holistically after considering the results of the study conducted by Schwartz et al. (2013). According to its results, openness to experience is the trait whose level can best be predicted on the basis of language use, involving such characteristics in the case of highly open individuals as markers of aesthetic interests, misspelt words or contractions in the specific case of online written communication. Finally, the results of the study are in line with ChamorroPremuzik’s (2006) findings, according to which the role of openness to experience in education increases with each educational stage and becomes equal to that of conscientiousness at university level. Referred to by Biedro´n (2011) as the will to achieve, conscientiousness certainly plays an important part in planning and organizing one’s learning. Consequently, the finding that frequent LLS users turned out to be significantly more conscientious than infrequent LLS users should not come as a surprise. Moreover, this personality

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trait was frequently viewed by the interviewed students as a desirable quality for language learners. Curiously, a number of interviewees expressed their concerns about not being conscientious enough and wished they had dedicated more time to learning English before they had commenced studying at university. This finding supports the results of Pourfeiz’s (2015) study, which showed that conscientiousness served as a valid predictor of the affective-evaluative component of LLS use. At the same time, the impact of high levels of the trait on the use of LLS and L2 development is far from unequivocally positive. This is because the interviewed students who viewed themselves as conscientious expressed their fear of making mistakes when communicating in English in the classroom. This could be attributed to highly conscientious people’s inclinations towards perfectionism, which might not be facilitative in the specific case of L2 learning due to its affective implications. Also, the conviction concerning the beneficial impact of a high level of conscientiousness on academic performance expressed by Dörnyei and Ryan (2015) might be somewhat overstated in view of the fact that the empirical investigation conducted by Khodaddy and Zabihi (2011) failed to confirm a positive relationship between personality and attainment operationalized as learners’ GPA in English. Importantly, the results of the k-means cluster analysis indicated that conscientiousness need not be viewed as a “rival” trait of openness to experience. In fact, participants who were more frequent strategy users were characterized by significantly higher levels of both traits. However, the impact of openness was both stronger and more consistent across all clusters. One more time, it could be argued that L2 learning differs remarkably from learning other subjects at school or at university and so do factors which determine learners’ attainment in these two fields, including LLS use. The analysis showed that high levels of extraversion corresponded with frequent LLS use, presumably by facilitating learners’ involvement in interaction in L2, both inside and outside the classroom. From the perspective of LLS use, relatively more extravert learners are more likely to make efforts to find interlocutors to hold conversations in English or ask questions in English. Indeed, earlier studies (for instance, Griffiths, 1991; Oz, 2014) linked extraverts’ more frequent use of social strategies to their being discovery-driven rather than reception-driven in learning as well as their desire to talk to strangers in an L2. The results of cluster analysis undertaken in the present study corroborate these findings. More generally, it could be inferred that being an extravert facilitates the use of social LLS, and cooperative strategies in general, which consequently enhances learners’ overall strategy repertoire. This can be related to the results of an earlier study by Konttinen (1970), according to which extraverts are more likely to develop L2 skills in general. The findings of the present study can also be related to more specific results of previous empirical investigations. For example, with regard to extraverts’ use of metacognitive strategies, they support insights from Fayyaz’s and Kamal (2011) study which confirmed a positive relationship between learners’ level of metacognitive awareness with regard to listening skills and their level of extraversion. Importantly, the beliefs about the usefulness of being extravert in learning English as L2 were expressed in the interviews, in which the students who considered themselves introverts expressed envy about the easiness with which extraverts interacted with others and wished they could employ more

