Methodology for Early Childhood Education and Care Research: Premises and Principles of Scientific Knowledge Building 3031241738, 9783031241734

Table of contents :
Preface
Contents
1 Introduction
1.1 Guidance for Readers
References
2 Scientific Knowledge
2.1 The Characteristic Features of Scientific Knowledge
2.2 Organizing for Collective Knowledge Building
2.3 A Disclaimer and Justifications
References
3 The Importance and Functions of Theory
3.1 Triangulation
3.2 Unit of Analysis and the Problem with Mixing Theories
3.3 Theory and Research Questions
3.4 Process Versus Product Studies
3.5 The Contextual Nature of Studying Individuals’ Knowing or Abilities
3.6 Communicative Framing
3.7 A Few Words on Ontology and Epistemology and the Constitutive Nature of Language Practices
3.8 Concluding Words
References
4 Quality Criteria
4.1 Science as an Argumentative Set of Practices
4.2 Inductive, Deductive, and Abductive Research
4.2.1 Points on a Continuum Rather than a Dichotomy
4.3 Generalization
4.3.1 Conceptual Generalization
4.4 Transcribing and Representing Empirical Data
4.4.1 Transparency
4.5 Findings Versus Results
4.6 Summary
References
5 Some Notes on Normativity and Research
5.1 A Philosophical Investigation of Norms
5.1.1 Norms for Research
5.1.2 Norms in Research and Norms in Drawing Conclusions from Research
5.1.3 Norms in the Semiotic Means of Research
5.2 The Politics of Representation
5.3 Summary and Conclusions
5.3.1 Bad Research Is Unethical
References
6 Scientific Language Practices
6.1 Being Linguistically Responsive to the Dynamic Nature of the Phenomena and Processes of Educational Research
6.2 Metaphors for Talking About the Empirical Basis of Research
6.3 Some Final Words on the Importance of Being Attentive to Terminology
References
7 Coda: Summary and the Importance of Being Mindful of Pareidolia
7.1 Pareidolia and Conclusions
References

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SpringerBriefs in Education Niklas Pramling

Methodology for Early Childhood Education and Care Research Premises and Principles of Scientific Knowledge Building

SpringerBriefs in Education

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Niklas Pramling

Methodology for Early Childhood Education and Care Research Premises and Principles of Scientific Knowledge Building

Niklas Pramling Department of Education Communication and Learning University of Gothenburg Gothenburg, Sweden

ISSN 2211-1921 ISSN 2211-193X (electronic) SpringerBriefs in Education ISBN 978-3-031-24173-4 ISBN 978-3-031-24174-1 (eBook) https://doi.org/10.1007/978-3-031-24174-1 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

This book is dedicated to Aino-Maja: May you continue asking, “How do you know that?”

Preface

This is a book about the distinguishing features of scientific knowledge and research and is intended to introduce and further the professional development of Ph.D. students, with a particular focus on conducting research in and on early childhood education and care. Much of what the book covers concerns fundamental matters of knowledge building. These matters tend to be taken for granted and therefore remain implicit, which constitutes a hindrance to students in the process of appropriating this professional knowledge. There is therefore great value, I premise, in trying to also explicate these matters of research as they are generative of how research, more concretely, is carried out, criticized, and valued. Many of the features discussed here are seldom discussed in theoretical literature, while others are frequently covered. However, it is valuable to see how the different issues and parts of research are inherently related to each other. This relationship-building work, so to speak, is an important ambition of this book. The content of this book is the insights I have appropriated through my own education (including my Ph.D. studies), as the director of and the supervisor at three national (Swedish) research schools, from my individual and collaborative work, and from readings in fields within as well as outside my prime areas of work. I have had the good fortune of having great teachers and supervisors throughout my education (studying cultural studies, literature history, psychology, and finally educational research), who have formed my understanding a great deal about the matters covered here. I wish to extend my gratitude to Lea Eldstål-Ahrens and Sofije Shengjergji for assisting with German and Greek, respectively, and to Louise Peterson, for generously and insightfully commenting on an earlier draft of this text. I would also like to thank the anonymous reviewers for their suggestions for developing the text. Finally, my gratitude goes out to my editor at Springer, Astrid Noordermeer, who has overseen the work in an excellent manner, as always. Needless to say, any faults in the present elaboration are entirely my own. Here, in passing, it may be noted that in scientific literature we need to say what is “needless to say”, which testifies to the foundational and prevalent feature of this form of knowledge in placing great value on explication, something that I will return to throughout this book. Learning to become a researcher does not simply mean learning to conduct research, in the sense of knowing how to carry out an empirical study; it also entails vii

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appropriating important practices for how to engage in informed dialogue, critique, and reasoning. With this book, I mean to introduce—and contribute to further developing the reader’s ability to develop their participation in—these latter kinds of practices. Gothenburg, Sweden November 2022

Niklas Pramling

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Guidance for Readers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 3 4

2 Scientific Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1 The Characteristic Features of Scientific Knowledge . . . . . . . . . . . . . . 6 2.2 Organizing for Collective Knowledge Building . . . . . . . . . . . . . . . . . . 9 2.3 A Disclaimer and Justifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3 The Importance and Functions of Theory . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Triangulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Unit of Analysis and the Problem with Mixing Theories . . . . . . . . . . . 3.3 Theory and Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Process Versus Product Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 The Contextual Nature of Studying Individuals’ Knowing or Abilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Communicative Framing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 A Few Words on Ontology and Epistemology and the Constitutive Nature of Language Practices . . . . . . . . . . . . . . . . . . . . . . 3.8 Concluding Words . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13 18 19 21 23

4 Quality Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Science as an Argumentative Set of Practices . . . . . . . . . . . . . . . . . . . . 4.2 Inductive, Deductive, and Abductive Research . . . . . . . . . . . . . . . . . . . 4.2.1 Points on a Continuum Rather than a Dichotomy . . . . . . . . . . 4.3 Generalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Conceptual Generalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Transcribing and Representing Empirical Data . . . . . . . . . . . . . . . . . . . 4.4.1 Transparency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Findings Versus Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

35 39 39 40 41 41 43 44 46

25 27 28 30 31

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4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 5 Some Notes on Normativity and Research . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 A Philosophical Investigation of Norms . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Norms for Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Norms in Research and Norms in Drawing Conclusions from Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 Norms in the Semiotic Means of Research . . . . . . . . . . . . . . . . 5.2 The Politics of Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Bad Research Is Unethical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

53 54 55

6 Scientific Language Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Being Linguistically Responsive to the Dynamic Nature of the Phenomena and Processes of Educational Research . . . . . . . . . 6.2 Metaphors for Talking About the Empirical Basis of Research . . . . . 6.3 Some Final Words on the Importance of Being Attentive to Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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55 56 57 59 61 62

65 68 68 69

7 Coda: Summary and the Importance of Being Mindful of Pareidolia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 7.1 Pareidolia and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

Chapter 1

Introduction

Abstract In this chapter, the topic of the book is introduced: methodology for conducting research in the field of early childhood education and care. The premises and themes of the book are presented, and the structure of the presentation is clarified. The dual-level analysis of theoretical principles and concrete tools for analysis is also introduced.

The book you are reading was written with the aim of being a valuable source of support in Ph.D. studies; that is, in learning to be a researcher. The frame of reference for my discussion will be educational science and related fields of inquiry, particularly emphasizing issues concerning early childhood education and care (ECEC) research. However, many of the points I make and the arguments I put forth will be of a more general nature and concern research and scientific knowledge as such. The topic of this book—that is, what characterizes scientific knowledge and how to conduct research (in early childhood education and care)—actualizes many aspects of learning to become a researcher that unfortunately tend to be taken for granted and are therefore seldom properly explicated. This fact poses a potential difficulty in learning about these fundamental issues of the professional knowledge involved in a Ph.D. education. Furthermore, while some concrete parts of conducting empirical research may be covered in analytical courses, more overarching issues of the philosophy and theory of science tend not to be conveyed but are covered, if at all, in separate courses. However, I argue that there is a point in managing these levels of reasoning, as it were, in relation to each other. This forms the rationale for this book’s ambition to provide insight into more concrete matters, such as how to reason about the relationship between theory and method or between empirical data represented in a study and the larger corpus of data available to the researcher, as well as to help the student become more familiar with more abstract and foundational issues and ways of reasoning in science and research. The latter can be understood as an ambition to contribute to students’ Bildung, a central concept of German (and Continental European) education discussions. The concept of Bildung is used in educational discussions to emphasize the more formative aspects of education. That is, it refers to a “wide concept of education” (Ødegaard, 2019, p. 37), including and emphasizing what metaphorically speaking © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_1

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lies beyond learning specific principles, distinctions, concepts, and facts. The term Bildung, Ødegaard (2019) clarifies, stems from the novel Wilhelm Meisters Lehrjahre by Wolfgang von Goethe, published in four volumes 1795–1796, in which “becoming is positioned as shaping-enlightening self-reflexivity coming of age through trial, testing and disruption, ultimately leading to transcendence into deeper understanding and, by association, democratic participation” (p. 25). The concept then became important in German philosophy and in educational debates in many other countries. The term as such does not have a corresponding word in English. The word Bildung stems from the German word “bilden” (to form/constitute) and the suffix –ung. As with other German words, this suffix is used in the formation of nouns from verbs (nominalization; see Chap. 6 of this book). Suggestions for translation have included edification, shaping, and formation (Ødegaard & White, 2016). Other metaphors used in translating Bildung (itself, of course, a metaphor) include “transcendence into deeper inquiry and understanding” (Ødegaard & White, 2016, p. 2). Metaphors such as “deeper understanding” imply that Bildung is constituted in contrast to skills and knowledge that can be taught through transmission, and that it as such arguably requires reflection or discussion. Thus, by implication, Bildung requires active participation by the learner and (also) denotes such development as community contribution and wisdom (what, metaphorically speaking lies beneath or above knowing the facts). Bildung also implies an image of learners as being able to make informed choices and account for those choices, which, in research, is what methodology is about. Hence, in suggesting that with this book I intend to contribute to “dual-level” learning, as it were, I want to emphasize, on the one level, learning the “crafts of the trade” of being a researcher, and on the other level, being informed through education into someone who can make active decisions and account for the bases and reasons for those choices and what they imply for knowledge building. There is thus, through forming one’s self—as a researcher, for example—a feature of this that implies the partly new identity embodied by the learner through participating in a research education, allowing the person to conduct research but also, as a researcher, to partake in and contribute to public debate. In Ødegaard and White’s (2016) elegant terms: “bildung could be understood as a series of subjective processes that sophisticate the individual as a participant in society” (p. 6), and particularly in societal domains such as science and education, we may add, in the present contextualization. Hence, throughout this book I intend to discuss more or less in parallel concrete matters of research practices and more theoretically abstract matters of foundations for the kind of knowledge-building tradition we call research and the institutionalized body of knowledge we call science. My hope is that this book will be useful to Ph.D. students by contributing to both these levels of understanding of the professional knowledge they are in the process of appropriating, through explicating what largely tends to remain all too implicit and taken for granted.

1.1 Guidance for Readers

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1.1 Guidance for Readers This book is structured in the following way. I have already briefly introduced its topic and rationale. In the next chapter (Chap. 2), I clarify the premises and understanding the book is based on. This is important, because I will argue that there are always premises of knowledge building, and it is important to attempt to explicate these in order to make them available to analytical scrutiny and discussion. Thereafter (Chap. 3), I delve into a particularly important feature of research and science: theory. I expound on my understanding of what a theory is and some of the important functions of theory in research. This is followed by a discussion of matters concerning how research objects are delimited and investigated, and how the research questions asked are related to theory. I also discuss a principal, important distinction between research studies in education and related fields (developmental research, psychology), long recognized but still with an unfortunate preponderance or slant: process versus product studies. In Chap. 4 I discuss some quality criteria that are highlighted in the kind of research I address, which is often qualitative. The meaning of qualitative is also discussed here, as much confusion can be observed in the use of this word in describing research. I discuss different research approaches, often referred to as inductive versus deductive. In this chapter I also discuss matters of generalization in so-called qualitative research (as critically discussed in the previous chapter), as well as more concrete issues of transcription and representation of empirical data in studies and analyses. Chapter 5 contains a discussion of norms in research. The issue of normativity in research is a sensitive topic, and grave simplifications are often expressed about it. In order to promote more productive debate about this matter, I present a conceptual differentiation and exemplification. Chapter 6 provides an elaboration on the importance of scientific terminology, particularly its metaphors. Finally, in Chap. 7, I summarize the major claims made in the book and the importance of being mindful of pareidolia, which I argue can be seen as a metaphor for an ability that is critical to a researcher. An important feature of research that I will not discuss separately and extensively in this book is ethics. That I do not elaborate on this feature should not be read as an implication that it is not important; on the contrary, research has to be carried out in ways that are ethically legitimate. It should also be noted, as is common knowledge today, that research ethics is not something that can be clarified beforehand, for example, by submitting one’s research plan to an ethics committee for approval. Rather, ethics is integral to the entire research endeavor and may come to the fore in unexpected ways, requiring a sensitive response by the researcher. In this book, I will primarily discuss ethical matters of two kinds: The first concerns those that are actualized by labelling and conceptualization. I will discuss this matter (in Chap. 5) in terms of what Mehan (1993) has referred to as the politics of representation. The second ethical matter I will raise involves the relationship between the quality of research and research ethics. I discuss this in Chap. 5 as well. As these are features of research ethics that I perceive are not extensively recognized or discussed, I will focus on them here (with additional features of research ethics being treated in a

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more integrated way and in passing). For more encompassing and deeper insight into the principles and dilemmas of research ethics in the context of ECEC research, see Farrell (2016) and the ethical code of the European Early Childhood Education Research Association (EECERA, 2015).

References EECERA. (2015). EECERA ethical code for early childhood researchers (revised version 1.2: May 2015). Accessed from https://www.eecera.org/about/ethical-code/ on May 26, 2021. Farrell, A. (2016). Ethics in early childhood research. In A. Farrell, S. Lynn Kagan & E. K. M. Tisdall (Eds.), The Sage handbook of early childhood research (pp. 187–195). Sage. Mehan, H. (1993). Beneath the skin and between the ears: A case study in the politics of representation. In S. Chaiklin & J. Lave (Eds.), Understanding practice: Perspectives on activity and context (pp. 241–268). Cambridge University Press. Ødegaard, E. E. (2019). Norway: ‘Danning’ and the infant—Local conditions for the early formation as persons. In M. Gradovski, E. E. Ødegaard, N. Rutanen, J. Sumsion, C. Mika, & E. J. White (Eds.), The first 1000 days of early childhood: Becoming (pp. 33–54). Springer. Ødegaard, E. E., & White, E. J. (2016). Bildung: Potential and promise in early childhood education. In M. A. Peters (Ed.), Encyclopedia of educational philosophy and theory (pp. 1–7). Springer.

Chapter 2

Scientific Knowledge

Abstract In this chapter, what characterizes scientific knowledge is introduced and discussed. Central concepts such as theory, method, and analysis are elaborated on through tracing their historical origin; that is, their etymology.

