Cognition, Metacognition and Academic Performance: An East Asian Perspective 9781138668461, 9781315618616

Table of contents :
Cover
Title
Copyright
Contents
Contributors
Preface
1 Cognition, metacognition and academic performance: what are the differences between East Asian and the Western?
PART I Cognition, metacognition and academic performance in China, Hong Kong and Taiwan
2 Relations of metacognitive and motivational strategies to test and homework performance in Chinese students
3 English-language learners in Chinese high schools: self-efficacy profiles
4 Academic achievement of Hong Kong Chinese students: motivational perspective
5 Development of metacognition and its relationship to academic performance and learning experience in East Asian students studying in Hong Kong
6 Cognition strategies, metacognition strategies and academic performance in Taiwan
PART II Cognition, metacognition and academic performance in Japan, Singapore and South Korea
7 Situating metacognition in context: importance of others and affect in metacognitive interventions
8 Strategies for achieving deep understanding and improving learning skills: new approaches to instruction and lesson study in Japanese schools
9 Academic help seeking, implicit beliefs of ability and achievement of Singapore students
10 Cultural reading on Korean students’ learning strategies
Index

Citation preview

Cognition, Metacognition and Academic Performance

Learning strategies and academic performance have been extensively investigated but relatively few studies were conducted in East Asia. This volume presents a reflection on the current status of metacognition and academic performance in the East Asian region. It serves to provide a more complete picture of the global study of how students’ learning and studying strategies affect their academic performance. This book will be of interest to researchers and educators in the area of education, education psychology, cross-cultural studies, education policy, curriculum and instruction and regional studies. Michael C. W. Yip is an Associate Professor in the Department of Psychology at the Education University of Hong Kong. His research interests include cognitive sciences, educational psychology and experimental psycholinguistics.

Routledge Research in Achievement and Gifted Education

URL: www.routledge.com/Routledge-Research-in-Achievement-and-GiftedEducation/book-series/RRAGE Books in the Series Include International Perspectives on Science Education for the Gifted Key Issues and Challenges Edited by Keith S. Taber and Manabu Sumida Policy and Practice in Science Education for the Gifted Approaches from Diverse National Contexts Edited by Manabu Sumida and Keith S. Taber Teaching Gifted Learners in STEM Subjects Developing Talent in Science, Technology, Engineering and Mathematics Edited by Keith S. Taber, Manabu Sumida and Lynne McClure Cognition, Metacognition and Academic Performance An East Asian Perspective Edited by Michael C. W. Yip Promoting Spontaneous Use of Learning and Reasoning Strategies Theory, Research, and Practice for Effective Transfer Edited by Emmanuel Manalo, Yuri Uesaka and Clark Chinn

Cognition, Metacognition and Academic Performance An East Asian Perspective

Edited by Michael C. W. Yip

First published 2018 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 711 Third Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2018 selection and editorial matter, Michael C.W. Yip; individual chapters, the contributors The right of Michael C. W. Yip to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book has been requested ISBN: 978-1-138-66846-1 (hbk) ISBN: 978-1-315-61861-6 (ebk) Typeset in Galliard by Apex CoVantage, LLC

Contents

Contributors Preface 1 Cognition, metacognition and academic performance: what are the differences between East Asian and the Western?

vii ix

1

M I C H AE L C. W. Y IP

PART I

Cognition, metacognition and academic performance in China, Hong Kong and Taiwan

5

2 Relations of metacognitive and motivational strategies to test and homework performance in Chinese students

7

EU N S O O K H O NG, Y U N P ENG, L O NNIE RO WE LL AND H ARO LD F. O ’NEIL , JR.

3 English-language learners in Chinese high schools: self-efficacy profiles

27

CH U AN G WAN G A ND DO -H O NG KIM

4 Academic achievement of Hong Kong Chinese students: motivational perspective

40

REBECCA W I N G-Y I CHENG A ND WING-KA I FUNG

5 Development of metacognition and its relationship to academic performance and learning experience in East Asian students studying in Hong Kong

53

KEVI N D O W N I NG A ND H IU T IN L EU NG

6 Cognition strategies, metacognition strategies and academic performance in Taiwan H U EY- M I N W U

70

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Contents

PART II

Cognition, metacognition and academic performance in Japan, Singapore and South Korea 7 Situating metacognition in context: importance of others and affect in metacognitive interventions

87 89

O S AM U TAK EU CHI A ND MA IKO IKEDA

8 Strategies for achieving deep understanding and improving learning skills: new approaches to instruction and lesson study in Japanese schools

101

Y U RI U ES AK A , TAT S U S HI FU KAYA A ND S HIN’ICHI ICHIK AWA

9 Academic help seeking, implicit beliefs of ability and achievement of Singapore students

122

W EN S H U L U O

10 Cultural reading on Korean students’ learning strategies

138

J O N G H O S HIN, MY U NG-S EO P KIM A ND Y OONJI K IM

Index

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Contributors

Rebecca Wing-yi Cheng is an Assistant Professor in the Department of Psychology at the Education University of Hong Kong. Her research interest is student achievement motivation, specifically on social goal orientation. Kevin Downing is Secretary to Council and Court and Director, Institutional Research Office at City University of Hong Kong. He is Editor-in-Chief of the international scholarly journal Educational Studies, which is listed in SCOPUS. Wing-kai Fung is a PhD candidate in the Department of Psychology at the Education University of Hong Kong. His research interests are self-regulation development, parenting style, mastery motivation in early childhood and achievement goals of students. Tatsushi Fukaya is an Assistant Professor at the Graduate School of Education of Gunma University in Japan. His research aims to understand how to promote and foster students’ metacognition in and out of classroom. He also conducts research on teacher education. Eunsook Hong is Professor Emerita of educational psychology at the University of Nevada, Las Vegas. Her research includes student learning, motivation, selfregulation and creative thinking. Shin’ichi Ichikawa is a Professor at the Graduate School of Education of the University of Tokyo. He was the president of Japanese Association of Educational Psychology and has been a member of National Council of Education. His main research interests are the analysis of teaching-learning processes and their applications to educational practices. Maiko Ikeda is Professor of Applied Linguistics in the Faculty of Foreign Language Studies, Kansai University, Osaka, Japan. Her main research interests are L2 learner strategies, collaborative learning and materials development. Do-Hong Kim’s research interests include the application of psychometric and quantitative methods to issues in educational and psychological assessment. Myung-Seop Kim is a doctoral candidate at Seoul National University, Seoul, South Korea. His research interests include social development of adolescents, creativity and social purpose.

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Contributors

Yoonji Kim is a master’s degree candidate at Seoul National University, South Korea. She is interested in the role of passion in academic motivation, life goal striving and social purpose. Hiu Tin Leung is a Research Fellow in the Knowledge Enterprise and Analysis unit at City University of Hong Kong. He is an experienced researcher in psychology with a special interest in fundamental learning processes. Wenshu Luo is an Assistant Professor at National Institute of Education, Nanyang Technological University, Singapore. Her primary research interest is in the area of student academic motivation and its contextual factors. Harold F. O’Neil, Jr. is Professor of Educational Psychology and Technology at the University of Southern California. His research includes self-regulation, workforce readiness and measures of creativity. Yun Peng is a doctoral student of Educational Psychology at the University of Nevada, Las Vegas. Her research focuses on study strategies, creative thinking and homework. Lonnie Rowell is an Associate Professor of Counseling at the University of San Diego. Increasing student motivation for school learning through various counseling approaches is one of his research interests. Jongho Shin is a Professor at the Department of Education at Seoul National University, Seoul, South Korea. His research interests include self-regulated learning, creativity and social purpose and life goal. Osamu Takeuchi is Professor of Applied Linguistics in the Faculty of Foreign Language Studies, Kansai University, Osaka, Japan. His research interests include L2 learner strategies, L2 affective factors and self-regulation in L2 learning. Yuri Uesaka is an Assistant Professor at the Graduate School of Education, the University of Tokyo, Japan. Her interest is developing effective instructional environments for enhancing the quality of student learning with psychological approaches. She also participated in studies focused on practical applications in real school settings. Chuang Wang is a Professor in Department of Educational Leadership at University of North Carolina at Charlotte and is interested in English language learners’ self-efficacy beliefs and use of self-regulated learning strategies. His research interests also include research design and program evaluation. Huey-Min Wu is an Associate Research Fellow working at the Research Center for Testing and Assessment, National Academy for Educational Research. Her research interests include large-scale assessment, computerized adaptive test and cognitively diagnostic test. Michael C. W. Yip is an Associate Professor in the Department of Psychology at the Education University of Hong Kong. His research interests include cognitive sciences, experimental psycholinguistics and educational psychology.