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social and collaborative strategies. It seems that in terms of the perceived usefulness of possessing a high level of the trait, not much has changed since the study conducted by Naiman et al. (1978), according to which 31% of good language learners directly linked the level of extraversion to the acquisition of oral skills in L2. At the same time, it is worth emphasizing that the beliefs about the positive impact of extraversion on L2 achievement were empirically confirmed by Oya et al. (2004), who demonstrated that teachers assessing learners’ performance tended to form better global impression of extravert students, as well as Ockey (2009), who found that better scores in oral tasks correlated with students’ level of assertiveness (one of the underlying facets of extraversion). The present investigation showed that the level of neuroticism influences the use of LLS in general, but the impact of the trait is far from consistent. Individuals who are characterized by a high level of neuroticism may suffer from maladjustment, have low stress tolerance, suffer from various types of anxiety, behave in a hostile way, or even develop depression (Magnavita, 2004), which may inhibit their learning ability and LLS use. In one of the interviews, a highly neurotic student complained about being anxious when using English in the classroom, being afraid of making a mistake, and pointed out that anxiety impeded comprehension and seriously limited her communicative ability. Perhaps one way to arrive at more conclusive results would be to investigate the relationships between the frequency of strategy use and the underlying facets of neuroticism, that is, anxiety, emotionality, or moodiness and linking them to self-perception (cf. Thomson, 2016). Finally, the results of the k-means analysis indicated that the level of agreeableness followed the pattern observed for extraversion and conscientiousness. Specifically, frequent strategy users were more agreeable than rare strategy users, yet the differences in the level of the trait were not statistically significant. The impact of the trait remains largely unknown, not only in the field of LLS, but also in other areas of SLA research (cf. Piechurska-Kuciel, 2020). As already mentioned, the results of the quantitative analysis provided support for some earlier findings concerning the relationship between agreeableness and affective and compensation L2 use (e.g., Fazeli, 2012; Obralic & Muralic, 2017). This said, more research needs to be done into the possible role of the trait in LLS use, particularly in view of the scarcity of corroborating evidence in the qualitative data obtained by means of the interviews.

5.5.4 Limitations of the Study While the methodology applied in the study has contributed to providing answers to the research questions formulated in Sect. 4.3.1, the research project is not free from limitations which mainly pertain to the data-collection instruments used to measure the self-reported use of LLS and the level of participants’ personality traits. When it comes to the SILL ver. 7.0 (Oxford, 1990), criticism has been expressed about its theoretical basis or potential psychometric weaknesses (cf. Dörnyei, 2003; Rose, 2015; Tseng et al., 2006; see Sect. 4.3.3.1). Indeed, even after introducing a number

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of amendments to the questionnaire, it remains an instrument created about three decades ago and thus to some extent outdated. Thus, despite the fact that it allows comparisons with a large number of other studies that have relied on this instrument, it may gradually cease to be a sufficient representation of nature and scope of LLS currently used by L2 learners. This having been said, although Oxford (2017) herself has advocated for a major shift in strategy research from the investigation of general tendencies to studies dedicated to contextualized use of LLS with respect to specific skills or tasks, it would be premature to discontinue large-scale quantitative research or abandon studies into LLS for the sake of investigating learners’ self-regulation (cf. Rose, 2012). Instead, attempts could be made to construct new questionnaires tapping into LLS use that would to the goodness criteria for psychometric tests. In particular, efforts should be made to improve the reliability of the affective strategy scale in view of the fact that many strategy researchers themselves have recognized the need to investigate learners’ affective states in greater depth (cf. Oxford, 2015; Pawlak & Oxford, 2018), reporting low reliability of the affective LLS category in comparison to the other scales (cf. Del Ángel Castillo & Gallardo Córdova, 2014; Hsiao & Oxford, 2002; Przybył, 2016). In the present investigation, the internal consistency reliability for this scale also proved to be rather low despite the modifications that were made on the basis of the pilot study. Efforts should therefore be continued to provide a more adequate representation of the affective scale of LLS. However, perhaps instead of addressing a panel of experts again, students’ reflections could be shared in interviews or journals so as to allow for a more concatenative approach (cf. Ellis, 1994, 2008). Moving on the NEO-FFI (Costa & McCrae, 1985, 1992), even though it has been validated in numerous studies, the reliability of some of its parts also proved to be problematic, which might also signal the need for its modification. This task, however, can only be undertaken by psychologists. Some concerns can also be raised with reference to the qualitative part of the study. Conducted in a group of volunteers, the interviews were indeed characterized by a certain degree of intimate familiarity between the participants and the interviewer who used to teach some of them in the past. In fact, this could have been one of the reasons why they had volunteered to be interviewed in the first place. Whatever the motivation, on the one hand, the students participating in the interviews were less likely to experience inhibitions or encounter difficulties in reflecting on their LLS or personal characteristics, but, on the other hand, they may have wished to be perceived in a positive rather than objective manner. While the design of the interview guide was aimed to counteract the practice of enhancing a biased self on the part of participants, it cannot be ruled out that some reports of learning practices could have been exaggerated and not reflective of reality. Another potential problem is that the interviews may not have been the best tool to allow capturing the link between personality and LLS use.