When encountering a new domain of knowing or, in Wittgenstein’s (1953) terms, a new language game, I find it useful to look into the history and transformation—the etymology—of its constituent concepts. Looking at some of the key concepts of science can help us get a better grasp on features of concepts that may no longer tend to be made explicit and thus to some extent remain hidden from learners. The following are some examples: Method = from the Greek méthodus [Mšθ oδ oς], originally pursuit, following after (meta[μετ α-] ´ after + hodós [Ðδ o´ ς ] a traveling road). The extended sense of any special procedure or way of doing things. -logy [λoγ ι´α] (methodology [Mεθ oδ oλoγ ι´α]) = knowledge about or the science of; methodology = knowledge about, or the science of, method. Theory [Θεωρ´ια] = from the Greek: contemplation, looking at, consider. Analysis [Aν αλυσ ´ η] = from the Greek: breaking up (Barnhart, 2004, pp. 657, 608, 1132 and 32)

Hence, from this etymological clarification we can say that method means the act of following a road or initiating a path and then following it to its end. Phrased differently, in this extended sense method means that it should be possible to follow the researcher’s reasoning and knowledge building from initiation to conclusion. That is, other researchers should be able to follow the logic of the study in order to be able to scrutinize the process of knowledge building. This implies that one cannot start at one place, with a particular set of theoretical premises and then shift these during the course of the study. Shifting theory within a study results in the method being inconsistent. This reasoning further implies that the different parts— or, metaphorically speaking, the steps of the road travelled—need to be consistent in their relationships. Hence, if one takes a particular theoretical point of departure, the method, analytical procedure, and so on need to be harmonious in order to follow the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_2

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knowledge building to its claims and conclusions. The suffix -logy originally means knowledge about or, in more modern translation, the science of . We recognize this suffix in many disciplinary names, such as sociology (knowledge about or the science of the social), psychology, and biology. Combining the meaning of method and the suffix -logy, we can say that methodology denotes knowledge about or the science of method. We can thus explicate methodology as the theoretical discussion about the choices and implications of method. Understood in this way, the topic of this book is methodology. Looking at the other examples above, we see that the original sense of theory as a way of looking at something reminds us of the perspectivity inherent in theory, which I will return to and discuss extensively. And the original sense of analysis, as breaking up, clarifies that this process means picking out parts of something, breaking up initial wholes or complexity into pieces. The purpose of this breaking up into pieces is to be able to perceive patterns that are otherwise hidden in the complexity of wholeness. Hence, the purpose of analysis is to identify patterns through separating out parts; parts that, when devoid of original complexes, allow us to perceive and systematize knowledge in order to orient ourselves in the world (this, of course, includes orienting ourselves in theoretically constituted worlds).

2.1 The Characteristic Features of Scientific Knowledge A fundamental premise of this book, based on insights from the philosophy of Wittgenstein (1969), is that we have to presume something to know something. Another premise of this book and its view on scientific knowledge is that it is important to try to make explicit premises generative of one’s arguing and knowledge building. Hence, here I will present what I understand as characteristic of scientific knowledge, in order for the reader to see where I come from, conceptually speaking. It is from this perspective (these premises) that I write this book. The premises I build upon are that scientific knowledge is characterized by being: . . . . . . . .

Systematic (methodical) Explicit and distinct Empirical and theoretical Cumulative Theoretically consistent Reductive Critically scrutinized Collective.

I will discuss each feature more extensively throughout the book, but will introduce them here. Being systematic means that our knowledge building cannot be arbitrary. Through method—that is, a systematic way of working with knowledge building—we gain systematicity. Being explicit means that, as opposed to everyday discourse in which people tend to leave large parts implied and taken for granted, in

2.1 The Characteristic Features of Scientific Knowledge

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scientific discourse an attempt is made to also make explicit the premises of one’s work: method, analysis, reasoning, and theorizing. Saying that scientific knowledge is distinct denotes how scientists try to make clear statements. It should not be unclear to the reader of a scientific text what is claimed and what the bases for those claims are. Phrased differently, in science we attempt to avoid being vague. Saying that scientific knowledge is empirical and theoretical means that the basis of scientific claims is in what has been found through empirical investigation—this is foundational to the tradition of research since Greek Antiquity—rather than speculation, introspection, or some other means of gaining insight. However, in the nature of science, empirical observation and investigation are not enough. In order to become scientific knowledge, such observations need to be represented in a way that allows understanding of a more general kind. Theoretical language provides such representational means for conceptualizing observations beyond the here-and-now of concrete investigation. It is important to remember that theory is empirically grounded; it is not merely made up in the abstract from philosophical principles. Philosophical speculation, or even more proper investigation, is not theory in the scientific sense. Emphasizing that scientific knowledge is cumulative indicates that a study cannot start from nothing, as if it were the first study. There are always previous work and insights that a study explicitly and/or implicitly builds upon. This is cogently formulated in the famous metaphor of “standing on the shoulders of giants”, traced to Bernard de Chartres (in the twelfth century) but today usually associated with Isaac Newton (seventeenth century). It is through building on the contributions—empirically, methodologically, theoretically—of previous research that scientific knowledge building becomes so powerful. Every scientist does not have to, and cannot, start anew every time a study is conducted. Building on previous research to contribute to cumulative knowledge building highlights the importance of locating one’s work in previous research, theoretical and methodological elaboration, and referencing where credit is due. The assertion that scientific investigation is characterized by theoretical consistency needs to be elaborated on. The claim is not that there is but one theory that all science—in a field or discipline—is informed by. For example, there is not only one theory in developmental psychology or one theory of sociology. Rather, there is an inherent value in there being a repertoire of theories in a research field or discipline. This is because theories provide perspectives, and being able to change perspective—or phrased differently, to re-theorize—what is investigated is therefore of great value. When I state that theoretical consistency is a characteristic of scientific knowledge, I refer to the importance of being constant within an investigation, a study. That is, one cannot start with one theory and then in the middle of one’s analysis, for example, use analytical concepts that stem from another theory. Such a shift results in a rendering that lacks systematicity (see the first characteristic listed and briefly introduced above). This is an important issue that I will discuss and exemplify at some length in this book. However, for now it is enough to say that theoretical consistency is pivotal to the systematic nature of an investigation and that theoretical plurality is critical to the vitality of a research field or discipline. It is important to be clear about this distinction. To phrase it differently, on a meta-level, it is an asset that there are a multitude of theories in a research field such as early

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childhood education and care, as different theories are theories of different things (learning, development, power, socialization, care, upbringing…) and constitute the object of study in different ways, allowing new insights to emerge. However, within the context of a study or an analysis it is problematic to adhere to different theories and combine different theories, as I argue in this book. That scientific knowledge is characterized by being critically scrutinized refers to the fact that critique is built into scientific knowledge building. When one intends to publish, and thus contribute to scientific literature, one’s text will have to pass through blind peer review. That is, when one submits a manuscript for a research article, or a research monography, the validity of the contribution will be critically evaluated by other scholars without their knowing the identity of the author(s) (and vice versa). This is important in order not to evaluate texts based on knowledge of their author(s) (whether positive or negative). The task of reviewers is to evaluate the manuscript in terms of whether its knowledge claims and conclusions can be substantiated by the research conducted. Critique is also part of scientific work in other ways. Two additional examples are public debate, such as the discussion between opponent (and potentially also the members of the examination board and the auditorium) and respondent at viva voce (disputation) in which a PhD thesis is put to the test of critical scrutiny, and scientific debate concerning how matters of mutual concern may be explained and what conclusions can and cannot be drawn based on different investigations. An important distinction to keep in mind as a Ph.D. student concerning criticism of one’s work—at the viva or when submitting article manuscripts to journals (or when discussing one’s work at research conferences, yet another forum for the critical scrutiny of research)—is that between criticism raised from within the theoretical tradition in which one’s study is located and from outside this tradition, building on other theoretical premises. Criticism from within a theoretical tradition may concern whether the study is in fact, as it states, a study based on this particular theoretical perspective. For example, an author claims that a study is socioculturally informed, in building on the theorizing of Vygotsky, but criticism asserts that how the study has been conducted and the data have been analyzed suggests that it is in fact not such as study but rather builds on other theoretical premises. A classic example of criticism raised within a theoretical tradition can be found in the sociocultural (cultural-historical) tradition of Vygotsky. In the English translation of his work that largely introduced his theorizing to the Western world, Mind in Society (Vygotsky, 1978), the term “internalization” was used. However, criticism was eventually raised that this term is disharmonious with the theoretical perspective, as it implies an unfortunate dichotomy (either/or) between outer and inner; precisely the kind of thought figure that Vygotsky attempted to avoid in order to be able to explain relationships (rather than either/or positions) and change. In response to this criticism, the metaphor of appropriation was eventually suggested as a replacement for the internalization metaphor, as appropriation avoids the dichotomy of inner/outer and implies something that is done (rather than something simply happening), thus requiring some effort of sense making by the learner, a process that is gradual and can offer resistance (see Wertsch, 1998, for a discussion). Hence, it was argued that the appropriation metaphor better represents the dynamics of learning and is harmonious

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with the theorization provided by Vygotsky and others in this theoretical tradition. This was thus a critical debate that emerged within a theoretical tradition and led to theory development. Contrary to critical discussion within a theoretical tradition, criticism from outside the theoretical tradition of a study may concern whether one should—or even could— avoid analyzing, for example, classroom communication without taking a gender perspective. This kind of criticism concerns the premises of a study, whereas the former (coming from within a theoretical tradition) concerns whether the work done and the conclusions drawn harmonize with the premises of the chosen theory. Hence, in the instance that criticism is raised from within a theoretical tradition, responding to it involves clarifying what this perspective means, what its premises are, and what arguably follows from them in conducting research. Contrary to this, in the instance that criticism is raised from outside the theoretical tradition to which the study adheres, responding to it involves the different premises of different theories and how the present study is consistent with the premises of its theoretical tradition, and what the arguments for its validity are (for an interesting example of scientific debate, see Billig, 1999a, 1999b; and Schegloff, 1999a, 1999b; as well as the journal Human Development for articles published in tandem with critical commentaries, e.g. Aronsson & Hundeide, 2002, commented by Wells, 2002, or Schoultz et al., 2001, commented by Candela, 2001). To conclude, different argumentative practices are implied for responding to criticism raised from within as opposed to from outside the theoretical tradition of the study.

2.2 Organizing for Collective Knowledge Building As I emphasize throughout this text, research is a collective endeavor. Even if only one name appears on a dissertation (in the case of a monography, that is; when a by-publication dissertation is written, the supervisors are generally listed as recognized co-authors of the individual studies), it is the product of collective work. This collective is in a sense both imaginary and real, made up of physically absent but intellectually present others (cf. Bakhtin, 1986) as well as actual persons who have commented on drafts at seminars, provided supervision, given lectures, and more. It is only through other scholars’ critical review that a text becomes part of the collective knowledge building of science. This should be kept in mind when organizing for research education. A particularly fruitful activity to this end is the seminar. To give a concrete example: The research group that I lead meets approximately every three weeks for a seminar. On these occasions, we discuss manuscripts for articles and chapters, have data sessions (cf. Derry et al., 2010), and discuss published research in our fields of interest. The texts to be discussed are sent out at least a week ahead of time, and every participant is expected to have read them and prepared comments and questions beforehand. The group consists of a substantial, but not overly extensive, number of scholars (somewhere between 10 and 20 usually take part in the seminars

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I lead), including master’s students, Ph.D. students, Ph.D.s, Associate Professors (Docents), and Professors. The seminar serves many functions. Junior scholars are socialized into academia and learn how to work: how to do analyses, build a case, discuss research matters, and so on. The members also learn to argue as well as to give and take criticism, which are fundamental to scientific knowledge building. The group further serves as a resource for collective meaning making, thinking (cf. Mercer, 2013), and remembering (cf. Middleton & Edwards, 1990). For the master’s and Ph.D. students, the seminars also function as instances of collective supervision (even though they, of course, have their own formal supervisors). In the long run, these recurring seminars can generate new topics for shared research and even develop into more extensive research programs. PhD students are therefore encouraged to inquire about the possibility to participate in this kind of seminar or, if none is available, to look into whether senior scholar(s) can organize something of this kind. It will provide an important arena for developing research and researchers, whether you are an emerging or an established scholar.

2.3 A Disclaimer and Justifications The observant reader will note that in this book I do not fully adhere to the quality criteria I set out. For example, while I argue that criticism in science needs to be specific (explicitly grounded, quoting from the studies criticized), I will generally not do this here. The reasons for this are threefold. First, it is very difficult for those whose work I could criticize in this book to find an adequate forum to respond to this; if criticism is raised in a research journal, those whose work is criticized would be expected to be invited to, and allowed to, write a rejoinder. Second, the fact that what I criticize in this context are common problems, rather than what is particular to a study, it would be somewhat unfair (even unethical; see Matusov, 2011; Roth & Cole, 2010, for an analogous case) to single out a study to address this criticism. Third, a reason for diverging from the common practice of scientific criticism is also contingent on the context of the discussion in this book (an introduction to methodology and scientific thinking, rather than contributions to a particular research issue, for instance how to understand teaching in preschool or what quality ECEC is). What I will criticize in this more general way includes matters of situatedness, in situ, context and influence, triangulation, research on quality, theory eclecticism, normativity, and, with reference to Roth and Cole (2010), referencing practices. As seen in this chapter, many of the characteristics I have listed and briefly introduced concern or actualize, in different ways, issues of theory. Therefore, I will start my discussion with precisely this critical feature of scientific knowledge and knowledge building.

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References Aronsson, K., & Hundeide, K. (2002). Relational rationality and children’s interview responses. Human Development, 45(3), 174–186. Bakhtin, M. M. (1986). The problem of speech genres (V. W. McGee, Trans.). In C. Emerson & M. Holquist (Eds.), Speech genres and other late essays (pp. 60–102). University of Texas Press. Barnhart, R. K. (Ed.). (2004). Chambers dictionary of etymology. Chambers. Billig, M. (1999a). Whose terms? whose ordinariness? Rhetoric and ideology in conversation analysis. Discourse and Society, 10(4), 543–558. Billig, M. (1999b). Conversational analysis and the claims of naivety. Discourse and Society, 10(4), 572–576. Candela, A. (2001). Earthly talk (Commentary). Human Development, 44, 119–125. Derry, S. J., Pea, R. D., Barron, B., Engle, R. A., Erickson, F., Goldman, R., Hall, R., Koschmann, T., Lemke, J. L., Sherin, M. G., & Sherin, B. L. (2010). Conducting video research in the learning sciences: Guidance on selection, analysis, technology, and ethics. Journal of the Learning Sciences, 19, 3–53. Matusov, E. (2011). Too many references, just cut a few and it will be perfect: APA versus Chicago (Commentary). Mind, Culture, and Activity, 18, 58–66. Mercer, N. (2013). The social brain, language, and goal-directed collective thinking: A social conception of cognition and its implications for understanding how we think, teach, and learn. Educational Psychologist, 48(3), 148–168. Middleton, D., & Edwards, D. (Eds.). (1990). Collective remembering. Sage. Roth, W.-M., & Cole, M. (2010). The referencing practices of Mind, Culture, and Activity: On citing (sighting?) and being cited (sighted?). Mind, Culture, and Activity, 17, 93–101. Schegloff, E. A. (1999a). ‘Schegloff’s texts’ as ‘Billig’s data’: A critical reply. Discourse and Society, 10(4), 558–572. Schegloff, E. A. (1999b). Naivete vs sophistication or discipline versus self-indulgence: A rejoinder to Billig. Discourse and Society, 10(4), 577–582. Schoultz, J., Säljö, R., & Wyndhamn, J. (2001). Heavenly talk: Discourse, artifacts, and children’s understanding of elementary astronomy. Human Development, 44, 103–118. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. In M. Cole, V. John-Steiner, S. Scribner & E. Souberman (Eds.), Harvard University Press. Wells, G. (2002). Responding in interviews and tests: Children learning to participate in the activity of evaluation (Commentary). Human Development, 45, 187–193. Wertsch, J. V. (1998). Mind as action. Oxford University Press. Wittgenstein, L. (1953). Philosophische untersuchungen/Philosophical investigations (G. E. M. Anscombe, Trans.). Blackwell. Wittgenstein, L. (1969). On certainty/Über Gewissheit. In G. E. M. Anscombe & G. H. von Wright (Eds.). Blackwell.