Preface

This book is among the first one on this topic to present a comprehensive review of the state-of-the-art research among the relationships of cognition, metacognition and academic performance from an East Asian perspective. All the contributions collected in the volume offer an overview of the theories and developments in this topic in the East Asian region, which aims to catalyze further research on unlocking the issues and nature of academic performance and learning processes. This book will be of particular interest to university students, researchers and teachers in the area of education, education psychology, cross-cultural studies, education policy, curriculum and instruction and regional studies. In addition, people who are working in education and educational psychology should find this book useful, in particular to formulate policy in education. The idea of this book initially arose when I was on sabbatical leave at the MARCS Institute for Brain, Behaviour and Development, Western Sydney University in 2015. One day, I had a chance to talk to a group of students on campus and they were from different countries over the world: roughly one-third of them were local Australian, the other one-third of students were Asian and the rest was from Europe or other Western countries. During our very interesting and insightful conversation, I found that there were very obvious differences among the group of students in terms of the learning approach, studying habits, learning goals, attitudes, visions, their futures etc. (as expected!), so I further think is there any universal theory can explain such topic? Subsequently, after many several subsequent dialogues with my colleagues at the MARCS Institute and students in the campus, I was quite sure that this was an excellent idea to go further on the topic and then I initiated this book project. Through various invitations and emails across different continents, I was very glad to receive great support and encouragement from different excellent colleagues and prominent scholars over the world. In this edited volume, we gathered a numbers of original works written by those renowned scholars and promising researchers over the world in this area. I am very grateful for their contributions. Here, I would like to give my deepest gratitude to colleagues and people on the editorial team for their insightful comments to each chapter and constructive discussions during various phases of this project. Of course, I also sincerely thank my graduate students and research assistants (Carol Chan, Dorothy Dou, Claire Kan, Katherine Leung and Minna Zhai) for their very good efforts on the project. Thank you so much! Michael Yip

1

Cognition, metacognition and academic performance What are the differences between East Asian and the Western? Michael C. W. Yip

Introduction Previous researches demonstrated that different cognitive strategies used by students (including university students, distance-learning students and college students with or without learning disabilities) could differentiate and well predicted their respective academic performance. The patterns of results are also consistent across different countries over the world. Along with the metacognitive development processes of the students, their academic performance will simultaneously influence their perceptions on their own cognitive strategies due to the jolt effects of individual’s self-efficacy (Bandura, 1997). For example, Bandura and his colleague reported in a study that students with a high self-efficacy rating were more willing to be persistent in facing challenging tasks than the students with a low self-efficacy rating (Bandura & Schunk, 1981). At the same time, students’ self-efficacy would be greatly influenced by the continuing feedback received on their academic results or academic performance, as well as their own attributions and interpretations of that feedback (Bandura, 1993; Schunk & Gunn, 1986). As a result, it creates a close linkage among the three main factors: cognitive strategies, metacognitive processes and academic performance. Therefore, to unfold the dynamics of these relations is a theoretically important question to our understanding of the basic learning processes of students (Weinstein, Husman, & Dierking, 2000), and then to further understanding of the academic achievement of students. Educational and psychological studies in this line of research have been extensively investigated in Western countries and only few studies were conducted in East Asian countries until recently. Due to the fundamental differences of educational context and culture between East and the West, researchers should alert the applications of those theories or models built by the research findings from the Western countries when formulating the educational policy in their own country. Therefore, it is a dire need to have a comparative approach in this line of research in order to obtain a comprehensive picture on this important topic. This book is among the first one in this research theme to present a comprehensive review of the state-of-the-art research on the relationships among cognitive factors, metacognitive factors and academic performance in the East Asian region.

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All the contributions included in this book offer an overview of the application of theories and new developments on this topic in the East Asian region. A common goal of this book is to catalyze future research on unlocking the relationships among those important factors on academic performance in particular and learning in general. During the past two decades, different scholars produced many fascinating works on this topic from an Asian perspective (Kember & Watkins, 2010; King & Bernardo, 2016; King & McInerney, 2016; Salili, Chiu, & Hong, 2001). This book aims primarily to continue the spirit to gather together a collection of excellent research papers that reflect the recent development from an East Asian perspective.

Highlights of the chapters In the first part of the book, five chapters with exciting new data and systematic review are presented to examine the current status quo to the relationships among cognitive factors, metacognitive strategies and academic performance of students in China, Hong Kong and Taiwan. In Chapter 2, Hong, Peng, Rowell and O’Neil, Jr. investigated the role of metacognitive and motivational strategies used by high school students during the test preparation, testing and homework processes. Under the self-regulated learning framework, the research team observed that the general academic performance was uniquely related to the Chinese cultural and educational contexts. In Chapter 3, Wang and Kim investigated how the self-efficacy profiles of Chinese high school students affected the learning performance of English (L2) and they found that the performance results were closely related to the use of self-regulated learning strategies by the student. In Chapter 4, Cheng and Fung used a motivational perspective to explain the outstanding academic performance of Hong Kong students in international assessment tests (such as PIRLS, PISA, TIMSS, etc.). But, they also observed that the psychological well-being of the students suffered behind the scenes. Hence, the research team claimed that the effects of learning motivation, along with the cultural and educational environments in Hong Kong, seem to be a double-edged sword to facilitate to students’ learning. In Chapter 5, Downing and Leung provided an excellent systematic review of the development of metacognition of Hong Kong university students and the mediating role of learning experience of Hong Kong university students on their academic performance. The information is particularly important for those researching instructional and curriculum design. In Chapter 6, Wu used the empirical data of the Taiwan Assessment of Student Achievement (TASA) to illuminate the relationships among cognitive strategies, metacognitive strategies and academic performance of Taiwanese students. Based on the results, several measures to enhance students’ academic performance and learning are suggested. In the second part of the book, four chapters concerning the same issues about the relationships among cognitive factors, metacognitive strategies and academic performance of students in Japan, Singapore and South Korea are presented.

Cognition, metacognition and performance

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In Chapter 7, based on their empirical study of language learning performance of Japanese students, Takeuchi and Ikeda suggested the importance of the social dimension (influence of teachers, peers and their interactions in the classroom) as well as affective variables (motivation, anxiety and self-efficacy beliefs) on metacognitive decision making and learning. In Chapter 8, Uesaka, Fukaya, and Ichikawa proposed new approaches to classroom instruction and teacher professional development that aims to achieve deep understanding and learning skills. The researchers further presented empirical evidence on the outcomes of the new approaches used in mathematics education in Japan. The results confirmed the positive benefits of these approaches on improving the quality of teachers’ instruction and thereby improving students’ use of learning strategies. As a result, they demonstrated that academic performance of the Japanese students was enhanced finally. In Chapter 9, Luo examined the mutual relationship among implicit beliefs of ability, help-seeking tendencies and students’ academic achievement by a representative large sample of secondary students in Singapore. The results showed differentiated associations among those variables. Implications of the results were discussed in terms of the academic context of Singapore. In Chapter 10, Shin, Kim and Kim offered a rich source of information on Korean students’ learning strategies. The research team reviewed the past twenty years of research studies focusing on Korean students learning and then provided solid empirical data from a large sample of Korean high school students on the relations of Korean students’ learning strategies to academic achievement, effort and interest through a personcentered approach. The results showed that the cultural characteristics of Korean students largely affects their metacognition and learning processes.

Conclusion We know that it is almost impossible to include all the exciting research in this area in a single book but we believe that this edition can provide up-to-date research findings on some of the important educational psychological studies from an East Asian point of view. Contributions to this book include not only chapters from empirical studies which use a wide variety of conceptual foundations, different theoretical perspectives and methodologies, but also chapters from systematic reviews of those issues. We sincerely hope that this book serves the prime purpose of catalyzing more of a different, new research direction in this area and is simply, as the Chinese idiom reads, “拋磚引玉”. (literally means to throw out a sprat to catch a mackerel)

References Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28, 117–148. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman. Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41, 586–598.

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Kember, D., & Watkins, D. (2010). Approaches to learning and teaching by the Chinese. In M. H. Bond (Ed.), The Oxford handbook of Chinese psychology (pp. 169–185). New York, NY, US: Oxford University Press. King, R. B., & Bernardo, A. B. I. (Eds.). (2016). The psychology of Asian learners: A festschrift in honor of David Watkins. Singapore: Springer. King, R. B., & McInerney, D. M. (2016). Culturalizing motivation research in educational psychology. British Journal of Educational Psychology, 86, 1–7. Salili, F., Chiu, C. Y., & Hong, Y. Y. (Eds.). (2001). Student motivation: The culture and context of learning. New York: Kluwer Academic/Plenum Publishers. Schunk, D., & Gunn, T. (1986). Self-efficacy and skill development: Influence of task strategies and attributions. Journal of Educational Research, 79, 238–244. Weinstein, C. E., Husman, J., & Dierking, D. R. (2000). Interventions with a focus on learning strategies. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 727–747). San Diego: Academic Press.

Part I

Cognition, metacognition and academic performance in China, Hong Kong and Taiwan

2

Relations of metacognitive and motivational strategies to test and homework performance in Chinese students Eunsook Hong, Yun Peng, Lonnie Rowell and Harold F. O’Neil, Jr.