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5.6 Conclusion The study discussed in the present chapter intended to shed light on the application of LLS by undergraduate EFL learners at Polish universities, describe them in terms of their dominant personality traits and account for the link between strategy use and personality. Overall, cluster analysis revealed that the most frequent strategy users tended to be both highly conscientious and highly open to experience. At the same time, they were emotionally stable rather than neurotic and extravert rather than introvert. This leads to the conclusion that the potentially welcome traits coexist in clusters and, rather than being competitive they complement in other to promote more successful L2 learning. This finding supports Dörnyei and Ryan’s (2015, p. 28) assertion that “successful language learners can combine their personality features to best effect by utilizing their specific strengths and compensating for their possible weaknesses in adjustment to the particular learning environment”. At the same time, such results are in line with Costa and McCrae’s (1998) view of the trait-dependence of educational, learning and instruction processes. Specifically, learners characterized by high levels of conscientiousness and openness to experience could be portrayed as good students thanks to their diligence and ambition to excel as opposed to individuals whose levels of these traits are low, characterized as reluctant scholars. More generally, the results of the present investigation support the view expressed by Gerrig and Zimbardo (2009), according to which the five-factor model of personality (Costa & McCrae, 1985, 1992, 2017) can be used in predicting academic achievement, though not always in a straightforward manner. Indeed, a number of direct relationships between students’ personality traits and their reported use of LLS were found in the quantitative part of the study as well as in learners’ reflections on the facilitators of L2 learning in the semi-structured interviews. At the same time, it was also demonstrated that the use of particular LLS categories cannot really be linked to the levels of selected personality traits in their own right (cf. Piechurska-Kuciel, 2020). Specifically, high levels of openness to experience, conscientiousness, and extraversion were shown to constitute a desirable combination of personal attributes that characterized frequent strategy users, particularly when accompanied by low levels of neuroticism. However, these results need to be treated with caution as at each stage of cluster analysis, a considerable number of participants could not be assigned to any cluster due to the fact that their individual sets of characteristics were far too distinct from the values of these characteristics obtained for the cluster centers. Also, as aptly pointed out by Dewaele (2022), having the “right” learner profile is no guarantee for successful L2 learning or TL achievement which are subject to the influence of multiple other variables, internal and external to the learner, which were not examined in the present study.

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Oya, T., Manalo, E., & Greenwood, J. (2004). The influence of personality and anxiety on the oral performance of Japanese speakers of English. Applied Cognitive Psychology, 18, 841–855. Oz, H. (2014). Big Five personality traits and willingness to communicate among foreign language learners in Turkey. Social Behavior and Personality: An International Journal, 42, 1473–1482. Panksepp, J. (2008). The power of the word may reside in the power of affect. Integrative Psychological and Behavioral Science, 42, 47–55. Pawlak, M., & Oxford, R. L. (2018). Conclusion: The future of research into language learning strategies. Studies in Second Language Learning and Teaching, 8, 525–535. https://doi.org/10. 14746/ssllt.2018.8.2.15 Piechurska-Kuciel, E. (2018). Openness to experience as a predictor of L2 WTC. System, 72, 190–200. https://doi.org/10.1016/j.system.2018.01.001 Piechurska-Kuciel, E. (2008). Language anxiety in secondary grammar school students. Wydawnictwo Uniwersytetu Opolskiego. Piechurska-Kuciel, E. (2020). The big five in SLA. Springer International Publishing. Pourfeiz, J. (2015). Exploring the relationship between global personality traits and attitudes towards foreign language learning. Procedia-Social and Behavioural Sciences, 186, 567–473. https://doi. org/10.1016/j.sbspro.2015.04.119 Przybył, J. (2016). Cultural variation in the use of language learning strategies: A comparative study. Koni´nskie Studia J˛ezykowe, 4, 439–461. Przybył, J., & Chudak, S. (2022). University students’ self-regulation in standard and enforced online language learning. Moderna Språk, 116, 47–66. Rose, H. (2012). Reconceptualizing strategic learning in the face of self-regulation: Throwing language learning strategies out with the bathwater. Applied Linguistics, 33, 92–98. Rose, H. (2015). Researching language learner strategies. In B. Paltridge & A. Phakiti (Eds.), Research methods in applied linguistics: A practical resource (pp. 421–438). Bloomsbury Publishing. Schwartz, H. A., Eichstaedt, J. C., Kern, M. L., Dziurzynski, L., Ramones, S. M., Agrawal, M., Shah, A., Kosinski, M., Stillwell, D., Seligman, M. E. P., & Ungar, L. H. (2013). Personality, gender, and age in the language of social media: The open-vocabulary approach. PLoS ONE, 8, e73791. Sharp, A. (2008). Personality and second language learning. Asian Social Science, 4, 17–25. Thomson, W. (2016). Depression, neuroticism, and the discrepancy between actual and ideal selfperception. Personality and Individual Differences, 88, 219–224. Tseng, W. T., Dörney, Z., & Schmitt, N. (2006). A new approach to assessing strategic learning: The case of self-regulation in vocabulary acquisition. Applied Linguistics, 27, 78–102. Tyszkowa, M. (1990). Zdolno´sci, osobowo´sc´ i działalno´sc´ uczniów (Learners’ abilities, personality and activity). Wydawnictwo Naukowe PWN. Wakamoto, N. (2000). Language learning strategy and personality variables: Focusing on extroversion and introversion. IRAL, 38, 71–81. Williams, M., Mercer, S., & Ryan, S. (2015). Exploring psychology in language learning and teaching. Oxford University Press. Wi´sniewska, D. (2014). The why and how of using mixed methods in research on EFL teaching and learning. In M. Pawlak (Ed.), Classroom-oriented research: Reconciling theory and practice (pp. 275–288). Springer. Yang, N. D. (1993). Understanding Chinese students’ language beliefs and learning strategy use (Paper presented at the annual meeting of International Teachers of English to Speakers of Other Languages, Atlanta, GA). ´ Zawadzki, B., Strelau, J., Szczepaniak, P., & Sliwi´ nska, M. (2010). Inwentarz osobowo´sci NEO-FFI Paula T. Costy Jr i Roberta R. McCrae: adaptacja polska: podr˛ecznik (The NEO-FFI personality inventory by Paul T. Costa Jr and Robert R. McCrae. Polish adaptation: Manual.). Pracownia Testów Psychologicznych PTP. Zhou, C., & Intaraprasert, C. (2015). Language learning strategies employed by Chinese Englishmajor pre-service teachers in relation to gender and personality types. English Language Teaching, 8, 155–169. https://doi.org/10.17507/tpls.0505.05