Chapter 3

The Importance and Functions of Theory

Abstract In this chapter, the decisiveness of theory for scientific knowledge building is argued, and different functions served by theory are discussed. In light of this discussion, practices such as triangulation and the mixing of theories are criticized. The important distinction between term and concept is made and exemplified with reference to learning theories. The theoretical nature of research questions is exemplified, and the difference between process and product studies is explained. The localization of a study is discussed in terms of the difference between context and contextualization. Ontology and epistemology are introduced through etymology, and examples of their relationship from the research field of early childhood education are discussed.

To explain and illustrate the importance of theory in research, consider the following fictive example from one of the classics of the philosophy of science, Norwood Hanson’s book Patterns of Discovery, first published in 1958: Let us consider Johannes Kepler: imagine him on a hill watching the dawn. With him is Tycho Brahe. Kepler regarded the sun as fixed: it was the earth that moved. But Tycho followed Ptolemy and Aristotle in this much at least: the earth was fixed and all other celestial bodies moved around it. Do Kepler and Tycho see the same thing in the east at dawn? (Hanson, 1958/1981, p. 5)

The question posed concerns how to understand seeing or, in research, making an observation. Two different senses of—or concepts of—seeing are potentially at play here. On the one hand, the two scientists see the same thing: It is the same light pattern that meets their retinas. On the other hand, each of them sees the opposite of what the other does: Where one sees stillness, the other sees movement. In terms of seeing as a physical process, it is the same light pattern (or information) for both scientists. However, in terms of what they see what they observe as, they differ. A basic premise of human sense making is that we do not merely register and process information; we make sense (Bruner, 1990). This means that we, both literally and metaphorically speaking, see something as something. In the cultural-historical theoretical tradition (aka a sociocultural perspective), this is conceptualized in terms of the semiotic mediation of perceiving (Luria, 1976; Vygotsky, 1978; Wertsch, 2007). According © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_3

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to this theoretical position, when we come into contact with and gradually appropriate cultural tools (e.g., concepts, distinction, metaphors, narratives), these come to shape how we perceive the world and its phenomena. Returning to Hanson (1958/1981), he argues in a similar vein, if in partly other terms: There is a sense, then, in which seeing is a ‘theory-laden’ undertaking. Observation of x is shaped by prior knowledge of x. Another influence on observations rests in the language or notation used to express what we know, and without which there would be little we could recognize as knowledge. (p. 19)

Saying that seeing in science is “theory-laden” is important. This clam is not only coherent with the previous reasoning from educational psychology (Bruner, 1990; Luria, 1976; Vygotsky, 1978; Wertsch, 2007) but also implies an important distinction between the seeing of everyday life versus the seeing practices of research. As humans, whether or not we happen to be scientists, we see something as something. But there is still an important difference between the seeing in everyday life, on the one hand, and the seeing by researchers on the other. The distinctive difference is that in research, systematic and explicit perspectives mediate perception, while in everyday life, people likely do not to any greater extent make explicit or reflect on the premises involved and the ensuing perspective they take on the world. Rather, on many occasions, people do not find reason to become aware of perspectives; rather, what is seen is experienced as the way it is. In research, things are different. Theorizing means making explicit and systematizing a particular perspective on something in order to be consistent in one’s perception and analysis. Hence, we could say that one of the functions of theory in research and science is to systematically perspectivize something. Phrased differently, theory provides a form of narrative in terms of which what we observe and experience makes a particular kind of sense. Not only does theory allow us to take and explicate a systematic perspective on something; it is also, Hanson suggests, decisive for what constitutes an observation. Arguing that there is a “linguistic” factor in seeing, he suggests: “Unless there were this linguistic element, nothing we ever observed could have relevance for our knowledge. We could not speak of significant observations: nothing seen would make sense” (p. 25). Something observed is discerned (or noted as significant) in the light of a particular perspective; the perspective provided by the theory (cf. the initial etymological clarification of theory) not only allows researchers to make sense of observations but is also critical to making observations (knowing what to pay attention to, what to observe). In Gestalt psychology (Katona, 1940; Köhler, 1947; Wertheimer, 1959) terms, we can thus say that theory constitutes a background against which things that are observed appear as figures of observation. I will return to the implications of this reasoning for different research approaches later in the book, when I discuss inductiveness and deductiveness. To summarize, an important point I have made here is that one of the functions served by theory in research is that it provides a systematic pattern (a form of narrative) for noticing and making sense of something. What a theory is can be further developed by saying that a theory consists of, and gains its systematic

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nature through, a number of concepts. These concepts, which collaboratively make up a theory, are defined in themselves and—and this is critical—in relation to each other. It is the explicit clarification of the relationship of a set of concepts, a relationship through which they gain their meaning, that makes up a theory. A concrete example of this is cultural-historical theory. This theory, founded on the pioneering work of Russian psychologists Lev Vygotsky and Alexandr Luria around the 1930s and later developed by other scholars, consists of such concepts as elementary and higher mental processes, the law of sociogenesis, cultural tools, mediation, appropriation, and the zone of proximal development (Daniels et al., 2007; Luria, 1976; Vygotsky, 1987, 1997, 1998). These concepts are defined in explicit relation to each other. What results from this relationship-building (synthesizing) work constitutes cultural-historical theory. Building on the insight of the “theory-laden” nature of scientific observation (Hanson, 1958/1981), it is important to realize that theory and observation of the empirical world cannot be considered entirely distinct. That is, if our observations in science are contingent on theoretical perspective, what we consider empirical data are already, in part, informed—or mediated—by our theory. What constitutes data is contingent on theory. From this follows that we cannot ask of a theory whether it is correct or not, comparing it with empirical data. This is because the empirical data are already informed by theory. There is also a relationship in the other direction: Theory in science has an empirical basis. Theory in science is no mere speculation; it is empirically grounded, even if theorization means abstracting from the particulars being empirically investigated. Rather than attempting to compare theory and empirical data in order to evaluate the potential correctness of a theory, we need to pose other kinds of questions to theory and empirical data. Instead, we can ask, and investigate, whether it is functional—in the sense of having explanatory value and power—to understand empirical phenomena in terms of a particular theory. We can ask whether we can say something of value, interest, and perhaps importance about the empirical phenomenon under investigation with a particular theory. Something that also needs to be kept in mind is that a theory is always a theory of something (learning, development—or the relationship between these—socialization, power, education…). It is therefore important to be cognizant in choosing theory so that, for instance, an interest in learning is not informed by a theory of socialization rather than a theory of learning. If there is a mismatch between the “of” of a theory (i.e., what it is a theory about) and what the study intends to investigate, there will be problems of translation and approximation that introduce additional problems (reasoning by analogy, for example, which constitutes a much looser and less systematic way of generating knowledge than when there is a well-aligned relationship between theory and the empirical phenomenon being investigated). That a theory is a theory of something also implies yet another aspect of the general argument of this book, that it is pivotal that the different parts of research are inherently related (and theoretically contingent): that theory “matches” the object of study—that is, that the theory employed is a theory of that which is studied. A fascinating historical elaboration on how philosophers began to expect a theory (or an “account”) to be empirically investigated, emerging in Greek Antiquity, can be

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found in Lloyd (1966/1992). As he clarifies, philosophers realized the importance of this principle well before they were able to actually do so, due to the nature of the questions asked (and theories proposed) and the possibilities to put them to the test. Also, as he shows, some of the core premises were not testable or, when they were, were still maintained in the light of contradictory empirical observations. At this time, science was not differentiated from other strands of knowledge building, such as philosophy (Lloyd, 1966/1992). Later, of course, science would be separated from philosophy, with the former studying empirical—and thus changing—phenomena, matters, and processes, and the latter investigating the allegedly eternal (e.g., “What is truth?”, “What is virtue?”—i.e., that which was supposedly unchanging, and therefore not following the rules of empirical study). Hence, early in Greek thinking we can see the emergence of several key principles, decisive features, of science: the centrality of critical scrutiny of knowledge claims and what this practice entails, including the requirement that theoretical claims have to be related to empirical investigation— simply speculating does not qualify as theorizing in a scientific sense—and that premises are also revisable in the light of empirical investigation. Lloyd’s historical elaboration also implies the importance of formulating researchable questions; that is, questions that are possible to answer in some sense through the knowledge-building practices of this tradition (to be discussed later in this chapter). Given the perspectivity of theory, a research student may ask whether this does not imply that it is valuable to perceive the phenomenon under investigation from more than one perspective; that is, from the perspectives of several theories. While this reasoning may appear sound, I will argue that it is important not to combine theories in an investigation. To make this argument, I will start with a visual metaphor: that of theory as a map. If we think of a theory as a map, this implies that it helps us get an overview of and thus orient ourselves in the world. Taking this image—a map (of say the Tokyo subway system)—as a metaphor for a theory, we can say that the stations are the concepts (defined in themselves) and the lines connecting them the explicit relationships between the concepts, together making up the theory. It is easy to see the value of such a map (theory): We would not be able to find our way in such a vast city (complex reality) without it. If we then imagine combining theories, or concepts from different theories, we get a different picture. Imagine that the representation in the form of a map of the Tokyo subway system is partly overlaid by other representations of (parts of) Tokyo, such as blueprints for buildings, stylistic drawings of the character of the city, photographs of street views with neon signs, a screenshot from Google Earth, and a historical map. Arguably, this map (theory) is no longer functional as knowledge; it does not, metaphorically speaking, provide an overview or allow us to orient ourselves in this space. The result is unsystematic. That is, it is unclear how the different parts relate to each other, how the relationships should be understood. It is hence important, I argue, that there be theoretical consistency within a study. There may still be a point in analyzing empirical data from other theoretical points of view as well, but such re-analyses are preferably conducted after completing the first study rather than mixing them in the same study.

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It is important to realize that combining theories in a study, in fact, does not yield a more complete—or even a complete—picture, as is often more or less explicitly claimed in so-called mixed-methods studies. In fact, there is no such thing as a complete picture. A picture is by definition partial and perspectival. Despite the inappropriateness of the “complete-picture” metaphor, the ideal it implies is worth discussing. The metaphor implies that capturing reality in all its complexity is not only achievable but also desirable. However, both ideas are mistaken. The world cannot be captured in all its complexity, and neither is this the ambition of science. The metaphor of theory as a map can function as a rhetorical tool in arguing this case. If we were able to map the world in all its complexity, we would have produced a copy of the world. But this copy would not serve us in getting an overview of and orienting ourselves in the world. We would consequently need yet another map to make sense of the first one. Hence, the “complete map” would be useless as knowledge. Scientific investigation always implies reduction. It is through reducing what we investigate that we can see something that is not visible to us in its ordinary complexity. Theories provide powerful means of reducing phenomena in ways that allow us to discern patterns that give us insight into the workings of and relationships between what we are interested in saying something about. Hence, reduction—or, metaphorically speaking, a picture (always incomplete)—is not a shortcoming to overcome but is rather necessary for investigation and explanatory value. It is thanks to having tools (theories) and practices (of method and analysis) that systematically reduce what is observed that research is able to say something insightful and powerful. The incompleteness is not a shortcoming. While all research is reductive, theories differ in how far they reduce what they study. For example, behaviorism (Skinner, 1958) reduces its object of study far more than cultural-historical theory (Fleer, 2014; Hedegaard, 2008), the latter having an analytical ambition to understand learning and development as contingent on the biological, social, and cultural, and, as part of this ambition, to understand individual action as related to institutional framing (Hedegaard et al., 2012; Olson, 2003; Wertsch, 1998). In nuancing the present discussion it should be recognized that, on occasion, conceptual resources (concepts and distinctions) from different theories can be used in the same study. Some theories can be subsumed under a particular tradition of theorizing (see Greeno et al., 1996, for an extensive elaboration on this idea). The theories from which concepts are related in a study need to have compatible units of analysis. One example of this would be theories implying activity as a unit of analysis, as distinct from theories implying units of analysis such as conceptions held or individuals’ expressions or thoughts or thinking (as analyzable without attending to their generation as responsive in and to an activity). Furthermore, when combining concepts and distinctions from different theories, the researcher should be able to clarify in text—explicate—why one theory does not suffice for investigating the matter in question, as well as what parts of the theories are related and how. Another important principle is that conceptualizations of the same phenomenon by different theories should not be combined. That is, to give an example, as different theories of learning will have different concepts of learning, if these concepts were combined

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it would result in an unclear and indistinct conceptualization of the investigated phenomenon. When insights from different theories are combined, the conceptualization should be of different—but related—matters; for instance, learning, teaching, agency, and identity formation (cf. above, on a theory being a theory of something). Clarifying how these matters are related would constitute theoretical advancement and thus an important contribution to research in a field such as ECEC. Hence, under certain conditions it is possible—and in some cases even desirable—to combine conceptual resources from different theories, but the researcher must know, and clarify to the reader, what he or she is doing and why this is necessary. Theories or concepts from different theories should not be combined in order to arrive at a “(more) complete picture”, as it were. A research study needs to be theoretically consistent, not only in the sense of being consistent with theory throughout the investigation but also with the different parts of the research being harmonious: theory, methodology, research questions, method, unit of analysis, representation of data, and the nature of claims (that is, about what and how claims are made). This should not be taken as an excuse to delimit the previous research one considers to studies from within the same theoretical tradition.1 Even research that takes a different theoretical point of departure needs to be reviewed and related to (while being attentive to and explicitly relating research results to the theory and method employed).

3.1 Triangulation It is common in studies in ECEC to conduct both observations and interviews, for example in order to see how preschool teachers speak about and act in relation to children’s play. It tends to be argued that that dual focus strengthens the study, with the same thing being studied in different ways, which is referred to as triangulation. However, there are severe problems with this reasoning. First, it implies what can be referred to as naïve realism; that is, the idea that what people say (in this case, in interviews) is simply a direct transfer or expression of what they think, and then, in the next step, that how they act (in the example, how they act in relation to children’s play) is a direct consequence and confirmation of this thinking. Hence, thinking, speaking, and acting with children are seen as standing in a simple one-to-one-toone correspondence. However, there are many explanations for why people may 1

It is quite common that references are misplaced. Something that has perhaps become more common, not only in popular-scientific texts but also in scientific fora, is to almost consistently place references at the end of sentences. This often leads to an unfortunate lack of clarity regarding where to locate claims, which in turn serves to hide one’s own contributions behind those of other researchers. For instance, “In this study I have shown how children change their participation in the practice of… when teachers do…” (Name, 2017, 2020). Writing in this way becomes confusing; the sentence starts by stating what the contribution of the present study is, but ends with references to other researchers’ work. Thus, it not only hides the contributions of the present study but also transfers the study’s findings to the work of other researchers.

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reason in one way in interviews and act in another way with children, as well as why the way people think cannot simply be equated with what they say (Schoultz et al., 2001; Vygotsky, 1987), which I will not delve into here. For the present discussion it is sufficient to realize that participating in, and responding to questions in, interviews and acting with children in preschool are fundamentally different practices, and there is no convincing theoretical reason why the two would cohere or one would merely mirror the other. For triangulation, this reasoning implies that what this term is often taken to indicate—in fact, contrary to what its proponents claim—means different ways of studying different things (e.g., how preschool teachers in interviews talk about activities with children and how they act in these activities, respectively) rather than different ways of studying the same thing. This has clear implications for conducting empirical research. Rather than pooling results from interviews and observations into one data set to answer one’s research question(s), it is important, I argue, to be clear about what one can (and cannot) make claims about based on what has actually been studied. That is, on the basis of conducting interviews with preschool teachers it is possible to make claims about how they reason or talk about a particular matter focused on in the interviews, whereas on the basis of making observations of preschool teachers engaging with children in play, it is possible to make claims about how they act in relation to children’s play. Claims about how they engage with children cannot be based on interview data, and claims about how they reason about this cannot be based on observational data involving their interaction with children. This means that if one wants to both conduct interviews with teachers and observe their actions with children, each data set, with its adjoining method, needs to have its own research question(s). One research question cannot meaningfully be addressed to both sets of data generated through interviewing and observing teachers. It could be interesting and valuable to study both, but in order to be distinct about the relationship between the how and what of the study they should not be conflated (see below).