Introduction Learners’ self-regulated uses of cognitive, metacognitive, and motivational strategies in academic contexts have been examined mostly within the social-cognitive theoretical framework (Bandura, 1986; Zimmerman, 2000, 2008) and the expectancy-value theory (Wigfield & Eccles, 2000). The construct “self-regulated learning” is derived from earlier work by Flavell (1979) and Bandura (1986). Flavell defined metacognition in areas such as metacognitive experience, metacognitive knowledge, activation of strategies, and goals. Baker and Brown (1984) separated metacognition into knowledge about cognition (awareness and monitoring/appraisal of cognitive process) and regulation of cognition (planning and evaluating). From this, the meaning of the term “regulation” took different turns into contemporary “self-regulation” in learning, notably by Bandura (1986) and Zimmerman (2000), who later included the motivation component in the description of self-regulated learning. According to the social-cognitive perspective (Zimmerman, 2000), self-regulation is defined as thoughts, affects, and behaviors used to attain learning goals. According to Zimmerman and Bandura (1994), self-regulated learners enlist self-reactive influences to motivate their efforts and use appropriate strategies to achieve success. Thus, self-regulated learners are responsible for their own learning, metacognitively and motivationally directing their own learning processes (e.g., Zimmerman, 1989, 2000), planning, monitoring, self-evaluating, and selecting proper cognitive strategies at various stages of learning process (i.e., metacognitive component), and are self-efficacious, regulate their efforts, and demonstrate persistence when they encounter difficult tasks (i.e., motivational component) (e.g., Wolters, 2003; Zimmerman, 2000). Contemporary perspectives of motivation such as the expectancy-value theory emphasize such constructs as task value and interest, in addition to self-efficacy and effort investment illustrated in the early social-cognitive framework (Wigfield & Eccles, 2000; Wolters, 2003). Task value and interest affect motivational process and outcome. In this formulation, self-regulated learners are described as highly motivated as they view tasks (e.g., learning, test-taking, or homework) as valuable (useful, important, or interesting), are self-efficacious, and regulate their efforts and perseverance during tasks to achieve goals (Bandura, 1993; Corno, 2001; Pintrich, 2000; Wigfield, 1994), as well as use effective metacognitive strategies such as planning learning

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activities, monitoring learning processes, and regulating the use of cognitive strategies such as selecting appropriate strategies for the task at hand (Hong, Peng, & Rowell, 2009; Pintrich, Wolters, & Baxter, 2000). Although most students self-regulate their learning to some extent, the degree of efficiency in using self-regulatory strategies varies among learners, thus adding to sources that cause varied levels of outcomes. Students’ motivational inclination (e.g., valuing of task) and motivational regulation (e.g., effort expenditure and perseverance) have shown positive relations with the use of cognitive and metacognitive strategies (Boekaerts, 1997; Pintrich & Schunk, 2002; Schunk, 2001; Wigfield, 1994). Bandura (1993) asserts that self-regulated learning not only requires a repertoire of cognitive and metacognitive strategies but also motivation for the task. Zimmerman (1990) describes the cyclical relation between motivational and metacognitive components of self-regulation by positing that a learner’s use of cognitive and metacognitive strategies enhances perception of self-efficacy, which in turn are assumed to provide the motivational basis for further self-regulation during learning. As such, the motivational component of self-regulated learning is integral to the working of cognitive and metacognitive strategy uses. For the current chapter, we posit that self-regulation operates through subsets of psychological functions that include motivational inclination and regulation process, and cognitive and metacognitive functioning. Thus, self-regulated learners appraise tasks (e.g., test preparation, test-taking, or homework completion) and direct, monitor, and self-evaluate their own behaviors while regulating their effort expenditure, are persistent when they encounter difficulties, and select and utilize appropriate cognitive and metacognitive strategies in order to complete tasks successfully. As the motivational and metacognitive constructs jointly affect learning and performance, being cyclical at times and sequential at other times, studying students’ uses of cognitive and metacognitive strategies without involving motivational components of self-regulated learning or vice versa may distort the understanding of psychological processes involved in learning.

Self-regulated learning in Chinese students Although numerous studies have supported the relations among motivation, cognitive and metacognitive strategy use, and academic achievement, studies on self-regulated learning have been conducted more with students from Western than Eastern parts of the world. In this chapter, we report studies of self-regulated inclination and behaviors applied in the context of test preparation, test-taking, and homework completion examined in Chinese secondary students.

Motivational and metacognitive regulation during test preparation Test value, motivational regulation, and test performance Chinese students, 326 seventh graders and 391 eleventh graders, in a large metropolitan area of mainland China were examined for their self-regulated behaviors

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during test preparation (Hong & Peng, 2008). Those students who held stronger test value reported having regulated their motivation by investing effort and being persistent while they were preparing for tests more so than those who held weaker test value (Hong & Peng, 2008). The test-value construct was measured by four indicators of perceived value in learning and future life decisions. Likewise, students who held stronger test value regulated their metacognitive activities by planning, self-checking, and selecting and using appropriate strategies more than those who held weaker test value. These findings supported previous studies conducted with students in Western countries that found a strong relation of motivational inclination (task value) with motivational/metacognitive regulation (Boekaerts, 1997; Schunk, 2001). Chinese students’ perception of test value demonstrated indirect effects on test performance through the mediation of motivational regulation, whereas test value did not show a direct effect on test performance. This is a significant finding, in that students’ perceiving tests as valuable triggers them to regulate their motivation by investing effort and persistence during test preparation. It is the effort investment during test preparation, rather than test value by itself that helps them perform better on tests. A similar phenomenon was described in Wise and DeMars (2005). Further, motivational regulation during test preparation demonstrated a direct influence on test performance in Chinese students (Hong & Peng, 2008), which is largely consistent with previous research on Western students conducted during testing (Sundre & Kitsantas, 2004). GRADE DIFFERENCES

As effort is strongly emphasized in Chinese culture (Hau, 1996), the relation between effort and performance is not surprising. However, the effect of Chinese students’ motivational regulation on test preparation declined in older students, indicating that the relation between effort-making during test preparation and test performance was not consistent among older students. This inconsistency might be the outcome of other educational factors that gradually play important roles in academic performance as students proceed through schooling. As an example, the volume of prerequisite knowledge that students need to acquire becomes tremendous in upper-grade levels. Having appropriate prerequisites or prior academic achievement becomes an important determinant in academic performance. Older students attending extra-curricular activities more regularly than younger students, be they academic or non-academic, can be another factor. As students’ lives change by the time they arrive at secondary schools, putting efforts into and being persistent during test preparation becomes a less consistent factor that affects their test performance. In a previous study of Western high school students, students who were aware of the need to expend more effort on studying did not necessarily study harder (Hong, Sas, & Sas, 2006). Older Chinese students in Hong and Peng’s (2008) study might have engaged in these behaviors mentioned above (Hong et al., 2006) more so than did younger students, thus generating a smaller effect of motivational regulation on test performance.

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Metacognitive regulation and test performance The level of perceived metacognitive engagement during test preparation did not demonstrate a significant relation with test performance in both Chinese junior high and high school students (Hong & Peng, 2008). Although a positive relationship between the use of metacognitive strategies and academic achievement has been demonstrated in students of Western countries (Kitsantas, 2002; Sundre & Kitsantas, 2004), and of some Eastern countries (Alia & Al-Weher, 2001; Phakiti, 2003), nonsignificant findings have also surfaced in some studies (Hong, O’Neil, & Peng, 2016; Kuyper, van der Werf, & Lubbers, 2000; Malpass, O’Neil, & Hocevar, 1999; Purpura, 1997; Schraw, 1997). That is, although Chinese students who were willing to work hard at test preparation might have been rewarded by increased test scores, the amount of metacognitive regulation during test preparation did not make a difference in test scores. It seems that in Chinese students, both younger and older, hard work produced positive results whether or not students applied metacognitive strategies during test preparation. Volet (1999) observed that learning strategies of Chinese students from Hong Kong and Singapore (i.e., countries with Confucian heritage) differed from those of Chinese students studying in Australia. The study by Hong and Peng (2008) seems to indicate that Chinese students’ motivational and metacognitive regulation in test preparation reflect, in part, their cultural heritage, where effort and persistence have been highly valued. The phenomenon of students (including college students) not using effective strategies, even when they are aware of them or choosing to use ineffective strategies, seems to be pervasive in students of Western countries (Barnett, 2000; Pressley, Yokoi, Van Meter, Van Etten, & Freebern, 1997) as well as in Chinese high school students (Hong & Peng, 2008). Beyond the effects of effort investment discussed above, the failure to use effective strategies may be due to failing to recognize occasions to apply them unless directed to do so (Winne & JamiesonNoel, 2002) or to lack of motivation to use the strategies (Barnett, 2000). These findings bring the importance of the role of educators to the forefront, as they can help students acquire metacognitive knowledge, and also help students use this knowledge to increase learning.