Chapter 6

Conclusions, Pedagogical Implications, and Directions for Future Research

The present volume could be classified as an example of research work seeking to map the relationships between individual characteristics of L2 learners. In line with contemporary trends in LLS research, it addresses the “context within” L2 learners by attempting to link strategy use to enduring learner characteristics in the form of personality traits (cf. Oxford & Amerstorfer, 2018). More specifically, in addition to the necessary overview of the relevant literature, the book has reported the results of a study that was aimed to determine the frequency of use of LLS by universitylevel L2 learners in Poland, their levels of the personality traits included in the FFM (Costa & McCrae, 1985, 1992) as well as the relationship between the two individual difference variables. In order to achieve the latter goal, cluster analysis was employed with the purpose of establishing distinct learner profiles with respect to strategy use and personality traits. The quantitative assessment of strategy use was based on participants’ responses to the adapted version of the SILL ver. 7.0 (Oxford, 1990), while the measurement of their personality traits relied on their responses to the Polish adaptation of the NEO-FFI (Costa & McCrae, 1992; Zawadzki et al., 2010). Based on the results of cluster analysis, three groups of learners, relatively homogenous in terms of their personality traits and LLS use, were identified. The findings were enriched with the outcomes of the thematic analysis of the data collected in the course of semi-structured interviews conducted with a subsample of the respondents who filled out both questionnaires, students who volunteered to take part in this stage of the study. On the whole, the analyses demonstrated that LLS use can be at least partly accounted for in terms of L2 learners’ personality traits, also pointing to a number of interesting tendencies in strategy use. Although the source of the participants’ preference for social and compensation strategies remains debatable, their most frequent use does indicate their importance for a considerable proportion of students. Such findings could also suggest that learners become familiar with these types of strategies before they start their education at university. One obvious implication for L2 teachers at universities is to capitalize on different types of compensation and communication strategies in their classes. It would appear that since students themselves at © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6_6