3.2 Unit of Analysis and the Problem with Mixing Theories Something a researcher needs to be clear about is what unit of analysis (Säljö, 2009) is appropriate for the study. This concept denotes how the empirical data are delimited for analysis, in the sense of what is more specifically analyzed (see also Dohn, 2021). This unit of analysis is contingent on theory. As explained by Säljö (2009, p. 206), unit of analysis refers to “the choice of a conceptualization of a phenomenon that corresponds to a theoretical perspective”. We can illustrate the meaning of unit of analysis by exemplifying what it is in a few research approaches (theoretical traditions): If the research is theoretically informed by variation theory (Marton, 2015; Marton & Tsui, 2004), the unit of analysis is patterns of variation. If it is theoretically informed by cognitive psychology, answers to questions in interviews could be the unit of analysis (see the classic Piagetian studies for concrete examples; e.g., Piaget,

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1926/1951). If it is theoretically informed by cultural-historical theory (a sociocultural perspective), the unit of analysis would be tool-mediated activity (Säljö, 2009; cf. Wertsch, 1994).2 The concept of unit of analysis can also be understood as related to an important distinction in analyses of communication, that between term and concept: What in everyday discourse is called a word can be analytically differentiated into term (the word as such) and concept (its meaning). This distinction is imperative for understanding the relationships between different strands of research on what is allegedly the same thing, and for conducting analyses. To illustrate with a concrete example: learning. In educational science, psychology, and other fields of research, learning is a topic of investigation. However, while these may all contain research on learning, what is in fact referred to with this term are conceptually distinct matters. Consider the following examples: . . . .

Learning as discernment Learning as knowledge acquisition Learning as changed participation Learning as the appropriation of cultural tools and practices.

These concepts of learning, when placed in parallel, illuminate how studies taking one or the other theoretical perspective in fact do not study the same thing. Phrased differently, coherence on a terminological level does not equal coherence on a conceptual level. In the research literature on learning, for example, there is a common conflation or collapsing of the terminological and the conceptual levels of words. This is often evident in claims about different interpretations of concepts. Consider the following. If we imagine someone arguing that learning as changed participationmeans that the individual with increased independence can participate in a certain kind of practice while someone else argues that it means being able to relate in more differentially and contextually relevant ways to other participants in a certain kind of practice, then we can say that this is a difference in interpreting the same concept (the concept 2

Variation theory (Marton, 2015; Marton & Tsui, 2004) builds on the premises that (a) meaning springs from difference, not similarity; (b) learning can be conceptualized as increased differentiation and reintegration; and (c) in order to facilitate learners’ discernment of something, it has to vary (while other things are kept invariant). To give a classic example, if everything that exists were blue, people would not be able to discern blue (as blue only exists in contrast to other colors); nor would they have a concept of color (as this category presumes more than one color). In order for us to discern something as blue, there also has to be non-blue. Cognitive psychology actually exists in two major traditions, the European and the American. The European, which I allude to here, fundamentally builds on the major contributions of Jean Piaget (e.g., 1970) and has an interest in the development of cognition (while the American is the so-called information-processing tradition, in which models of human thinking, memory (e.g., Atkinson et al., 1996), etc. are built on the analogy of the information processor (the computer). Cultural-historical theory (Daniels et al., 2007; Luria, 1976; Vygotsky, 1987) (aka sociocultural theory) builds on the founding works of Lev Vygotsky and Alexandr Luria, and subsequent development, with a focus on human development as a process informed by biology, culture, and society. Central to this theory is how human inventions (cultural tools and artefacts) come to mediate people’s perception and thinking.

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being learning as changed participation). This is different from my previous example of learning, in which it was understood (conceptualized) as discernment, acquisition, changed participation, and appropriation of cultural tools and practices, respectively, which are not different interpretations of the same concept of learning but rather different concepts of learning. There is much confusion about this difference in educational literature; all too frequently, claims are made about different interpretations of a concept, when closer analysis in fact reveals that what are referred to are different concepts. This confusion arguably stems from an inability to distinguish between term and concept. Much analytical and theoretical clarity would result if researchers kept this distinction in mind.3

3.3 Theory and Research Questions I have already argued that it is important to be theoretically consistent in a study— both in the sense of not shifting theory during a study as well as being harmonious with the theory informing the study in other parts of it, such as methodology, method, form of empirical data, and analysis. Here, I will briefly point out yet another feature of this relationship between theory and other parts of a study: to speak with Hanson (1958/1981), the theory-laden nature of the research questions. My reasoning here also relates to what I previously discussed in terms of the importance of not considering theory and empirical data as independent of one another, with the correctness of theory being tested against empirical data. Instead, I argued that empirical data are already theoretically informed, whether implicitly or explicitly, and that theory in science has an empirical basis. These two lines of reasoning—the importance of theory throughout the parts of a study on the one hand, and the fact that the relationship between theory and empirical data is more complex than one simply being the test bench for the other—now intersect in the following manner. Different theories cannot in a simple way be tried against the same empirical data to determine which is the better theory. One reason for this, due to the theory-laden nature of research, is that different theories, even those that at least on a terminological level are theories on the same thing, largely pose different research questions. To illustrate this, consider the following authentic examples of research questions posed in studies informed by variation theory. One of them: 3

When defining terms conceptually, it is crucial not to include the term itself in the (alleged) definition. For example, do not write “Intersubjectivity is defined as how participants intersubjectively…” or “Learning in this study is defined as learning to…”. If the term to be conceptualized (theoretically specified)—in these examples “intersubjectivity” and “learning”—is included in the definition, the reasoning becomes entirely circular and no definition is provided. To define a concept means to explicate it in other terms.

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. What objects of learning are constituted within the snake-game activity? . What are the different learning possibilities of [the] part-whole relationship offered within the different enactments of the activity? (Ekdahl, 2021, p. 602). and the other: . What mathematical concepts can be explored and framed within the story [Goldilocks]? . What challenges for learning mathematical concepts does the story impose? (Palmér & Björklund, 2020, p. 250). Consider, as a contrast, these authentic examples from studies theoretically informed by a sociocultural perspective (cultural-historical theory). The first: (1) How do the children communicate and negotiate in and about the play activity (i.e. metacommunicate)? (2) How do they scaffold each other in their musical performances? (Lagerlöf, 2015, p. 304). and the second: How do children co-construct their developmental trajectories? How [do] significant others contribute to the co-construction of a child’s account of themselves? (Roncancio-Moreno & Branco, 2017, p. 38). Note also how the research questions are informed by their theoretical framing: Ekdahl (2021) uses “objects of learning” and Lagerlöf (2015) “scaffold” in one question each. A study informed by variation theory (Marton, 2015; Marton & Tsui, 2004) will typically ask what it means to know… or what is critical for developing an understanding of… A study informed by cultural-historical theory (aka a sociocultural perspective) will typically ask how do children become participants in… or how do children use new technology to… Note that I write “typically”. There are, of course, exceptions. Looking at research studies, it is certainly possible to find contrasting cases to the distinction I have illustrated here. For example, even a study informed by a sociocultural perspective may ask what questions, as illustrated in this example: (1) What activities develop when preschool children play Memory games in two versions: (i) as an analogue game and (ii) as a digital game? (2) How do the artefacts employed mediate and re-mediate these activities? (Nilsen et al., 2021, p. 233). However, here the “what” concerns the nature of evolving activity, which relates to the unit of analysis from this theoretical point of view (Säljö, 2009), as I have discussed, which is very different from what “what” refers to in studies taking a variation theory point of view. (Note also the use of the cultural-historically (sociocultural perspective) theoretical terms “mediate” and “re-mediate”.) As these examples illustrate, the nature of the research questions posed is different from different theoretical points of view. This fact also has implications for method and empirical data (see also Hedegaard, 2012).

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To summarize, when formulating research questions there are some things to consider. The first is that the questions have to be consistent with the theoretical tradition one is building upon, including its methodology. The second is that the questions posed, in some reasonable way, must be possible to answer through the procedures of research; that is, according to the criteria of this form of knowledge building. This means, among other things, that they cannot be too far-flung (cf. the historical note earlier in this chapter on the emergence of testing theoretical accounts, with reference to Lloyd, 1966/1992). The third is that the questions must be empirical in two senses: (a) they can be answered through analysis of empirical data and (b) they require empirical data to be answered. Research questions are often formulated in terms of “how can…” rather than “how is…”. The former does not require empirical data but can be answered through reasoning, whereas the latter requires empirical data to be answered. Another feature of research questions is what kind of studies they are posed in. I will elaborate on this in the next section.

3.4 Process Versus Product Studies An important distinction in research on learning and development is between “process” and “product” studies (Schär, 2021; Valsiner, 2005a; Vygotsky, 1987; Wallerstedt et al., 2014). Already in the 1930s, prominent developmental scientist Werner (1937) discussed the important difference between studying the phenomena of learning and development as processes rather than as achievements (e.g., as represented by scores on a test before and after, respectively, taking part in teaching or any other activity). Another prominent scholar who pointed out this important difference in research even earlier was Vygotsky. He wrote about process studies in terms of studying something historically: “To study something historically means to study it in the process of change” (Vygotsky, 1978, p. 46f., italics in original).4 And, as he elaborates, “To encompass in research the process of a given thing’s development in all its phases and changes […] fundamentally means to discover its nature, its essence, for ‘it is only in movement that a body shows what it is’” (Vygotsky, 1978, p. 65). In a similar vein, other prominent scholars have argued that many studies fail “to illuminate the dynamics of the teaching and learning processes” (Scribner & Cole, 1973, p. 555). Explicitly building on Werner, Valsiner (2005a) succinctly puts it thusly: “the received norms of how science is to proceed seem to eliminate the core of the phenomena–development–from consideration. The study of developmental processes is easily being replaced by investigation into outcomes of these processes” (p. 4). Furthermore, Valsiner (2005b) argues that Werner “pointed to the limitations of the reduction of psychology to the investigation of products, and called for the 4

Even though the reference here is to 1978, it should be recognized that this is a collated volume of separate texts that were written by Vygotsky in the 1930s. The particular text cited here is from 1931.

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primacy of the study of processes (in contrast to outcomes) as central for all psychology” (p. 394). Valsiner continues: “Without any doubt ‘outcomes’ (i.e. stable states of functioning) of the organism are visible, recordable, and analyzable ‘anchor points’ for the description of organisms’ development. Yet mere description of outcomes is in principle mute to their explanation” (p. 395). Against this background, and with an interest in learning and/or development (or related phenomena), we may ask whether we are studying conditions for and results of learning/development or how someone learns/develops (e.g., actualizing previous experience in making sense of novel observations). We can schematically illustrate this distinction with three figures (Figs. 3.1, 3.2 and 3.3). Figures 3.1, 3.2 and 3.3 schematically illustrate process versus product studies, and how they can be subsumed under one investigation. It may then appear that the combination (as illustrated in Fig. 3.3) is the preferable one. However, this need not

Fig. 3.1 A schematic illustration of two measuring points, before and after a lesson/an activity/a theme. On the basis of differences between the outcomes of these measurements, an inference about learning is made. However, learning has not been studied empirically. This illustrates a product study. It also denotes a study of differences in knowledge, but not of how these differences come about (i.e., learning)

Fig. 3.2 A schematic illustration of an activity (a lesson, a theme) followed from initiation to conclusion to see how participants learn (change their participation, appropriate cultural tools and practices, increasingly discern…), without measuring what knowledge they have before and after this activity. This indicates a process study, and exemplifies a study of learning

Fig. 3.3 A schematic illustration of a study in which an initial measuring point precedes the following of an activity (a lesson, theme), followed by another measuring point. This indicates a product and process study, and potentially encompasses learning and knowledge

3.5 The Contextual Nature of Studying Individuals’ Knowing or Abilities

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be the case. In fact, it is not unproblematic to synthesize the two sources of data (i.e., the measurement data and the observation data); the tests (measuring points) also co-constitute social practices with implications for the participants’ learning. The point is not that one or the other is better; rather, the design of a study has to be coordinated with what the study is intended to say something about (i.e., what the intended knowledge contributions are). These illustrations can serve as tools for thinking about the planning and carrying out (and evaluation) of a study: What method will be functional; what kind of empirical data will be necessary; what advantages and challenges does this kind of study pose? It is also important to realize that these two kinds of studies – Require different kinds of empirical data – Require different kinds of analyses. If we want to analyze processes (learning, development, sense making, communicating, reasoning, arguing, etc.)—or in Fleer’s (2014) words, “studying development in motion and not retroactively” (p. 7)—data allowing us to follow the continuous (over a period of time) change of the phenomenon under investigation become critical (rather than merely having different measuring points at certain intervals, e.g. before and after measurements or test data). Hence, process studies require audio or audio/video data. These data will then be analyzed as sequentially unfolding and responsive (inter)action. There are a number of analytical traditions for such analyses.

3.5 The Contextual Nature of Studying Individuals’ Knowing or Abilities For obvious reasons, in educational science and related fields of inquiry, clarifying what children, youth, and adults know and are able to do constitutes a research interest. This interest may, or may not, be related to their participation in some kind of teaching. With this research interest it may be worth keeping in mind that, arguably, every way of studying something—such as, in this example, someone’s knowing or abilities—is situated in, and contributes to constituting, a contextualization. The relationship between individual knowing and action on the one hand and settings or institutions on the other constitutes a classic question in research (Olson, 2003; Wertsch, 1998; Wertsch et al., 1995). The concept of context is often employed in such analyses and discussions (Chaiklin & Lave, 1996; van Oers, 1998). The problem with the concept of context is that it metaphorically constitutes the setting or institution as something that surrounds the individual and his or her processes. Hence, context is an example of the common container metaphor (Lakoff & Johnson, 1980). There are several problems with this metaphor when it comes to understanding the relationship between individual knowing and action, and the setting or institution it relates to. First, context as a container implies that it is already there beforehand. Second, context as a container is static. Third, container metaphors are difficult to use

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in making sense of change and dynamic features of actions. Consequently, change in regard to containers is typically conceptualized in terms of “influence”, as in a fluid running from one container to another (cf. Semino, 2008). A classic example of context as a container—in fact contexts as containers, each encompassing the former—is the ecological model by Bronfenbrenner (2005). Finally, fourth, if the context is a container influencing those in it, an implication is that all who are in it will be influenced in the same way. But we know through empirical research (as well as through everyday observation) that people respond differently to the same situation and activity; there is no such simple linear—or causal—relationship between a context (a container, a room) and people’s actions (reasoning, thinking). With these identified problems of explanation, rather than representing context as a container and defining it as “that which surrounds” (Cole, 1996, p. 132), we need to reconceptualize it if we are interested in being able to analyze dynamic and evolving phenomena such as learning, development, and interaction (Wertsch, 1998). Furthermore, conceptualizing the relationship between context and individual in terms of influence provides no explanation of how this comes about or what the mechanism of this process is. Simply stating that there is influence between context and individual, or between contexts, constitutes a case of black-boxing; that is, rather than explaining what needs to be explained, this is hidden from view for analysis through a label: influence. Furthering this reasoning, van Oers (1998) makes a useful distinction between context and contextualizing. Emphasizing the importance of the latter concept, he suggests that this allows us to precisely analyze the dynamic features of human action. Contextualizing is something someone does rather than, as in the case of context, something already there that somehow influences individuals. Building on van Oers’s (1998) distinction, I would argue that both concepts are often used in research in the social sciences. The concept of context—as a form of container—is often employed at the beginning of a study to describe the institutional setting where the study takes place. For example, the researcher may describe the preschool where the fieldwork was conducted (where it is located: in the countryside, in a city, how big it is, how many teachers work there, what indoor and outdoor areas it contains, etc.). But in the analysis, contextualizing may be used in order to analyze how participants make sense of what they encounter: how they establish relationships between the new and their previous experience (e.g., what they clarify that they see something as, similar to or different from, reminding them of, what perspective they take on it, etc.). Hence, from my understanding, in research studies both concepts— and these are different concepts (cf. my discussion above on the distinction between term and concept)—are often used, with context being employed as a narrative concept (describing the features of the setting that are considered relevant to one’s exploration) and with contextualizing being employed as an analytical concept (in order to make sense of the participants’ sense making). (There is another analytical strand implicit in my reasoning about context and contextualizing that I will make explicit and discuss later in this book, concerning reification and its ensuing problems in researching dynamic processes [see Chap. 6].)