Self-regulated behaviors during testing Test value and test performance A study of 438 tenth-grade students (182 males and 256 females) in a large metropolitan area in mainland China examined their self-regulated behaviors while taking tests (Peng, Hong, & Mason, 2014). In this study, “tests” referred to tests in general, not in specific subject domains. For example, an item measuring students’ test value reads: “It is important for me to do well on my tests.” Test performance was measured in mathematics. Chinese tenth-graders who placed high value on testing and test performance reported high self-efficacy and effort investment during testing and reported using more cognitive and metacognitive strategies as compared to their peers who placed low value on testing. Other

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studies of Western and Eastern students also found positive relations, demonstrating that students who perceive tests as useful and important tend to report higher self-efficacy and effort expenditure, employing more cognitive and metacognitive strategies, and using more appropriate test-preparation or test-taking strategies than students who perceive tests as not valuable (Aydin, Uzuntiryaki, & Demirdöğen, 2011; Eccles, Vida, & Barber, 2004; Hong & Peng, 2008). Perceived value about testing and test performance, however, neither directly nor indirectly influenced test performance. In the study by Hong and Peng (2008) on the relation of test preparation and test performance, discussed earlier, motivation regulation mediated the relation between test value and test performance which was measured by two indicators – Chinese language and mathematics test scores. Whether the difference in the indirect effect of test value on test performance is due to test-taking versus test-preparation strategies or to test scores on different subject matters is not clear, requiring additional research. Another important note is that the number of motivational constructs was different in these studies, which might have caused this difference. Further, in a study conducted of Western students, task value predicted persistence more strongly than performance (Anderman & Wolters, 2006), warranting further investigation of relations between various subcomponents of motivation constructs and test performance.

Self-efficacy, effort investment, metacognitive strategy use, and test performance Self-efficacy beliefs were related to effort investment and metacognitive strategy use during test-taking and test performance in mathematics in Chinese tenth-graders (Peng et al., 2014). Similar results were obtained in studies of non-Chinese students (e.g., Awang-Hashim, O’Neil, & Hocevar, 2003; Zusho, Pintrich, & Coppola, 2003). Self-efficacy has shown consistent and strong evidence as a positive enabler of student achievement (Bandura, 1993; Yip, 2012). Self-efficacy also demonstrated positive indirect effects on the use of test-taking cognitive strategies through the influence of increased effort and metacognitive strategy use. That is, Chinese students with higher self-efficacy made an effort to do well on the test and used cognitive and metacognitive strategies more than those with lower self-efficacy.

Self-efficacy, test anxiety, and test performance Perhaps a cultural factor might have played a part in the relation of motivational inclination with test anxiety and test performance. Chinese tenth-graders’ selfefficacy beliefs did not have a significant inverse relation with test anxiety, unlike findings with Western students (Bandalos, Yates, & Thorndike-Christ, 1995; Bembenutty, 2008; Rouxel, 2000). In Chinese culture, students tend to attribute their success to diligence and effort more than to ability (Grant & Dweck, 2001; Rao, Moely, & Sachs, 2000). Chinese students, whether they are confident

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or not in particular test subjects, may be anxious during the test because they are aware of the significance of test scores in their future education (e.g., placement in key schools, college entrance) or career opportunities (Ashmore & Cao, 1997; Cheng, 2008). This cultural influence might also have been in place in the nonsignificant relation between effort and mathematics test performance, in that there may be no distinct patterns of effort investment between high and low performers in Chinese students. Perhaps the levels of effort students expend may not be systematically related to test performance in Chinese students due to their awareness of the importance of test scores, a rather prominent phenomenon in Eastern societies.

Test anxiety, effort, and cognitive/metacognitive strategy uses Chinese tenth-graders who invested more effort reported more active engagement in both metacognitive and cognitive strategy use (Peng et al., 2014). It is not surprising to find the strong relation between effort expenditure and heightened use of test-taking strategies, and this relation was also indicated in Western students (Stipek, 1996). Test anxiety has been widely documented as negatively interfering with cognitive and metacognitive processes, persistence, and test performance (Bembenutty, 2008; Hong & Karstensson, 2002; Kim & Rocklin, 1994; O’Neil & Abedi, 1992; Tobias, 1985). Study results with Chinese tenth-graders (Peng et al., 2014) were consistent with previous findings with Western students, except for the metacognitive strategy use. The more worried test-takers were about testing, the less they regulated effort expenditure and the less they invoked the use of cognitive strategies such as test tactics (e.g., reading test instructions carefully, or using information obtained from other questions and options). Consequently, test anxiety was negatively related to test performance. Interestingly, a positive relation between text anxiety and the reported use of metacognitive strategies during testing was indicated in Chinese tenth-graders. Wigfield and Meece (1988) also suggested that a degree of worry or concern may be necessary to motivate students to try harder on tests. Therefore, it is reasonable to assume that test anxiety aroused Chinese students’ awareness about the test and engaged them to think metacognitively when completing tests. This positive relationship was also found in a study by Spada, Nikcevic, Moneta, and Ireson (2006), in which test anxiety demonstrated a positive direct effect on metacognition. These theories and empirical findings, however, explain only part of the reported behaviors by Chinese students. For example, whereas test anxiety in Peng et al. (2014) was positively related to metacognitive strategy use, it was negatively related to other variables, thus indicating that the positive influence on metacognitive strategy use was not transferred to performance increase. More research on these relations is warranted. Consistent with previous findings showing a high correlation between metacognition and cognitive strategy use (Akyol, Sungur, & Tekkaya, 2010; Liu, 2009; Purpura, 1997), the use of metacognitive strategies by Chinese tenth-grade

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students did have a direct effect on the use of cognitive strategy. Test takers who used metacognitive strategies, that is, planning, monitoring, and selecting, and using appropriate cognitive strategies, were more likely to use effective test strategies such as eliminating answers, avoiding errors, using hints, or using time wisely. The findings that metacognitive strategies used during the test had both direct and indirect effects on the use of test strategies, both through the influence of selfefficacy and effort, may indicate that metacognitive strategy took an executivefunction role and might have helped students regulate cognitive behavior (i.e., use of test strategies). However, both metacognitive and cognitive test strategies did not show significant direct effects on math achievement in Chinese students. As mentioned above, the impact of metacognitive activities on academic achievement and test performance of Western students are not consistent, some showing positive effects (Hong et al., 2006; Kitsantas, 2002; Sundre & Kitsantas, 2004) and others showing nonsignificant relations (Hong & Peng, 2008; Kuyper et al., 2000; Malpass et al., 1999). Again, the same reasoning discussed above may apply in the testing situation – that is, knowing effective strategies does not mean that students apply them (Pressley et al., 1997). Further, cueing students with metacognitive strategies did not always help students invoke metacognitive or cognitive strategies during testing (Veenman, Kerseboom, & Imthorn, 2000). Purpura (1997) speculated on this phenomenon that the use of metacognitive strategies was automatic for high-ability test-takers, resulting in having less of a need to report using metacognitive strategies. This assertion may or may not be applicable to Chinese students, warranting an investigation of this particular relation. In the Chinese school system, where students need to take various high-stakes exams, test-taking skills are taught regularly to Chinese students and teachers encourage students to use test-taking strategies (Rao et al., 2000; Xu & Wu, 2012; You, 2004). It could be possible that in the current sample from a Chinese high school, students with high or low academic achievement were not distinctively different in the use of test-taking strategies during tests, thus showing no relationship between test strategies and test performance.

Gender difference While male students felt more confident about testing than did female students, they also reported higher anxiety during the test (Peng et al., 2014). The findings on self-efficacy are consistent with prior work in which male students in Western countries perceived themselves having higher self-efficacy than female students (Fredricks & Eccles, 2002; Jacobs, Lanza, Osgood, Eccles, & Wigfield, 2002). Although self-efficacy mediated gender effects on effort, the effect size was small. The finding that male Chinese students had higher test anxiety than female students was not congruent with previous findings with Western students that female students in general feel more anxious than male students during testing (Jain & Dowson, 2009; Rouxel, 2000), although Benson, Bandalos, and Hutchinson (1994) found no evidence of gender differences. It is possible that male Chinese

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students, compared to females, were experiencing higher performance pressure, reporting higher cognitive concerns (worry anxiety) about their performance during the test. As educational and cultural contexts may have impacts on the test anxiety of males and females, more research is warranted. No gender differences were found in test value, effort, and metacognitive strategies in Chinese tenthgraders. As Chinese society, from teachers to parents and to students, acknowledges the importance of test scores in education and income mobility (Hau & Salili, 1996; Rao et al., 2000), both male and female students may value tests and worry about tests and test performance to a similar degree during testing. Summarizing this section on self-regulated behaviors in test preparation, motivation variables influenced the use of test-taking strategies and demonstrated stronger impacts on test performance than did test-taking metacognitive and testtaking strategies. Promoting the development of students’ motivation, especially focusing on self-efficacy, would strengthen students’ confidence during testing, which would also improve the use of test-taking strategies. Students with high self-efficacy beliefs take on challenging tasks, persist when faced with difficulties, and believe they will do well (Schunk & Pajares, 2002). Various strategies to enhance students’ self-efficacy beliefs have been discussed, for example, providing students with opportunities to experience success, introducing activities that are optimally challenging, and providing informative feedback (Niemiec & Ryan, 2009; Rowell & Hong, 2013; Schunk & Pajares, 2002). In China and much of Asia, testing is an integral part of schooling. Increasing educators’ understanding of students’ perceptions about test-taking motivation and strategy use will help guide educators to formulate helpful strategies for students preparing and taking tests.