197

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6 Conclusions, Pedagogical Implications, and Directions for Future Research

least try to cope with their L2 shortcomings, others is no reason for insisting on communicating in the TL rather than resorting to students’ mother tongue. Moreover, it could be presumed that interacting with students outside the classroom, for instance in emails or online course forums, could be done through the medium of the L2, even if this means that the use of different types of communication strategies becomes indispensable. The infrequent use of affective LLS reported by the participants could, first of all, be deemed as worrying since affect exerts a powerful influence on virtually all key indicators of success in L2 learning and teaching and it is believed that recognizing one’s affectivity is vital for such affective factors as self-confidence, self-esteem, and attitudes (Gabry´s-Barker, 2010). Without acknowledging that succeeding in L2 learning is emotionally driven as well as reflecting on one’s emotional state and wellbeing, an L2 learner may never succeed in exercising control over self-referential judgements, experience low situational self-esteem and anxiety, and struggle with self-efficacy beliefs (cf. Griffiths, 2018; Oxford, 2002). Given the importance of affectivity, which, according to Gabry´s-Barker (2010) “functions as a stimulus for action and type of approach taken as well as a monitor and controller of cognitive processing, grounded in an individual learning situation” (p. 45), investigations of affect are by all means welcome. Indeed, affect was listed by Grabe (2002) among the variables which could be the source of language problems and it has become an area of growing interest of SLA researchers in recent years. More recently, Pawlak and Oxford (2018) emphasized the need for further studies investigating the role of affect in L2 learning, particularly with respect to the strategy domain. It thus seems warranted to expect that studies of the role of affect in LLS use will draw upon new tools that would be characterized by high levels of validity and reliability. In fact, the availability of tools designed to measure individuals’ emotional states is growing and this applies in equal measure to online self-reporting instruments (cf. Betella & Verschure, 2016) and those developed by neuroscientists (cf. Dieckmann & Unfried, 2014). Perhaps some of these instruments could also be used to help us better understand the role of the affective dimension of strategy use. While it has been established that the levels of the “big” five traits are to a large extent biologically determined and relatively stable (cf. Costa & McCrae, 2017), it has also been proved that the level of openness can be influenced by cognitive training. The results of a longitudinal study conducted by Jackson et al. (2012) indicated that the level of openness increased as a result of cognitive training implemented as a 16week program in inductive reasoning accompanied by weekly practice of doing crosswords and solving Sudoku puzzles. Although no similar results have been obtained in a group of young adults so far, the potential for similar development cannot be ruled. More broadly, L2 learning could be expected to affect language learners’ personality, thus making the relationship between personality and L2 learning reciprocal (cf. Dewaele, 2022). It would thus appear that elements of cognitive training could well be introduced into classroom language instruction. In fact, it would be technically and economically feasible to accommodate elements of cognitive training even within a single term of an L2 course, which generally lasts for at least 15 weeks at Polish universities. Some elements of such training could indeed involve crosswords

6 Conclusions, Pedagogical Implications, and Directions for Future Research

199

puzzles, which are quite commonly included as vocabulary practice activities in EFL books and supplementary materials for teachers, for either individual or pair work. A preference for the latter option seems reasonable as it enhances the use of both social and compensation strategies, which were shown in the present study to be more frequently used by university students than any other strategy type. Of course, cognitive training could go far beyond doing crosswords and encompass strategies of inferencing, in the sense that Bialystok (1978) defined them, that is as strategies which enable L2 learners to arrive at new linguistic information. More generally, it could be assumed that L2 learners at universities would benefit from the application of guided discovery, as understood by Marton (1988), which involves actively testing hypotheses about the target language. Turning the L2 learning process into a series of discoveries assisted by the teacher seems tempting, but it is certainly not a new idea. In fact, it can be related to two widely acknowledged theoretical models. The first one, proposed by Vygotsky (1986), assumes that the provision of the necessary scaffolding allows progression through the zone of proximal development. The second can be associated with the cognitive approach to L2 learning, which rests on the benefits of integrating the components of communication, that is internal, behavioral, and external representations, by actualizing the potential of information (cf. Dakowska, 2013). The implications stemming from the relationships between the levels of the remaining personality traits and the frequency of LLS use are by no means as clearcut as those concerning openness to experience. Moreover, to the best knowledge of the present authors, no studies exist which would prove evidence that the levels of the other ‘big’ five personality traits can be modified. At the same time, the finding that highly conscientious and extraverted students tended to be significantly more frequent strategy users in general and with reference to specific categories should not be ignored. On the contrary, the fact that high levels of extraversion or conscientiousness may boost learners’ overall LLS employment could be capitalized on by both L2 learners and their teachers. Whereas an individual cannot really influence the level of their personality traits, perhaps with the exception of openness to experience, as indicated above, SLA researchers have always emphasized the volitional aspect of strategy use and the extendibility of one’s strategy repertoire (Cohen, 1998, 2014; Oxford, 1990, 2011, 2017). Becoming aware of one’s personality traits can therefore serve as a starting point for reflecting on how they affect the process of L2 learning. Specifically, individuals whose levels of conscientiousness or extraversion are low might be interested in reviewing a list of LLS, such as the one provided in the SILL in order to compensate for potential deficiencies in strategy use by resorting to strategic devices which they might not have been aware of. Although a certain degree of expertise in the field of human personality appears inevitable here, the use of specialist psychological tests is not indispensable in this case. In particular, one cannot easily dismiss the importance of observation in the case of L2 teachers. Experienced teachers are likely to easily notice at least some of their learners’ personal characteristics, including their cardinal traits, which, by definition, are reflected in daily behavior, passions or priorities. To use Allport’s (1961) nomenclature, many teachers might be able to identify learners’ cardinal traits, and,