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3.6 Communicative Framing Arguing that there is no neutral context for studying someone’s knowing or understanding is often conceptualized in terms of knowing, understanding, etc. being situated. At times, the notion of situated is taken as localizable; that is, as limited to a particular space. However, it makes more theoretical sense to conceptualize it as contingent on framing (Pramling, 2006b; Sommer et al., 2010) than on location. Instead of place, situated thus comes to be understood in terms of actions. Phrased differently, knowing or understanding is situated if it is contingent on communicative framing; that is, how participants initiate, and respond to, the activity in which someone’s knowing, understanding, etc. is studied. We can further elaborate on the issue of situatedness in the following way. In referring to the situated nature of phenomena, many studies use the notion of “in situ”. However, there are some inconsistencies in how this term is used. It is generally used in the phrase “in situ activities”. However, arguably, any activity is situated. Any activity is located physically, communicatively, imaginarily, or “digitally”. Hence, if one takes the notion of in situ to refer to the nature of the activity being studied, it becomes superfluous. However, it is more reasonable to understand in situ as denoting an analytical commitment—that is, referring to a particular analytical approach, whereby activities are analyzed as unfolding in real time through participants’ responsive actions, including how they indicate that they recognize the framing (or setting) of the activity (which may be an institution or a particular cultural practice). When writing about studying in situ activities rather than studying activities in situ, epistemology is conflated with ontology. This unfortunate process, I suggest, may be conceptualized as a form of (the neologism of) “ontologization”. That is, what is an analytical choice becomes displaced into the world as investigated. What I call ontologization implies a fallacy: from premising or imagining that we could think about so-and-so as if it were… (which could be very productive—for a general discussion, see Pramling et al., 2019—and this is in a sense what theorizing implies) (epistemology) to this is, in fact, how it is (i.e., making a reality claim, an ontological statement). Two examples of such a transformation of epistemology into ontology are post-humanist thinking and critical perspectives, in which the perspectivity inherent in one’s approach remains unrecognized (as evident in reasoning about exposing how it [allegedly] really is behind the “appearance” or “smokescreen”). (I will return to this later in this book; see Chap. 7.) Studying activities in situ is important to many research interests, but implying that some activities are in situ while others are not conflates epistemology with ontology. (This is thus yet another example of what I discuss throughout this book in terms of collapsing one’s perspective—theory—with the world as investigated; something I will conceptualize in the final chapter of the book in terms of pareidolia, which I will suggest can be exemplified by the fallacy of what I call ontologization or rather, as I will explain later, ontologizing.

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3.7 A Few Words on Ontology and Epistemology and the Constitutive Nature of Language Practices An important pair of concepts in the philosophy of science, briefly mentioned in the previous paragraph, are ontology and epistemology: Ontology [Oντ oλoγ ι´α] “study of being”, “from Greek on (genitive óntos [Ôντ oς]) being” ¯ and “-logía -logy” [λ´oγ oς + -´˘ια] Epistemology [Eπισ τ ημoλoγ ι´α] “study or theory of knowledge”, “from Greek episteme knowledge […] understand, know how to do from epi- over, near + hístasthai to stand” and “-logy” [™π ´ισ τ αμαι < ™π ´ι + †σ τ αμαι]. (Barnhart, 2004, pp. 728 and 337)

Ontology refers to how we premise the nature of something, while epistemology refers to how we understand how we can learn about (or—in research—study, investigate) that something. However, it need not be the case that we first consider ontology and then epistemology. Rather, in research we may come to realize that our practices of investigation (our methods) imply a particular epistemology and constitute what we study as being of a particular kind (ontology). (This reasoning is again a small reminder of the fact that research is not a linear process; rather, doing research is a reflective and thus, metaphorically speaking, more circular kind of process [cf. Fleer, 2014].) I will give some concrete examples here. The first example comes from the history of studying play. An important strand of research on play takes it departure in Gregory Bateson’s observations of animals playing at a zoo (Bateson, 1972/2000). A contribution of this work was a conceptualization of play as (meta)communication. Hence, constituting play in these terms results in a new ontology of play. It follows that epistemology needs to be reconsidered; if one understands play as communication (metacommunication), it needs to be studied in terms of communicative processes between play partners (this could also be done with single players; particularly young children typically speak aloud when playing by themselves and animating dolls, for example). Building on Bateson’s work, Garvey (1977/1990) studied the communicative practices of children playing together. She did this using what was then new technology for research, video observations, which were made through a one-way mirror. Hence, the researcher could see and hear the children communicating, but they could not see the researcher (and presumably had no awareness of being observed). This latter practice, which was common in psychological research, is today likely non-existent. However, the debate on whether or not such observation is ethical and how to value the important contributions historically generated in this way versus the ethics of observing and studying people without their knowing is a long-standing one, and will not be reiterated here. For the present purpose, it is sufficient to point out that this practice of doing research constitutes children as objects of research. However, with the emerging interest and concern in research for the child’s (or participant’s) perspective (which historically can be grounded in the formative work of developmental psychologist Jean Piaget, e.g. 1923/1926, 1926/1951; see also Hedegaard, 2012; Peters et al., 2020), it has

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become important to find ways to conduct research with children (as participants) that allow them to emerge as subjects rather than as objects. There is, for example, a discussion about “research on or for children” (Mauthner, 1997, p. 16, my italics) or research with children (Beazley et al., 2009; Einarsdóttir, 2007; Fleer & Ridgway, 2014). The first distinction concerns the status of children in research: Are they sources of information (about themselves, their lives, their perspectives or perceptions), or are they to (also) benefit from participating in research? What thus may be referred to as research on children is important— we simply need to know about many matters that are central to children’s lives, learning, and development in order to provide ample developmental conditions for their well-being, learning, and development. The question of research for children is less recognized and discussed. It is important to keep in mind that children and preschool teachers (and other research participants) are not resources for the researcher’s academic advancement. Rather, the researcher is in the service not only of the scientific community but also of children and preschool teachers, in the sense that the fruits of the researcher’s labor should facilitate children’s learning, development and well-being, as well as preschool teachers’ ability to support those processes. This imperative implies that, as researchers in ECEC, we have a responsibility to conduct empirically, theoretically, methodologically, and ethically sound research for the scientific community and for children and preschool teachers. Scientific knowledge building is a time-consuming process—writing an application for funding, getting access and permission, conducting fieldwork, doing analyses, writing up, and publishing generally take several years—and it is generally other children than those who participate in a study who will reap the sown seeds of the generated knowledge, when it is returned back to and comes to inform the work of educational institutions (e.g., preschool and schools) and preschool/teacher education programs. Despite this, however, in some cases already the children participating in a research study can be shown to have profited from their participation. A clear example of this can be found in Pramling’s studies (see Pramling, 1996, for a summary), in which the children participating in the groups with the teachers working from particular theoretically-informed principles developed their understanding of a number of features of their world as compared to children in the comparison groups. The latter, in a sense, did not participate in the study but merely served as comparison groups for studying children’s understanding. Also, simply being recognized by someone as having something of interest to say, and perhaps being asked new kinds of questions, potentially has a developing impact. Furthermore, as research in early childhood education (and education more generally, of course) is closely related to particular institutions (preschools and schools) and the education of teachers (teacher/preschool teacher education programs), it should be kept in mind that the research conducted should also be of value to the children and teachers at these educational institutions. In discussions about power inequalities between researchers and children, there tends to be an implicit ideal according to which the researcher and child (e.g. interviewer and interviewee) should be on equal standing. However, from a communicative theoretical point of view (Linell, 2014; Pramling & Säljö, 2015; Rommetveit,

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1974) there are always inequalities in human communication—people have different experiences, understand things in different ways, engage in different ways and to different degrees—and fundamentally, it is our differences (in knowing, experience, interest) that make us interesting to one another; without differences, we would simply have nothing to offer each other, nothing to talk about and learn from each other (Pramling, 2006a). Furthermore, from a communications theory perspective, the one who initiates a talk (e.g., an interview) by necessity communicatively frames the activity in certain terms (about what to talk about and how to talk), to which the other participant(s) by implicit communicative contract have to respond (align with, negotiate, or reject). Hence, already constituting the talk (its terms) of communicative necessity reconstitutes an inequality between participants. However, this in itself is not a problem but rather a precondition for knowledge building. Another example of the relationship between ontology and epistemology is communications research. Do we conceptualize communication as the transmission of information in a conduit (see Reddy, 1993, for an insightful critique of such a view), which has historically been prevalent, or do we conceptualize it as mutually constituted and coordinated action (Linell, 2014)? These constitute two different communicative ontologies (information transmission versus mutual sense making), and these ontological differences have implications for epistemology. Concretely, the unit of analysis (Säljö, 2009; see This chapter in this book) we use will differ. In the first case, we can document what the communicator (the sender) transmits and compare this with what the listener (the receiver) can reproduce. If we instead constitute communication as mutual sense making, we need to study how participants responsively make clear to each other and themselves what they mean by what they say, and how they perceive the responses from the other(s) participating in the mutual activity (see Pramling & Säljö, 2015).

3.8 Concluding Words Followed to its ultimate conclusion, the argument of this book and especially the extensive and multifaceted discussion herein on the importance and functions of theory in research is that with scientific knowledge, what we know is always contingent on how we know. What through research is revealed, as it were (as already hinted at, and to be discussed later in the book, I find this common metaphor problematic), is not the world as such (whatever that is) but how the world appears when reduced to and analyzed from a systematic perspective in the form of theory. There is no aperspectival knowledge. This argument implies the critical importance of researchers keeping alive a meta-perspective throughout their investigations and when communicating their results. Clarifying how the knowledge produced is contingent on how it was produced constitutes an important quality criterion in research, which is the topic I will discuss next.

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References Atkinson, R. L., Atkinson, R. C., Smith, E. E., Bem, D. J., & Nolen-Hoeksema, S. (1996). Hilgard’s introduction to psychology (12th ed.). Harcourt Brace. Barnhart, R. K. (Ed.). (2004). Chambers dictionary of etymology. Chambers. Bateson, G. (2000). Steps to an ecology of mind. University of Chicago Press. (Original work published 1972). Beazley, H., Bessell, S., Ennew, J., & Waterson, R. (2009). The right to be properly researched: Research with children in a messy, real world. Children’s Geographies, 7(4), 365–378. Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development. Sage. Bruner, J. S. (1990). Acts of meaning. Harvard University Press. Chaiklin, S., & Lave, J. (Eds.). (1996). Understanding practice: Perspectives on activity and context. Cambridge University Press. Cole, M. (1996). Cultural psychology: A once and future discipline. The Belknap Press. Daniels, H., Cole, M., & Wertsch, J. V. (Eds.). (2007). The Cambridge companion to Vygotsky. Cambridge University Press. Dohn, N. B. (2021). Units of analysis in learning research: Transparency, fit for purpose and purposeful fit. Learning, Culture and Social Interaction, 31, 1–5. https://doi.org/10.1016/j.lcsi. 2020.100426 Einarsdóttir, J. (2007). Research with children: Methodological and ethical challenges. European Early Childhood Education Research Journal, 15(2), 197–211. Ekdahl, A.-L. (2021). Different learning possibilities from the same activity—Swedish preschool teachers’ enactment of a number relation activity. Scandinavian Journal of Educational Research, 65(4), 601–614. https://doi.org/10.1080/00313831.2020.1739131 Fleer, M. (2014). A digital turn: Post-developmental methodologies for researching with young children. In M. Fleer & A. Ridgway (Eds.), Visual methodologies and digital tools for researching with young children (International perspectives on early childhood education and development, 10) (pp. 3–11). Springer. Fleer, M., & Ridgway, A. (Eds.). (2014). Visual methodologies and digital tools for researching with young children. Springer. Garvey, C. (1990). Play (enlarged edition). Harvard University Press. (Original work published 1977). Greeno, J. G., Collins, A. M., & Resnick, L. B. (1996). Cognition and learning. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 15–46). Macmillan. Hanson, N. R. (1981). Patterns of discovery: An inquiry into the conceptual foundations of science. Cambridge University Press. (Original work published 1958) Hedegaard, M. (2008). Developing a dialectic approach to researching children’s development. In M. Hedegaard, M. Fleer, J. Bang, & P. Hviid (Eds.), Studying children: A cultural-historical approach (pp. 30–45). Open University Press. Hedegaard, M. (2012). Analyzing children’s learning and development in everyday settings from a cultural-historical wholeness approach. Mind, Culture, and Activity, 19, 127–138. Hedegaard, M., Aronsson, K., Højholt, C., & Skjær Ulvik, O. (Eds.). (2012). Children, childhood, and everyday life: Children’s perspectives. Information Age. Katona, G. (1940). Organizing and memorizing: Studies in the psychology of learning and teaching. Columbia University Press. Köhler, W. (1947). Gestalt psychology. Liveright. Lagerlöf, P. (2015). Musical make-believe playing: Three preschoolers collaboratively initiating play ‘in-between.’ Early Years, 35(3), 303–316. Lakoff, G., & Johnson, M. (1980). Metaphors we live by. University of Chicago Press. Linell, P. (2014). Interactivities, intersubjectivities and language: On dialogism and phenomenology. Language and Dialogue, 4(2), 165–193.