Self-regulated behaviors during homework In this section we extend the work on self-regulated learning to homework situations within the context of the Chinese education system based on two recent studies of Chinese tenth-grade students, one focusing on effects of motivation and worry anxiety on homework performance in mathematics and English as a foreign language (Hong, Mason, Peng, & Lee, 2015), and the other based on a study of Chinese students (Grades 7 and 11) about self-regulated behaviors during the homework process and differences between grade and achievement levels (Hong et al., 2009).

Relations among motivational and metacognitive behaviors in homework, homework worry anxiety, and homework performance While examining the relations of homework motivation and homework performance of 268 Chinese tenth-graders, Hong et al. (2015) focused on how worry anxiety about homework mediates the relations between homework motivation constructs and homework achievement. The items measuring homework worry anxiety were similar to measures of test anxiety, with the context being

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homework assignments. Sample items of worry anxiety for mathematics homework are: “While completing mathematics homework assignments, I find myself thinking about the consequences of failing” and “When I complete mathematics homework, I think about how important it is to get a good grade in mathematics course” (Hong et al., 2015). For English as a second language, “mathematics” was replaced with “English.” Constructs of homework motivation included homework value, self-efficacy, motivation application/regulation, and homework worry anxiety.

Mediating and direct effect of homework worry: subject-domain matters The direct and indirect effects of homework worry on homework achievement were different across two homework subjects. In mathematics homework, worrying about homework consequences mediated the relations between homework motivation and homework achievement on all constructs examined, whereas in English homework, only one significant mediating effect was found, demonstrating that students worry about different subject matters to different degrees. In mathematics, when homework value (usefulness and importance of homework) was mediated by homework worry anxiety, it had an adverse indirect effect on homework effort and on homework achievement. That is, for students who are highly worried about mathematics homework, their high ascription to homework value seemed to have reduced the level of effort during homework as well as homework achievement. Interestingly, however, self-efficacy on homework brought a positive indirect effect on homework effort when self-efficacy was mediated by worry anxiety. Thus, in Chinese tenth-graders, although worrying about homework has a negative impact on application of homework effort, students’ sense of self-efficacy may lessen the negative impact of worry anxiety on homework effort. However, in English homework only one relation was significant; worry about English homework mediated the relation between homework value and homework effort, in that students who assigned high value to English homework reported a decreased homework effort when this relation was mediated by worry anxiety. Further, the mediating effect of worry anxiety was weaker in English than in mathematics homework. Other than this weak relation, worry anxiety regarding English homework assignments did not have mediating effects on the relation of homework value and self-efficacy with either the amount of effort they invested in homework or homework achievement. In brief, indirectly through the influence of worry anxiety, valuing homework had an exacerbating effect on homework effort and homework achievement, whereas efficacy beliefs about homework had an ameliorating effect on effort regulation and achievement in homework, especially in the mathematics domain. Chinese students with high worry anxiety about homework invested less effort, more so with mathematics than with English homework. This phenomenon has been evidenced in non-homework academic performances (Awang-Hashim et al.,

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2002; Ikegulu, 2000). As found in numerous previous studies in testing (e.g., Kim & Rocklin, 1994), worry anxiety also had a negative effect on mathematics homework achievement. As the stakes are high with mathematics (for example, important to admission to a respected college or university and more options for career choices), the adverse effects of worry anxiety on other motivation variables were likely more prominent in mathematics than in English as a second language. In addition, Chinese students, like students in other countries, might have perceived that mathematics requires cognitive attention and higher-order skills that they may or may not possess to do homework, thus showing stronger anxiety effects (Sarason, 1988; Tobias, 1985, 1992). Types of homework assignments that Chinese students have encountered in the past might have been an important factor in the findings of the study by Hong et al. (2015). When homework contents were examined, most of English homework assignments involved copying vocabularies or paragraphs several times, grammar, or working on exercises on certain pages of their textbook designated by classroom teachers (e.g., fill in the blank about a sentence), with reading comprehension assigned rarely. In mathematics, although assignments were given from the textbook pages, almost all items assigned involved problem solving that required understanding of mathematics concepts and skills. Thus, differences in cognitive loads imposed by homework task and difficulty levels and/or perceived importance might have caused the apparent domain differences in these relations. The skill deficit model (Everson, Millsap, & Browne, 1989; Musch & Broder, 1999; Tobias & Everson, 1997) applied to mathematics homework may not be as relevant to English homework. Therefore, it is not unexpected that students’ worry anxiety in mathematics demonstrated direct and mediating effects on homework achievement, but not in English. As has been documented in academic situations (Lodewyk, Winne, & JamiesonNoel, 2009; Wigfield & Eccles, 2002; Wolters & Pintrich, 1998), homework self-efficacy not only had a strong influence on students’ application of effort and persistence but also assisted students in achieving homework success in both mathematics and English homework. The findings of the similar pattern in these relations across the two characteristically different subject domains are worth noting.

Effort investment and homework achievement: subject-domain matters again Although the effect of effort investment on academic achievement has been evidenced (Wise & DeMars, 2005), this relation has not been obvious in homework. In the study with Chinese students (Hong et al., 2015), again subject-domain difference was evident. The positive relation of effort/persistence with homework achievement was shown in mathematics, but not in English as a second language. Also, homework effort/persistence positively mediated the relation between homework value and homework achievement and between homework self-efficacy and homework achievement only in mathematics homework. That is, perceiving mathematics homework as useful and important and having confidence

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in mathematics homework completion influence homework achievement directly and indirectly through effort investment to do homework. Chinese students in this sample reported not investing as much effort in English homework as they did for mathematics homework, possibly due to the homework characteristics and the level of stakes attached to each subject as described above. That the effect of homework effort was not strong in this study points to the need for further investigation into various areas of concern. Both homework value and effort mean scores were higher than other variables in this study, especially in mathematics homework. As discussed above in the testing section, Chinese students tend to attribute their success more to diligence and effort than to competence (Grant & Dweck, 2001). Unlike the positive relation found between effort investment and other motivation variables and achievement in Western students (Trautwein, 2007; Wigfield & Eccles, 1992, 2002), Chinese students in this study, whether they are high or low achievers, might have reported their effort levels more in line with their beliefs about the importance of diligence, thus not showing strong relations of homework effort with other variables in this study.

Differences between grade and achievement levels and among different motivational and metacognitive strategies Group differences in homework self-regulation in Chinese students (330 seventhand 407 eleventh-graders) have been studied by Hong et al. (2009). Group differences examined were two grade levels and three achievement groups. In addition, six homework self-regulation inclinations and behaviors were compared. These variables included two motivational inclinations (utility value, intrinsic value), two motivational regulation constructs (effort, persistence), and two metacognitive regulation constructs (planning, self-checking). We first discuss the differences among six variables, then group differences to understand the pattern that emerged in relation to Chinese students’ self-regulated homework behaviors.

Differences among six homework self-regulation constructs Chinese students did not like doing homework as much as they thought it was useful, regardless of grade or gender. The apparent contrast in Chinese students’ views on utility and intrinsic value deserves an elaboration. As most Chinese view education and a diploma as a chance for social advancement, it is important for students to receive high grades in school (Lin & Chen, 1995). As such, homework has been valued by schools and parents as a utility for high achievement in school. The high rating on utility value by Chinese students is thus understandable, as their beliefs and perceptions develop in the contexts of their home, school, and the broader culture (Rogoff, 1990). Both seventh- and eleventh-graders in this study reported expending effort more than using metacognitive strategies for homework. Self-checking homework progress was especially low as compared to planning. Again, as effort is strongly emphasized in Chinese culture (Hau, 1996), the high self-rating of effort is not

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surprising. Chinese students might plan, put forth effort in homework, and complete it dutifully whether they like it or not. Yet, students might have not viewed monitoring as necessary because they strive to complete homework anyway or they might not have realized that they have been monitoring homework progress. As a positive relation between strategy use and achievement has been demonstrated in some studies (Kitsantas, 2002) and with the finding of younger high-achieving Chinese students reporting a higher level of metacognitive strategy use in this study than older students (see below), strategy instruction may be beneficial to students.