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6 Conclusions, Pedagogical Implications, and Directions for Future Research

possibly, their central traits as well. Armed with this kind of knowledge, such teachers may, and perhaps even should adjust strategy instruction accordingly, on condition that such strategies-based instruction is provided in the first place. Students whose levels of key personality traits, including openness to experience and conscientiousness, are low, are particularly in need of assistance from their teachers. This assistance could start with providing a scaffolding for the process of enhancing English proficiency, involving both stimuli that would encourage students to challenge themselves intellectually and a framework which would compensate for the deficiencies in the level of conscientiousness. Responding to the specific needs of learners characterized by low openness and low conscientiousness, L2 instructors could arrange a set of activities addressing various drivers of students’ motivation, especially its intrinsic component which is believed to distinguish high achievers from underachievers (cf. Vefali, 2008). Also, given the fact that the perception of motivation has shifted from a constant ID to a dynamic variable (cf. Pawlak, 2012; Waninge et al., 2014), EFL teachers can feel empowered to boost students’ interest in language lessons and actively stimulate L2 learners’ involvement in classroom activities. Popular activities which could be used for this purpose involve language games (e.g., board games, card games, quizzes, crosswords and puzzles, dominoes, bingo or role plays), but also activities which constitute part and parcel of classroom L2 instruction provided that they do not become monotonous and are well-planned in advance. Thus, along with the authors of resource books for English teachers, such as Seymour and Popova (2005) or O’Dell and Head (2003), the present authors strongly believe that simple categorization tasks, information gap activities, spot-thedifference tasks, completing grids, or even guessing words by mimicking or defining them, can all positively affect learners’ interest and stimulate their motivation to face intellectual challenges. Since learners differ considerably with respect to the level of their personality traits, it is evident that it is not only teachers’ attitudes and beliefs that are of vital importance but also the choice of learning tasks that should be varied enough to cater to the needs of different students. The group of students who are likely to require considerably more assistance as infrequent strategy users are students characterized by low levels of conscientiousness. It seems that they would benefit in particular from guidance on organizing and controlling the language learning process. Relevant procedures are frequently provided by university centers for students with Asperger’s syndrome, those anxious about failure, students with excessively high levels of perfectionism, as well as those suffering from concentration loss, dyslexia, bipolar disorder, or schizophrenia. It is crucial to teach strategic skills to individuals who are infrequent strategy users as their limited repertoires of LLS can be the outcome of low levels of the traits of openness to experience and conscientiousness, with such a situation having a detrimental effect on the development of their autonomy. More generally, it could be argued that EFL teachers cannot confine themselves to merely planning and implementing L2 classes. An indispensable part of the instructional process is analysis of learners’ needs and getting them to reflect on how they can further develop as whole persons. This is particularly important for individuals who are relatively less open to experience and display low intellectual curiosity, as this can result in a