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Lloyd, G. E. R. (1992). Polarity and analogy: Two types of argumentation in early Greek thought. Hackett. (Original work published 1966). Luria, A. R. (1976). Cognitive development: Its cultural and social foundations. (M. LopezMorillas & L. Solotaroff, Trans.). Harvard University Press. Marton, F., & Tsui, A. B. M. (Eds.). (2004). Classroom discourse and the space of learning. Lawrence Erlbaum. Marton, F. (2015). Necessary conditions of learning. Routledge. Mauthner, M. (1997). Methodological aspects of collecting data from children: Lessons from three research projects. Children & Society, 11, 16–28. Nilsen, M., Lundin, M., Wallerstedt, C., & Pramling, N. (2021). Evolving and re-mediated activities when preschool children play analogue and digital memory games. Early Years, 41(2–3), 232– 247. Olson, D. R. (2003). Psychological theory and educational reform: How school remakes mind and society. Cambridge University Press. Palmér, H., & Björklund, C. (2020). Framing mathematics teaching with narratives: The ambiguity of Goldilocks. In M. Carlsen, I. Erfjord, & P. S. Hundeland (Eds.), Mathematics education in the early years: Results from the POEM4 Conference, 2018 (pp. 249–262). Springer. Peters, M. A., White, E. J., Besley, T., Locke, K., Redder, B., Novak, R., Gibbons, A., O’Neill, J. Tesar, M., & Sturm, S. (2020). Video ethics in educational research involving children: Literature review and critical discussion. Educational Philosophy and Theory. https://doi.org/10.1080/001 31857.2020.1717920. Piaget, J. (1970). Piaget’s theory. In P. H. Mussen (Ed.), Carmichael’s manual of child psychology (3rd ed., Vol. 1, pp. 703–732). Wiley. Piaget, J. (1926). The language and thought of the child (M. Warden, Trans.). Harcourt, Brace. (Original work published 1923). Piaget, J. (1951). The child’s conception of the world (J. Tomlinson & A. Tomlinson, Trans.). Littlefield Adams. (Original work published 1926). Pramling, I. (1996). Understanding and empowering the child as a learner. In D. R. Olson & N. Torrance (Eds.), The handbook of education and human development: New models of learning, teaching and schooling (pp. 565–592). Blackwell. Pramling, N. (2006a). Minding metaphors: Using figurative language in learning to represent (Göteborg Studies in Educational Sciences, 238). Acta Universitatis Gothoburgensis. Open Access: http://hdl.handle.net/2077/16798. Pramling, N. (2006b). ‘The clouds are alive because they fly in the air as if they were birds’: A reanalysis of what children say and mean in clinical interviews in the work of Jean Piaget. European Journal of Psychology of Education, 21(4), 453–466. Pramling, N., & Säljö, R. (2015). The clinical interview: The child as a partner in conversations vs. the child as an object of research. In S. Robson & S. F. Quinn (Eds.), International handbook of young children’s thinking and understanding (pp. 87–95). Routledge. Pramling, N., Wallerstedt, C., Lagerlöf, P., Björklund, C., Kultti, A., Palmér, H., Magnusson, M., Thulin, S., Jonsson, A., & Pramling Samuelsson, I. (2019). Play-responsive teaching in early childhood education. Springer. Open Access: https://link.springer.com/book/10.1007%2F978-3030-15958-0. Reddy, M. J. (1993). The conduit metaphor: A case of frame conflict in our language about language. In A. Ortony (Ed.), Metaphor and thought (2nd ed., pp. 164–201). Cambridge University Press. Rommetveit, R. (1974). On message structure: A framework for the study of language and communication. Wiley. Roncancio-Moreno, M., & Bronco, A. U. (2017). Developmental trajectories of the self in children during the transition from preschool to elementary school. Learning, Culture and Social Interaction, 14, 38–50. Säljö, R. (2009). Learning, theories of learning, and units of analysis in research. Educational Psychologist, 44(3), 202–208.

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Schär, R. G. (2021). An argumentative analysis of the emergence of issues in adult-children discussions. John Benjamins. Schoultz, J., Säljö, R., & Wyndhamn, J. (2001). Heavenly talk: Discourse, artifacts, and children’s understanding of elementary astronomy. Human Development, 44, 103–118. Scribner, S., & Cole, M. (1973). Cognitive consequences of formal and informal education. Science, 182(4112), 553–559. Semino, E. (2008). Metaphor in discourse. Cambridge University Press. Skinner, B. F. (1958). Teaching machines. Science, 128(3330), 969–977. Sommer, D., Pramling Samuelsson, I., & Hundeide, K. (2010). Child perspectives and children’s perspectives in theory and practice (International perspectives on early childhood education and development, 2). Springer. Valsiner, J. (2005a). General introduction: Developmental science in the making: The role of Heinz Werner. In J. Valsiner (Ed.), Heinz Werner and developmental science (pp. 1–17). Kluwer Academic/Plenum. Valsiner, J. (2005b). General synthesis: Recurring agendas: Integration of developmental science. In J. Valsiner (Ed.), Heinz Werner and developmental science (pp. 391–424). Kluwer Academic/Plenum. van Oers, B. (1998). From context to contextualizing. Learning and Instruction, 8(6), 473–488. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes . In M. Cole, V. John-Steiner, S. Scribner & E. Souberman, (Eds.). Harvard University Press. Vygotsky, L. S. (1987). The collected works of L. S. Vygotsky, Volume 1: Problems of general psychology, including the volume. Thinking and speech (R. W. Rieber & A. S. Carton, Eds., N. Minick, Trans.). Plenum. Vygotsky, L. S. (1997). The collected works of L. S. Vygotsky, Volume 4: The history of the development of higher mental functions (M. J. Hall, Trans., R. W. Rieber, Ed.). Plenum Press. Vygotsky, L. S. (1998). The collected works of L. S. Vygotsky, Volume 5: Child psychology (R. W. Rieber, Ed.; M. J. Hall, Trans.). Plenum, M. J. Hall. Wallerstedt, C., Pramling, N., & Säljö, R. (2014). Learning to discern and account: The trajectory of a listening skill in an institutional setting. Psychology of Music, 42(3), 366–385. Werner, H. (1937). Process and achievement–A basic problem of education and developmental psychology. Harvard Educational Review, 7(3), 353–368. Wertheimer, M. (1959). Productive thinking (Enlarged ed.). Greenwood Press. Wertsch, J. V. (1994). The primacy of mediated action in sociocultural studies. Mind, Culture, and Activity, 1(4), 202–208. Wertsch, J. V. (1998). Mind as action. Oxford University Press. Wertsch, J. V. (2007). Mediation. In H. Daniels, M. Cole, & J. V. Wertsch (Eds.), The Cambridge companion to Vygotsky (pp. 178–192). Cambridge University Press. Wertsch, J. V., del Río, P., & Alvarez, A. (Eds.). (1995). Sociocultural studies of mind. Cambridge University Press.

Chapter 4

Quality Criteria

Abstract In this chapter, quality criteria for the kinds of studies predominantly conducted in the field of early childhood education are discussed. This kind of research is often referred to as qualitative, and thus as standing in contrast to quantitative research. The often conflated meanings of these terms are critically commented upon. Practices of quality assurance and the matter of ecological validity are exemplified and discussed. Further, the difference between inductive and deductive approaches is discussed, and it is argued that these constitute points on a continuum rather than dichotomous poles, as well as why all research could be conceived of as abductive. The contested nature of generalization in so-called qualitative studies is discussed, and is argued to be contingent on a simplification that is unproductive for thinking about matters concerning a study and its wider reach. An alternative perspective on this matter is presented.

The kind of research that dominates educational science (and related fields of inquiry such as child and youth studies) is often referred to as qualitative research. In this kind of research, there are particular quality criteria for scrutinizing and evaluating. However, before I discuss these, I will engage in a meta-discussion about the denomination of qualitative research. The term qualitative research is frequently conflated and confusing in references to it. It is commonly referred to as denoting an overarching approach to research, to method, to analysis, and to empirical data, respectively. These very different references are often interchanged in accounts. Such conflation—the lack of distinction—makes it unclear what qualitative actually refers to, and therefore also how it relates to its binary, quantitative. When using the terms qualitative and quantitative in research, we must be more mindful and explicitly distinct about what each denotes. Certain methods are typically referred to as qualitative. However, methods—such as interviews or video observations—are not, as such, qualitative (or quantitative). It is possible to represent what is captured through these (and other) methods as numerical data and/or descriptions or abstract categories (e.g., ways of understanding or a variation of responses). Hence, what is captured through a method can typically be analyzed quantitatively (numerically) and/or qualitatively (e.g., in term of participants’ sense making). It then becomes problematic to talk about qualitative and quantitative methods. The © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_4

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common conflation of what qualitative (or quantitative) refers to (approach, method, empirical data, analysis) is highlighted in what today is often advocated in terms of mixed-methods research. My reasoning does not imply that it is misplaced or without merit to conduct both quantitative (numerical) and qualitative (participant interaction and sense making) analysis in a study; in fact, there can be great value in doing so (Johnson & Mercer, 2019). The numerical analysis of data—for example, identifying all instances of a communicative phenomenon (e.g., a particular kind of question and the frequency with which it is directed at boys and girls, respectively)—and qualitative analysis (of the interaction between participants in classrooms in relation to instances of these questions and their answers and follow-up) would be worthwhile and make contributions that analyzing only one or the other would not. Hence, my argument is not that it is not valuable to analyze data both numerically and in terms of actions/sense making/participation but that there is much conceptual confusion in contemporary literature in educational research, particularly emphasized in socalled mixed-methods research. In order to make methodological advancements, researchers need to be more explicit and distinct in what they are referring to with terms such as qualitative and quantitative. After this excursion into the matter of the qualitative/quantitative discussion, we can now return to the issue of quality criteria, highlighted in the kind of research that is common in educational science and adjacent fields of inquiry. While in what has traditionally been referred to as quantitative research there is a well-developed set of concepts and procedures for assuring the quality of research—reliability, validity, and generalization, as these are understood in that tradition (e.g., Pedhazur & Pedhazur Schmelkin, 1991)—many researchers have argued that these concepts, defined as such, are not adequate for evaluating what is typically referred to as qualitative research (e.g., Barbour, 2014). I will not reproduce this long-standing discussion here; instead, I will more directly discuss how quality has been assured, and still is today, in this tradition of research. A practice that was prevalent in earlier educational science (as well as in psychology and other disciplines) involved was what was referred to as inter-rater reliability (Clark-Carter, 1997). This practice meant that a sample of a study’s preliminary results was independently coded by a peer. For example, if the results consisted of a set of categories representing the variety of ways of understanding a certain content of teaching, the respective categorizations of the researcher and a peer were compared to determine whether the categorization was robust; that is, whether another researcher would arrive at the same result (categorization) as the researcher. A percentage of correspondence was thus computed, resulting in an inter-rater reliability score. Typically, discrepant cases were then discussed between researcher and peer to determine whether, though clarification of the interpretive process, they could agree on how to categorize these examples. This practice—that is, conducting an inter-rater reliability measure—is less common today. The reason for this is not that the practice as such has fallen into disrepute, but rather that research in educational science tends to be reported and grounded in empirical data in different ways than was done a few decades ago. Whereas results were previously represented in terms of a set of categories (with frequency) and some brief example, today results

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are typically represented through excerpts from empirical data and adjacent analysis. This change relates to a developed prevalence of analyzing processes (e.g., interaction) rather than conceptions. While conception lends itself to be represented in terms of a set of categories, analyzing processes and actions requires representations that allow researchers to follow how participants respond to each other’s responses (cf. Chap. 3 on product vs. process studies). Therefore, the dominant way of representing results in educational science today is through providing excerpts from interactional data, followed by a closely adjacent analysis in which critical features and analytical claims are pointed out with reference to particular (parts of) utterances or other actions (in transcripts, generally represented sequentially on a turn-by-turn or line-by-line basis). The practice of presenting results by grounding analytical claims with reference to represented empirical data means that inter-rater reliability is no longer functional. Instead, by closely aligning analytical claims and represented empirical data, the researcher guides the reader through the analysis and thus through how the knowledge claims are grounded and motivated empirically (as analyzed from a particular theoretical perspective). This mode of representation not only allows the reader to see and evaluate how claims are grounded in empirical data, but also allows the researcher to re-interpret empirical data from other theoretical points of view, illuminating other features of the activities represented. Representing the empirical basis for one’s analysis and grounding one’s analytical claims with close reference to this data, I argue, constitute a democratization of the knowledge-building process. Anyone (with some degree of scientific training and theoretical understanding) can scrutinize the relationship between knowledge claims and its, theoretically informed, empirical basis. There is therefore great value in this practice. Whether research claims are valid is also, of course, critical in research typically referred to as qualitative (however problematic this label is, as I have discussed). In this kind of research, particularly one kind of validity is emphasized as relevant for evaluating the quality of a study: ecological validity. In the traditions I primarily discuss here—educational science and related fields of inquiry—the term ecological validity refers to the relationship between what and how something has been studied, on the one hand, and what claims and about what these claims are made on the other (cf. Chap. 3). To illustrate this concept, we can return to an example I have already discussed (in terms of triangulation, above). What is actually studied versus what one’s claims are made about is highlighted in discussions of triangulation and validity. According to common arguments in mixed-methods research, using what is presented as both qualitative and quantitative methods [sic!; see above] means giving a complete picture of something, and thus increasing a study’s validity. However, for example, interviewing teachers and observing them (with or without video) at work does not mean studying the same thing; there is a critical difference between studying how someone talks about something and how they carry out the activity referred to. Rather than combining these to give an allegedly complete picture, empirical data generated through one method could be used to answer one question and empirical data generated from a different method could be used to answer another question. Hence, using more than one method

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does not increase validity; rather, if data obtained from these different methods are combined or conflated, they blur what is actually studied and the validity is hence decreased. In fact, studies investigating this relationship—in the form of process–product studies (cf. my discussion about product versus process studies and their possible combination in Chap. 3)—“found that what teachers and students did in classrooms was often, if not always, quite different from what they (and others) believed they did. The evidence suggested that the difference between belief and reality depended on social expectations and on the teacher’s beliefs and awareness or sensitivity to what she/he was doing” (Nuthall, 2004, p. 284). These problems with talking about and reflecting on one’s own actions are emphasized when it comes to sensitive issues. For example, interviewing teachers about their interaction with boys and girls in the classroom (gender equity) may, and has been shown to, yield a picture that is highly contrary to the teachers’ beliefs (Nuthall, 2004). Other potentially sensitive issues could include ethnicity, language background (majority versus minority language speakers), and social class. Even something that may appear to be non-sensitive— such as how preschool teachers perceive teaching or play in preschool—may well be experienced as sensitive by participants due to their understanding of these terms and their professional role, causing social expectations to enter their reasoning, for example when interviewed about these matters. And a point here is that there is no way to determine beforehand, or generally for all classrooms, what all participants regard as sensitive or non-sensitive issues; therefore, social expectations cannot be ruled out in participants’ accounts of (reflections on, talking about) the practices they engage in. Thus, conclusions about the latter should not be drawn based on empirical data on the former. A classic example of what today would not be seen as ecologically valid is behavioristic research, in which animals (typically pigeons and rats) were observed in laboratories and based on which claims were made about human learning at large (Säljö, 2009). To increase ecological validity, it is critical to be mindful of the relationship between what is actually studied (and how) and what claims (and about what these claims) are made. If, for example, we want to say something about how teachers partake in play with children in preschool, we cannot study how they talk about this but must instead document and analyze activities in which they actually do play with the children. It is important not to take my reasoning about ecological validity and triangulation, respectively, as implying that interviewing is not a good research method in the educational sciences and related fields of inquiry. On the contrary, the interview is a valuable and functional method in these fields of research (and others). There is much to be learned, and much that we have collectively learned, through research based on interviews, the classic research conducted by Piaget (1923/1926, 1926/1951) being an obvious and clear case in point. My argument merely concerns the relationship between method and knowledge claims, and thus to what is referred to here as ecological validity.

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To summarize, the validity of the kind of research discussed here is increased by: • Making explicit how one’s knowledge claims are grounded in theoretically informed analysis of empirical data; • Showing the reader the validity of one’s knowledge claims by grounding them in the represented empirical data; and • Leading the reader through the analysis (on a turn-by-turn or line-by-line basis). These principles make it possible for the reader to critically evaluate the study’s validity and make alternative analyses, and therefore open up for scientific discussion grounded in empirical data. Phrased differently, it is important in a research study to clarify how, using these theoretical tools (concepts and distinctions), I analyzed these empirical data in this way, which led to this result, which is of interest, relevance, and perhaps importance to the understanding of so and so. This reasoning implies a general principle: Science is an argumentative set of practices.

4.1 Science as an Argumentative Set of Practices Saying that science is an argumentative set of practices, among other things, implies that empirical data do not speak for themselves. Rather, it is the task of the analyst to show that and how the empirical foundation for the study tells us something of relevance and value about what we want to know. “The point of a theory does not lie in its correspondence with the world”, Säljö (2009, p. 204) argues, “but rather in its explanatory power in relation to a set of issues”. Hence, rather than asking whether a knowledge claim is true, this reasoning also highlights asking questions such as why it is relevant, interesting, and perhaps important for us to know the answers to the questions asked. Hence, a result cannot simply be presented in terms of readymade categories or claims. A task for the analyst is to clarify and argumentatively convince the reader of the validity of one’s claims and of how they say something of relevance to the research field. How this argument appears is contingent on, among other things, the relationship between empirical data and theory in the analysis. This issue is discussed in the next section.