Grade differences in homework self-regulation The pattern and significance of grade-level differences are important to discuss. Older Chinese students perceived homework as less useful, enjoyed doing homework less, expended less effort, persisted less, and engaged in planning and self-checking less than did younger students (Hong et al., 2009). These findings replicate previous studies of students from Western culture that found a similar pattern of declines in valuing school work (Wigfield et al., 1997) and in meaning and interest in homework (Cooper, Lindsay, & Nye, 2000), and in effort and persistence in homework completion (Hong & Milgram, 2000). Knowledge of metacognitive strategies may improve with age at the early childhood or elementary level (Warton, 1997), but students in Hong et al. (2009) reported that they used such strategies less in high school than in middle school. Chinese students receive a variety of drill-and-practice type assignments and more students disliked such homework than liked it. Hong et al. (2000) observed that both Chinese and U.S. students, especially older students, favored unstructured over structured (practice-type) homework assignments. Perhaps the type of homework assigned to students could be a reason that students dislike homework. Others have suggested that the negative changes may be explained by structural changes in the school environment (Watt, 2004). High schools in China, as in Western high schools, provide structures that are different from elementary or junior high schools in class organization and instructional delivery. These environmental changes may be a source of general declines that are present across cultures.

Achievement-level differences in homework self-regulation The expected trend of high achievers reporting their homework self-regulation level higher than low achievers was shown only in the seventh-graders, as found in students in Western countries (Lepper, Corpus, & Iyengar, 2005). That no differences in overall homework self-regulation were found among the three levels of achievers of eleventh-graders, along with low scores among all levels of achievers, is concerning. Similarly, in Rao et al. (2000), whereas high and low achievers in high school in Hong Kong were not different in their use of self-regulated learning strategies, the difference was significant in the middle-grade Chinese students (Salili &

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Lai, 2003). Whether the no-difference found in older Chinese students (Hong et al., 2009) indicates their apathy toward schoolwork in general or whether this phenomenon applies only to “homework” situations is to be further understood not only through the lens of cultural impact but also the developmental impact that seems to be ubiquitous across cultures. Homework experiences have been shown to be positively related to students’ use of learning strategies as well as to students’ responsibility for academic outcomes (Zimmerman & Kitsantas, 2005). However, homework will not likely fulfill its purpose of helping students in developing skills and responsibility and extending learning, as long as students perceive it negatively. Furthermore, understanding and addressing high school students’ low reported scores in homework valuing, motivation, and strategy use is important as it has implications for learning in school and beyond formal schooling.

Conclusions and educational importance Metacognitive and motivational inclination and behaviors discussed in this chapter were informed by social-cognitive and expectancy-value theories on motivation and social-cognitive perspectives on self-regulated learning (Bandura, 1986; Wigfield & Eccles, 2000). The pattern of relationships among constructs replicated most of the previous findings with Western students, a few findings that were culturally specific notwithstanding. In general, motivation variables during test preparation, testing, and homework process showed stronger impacts on test and homework performance than did cognitive and metacognitive strategies. A high sense of efficacy belief has been evidenced to be related to increased effort investment and to high achievement in Chinese students as well as students from Western societies (Hong et al., 2015; Peng et al., 2014; Schunk & Pajares, 2002). To improve students’ confidence level, teachers may provide students with ample opportunities to experience success by introducing learning activities that are optimally challenging while providing informative feedback (e.g., Niemiec & Ryan, 2009). The findings that were not consistent with those from Western students reflect Chinese cultural and educational contexts. The nonsignificant relations between metacognitive strategy use and between effort and performance during test preparation and/or homework situations could be partly cultural and educational climate– related (e.g., working hard works no matter whether/what strategies are used). The relations of homework worry anxiety with homework value, efficacy beliefs, and motivation application, as well as with homework achievement are worth noting, especially the differences in relations, significance, and effect size, across the two subject matters: mathematics and English as a second language. More studies that examine motivation constructs with worry anxiety are simultaneously warranted to see whether these findings hold in various grade levels and locations in China (e.g., rural versus urban). Students who are not motivated or are anxious about testing or homework tend not to invest full effort, producing less reliable assessments of test or homework

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performances, likely underestimating their actual level of competency, especially in homework or low-stakes testing (Wise, 2009). This becomes an important concern when classroom teachers use students’ homework scores as part of course grades, as many Chinese teachers do (Fang, 2011; Joong, 2012). The subjectdomain differences found in Chinese students (Hong et al., 2015) illustrate the importance of acknowledging domain differences to understand and develop instructional strategies. The findings may reflect both cultural and education contexts in China (Stankov, 2010) as well as differences in rigor, expectation, and difficulty across the two subject areas taught in schools and perceived by students. To help students having homework difficulties and to increase their homework motivation and homework success, the source of difficulties should be ascertained within specific subject domains. However, understanding that some homework behaviors are domain-general and applicable to students in general also helps educators when preparing homework help for students, as this understanding may simplify the preparation of interventions for their students. Teachers rated homework behaviors of male students more unfavorably than their female peers on most measures of homework problems (Hong, Wan, & Peng, 2011). Again, the subject-domain differences were evidenced in the homework difficulties, with discrepancies between students and teachers and across gender more evident in English as a second language than math homework, indicating inconsistent views more on English than mathematics homework, which is viewed as more difficult and/or important consistently by both teachers and students (Hong et al., 2011). To lessen discrepancies and improve awareness of students’ homework behaviors, teachers need to grade and provide feedback on students’ homework. Without the feedback process, teachers will have insufficient understanding of not only the difficulties that students experience in homework completion, but whether they are helping students improve homework motivation. As China has been undergoing rapid socio-cultural and economic changes (Li, 2008; Webber, Wang, & Zhu, 2003; Yao, 2006), it is expected that efforts to develop an education system that meets the challenges of modernization are also happening. However, the examination-oriented education system and teaching practices have not seen much change to date, although for the past few decades Chinese officials have been giving consideration to significant structural and curriculum reforms in education (Guan & Meng, 2007; Song, 2008). For the time spent on test preparation, testing, and homework to be useful, educators need to help students see the value of tests and homework for learning beyond performing to obtain high scores. At the same time, however, educators must view test preparation, testing, and the homework process from an instructional and learning opportunity standpoint. With this stance, they will more likely be able to help students’ value and utilize testing and homework as learning opportunities and direct their focus on learning rather than just raising performance scores. China is in the process of a transition from examination-oriented to futureoriented education (Song, 2008), expending efforts to reduce the heavy burden on students and raising a new generation by helping them develop various types of abilities, including creative ability (Guan & Meng, 2007; Woronov, 2008).

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This chapter provides Chinese educators with some suggestions that students need a variety of instructional approaches and homework assignments, especially when society is promoting creative thinking (Hong et al., 2016), a topic that is beyond the current chapter. We end this chapter with two questions to Chinese educators, as well as educators across the globe: (a) are educators embracing social-educational reforms that impose changes in classroom practices? and (b) are educators willing to learn about how students learn and about new ways to understand students, from their motivation to strategy uses, and apply new knowledge about students to classroom instruction?

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3

English-language learners in Chinese high schools Self-efficacy profiles Chuang Wang and Do-Hong Kim

Introduction The number of Chinese students studying overseas has increased exponentially during recent years. For example, 274,000 Chinese students were enrolled in higher education institutions in the United States in the 2013–2014 academic year, which is a 17% increase from the 2012–2013 academic year (Institute of International Education, 2014). Chinese students have become the largest group of international students in the United States. In the Michigan State University alone, Chinese undergraduate enrollments grew from 43 in 2005 to 4,000 in 2014 (Briggs, 2015). The biggest challenge of Chinese students in the United States is the language barrier (Wang & Zuo, 2014). Therefore, it is of critical importance to help Chinese students improve their English proficiency before coming to the United States. Motivational constructs such as self-efficacy beliefs and self-regulated learning strategies and their associations to academic achievement have been investigated in previous research (e.g., Bandura, 1997; Nyikos & Oxford, 1993; Oxford, 2011; Wang, Schwab, Fenn, & Chang, 2013). In the context of learning English as a second/foreign language, Diseth (2011) noted positive relationships between self-efficacy beliefs, the use of language learning strategies, and English language proficiency for Norwegian undergraduate students, and this is one of the few studies that examined the relationships between these three important constructs (Wang, Kim, Bong, & Ahn, 2013). Therefore, it is important to continue this line of research to examine these relationships in the context of foreign language acquisition with Chinese high school students.