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limited strategy repertoire and thus in very limited manifestations of autonomy in L2 learning. Teachers working with young adults may also consider explaining the mechanism of self-regulation to students as this might allow reflection on the process of L2 learning and foster the development of autonomy in this area. Such actions could also aid recognition of the affective dimension of L2 learning and potentially lead to more adept employment of affective. A number of individual differences affecting the process and product of L2 learning are obvious to the language teacher from the get-go. This also surely applies to some extent to personality traits and strategy use, even if the use of research instruments dedicated for this purpose is not involved. After all, teachers have numerous opportunities to observe their learners during L2 classes and draw conclusions accordingly. In the case of LLS, teachers can not only track and evaluate the use of strategies in class but also discuss this issue with their students since some strategies may not be amenable to observation. At the same time, since learners’ personality influences their performance in the classroom and also underlies their strategic choices, teachers would also benefit from expanding their knowledge about language learners as whole persons. From a practical point of view, knowing one’s students well may facilitate the choice of proper classroom procedures or types of interaction. Even if the teacher experiences a temporary failure, reflecting on learners’ characteristics could prove beneficial by stimulating reflection and providing an impulse for modification of instructional practices. Some suggestions for future research could be made on the based on the results of the study and careful reflection on its limitations. These could be grouped under the three major categories. Firstly, alternative versions of personality and strategy inventories could be considered in future research. For example, instead of the NEOFFI (Costa & McCrae, 1992), one of its alternatives, such as the NEO-PI-R (Costa & McCrae, 2008) or the IPIP (Goldberg et al., 2006) could be employed. Their use might not merely result in an improved reliability and validity but also enable researchers to better capture the correspondence between the underlying facets of the “big” five personality traits and learners’ strategic choices. As far as the SILL (Oxford, 1990) is considered, it could certainly be subject to further adaptations. For one thing, further changes could be made to make sure that the strategies in includes are reflective of current realities of L2 learning. In addition, efforts should be made to include items that would help capture the affective strategies that L2 learners employ when confronting challenges of L2 learning. This could be achieved through in-depth interviews focusing on the role of affect in learning different TL skills and subsystems and the ways in which affective reactions of this kind are handled. Secondly, research could address the reasons behind learners’ neglect of affective strategies and perhaps provide EFL teachers with suggestions as to how to increase students’ interest in the emotions which they experience in L2 learning. Thirdly, there is a need to conduct research into the link between LLS use and self-regulation (cf. Dörnyei & Ryan, 2015; Oxford & Amerstorfer, 2018). Studies investigating this relationship could contribute to better understanding of the complexities of the L2 learning process but also avoid in situation in which insights from past strategy research would be discarded (Rose, 2012). Moreover, it seems reasonable to expect that reconciling

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research into self-regulation and strategy use could translate into concrete pedagogical recommendations (Pawlak & Oxford, 2018). The present volume hopefully represents the so-much-needed step in this direction.

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Appendices

Appendix A: Values of Bivariate Item-Scale Spearman’s Correlation Coefficients for LLS Scales Subscale Memory strategies

Subscale Cognitive strategies

Item

ρ value

Significance (p value)

1

0.53

< 0.001

2

0.51

< 0.001

3

0.57

< 0.001

4

0.62

< 0.001

5

0.44

< 0.001

6

0.33

< 0.001

7

0.49

< 0.001

8

0.37

< 0.001

9

0.53

< 0.001

ρ value

Significance (p value)

1

0.28

< 0.001

2

0.67

< 0.001

3

0.59

< 0.001

4

0.60

< 0.001

5

0.62

< 0.001

6

0.59

< 0.001

7

0.62

< 0.001

8

0.59

< 0.001

Item

(continued)

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Przybył and M. Pawlak, Personality as a Factor Affecting the Use of Language Learning Strategies, Second Language Learning and Teaching, https://doi.org/10.1007/978-3-031-25255-6

205

206

Appendices

(continued) Subscale

ρ value

Significance (p value)

9

0.64

< 0.001

10

0.59

< 0.001

11

0.22

< 0.001

12

0.42

< 0.001

13

0.56

< 0.001

14

0.41

< 0.001

Item

Subscale

Item

ρ value

Compensation strategies

1

0.54

< 0.001

2

0.52

< 0.001

Subscale Metacognitive strategies

Significance (p value)

3

0.53

< 0.001

4

0.55

< 0.001

5

0.56

< 0.001

6

0.52

< 0.001

7

0.50

< 0.001

8

0.29

< 0.001

Item

ρ value

Significance (p value)

1

0.66

< 0.001

2

0.58

< 0.001

3

0.64

< 0.001

4

0.64

< 0.001

5

0.59

< 0.001

6

0.70

< 0.001

7

0.66

< 0.001

8

0.64

< 0.001

9

0.64

< 0.001

Subscale

Item

ρ value

Significance (p value)

Affective strategies

1

0.53

< 0.001

2

0.31

< 0.001

3

0.52

< 0.001

4

0.46

< 0.001

5

0.28

< 0.001 (continued)