4.2 Inductive, Deductive, and Abductive Research A common distinction between research approaches is between inductive and deductive research. In an inductive study, categories are generated and emerge from the empirical data. In contrast, in a deductive study, empirical data are analyzed in terms of particular concepts that are determined beforehand; that is, empirical observations are sorted into preexisting categories (slots). It is easily realized that research cannot be either entirely inductive or entirely deductive. This is because, if a research study were entirely inductive, nothing that

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was observed would be discerned as significant (cf. Hanson, 1958/1981). What makes observations (results) significant is that they are presented against some degree of background knowledge (and contingent on a particular theoretical perspective). That is, it is only in relation to something that is already known that novel observations appear as more or less similar and different, and as more or less significant. What is significant is theory-laden; that is, taking a particular theoretical perspective, some things are relevant to pay attention to (become the figure of attention) while other features of activities or situations recede into the background (cf. Köhler, 1947; Wertheimer, 1959). In contrast, if a study were entirely deductive, we would learn nothing new qualitatively. Rather, only that which fits the gaps in the filter, metaphorically speaking, would be considered. (At times in such studies there is an additional category called “miscellaneous” or similar for those cases that do not fit into the preexisting categories; this turns the observations referred to as such into deviations, rather than parts of the results and reasons to reconsider the categorization [results] presented.) An entirely deductive approach implies making ourselves rationally blind to observing as significant that which does not readily align with our preconceptions. (It could be argued that one of the great strengths of science is that it encompasses practices and principles for allowing researchers to arrive at conclusions [results] that are counterintuitive.)

4.2.1 Points on a Continuum Rather than a Dichotomy In light of my reasoning in the previous section, it could be argued that all research is abductive. What is referred to here as abductive denotes a research approach that builds on certain premises, whether they are explicit or implicit, and is open to what does not fit, allowing for new discovery. However, research studies can be located further toward one or the other end of the continuum. Hence, even if we argue that all research by necessity is abductive, it can be more or less inductive or deductive. The latter are predominance rather than dichotomous poles. If we understand inductive and deductive approaches as points on a continuum, some examples at the one end (inductive) would be Conversation Analysis (CA) and Grounded Theory, while the other end (deductive) would comprise research sorting people’s expressions into preceding categories of, for example, social class, gender, and ethnicity. A meta-comment in relation to this discussion is that it implies that our knowledge contains an inherent tension: With an increased appropriation of cultural tools (knowledge), on the one hand we can see (in both the literal sense of ocular observation and the metaphorical sense of gaining insight—both senses subsumed and united in perception), and on the other hand risk becoming rationally blind to, what falls outside these tools (this knowledge). Hence, learning implies a simultaneous increase and decrease in our perceiving of things. However, through dialogue with others we are able to become aware of other ways of seeing (cf. Linell, 2014; Marková, 2003). We may also, through metacommunicating about our communication (sense making, perceiving), recognize our perspectivity and re-mediate our thinking and

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perceiving. Developing such meta-awareness, I argue, is therefore decisive for a researcher’s competence. It also testifies to the importance of engaging in scholarly debate with other researchers on how to understand issues of interest and importance. This reasoning thus also reminds us of the collective nature of scientific knowledge building and the importance of critique therein (cf. the initial list of criteria for such knowledge).

4.3 Generalization A common criticism raised against so-called qualitative research (however, regarding this label, see the discussion earlier in this chapter) is that it is not possible to generalize from such studies. I will argue here that this claim is mistaken, that it builds on a taken-for-granted notion of generalization, and that it is important to make distinctions that afford a more differentiated and relevant discussion of the relationship between the specific and the more general; that is, generalization. There are several reasons, I suggest, why the claim that it is not possible to generalize from “qualitative research” is faulty. One reason is a lack of realization that the very semiotic means of scientific knowledge building (as in everyday discourse) in themselves are generalizations. That is, on a fundamental level, language is generalization; so to use language is to generalize (Sapir, 1921; see also Vygotsky, 1987). To use a simple example from everyday discourse: If we want to describe a house we have observed, we may refer to it in terms of being yellow, two-story, wooden, or of having Victorian architecture, etc. These are all categories (color, material…); that is, generalizations. Hence, they are not specific to the particular house we have observed and want to describe. Paradoxically, it is through the addition of more such general terms (categories) that our description becomes increasingly specific. Hence, as this simple example illustrates, we cannot not generalize when using language (whether it is an everyday language or a scientific one). Recognizing that we cannot avoid generalizing, due to the nature of the semiotic means (the language) of scientific knowledge building, we must ask more qualified questions of research than whether it is possible to generalize from it. Rather, we need to ask how we generalize and what we generalize (i.e., how we master the relationship between what we study and what we make claims, or draw conclusions, about). A premise of this reasoning is that there are different forms of generalization, of which the commonly taken-for-granted form (empirical generalization) is but one.

4.3.1 Conceptual Generalization One form of generalization that is particularly important in the context of my recurring discussion of the theory-laden nature of research is conceptual generalization. While the semiotic means of our communication are generalized in nature, different

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languages differ in their generalization. For example, a theoretical language is more general than a local language (words specific to a particular setting, for example). In fact, one of the functions of theory is that it allows us to see empirical data— what we in some way observe—as instances of more general categories. Taking a theoretical perspective, we see something that is observed, in a systematic manner, as something (Hanson, 1958/1981; cf. Bruner, 1990; Luria, 1976; Wertsch, 2002). Conceptualizing observations (results) in theoretical terms allows them to communicate beyond the particular settings and activities where they were made. Phrased differently, conceptualizing observations in a theoretical language allows even other researchers to recognize novel observations in terms of such concepts. However, this should not be understood as being done in an instrumental way (as in an extreme case of deduction—see above—in which novel observations are reduced to what is already familiar). Using concepts in a more flexible way is important for allowing reconceptualization. This is done by keeping a meta-perspective in mind—or by setting the same principle in motion through engaging in scholarly debate, including having collaborative data sessions—and understanding concepts as analytical tools rather than as slots simply to be filled with additional examples. To give a concrete example of conceptual generalization from educational science: In research in classrooms, a particular communicative pattern of teacher–pupil interaction was observed (Cazden, 2001; Mehan, 1979; Pontefract & Hardman, 2005; Wells, 1999). These observations were conceptualized in terms of the sequence of Initiation–Response–Evaluation (or Follow-up), or IRE (IRF). This research was conducted in particular cultural contexts (context as a narrative term; cf. my previous discussion about context in Chap. 3) and in particular classrooms. However, by conceptualizing the observations in a language that was not specific to these contexts, researchers investigating classroom communication in other cultural contexts and classrooms could observe similar patterns. Eventually, it was shown that the identified communicative pattern is typical of communication in school in highly different cultural contexts. Hence, on the basis of conceptual generalization, empirical generalization could be done. With a conceptual (theoretical) language that made sense beyond particular contexts (settings, classrooms), novel observations could be related in order to clarify what is general to classroom communication as such and what may be specific to a particular cultural context. Hence, generalization needs to be understood in a dynamic relationship to specification. A theoretical language allows researchers to see what is significant, in terms of both what is similar to (or even identical to) previous observations (results) and what is dissimilar. Clarifying what these similarities (identities) and differences are, and how they can be explained, is central to theoretical elaboration. Mirroring parts of this reasoning, Nuthall (2004) argues: “Generalization across individual cases is the function and substance of theory building” (p. 297). However, I would qualify this claim somewhat—that is, reformulate it as: One of the functions of theory building is to generalize across individual cases or observations (for other functions of theory, see above). The question of generalization is also actualized when one considers the relationship between the pieces of empirical data represented and analyzed in a study (e.g., in the form of excerpts of communication) and the larger corpus of data. This will be discussed in the next section.

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4.4 Transcribing and Representing Empirical Data When representing empirical data for analysis in a research study—building on interactional/communicative data—it is rarely, if ever, possible to include the entire corpus. The primary forum for publishing research, an article in a research journal, requires authors to be brief, while still grounding their claims empirically. Hence, a thoughtful selection has to be made. How this is done implies different ways of understanding the generalizability of the claims made in the study. Therefore, in studies it is important to be mindful of and explicate selection criteria. In a commentary on this issue—that is, how to select from one’s larger corpus of data—Erickson (2006) argues that without making explicit the nature of this relationship, the points presented in a study, “although they may be of intrinsic interest and may even be dramatically compelling, could also be outliers, that is, cases that are exceptional in certain ways that the research report never makes clear” (p. 185). Therefore: The analyst’s task is not only to show what is happening in key instances, but to explain to the reader how and why those instances are of key importance analytically, that is, where those instances presented and discussed in detail fit into the overall patterns of variation that are found within an event as a whole, or across a number of examples of such events. Simple frequency tables are useful in showing these overall patterns of variation. The readers should be able to come away from an analysis not only “tree-wise” but also “forest-wise.” (p. 185)

This well-founded metaphorical distinction between “tree-wise” and “forest-wise” highlights the importance of the analyst making explicit the relationship between the analyzed excerpts and the larger corpus of data. It is important to realize that there are many different ways to constitute this relationship, including: • Contrastive analysis • Manifest content approach • Significant event (Erikson, 2006; see also Derry et al., 2010). What is referred to here as a contrastive analysis investigates every instance of something particular in the larger corpus; for example, how intertextual ties are established—that is, how references are made in regard to what was done earlier and what will be done later. What is called a manifest content approach denotes locating every instance in which a particular topic or feature of a topic is mentioned; for example, every time “democracy” is mentioned in a discussion. The significant event, finally, refers to something that has a discernable beginning and end, and the analysis focuses on the entire event from beginning to end. Another common strategy in data selection is to single out the most prevalent patterns for analysis. For example, if a particular kind of question from a teacher repeatedly results in the children asking for further clarification of what something means, such instances are taken as indicative of the general nature of the corpus (see Cohen et al., 2017, on internal generalization). However, it is also possible to do the opposite; that is, to single out from the corpus cases that are unusual. For example, if the dominant mode of interaction in an activity is that the teacher’s questions result in

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minimal responses (yes/no, mm), every instance that digresses from this pattern (i.e., in which the teacher’s question leads to more elaborate responses) may be singled out for analysis. In this case, the analyzed excerpts are not representative of the larger corpus of data in terms of showing the prevalent pattern of interaction. Rather, in this case, it is their contrast to the general pattern that makes them interesting to analyze in more detail. These are all legitimate ways of managing the relationship between the analyzed data (excerpts) in a study and the larger corpus of data, but they are different and the analyst needs to make explicit—clarify—(a) what relationship exists between these bodies of data and (b) what this relationship implies for questions of generalization (what is generalized and on what basis; cf. above). Implied in the reasoning above on clarifying the relationship between the entire data set and the excerpts that are represented and analyzed in the study (the forest and the trees, using Erickson’s metaphor) is the matter of explication. While explication is a key feature of scientific knowledge (cf. Chap. 1), when discussed in relation to transcripts and selection criteria, it is often referred to using the metaphor of “transparency”. I will therefore critically discuss this metaphor in the next section.

4.4.1 Transparency A common metaphor for reasoning about the quality of transcriptions is “transparency”. This metaphor aligns well with long-standing metaphors for knowing and learning in terms of vision. Some common examples are “I see your point” and “with insight” (see Rorty, 1979, for a classic critique of such metaphors; see also my discussion above on theory as a map). However, limiting ourselves here to the discussion of the quality of transcriptions in terms of their transparency, as it were, I argue that this is somewhat problematic. The reason I find the metaphor of transparency problematic in this context is that it hides the knowledge presumed (another visual metaphor!). That is, claims about transparency presume an implied reader. We may ask: Transparent to whom? For example, a Conversation Analysis (CA) transcription presumes a reader who is well versed in interpreting the transcription conventions employed. To other researchers, transcription signs such as **, + + , ––„„„, ∆, , >> –, ppp (Mondada, 2007), and $, and + » (Kimura et al., 2018) are not transparent. This reminds us of the important fact that a transcription has to be designed to do justice not only to the empirical data and allow the researcher to ground claims in order to answer his or her questions, but also to the intended audience(s): Whether we plan to publish in a journal within a particular specialized communicative tradition or in one devoted to a research field, such as early childhood education, for example, is important to what becomes a functional—or transparent, as it were—mode of transcription. As I have hinted at, the practice of conducting inter-rater reliability measures appears to have become somewhat of a thing of the past. It was previously common practice, but today is less so. Instead, in more contemporary work, evaluating a study’s

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quality is done differently. Today, one’s results are typically presented through an analysis closely adjacent to and minutely grounded in excerpts of empirical data. This generally takes the form of (a) a transcript, (b) a summary of what the analyst considers important actions and responses in the sequence represented by the excerpt, and (c) an analysis of the excerpt (cf. Bateman & Church, 2017; Derry et al., 2010; Johnson & Mercer, 2019; Jordan & Henderson, 1995; Mercer, 2004). Sometimes Steps b and c are merged rather than distinct. Regardless, the analysis is grounded in the excerpt, by referencing to where (which turn or line) it is possible to see what the analyst claims. In this way, the analysis is explicitly grounded in the empirical data. This allows the reader to see what the grounds are for presenting the results and making knowledge claims, and it becomes possible for him or her to scrutinize the analysis (and its ensuing knowledge claims) as well as re-analyze the excerpts from another theoretical point of view. While the former is critical to evaluating the quality of the scrutinized study, the latter does not result in an evaluation of the quality of the investigated study but rather a possible independent knowledge contribution. Something that is of particular importance here, I argue, is that this practice of guiding the reader through one’s analysis (and how one arrives at one’s claims and conclusions) means a democratization of evaluating research. Rather than being provided a number (percentage agreed upon) arrived at through a (re)categorization process to which readers have no access (inter-rater reliability measure), every (qualified) reader can check the validity of the study him- or herself. This practice, which has become standard today, implies the importance of representing one’s analysis rather than simply the results as such (without any information on how the researcher arrived at them). Arguably, this shift in practice for evaluating research is contingent on a shifting of research interests, from categories (of understanding, of perspectives)—which constitute kinds of products, to return to a previous discussion (see Chap. 3)—to how things emerge and evolve (sense making, reasoning, arguing)—to continue with this distinction, with the processes of learning, knowing, and teaching. This shift in research interest, I further argue, has co-emerged with the advent and development of technologies for capturing more fleeting matters of interaction (Pramling, 2006b) in the form of audio- and audio–video-recording devices. There are, of course, times when it is impossible or improper to document activities through video recordings (e.g., ethically sensitive situations; Peters et al., 2020). In such cases documenting through other means, such as field notes, is not only necessary but can also be considered a form of validity, which Fleer (2014) refers to as tool validity. This concept denotes the relationship between the research tool (e.g., the video camera) for documenting activities and the setting and topic of the study; that is, how the tool affords the capturing of the phenomenon in focus (cf. also my discussion concerning interviewing teachers about how they address boys and girls in the classroom). The transition from inter-rater reliability measures to representing empirical data and conducting the analysis closely adjacent to excerpts/transcripts, allowing the reader to see the process of going from data to claims, as described here, constitutes a new norm for quality assurance in research. This is what I will discuss more

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thoroughly in the next chapter. However, before engaging in this discussion I will address a terminological matter that actualizes methodology: the matter of how to understand the outcomes of empirical investigation.