Theoretical framework and related literature Self-efficacy is context-specific and is defined as a person’s belief to successfully complete a specific task based upon self-assessment of the skills he/she possesses (Bandura, 1986; Pajares, 1996). Efficacious students are more likely to persist when attempting to accomplish seemingly difficult tasks and are less likely to experience stress and anxiety during the learning process (Anam & Stracke, 2016; Pajares, 1996; Stevens, Olivarez Jr., Lan, & Tallent-Runnels, 2004). People who

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hold low self-efficacy beliefs do not like to face challenges and usually avoid difficult tasks (Schunk, 1990). Liem, Lau, and Nie (2008) conducted a national study with high school EFL students in Singapore and noted that efficacious students were more likely to adopt the performance-approach whereas less efficacious students were more likely to take the performance-avoidance approach. In the United States, high school students’ grade point average (GPA) was found to be associated with their homework quality, and this relationship was mediated by self-efficacy beliefs (Zimmerman & Kitsantas, 2005). According to the social cognitive theory, students have cognitive abilities to self-organize, self-reflect, and self-regulate in response to changes in learning tasks, and set their own goals. In order to do so, students have to be proactive in their development and know about their capabilities in order to regulate their actions. Key to this view of human agency are self-efficacy and self-regulation (Pajares, 2009); Zimmerman, 2000). Self-regulation refers to “self-generated thoughts, feelings, and actions that are planned and cyclically adapted based on performance feedback to attain self-set goals” (Zimmerman, 2000, p. 14). This cyclical loop includes three phases: forethought, performance, and self-reflection. In the context of English as a second/foreign language, many scholars use terms like cognitive and metacognitive strategies to refer to self-regulated learning strategies (e.g., Oxford, 1990, 2011). Oxford (1990) classified language learning strategies into two categories: direct strategies and indirect strategies. Direct strategies include memory strategies, cognitive strategies, and compensation strategies. Indirect strategies include metacognitive strategies, affective strategies, and social strategies. Other scholars classify the use of awareness, planning, monitoring, and reflections of the learning process into metacognitive knowledge (e.g., Zhang 2010). Oxford (2011) later developed the Strategic Self-Regulation (S2R) model in the context of language acquisition and claimed that language learning strategies are self-regulated learning strategies since these strategies are intentional. In this paper, we use the term self-regulated learning strategies to refer to any strategies that fall into the three phases of self-regulation: forethought, performance, and self-reflection. As part of the metacognitive knowledge, selfefficacy is considered the forethought part of the self-regulation process (Zimmerman, 2000). Zimmerman and Martinez-Pons (1990) developed 14 classes of self-regulated learning strategies working with elementary, middle, and high school students in New York City. These 14 classes of self-regulated learning strategies were further refined into 11 categories based upon a similar study with middle school students in Ohio in the United States (Pape & Wang, 2003). However, an extremely high correlation (r = .97) was noted between strategy use and self-regulation (Lee, Yin, & Zhang, 2010) and other scholars suggest to combine these factors when studying Chinese students’ learning strategies (e.g., Rao & Sachs, 1999). As a result, we did not distinguish the categories of self-regulated learning strategies in this study and considered all self-regulated learning strategies as a unitary construct. Students’ self-efficacy beliefs are strongly associated with their efforts to strategically regulate their learning processes (Zimmerman & Martinez-Pons,

English-language learners 29 1990). This is because efficacious students are more likely to take responsibility of the learning process (Zimmerman & Kitsantas, 2005). Zimmerman, Bandura, and Martinez-Pons (1992) subcategorized self-efficacy into self-efficacy for selfregulation and self-efficacy for academic achievement. Based upon their data, they reported that “students’ perceived self-regulatory efficacy would influence their perceived self-efficacy for academic achievement, and their efficacy should, in turn, influence their personal goals and grade achievement” (p. 665). Eshel and Kohavi (2003) reported a positive relationship between self-efficacy beliefs, use of cognitive strategies, and academic achievement, and this relationship was echoed in the context of EFL (Wang et al., 2013). In an international context, this relationship was confirmed with Asian students (Rao, Moely, & Sachs, 2000) as well as with European students (Tilfarlioglu & Cinkara, 2009). A mediating role of self-regulation was also found in the relationship between self-efficacy beliefs and academic achievement (Komarraju & Nadler, 2013). The instrument that was used to identity self-efficacy profiles in the current study was the Questionnaire of English Self-Efficacy (QESE). This instrument was designed to measure students’ perceptions about their capabilities to accomplish certain tasks using English listening, speaking, reading, and writing skills. The QESE has been adapted to fit into the cultural context of language learning in China, Germany, Korea, and the United States (Wang, Hu, Zhang, Chang, & Xu, 2012, Wang et al., 2013; Wang et al., 2013; Wang, Kim, Bai, & Hu, 2014). These studies were based on variable-centered approaches such as factor analysis and item response theory, which seek to describe the links between a given set of variables and the response patterns of participants. Although these methods provide valuable information about the psychometric properties of the scale, these approaches do not capture unobserved heterogeneity that may exist in the data. Different from the variable-centered approaches, person-centered approaches to data analysis consider unobserved heterogeneity within subsets of populations. Latent class analysis (LCA), a person-centered approach, can be used to identify latent groups in the population based on a set of categorical observed variables. Latent profile analysis (LPA), a variant of LCA, allows the use of continuous observed variables. Therefore, LPA was adopted in this study. Various levels and dimensions of perceived self-efficacy beliefs were identified in the literature (Bandura, 1997). It is therefore reasonable to hypothesize that there exists a number of different underlying latent dimensions to EFL learners’ self-efficacy beliefs, and that discrete self-efficacy profiles would be identifiable. We also hypothesize that significant differences exist between the groups of students identified by self-efficacy profiles with respect to their use of self-regulated learning strategies and English language proficiency. Using QESE, Kim and her colleagues (Kim, Wang, Bong, & Ahn, 2015) examined Korean college students’ self-efficacy profiles in relation to the use of self-regulated learning strategies and the English language proficiency levels in the process of studying English as a foreign language (EFL). This study used the same instrument (QESE) and LPA to examine different patterns of EFL students’ self-efficacy beliefs for learning English in China.

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The research questions that guided this study are: (a) Can QESE be used to identify Chinese students with different levels of English self-efficacy beliefs? (b) Are there significant differences with respect to the use of self-regulated learning strategies among the groups identified by QESE with LPA? (c) Are there significant differences with respect to the English proficiency among the groups identified by QESE with LPA?

Methods Participants Participants were 199 high school students in China, of whom 118 (59%) were males and 81 (41%) were females. Their age ranged from 15 to 19 years (M = 16.35, SD = 0.65). Most of the students started learning English from Grade 3 (with a few starting in first grade) in elementary schools, so their experience in learning English ranged from 9 to 11 years. The school is located in the northwest region of China, and the student population is mostly from Chinese middle-class families.

Instrument The Questionnaire of English Self-Efficacy (QESE) scale was used. The scale consists of 32 items (Table 3.1) and is measured on a seven-point rating scale from 1 (I cannot do it at all) to 7 (I can do it very well). It was designed to measure the following four areas: (a) self-efficacy for listening tasks (Items 1, 3, 9, 10, 15, 22, 24, and 27); (b) self-efficacy for speaking tasks (Items 4, 6, 8, 17, 19, 20, 23, and 30); (c) self-efficacy for reading tasks (Items 2, 12, 16, 21, 25, 26, 29, and 32); and (d) self-efficacy for writing tasks (Items 5, 7, 11, 13, 14, 18, 28, and 31). High internal consistency (Cronbach’s alpha) of participants’ responses to QESE was indicated by previous research (Wang & Bai, in press): .95 for all items, .93 for listening, .90 for speaking, .89 for reading, and .89 for writing. Results Table 3.1 Item means by profiles Items 1. Can you understand stories told in English? 2. Can you do homework/home assignments alone when they include reading English texts? 3. Can you understand American TV programs (in English)? 4. Can you describe your university to other people in English? 5. Can you compose messages in English on the Internet (Facebook, Twitter, blogs, etc.)?

Class 1 Class 2 Class 3 2.89 4.07

4.23 5.43

4.88 5.88

1.71

2.76

3.82

3.00

4.78

5.70

2.61

3.56

5.10

Items

Class 1 Class 2 Class 3

6. Can you describe the way to the university from the place where you live in English? 7. Can you write a text in English? 8. Can you tell a story in English? 9. Can you understand radio programs in Englishspeaking countries? 10. Can you understand English-language TV programs made in China? 11. Can you leave a note for another student in English? 12. Can you guess the meaning of unknown words when you are reading an English text? 13. Can you form new sentences from words you have just learnt? 14. Can you write e-mails in English? 15. Can you understand English dialogues (audio recordings) about everyday school matters? 16. Can you understand messages or news items in English on the Internet? 17. Can you ask your teacher questions in English? 18. Can you produce English sentences with idiomatic phrases? 19. Can you introduce your teacher (to someone else) in English? 20. Can you discuss subjects of general interest with your fellow students (in English)? 21. Can you read short English narratives? 22. Can you understand English films without subtitles? 23. Can you answer your teacher’s questions in English? 24. Can you understand English songs? 25. Can you read English-language newspapers? 26. Can you find out the meanings of new words using a monolingual dictionary? 27. Can you understand telephone numbers spoken in English? 28. Can you write diary entries in English? 29. Can you understand English articles on Chinese culture? 30. Can you introduce yourself in English? 31. Can you write an essay in about two pages about your lecturer in English? 32. Can you understand new reading materials (e.g., news from Time magazine) selected by your instructor?