Appendices

207

(continued) Subscale

Item

ρ value

6

0.52

< 0.001

7

0.51

< 0.001

Significance (p value)

8

0.37

< 0.001

9

0.36

< 0.001

Subscale

Item

ρ value

Social strategies

1

0.424

< 0.001

2

0.688

< 0.001

Significance (p value)

3

0.589

< 0.001

4

0.724

< 0.001

5

0.705

< 0.001

6

0.571

< 0.001

Appendix B: Values of Bivariate Item-Scale Spearman’s Correlation Coefficients for Personality Scales

Scale Openness to experience

ρ value

Significance (p value)

3

0.41

< 0.001

8

0.16

< 0.001

13

0.67

< 0.001

18

0.39

< 0.001

23

0.59

< 0.001

28

0.36

< 0.001

33

0.39

< 0.001

38

0.21

< 0.001

43

0.70

< 0.001

48

0.62

< 0.001

53

0.50

< 0.001

58

0.55

< 0.001

NEO-FFI item

208

Appendices

Scale

NEO-FFI item

Conscientiousness

Scale Extraversion

Scale Agreeableness

ρ value

Significance (p value)

5

0.53

< 0.001

10

0.65

< 0.001

15

0.70

< 0.001

20

0.59

< 0.001

25

0.66

< 0.001

30

0.61

< 0.001

35

0.64

< 0.001

40

0.50

< 0.001

45

0.53

< 0.001

50

0.70

< 0.001

55

0.70

< .001

60

0.49

< 0.001

NEO-FFI item

ρ value

Significance (p value)

2

0.70

< 0.001

7

0.45

< 0.001

12

0.28

< 0.001

17

0.67

< 0.001

22

0.66

< 0.001

27

0.51

< 0.001

32

0.69

< 0.001

37

0.73

< 0.001

42

0.60

< 0.001

47

0.46

< 0.001

52

0.60

< 0.001

57

0.36

< 0.001

ρ value

Significance (p value)

4

0.50

< 0.001

NEO-FFI item 9

0.46

< 0.001

14

0.61

< 0.001

19

0.46

< 0.001

24

0.58

< 0.001

29

0.28

< 0.001

34

0.34

< 0.001

39

0.69

< 0.001 (continued)

Appendices

209

(continued) Scale

Scale Neuroticism

NEO-FFI item

ρ value

Significance (p value)

44

0.50

< 0.001

49

0.50

< 0.001

54

0.48

< 0.001

59

0.59

< 0.001

ρ value

Significance (p value)

1

0.57

< 0.001

NEO-FFI item 6

0.70

< 0.001

11

0.67

< 0.001

16

0.51

< 0.001

21

0.70

< 0.001

26

0.76

< 0.001

31

0.43

< 0.001

36

0.47

< 0.001

41

0.62

< 0.001

46

0.59

< 0.001

51

0.64

< 0.001

56

0.57

< 0.001

Appendix C: Interview Guide (Translated into English): The Relationships Between LLS and the Learner’s Personality 1. Introduction. a. How important is English for you? b. Do you think you can actually learn a language? 2. Strategy repertoire. a. How often and when do you learn English? b. To what degree do you plan your learning? c. Do you happen to memorize English words, phrases or grammar rules? If so, when? d. How do you learn English vocabulary? e. Can you use the vocabulary you have learnt efficiently? If so, how? f. Do you reflect on the efficiency of your language learning strategies? g. How do you try to understand English grammar? Are you interested in increasing the range of various structures that you can apply?

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Appendices

h. Are you particularly interested in improving one of the four basic skills (reading, writing, listening, speaking)? If so, do you do anything to foster the improvement? i. Can you identify and reflect on the emotions which you experience when learning English? j. Do you make any efforts to optimize these emotions? k. To what degree do you consider your learning an interpersonal experience? l. Do you use the Internet to learn English? Do you (also) use it to communicate in English? m. Do you think that communicating in English allows you to improve your command of the language? 3. Personality. a. b. c. d. e.

What type of people is it easy to learn English for? Do you happen any of the qualities you have just mentioned? Do you use some learning strategies more often than others? Which of your characteristics make it difficult for you to learn English? Do you learn English because it is a duty or because it has been your choice?

4. Conclusion a. Do you think that good intrapersonal knowledge allows the learner to learn English better? b. Does increasing knowledge of the language learner allow the English course instructor to teach better? c. Acknowledgements