3.68

5.13

5.97

3.79 2.50 2.18

4.80 4.07 3.12

5.78 4.96 3.98

2.36

3.38

4.18

3.18 3.54

4.93 4.56

5.84 5.24

4.00

4.87

5.54

2.57 2.93

2.93 4.28

4.45 4.97

2.54

3.66

4.46

3.00 3.93

4.26 5.28

5.18 6.25

2.86

4.96

6.00

1.96

3.70

4.91

2.25 1.96 4.11 2.89 3.11 4.43

3.55 2.59 4.83 3.49 4.02 5.34

4.58 3.81 5.98 4.74 4.87 6.10

5.14

5.62

6.37

2.89 2.68

4.57 3.59

5.72 4.67

3.89 2.71

5.24 4.48

6.21 5.47

3.46

4.68

5.69

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Chuang Wang and Do-Hong Kim

of confirmatory factor analysis in the samples of Chinese and German college students support factorial validity and factorial invariance (Wang et al., 2013). The psychometric properties of QESE were also examined with item response theory, and results suggest that the rating scale functioned effectively and the item hierarchy was consistent with the expected item order (Wang et al., 2014). Student use of self-regulated learning strategies was measured with the Questionnaire of English Self-Regulated Learning Strategies (QESRLS), which includes 65 items in 11 categories (Appendix A) developed from self-regulation theory (Zimmerman & Martinez-Pons, 1990). Students were asked to respond by circling one of the four choices where “0” stands for “never use this strategy”, “1” stands for “seldom use this strategy”, “2” stands for “sometimes use this strategy”, and “3” stands for “use this strategy frequently”. The internal consistency (Cronbach’s alpha) for QESRLS was .92 (Wang & Bai, in press). An iterative process of repeated independent translation and blind back-translation (Brislin, 1970) was used to ensure the congruence of meaning between the English and Chinese versions of the two questionnaires (QESE and QESRLS).

Appendix A Questionnaire of English self-regulated learning strategies Category 1: Self-Evaluation (4 items) • • • •

Check my English homework before turning them in. Proofread my English composition after I complete writing. Adjust my reading speed according to the difficulty of the article. When I finish my English composition, I have a rest and then read it again to check whether it should be revised.

Category 2: Organization and transformation (18 items) • • • • • • • • • • • • •

Write an outline before writing English compositions. Write an outline after reading an English article. Summarize the main idea of each paragraph when reading. Summarize the theme of an English article when I read it. Classify news words in order to memorize them. Use Chinese phrases which are similar to English words in pronunciation to memorize the pronunciation of these words. Make a chart to summarize the grammatical points learned. Recite similar words altogether. Compare the similarities and differences between English and Chinese. Memorize English words whose pronunciations are similar. Memorize a new word by memorizing where I learn it. Consider how to say something in English in my mind before saying it out loud. When I listen to English, I translate it into Chinese to help me understand it.

English-language learners 33 • • • • •

Translate what I have read in English into Chinese to help me understand it. Think out a composition in Chinese before writing it in English. Underline key points during my English reading. Make sure to write a topic sentence in each paragraph in writing. Make sure that the content of each paragraph supports its topic sentence in English writing.

Category 3: Rehearsal and memorization (5 items) • • • • •

Recite English texts in the process of studying English. Review the cards of new words in order to memorize them. Read texts I have learnt again and again in order to recite them. Write new words many times in order to memorize the spellings. Read new words repeatedly in order to memorize them.

Category 4: Seeking social assistance (3 items) • • •

Consult teachers when I encounter difficulties in the process of studying English. If I cannot follow someone’s English, I let him/her speak slowly. Ask classmates when I have questions in my English study.

Category 5: Persistence when faced with challenges (4 items) • • • •

Keep reading when I encounter difficulties in English reading. Read an English article several times if I don’t understand it the first time. Search related documents when I have difficulties in studying English. Listen to tape-recorded English several times if I cannot understand it the first time.

Category 6: Seeking opportunities to practice English (8 items) • • • • • • • •

Listen to American or British broadcasts to improve my pronunciation. Use sentence patterns just learnt to make new sentences for practice. Send emails to friends in English on my initiative. Try my best to find opportunities to practice my oral English. Watch English TV programs on my initiative. Listen to English radio programs on my initiative. Try to use various English expressions to express the same meaning. Use words just learnt to make new sentences on my initiative.

Category 7: Record keeping and monitoring (2 items) • •

Write down the mistakes I often make in the process of studying English. Take notes in English classes.

Category 8: Self-consequences (2 items) • •

Reward myself when I make progress in studying English. Have a break when I am tired during my English study.

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Chuang Wang and Do-Hong Kim

Category 9: Goal setting and planning (4 items) • • • •

Set a goal to study English. Make a study plan in the process of studying English When a friend wants to play with me but I have not finished my homework yet, I do not play until I finish my homework. Find a quiet place when the environment is disturbing.

Category 10: Review of records (2 items) • •

Review English texts I have learned. Review my notes of English class before examinations.

Category 11: Interpretation guessing (12 items) • • • • • • • • • • • •

Pay attention to what pronouns refer to during reading. Guess the meaning of new words by considering their contexts. Guess what people mean by reading their expressions and movements when watching an English movie. When I listen to English, I pay attention to the stressed words or phrases in order to comprehend the sentence. Use the title of an English article to help understand that article. When somebody speaks English, I guess what he/she will say according to what he/she has said. When I talk with somebody in English, I pay attention to his/her expressions to check if he/she can follow me. When I read an English article, I imagine the scene described in the article in order to memorize what I have read. Memorize meanings of words by using prefixes and suffixes. Pay attention to English speaker’s tones. Pay attention to the beginning and end of each paragraph in my English reading. Use my background knowledge to comprehend English articles.

English proficiency was measured with a Chinese national standardized test in English proficiency with a total score of 150. This test was developed by the National Higher Education Entrance Examination Center of the Ministry of Education in China and released to local schools for practice. The content of these English language proficiency tests includes English vocabulary, grammar, syntax, English reading comprehension skills, English writing skills, and English-Chinese translation skills.

Data analytical procedure Latent profile analysis (LPA) was used to identify the latent profiles underlying the data. Analyses were conducted using Mplus version 7.0 (Muthén & Muthén, 1998–2012). Statistical model fit was evaluated using multiple fit indices including

English-language learners 35 the Bayesian Information Criteria (BIC), Adjusted BIC (ABIC), the Lo-MendellRubin Likelihood Ratio Test (LMR-LRT), and the Bootstrap Likelihood Ratio Test (BLRT). Smaller values of the BIC and ABIC indicate a better fit. Significant LMR-LRT and BLRT results indicate a better fit. Entropy, a measure of classification uncertainty, was also used to determine the fit of the model. The entropy ranges from 0 to 1, with higher values indicating good classification of participants. Multivariate analysis of variance (MANOVA) was used to compare the group differences (classified by LPA) with respect to student use of self-regulated learning strategies and their achievement scores in an English language proficiency exam.

Results Underlying latent profiles A three-profile solution fitted the dataset and was interpretable. Table 3.2 presents the model fit information for the LPA models. All models under study exhibited high entropy values, indicating a good classification of students. The three-profile model had lower BIC and ABIC values relative to the two-profile model. Although the LMR-LRT was non-significant, the BLRT was significant. The BLRT was chosen over the LMR-LRT because of its consistency in detecting the correct number of classes within a population (Nylund, Asparouhov, & Muthèn, 2007). The BIC, ABIC, BLRT results, and substantive consideration all point toward the three-profile model. Of the 199 students included in the analysis, 14% were members of Profile 1, 41% were members of Profile 2, and 45% were members of Profile 3. The item means are provided in Table 3.2. Students in Profile 1 had lower scores in all 32 items as compared to Profile 2 and Profile 3. Students in Profile 3 had higher scores in all items. These classes were labeled ‘low self-efficacy profile’ (Profile 1), ‘medium self-efficacy profile’ (Profile 2), and ‘high self-efficacy profile’ (Profile 3). The low self-efficacy profile consisted of mostly males (82.1%). Slightly more than half of students were male in the medium (56.1%) and high self-efficacy profiles (55.1%). A chi-square test showed that a greater proportion of male students fell into the low self-efficacy profile, χ2(df =2, n = 199) = 7.07, p = .03. Statistically significant differences, using Wilks’ Lambda, were noticed in the combination of student use of SRL and their English proficiency, F(4, 218) = 8.88, p < .001, partial η2 = .14. Table 3.2 Model fit criteria for one- to three-profile models Model

BIC

ABIC

Entropy

L-M-R LRT (p)

Bootstrap LRT (p)

One-profile Two-profile Three-profile

21876.07 20408.44 20036.83

21673.31 20101.14 19624.98

n/a .97 .95

n/a .011 .148

n/a