4.5 Findings Versus Results How to refer to the outcomes of scientific investigation can be worth reflecting on. Basically, two terms are used: finding(s) and result(s). As these have different connotations, as part of the methodology one must be cognizant of these differences. A not uncommon observation by reviewers scrutinizing article manuscripts (i.e., peer review) is that the kinds of studies commonly conducted in the field of ECEC, and typically referred to as qualitative (however, see the critical discussion of this previously in this Chapter), do not report “results” but rather “findings”. Implied in this claim is the premise that, in order to have “results”, the outcomes need to be contingent on some manipulation by the researcher(s) or teacher(s). That is, the researcher (or preschool personnel) must carry out some kind of intervention for the outcome to be a result. Such an intervention could be in the form of action research (or similar approaches) or (quasi) experimental procedures. The results are then considered the outcomes of these procedures. In contrast, findings are seen as what emerges from a study without intervention; for example, when observing and video documenting ordinary activities. A conclusion from this, quite common, way of reasoning would then be to speak of findings rather than results in most ECEC studies, with the exception of those kinds of studies in which variables are manipulated (design research, action research, experimental studies). However, I argue that the matter of how to refer to the outcomes of research—in terms of findings or results—could be approached from a different point of view, leading to another conclusion. My contrasting argument goes like this. If “results” indicate that the outcomes are contingent on something done rather than merely something found (“findings”), then “results” are harmonious with a premise of the contemporary theory of science: that the knowledge produced through the research is contingent on our methodology (theoretical premises, method, and analytical procedures). The world does not simply present itself as knowledge. As I state elsewhere in this book, in research, what we know is contingent on how we know. From this alternative argument, “findings” imply that knowledge is already there and we stumble over it, so to speak; no particular procedures or perspectives are necessary. Such a naive view is also evident in the example of empirical work referred to as “data collection”. However, as I will argue later in this book, the world does not consist of data that we collect; rather, we transform the empirical world into data through the tools and practices of research (concepts, distinctions, perspectives, transcription practices). Thus, in conclusion, in opposition to the common reviewer comment that studies without manipulation do not have results but only findings, I would argue that “results” better align with a premise of scientific knowledge building—that is, that what researchers

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do contributes to what emerges, and that this implies clarifying how the knowledge contributions of one’s study are contingent on the theoretical premises and their implications for carrying out the study (i.e., methodology). Hence, I would argue that it makes more sense, from this point of view, to use “results” than “findings”. Be mindful that restating the premise of a study as if it is a result constitutes a fallacy. It is quite common to see studies starting from a particular premise—to give a concrete example, that human knowing is contingent on the appropriation of cultural tools, as argued in cultural-historical theory—and then in the results and discussion restating this premise as if it is a result or finding from one’s study. However, if a study is built on the premise that human knowing is contingent on the appropriation of cultural tools, the analysis has to clarify what tools these are in the learning of something (the content of learning, if you will) and how learners appropriate them. The research questions have to reflect the latter (in this example, the what and how) rather than the former (whether human learning is contingent on cultural tools, as this is a premise of the study). Similarly, if a study is built on the premise that children (or humans generally) learn through social interaction, the result cannot be that children (humans) learn through social interaction, but rather how they do this and what they learn from interacting with a particular partner or different kinds of partners (other children or teachers, for example). The premises of a study have clear implications for what research questions are relevant to ask, what to analyze, and what to present as results, but they should not be mistaken for one another. When discussing the matter of results it is important to make another distinction, I argue, between analysis and results. Today, the result sections of research articles often consist of transcripts followed by an analytical commentary (see e.g., Johnson & Mercer, 2019, and Wallerstedt et al., 2014, for examples with meta-discussions). There are great advantages to this mode of presentation. However, this practice of presenting results may paradoxically also make the results less distinct (and “distinct” is a criterion of scientific knowledge, as I argue in Chap. 1). My argument goes like this. Even if the result section of a study includes a thorough analysis, the question of what the study’s results are can never be answered through simple reference (“You have to read the results chapter”). Rather, results imply an abstraction from the concrete and minute analysis: a pattern that emerges through the analysis. The results are on a more principal level. A reader should not have to read the analysis to find out what the results of the study are; the results have to be abstracted (summarized as some kind of pattern) from the analysis. However, a reader would need access to the analysis in order to be able to evaluate—check the validity of –the knowledge claims put forth. It is important, I argue, not to confuse the analysis (however detailed it may be) through which the results emerge with the results as such. There is an important difference between empirically and analytically grounding your results and the results as such. In communicating research, the question of the results is generally decisive. At viva voce, at research conferences, or in interviews with journalists, what you have found—i.e., what the results of your study are—is what is most sought after. It is therefore important to take care to formulate the results distinctly. They should not be formulated in overly general terms, for example “The results show what children

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do to enter play”. Try instead to be more precise: for example, to continue with the previous example, “The results show that children enter ongoing play by doing (a)…, (b)…, (c)…, and (d)…”; or additionally, particularly if you have a research question addressing this issue, perhaps “Of these actions, (b) is the most productive in the sense that children more frequently gain access to play when they do this than when they do (a, c, or d)”; and then, as a further theorization of the result, “An explanation for this is…”. The problem with a more general phrase like “The results show what children do to gain access to play” is not only that it is not sufficiently specific, but also that it clarifies what the character of the result is rather than what the result is. Clarification of the results often begins with such a phrase, but it is important to also take the subsequent step and clarify what the results are (i.e., in this example, what the children do in order to achieve this). Phrased differently, it is crucial to also take the step from stating that the results say something about this to clarifying what they say about it. Research is distinct from developmental work and evaluation. In education science, particularly when conducting what is sometimes referred to as practice-near research—that is, researcher-school/preschool-personnel collaborative knowledgebuilding projects—questions about what distinguishes research from other partly adjacent activities, such as developmental work and evaluation, come to the fore. Here, I will merely point out some important features (for a more extensive discussion, see Cohen et al., 2017). Pointing something out, for example that more girls than boys read literature, does not constitute much of a knowledge contribution and would hence not be considered research but rather simply information. However, with theoretical elaboration (e.g., how this says something about… and has implications for…, etc.) it becomes an important contribution. Hence, from this point of view, institutes that gather and provide information do not conduct research (e.g., the Swedish Statistiska Centralbyrån [Statistics Sweden] (SCB) and similar institutes in other countries). Scientific knowledge building entails more than merely reporting information; it also requires making sense of (i.e., theoretically conceptualizing) it in relation to research question(s) and to collective knowing (previous research of relevance). When it comes to the distinction between developmental work and research, the former aims at arriving at some kind of solution to a problem, as perceived by participants (e.g., teachers) in a setting (a classroom, a preschool). Research is aimed at theorizing; that is, developing knowledge with a wider reach and of a more principled kind than what is specific to a particular setting. In order to have this wider reach, knowledge has to be formulated in less local terms, and must thus be formulated theoretically. The latter point thus, again, testifies to the fact that theory is crucial to science (and everything this entails, such as systematicity, explicitness, and perspective awareness). Pondering over the results of a study, an important distinction is that between showing something and creating new knowledge. That is, there may be a contribution to be made by showing something; for example, how principles that are known beforehand come to the fore in educational practices. However, this kind of contribution is a pedagogical one rather than a contribution to pedagogical

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(educational, etc.) research. The latter does not merely show or illustrate something previously known but contributes new knowledge. The elaboration on results (and findings) can also be related to the importance of consistency (cf. the systematic nature of research). A feature of this consistency involves the relationship between research questions and results. It is important that these be harmonious; that is, in commensurable terms. Simply put, if it is behavior that is addressed, results should be presented in terms of behavior(s); if it is conceptions held that are addressed, results should be presented in terms of conceptions; and if it is actions that are addressed, results should be presented in terms of actions. If there is a mismatch here, for example having questions addressing actions and then presenting results in terms of concepts held by participants, it becomes unclear how this relationship should be understood and why questions about concepts were not asked. Finally, below are some principles to follow when presenting the results of a study. Try to ensure that the presentation is: • Clear – What are the results (the answers to your questions)? • Convincingly grounded – Not merely claiming something but explicitly grounding it in the empirical data • In the right form – Coordinated with the form of the research questions and the unit of analysis that follow from the theoretical point of view taken • Concise – Even when presenting a multifaceted and insightful analysis, it is critical to be able to clarify relatively briefly what the (main) results are.

4.6 Summary In this chapter, I have discussed important quality criteria for the kind of research that dominates the field of ECEC. I have discussed ecological validity, matters of generalizability, and the relationship between theory and empirical investigation in relation to inductive, deductive, and abductive approaches. I have mapped a transition from inter-rater reliability to a contemporary dominance of a practice in which the researcher leads the reader through the analysis, and in which both analysis and results, closely adjacent to this, allow the reader to critically evaluate the knowledge claims. I have argued that this practice is contingent on a shift in dominant research interest into processes, and that it implies a democratization of evaluating the quality of research results.

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References Barbour, R. S. (2014). Quality in data analysis. In U. Flick (Ed.), The Sage handbook of qualitative data analysis (pp. 496–509). Sage. Bateman, A., & Church, A. (Eds.). (2017). Children’s knowledge-in-interaction: Studies in conversation analysis. Springer. Bruner, J. S. (1990). Acts of meaning. Harvard University Press. Cazden, C. B. (2001). Classroom discourse: The language of teaching and learning (2nd ed.). Heinemann. Clark-Carter, D. (1997). Doing quantitative psychological research: From design to report. Psychology Press. Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education. Routledge. Derry, S. J., Pea, R. D., Barron, B., Engle, R. A., Erickson, F., Goldman, R., Hall, R., Koschmann, T., Lemke, J. L., Sherin, M. G., & Sherin, B. L. (2010). Conducting video research in the learning sciences: Guidance on selection, analysis, technology, and ethics. Journal of the Learning Sciences, 19, 3–53. Erickson, F. (2006). Definition and analysis of data from videotape: Some research procedures and their rationales. In J. L. Green, G. Camilli, & P. B. Elmore (Eds.), Handbook of complementary methods in education research (pp. 177–191). Lawrence Erlbaum. Fleer, M. (2014). A digital turn: Post-developmental methodologies for researching with young children. In M. Fleer & A. Ridgway (Eds.), Visual methodologies and digital tools for researching with young children (International perspectives on early childhood education and development, 10) (pp. 3–11). Springer. Hanson, N. R. (1981). Patterns of discovery: An inquiry into the conceptual foundations of science. Cambridge University Press. (Original work published 1958). Johnson, M., & Mercer, N. (2019). Using sociocultural discourse analysis to analyse professional discourse. Learning, Culture and Social Interaction, 21, 267–277. Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. Journal of the Learning Sciences, 4(1), 39–103. Kimura, D., Malabarba, T., & Hall, J. K. (2018). Data collection considerations for classroom interaction research: A conversation analytic perspective. Classroom Discourse, 9(3), 185–204. Köhler, W. (1947). Gestalt psychology. Liveright. Linell, P. (2014). Interactivities, intersubjectivities and language: On dialogism and phenomenology. Language and Dialogue, 4(2), 165–193. Luria, A. R. (1976). Cognitive development: Its cultural and social foundations (M. LopezMorillas & L. Solotaroff, Trans.). Harvard University Press. Marková, I. (2003). Constitution of the self: Intersubjectivity and dialogicality. Culture & Psychology, 9(3), 249–259. Mehan, H. (1979). Learning lessons: The social organization of classroom instruction. Harvard University Press. Mercer, N. (2004). Sociocultural discourse analysis: Analysing classroom talk as a social mode of thinking. Journal of Applied Linguistics, 1(2), 137–168. Mondada, L. (2007). Multimodal resources for turn-taking: Pointing and the emergence of possible next speakers. Discourse Studies, 9(2), 194–225. Nuthall, G. (2004). Relating classroom teaching to student learning: A critical analysis of why research has failed to bridge the theory-practice gap. Harvard Educational Review, 74(3), 273– 306. Pedhazur, E. J., & Pedhazur Schmelkin, L. (1991). Measurement, design, and analysis: An integrated approach. Lawrence Erlbaum. Peters, M. A., White, E. J., Besley, T., Locke, K., Redder, B., Novak, R., Gibbons, A., O’Neill, J. Tesar, M., & Sturm, S. (2020). Video ethics in educational research involving children: Literature review and critical discussion. Educational Philosophy and Theory. https://doi.org/10.1080/001 31857.2020.1717920.

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Piaget, J. (1926). The language and thought of the child (M. Warden, Trans.). Harcourt, Brace. (Original work published 1923). Piaget, J. (1951). The child’s conception of the world (J. Tomlinson & A. Tomlinson, Trans.). Littlefield Adams. (Original work published 1926). Pontefract, C., & Hardman, F. (2005). The discourse of classroom interaction in Kenyan primary schools. Comparative Education, 41(1), 87–106. Pramling, N. (2006). ‘The clouds are alive because they fly in the air as if they were birds’: A reanalysis of what children say and mean in clinical interviews in the work of Jean Piaget. European Journal of Psychology of Education, 21(4), 453–466. Rorty, R. (1979). Philosophy and the mirror of nature. Princeton University Press. Säljö, R. (2009). Learning, theories of learning, and units of analysis in research. Educational Psychologist, 44(3), 202–208. Sapir, E. (1921). Language: An introduction to the study of speech. Harcourt, Brace. Vygotsky, L. S. (1987). The collected works of L. S. Vygotsky, Volume 1: Problems of general psychology, including the volume Thinking and Speech (R. W. Rieber & A. S. Carton, Eds., N. Minick, Trans.). Plenum. Wallerstedt, C., Pramling, N., & Säljö, R. (2014). Learning to discern and account: The trajectory of a listening skill in an institutional setting. Psychology of Music, 42(3), 366–385. Wells, G. (1999). Dialogic inquiry: Towards a sociocultural practice and theory of education. Cambridge University Press. Wertheimer, M. (1959). Productive thinking (Enlarged ed.). Greenwood Press. Wertsch, J. V. (2002). Voices of collective remembering. Cambridge University Press.

Chapter 5

Some Notes on Normativity and Research

Abstract In this chapter, the contested matter of normativity in research is investigated. Through a philosophical differentiation of normativity, how this matter relates to different parts of knowledge building and dissemination is discussed. Through this discussion, a more differentiated and informed discussion about normativity in research is initiated, beyond the unproductive simplifications according to which research can be divided into normative and non-normative, or the claim that all research is normative.

A quite common claim, by politicians and even other researchers, is that educational research is normative. This is particularly directed toward the kind of research in which researchers and teachers work together to generate new knowledge (e.g., design studies).1 This claim is always expressed in a way that suggests that it should not be the case. Hence, it is intended as a critical remark, in the everyday sense of the term. However, it is not criticism in the sense the term is employed in scientific debate, as it is merely a groundless claim, lacking basis in empirical observation and/or theoretical elaboration. Even though it is not well-grounded or -argued, however, this recurring claim indicates that there is something that needs to be discussed. Therefore, in this Chapter I will suggest tools (distinctions and conceptions) to use for thinking in order to be able to contribute to a differentiated, informed, and nuanced discussion about research and normativity. This is important for taking serious scholarly debate beyond such simplifications as research being distinguishable between normative and non-normative work (as in proper versus discreditable research) on the one hand and the claim that all research is normative on the other. To contribute to such an informed discussion of norms in research, I will distinguish between and discuss four types of norms: 1

As such opinions tend to be uttered rather than actually argued in writing, it is difficult to document them in scientific literature. However, researchers, particularly those working with practice-near approaches, are likely to have experienced this view.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_5

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(1) (2) (3) (4)

5 Some Notes on Normativity and Research

Norms for research Norms in research Norms in drawing conclusions from research Norms in the semiotic means of research.

5.1 A Philosophical Investigation of Norms When analyzing concepts, I often find it useful to start in the etymology—the history and transformation—of words (cf. Chap. 1 of this book). In the case of “norm”, it stems from the Latin “norma carpenter’s square, rule, pattern” (Barnhart, 2004, p. 709, italics in original). A carpenter’s square is a tool used as a straight-edge, for example when needing to establish right angles. Hence, in its original conception, norm refers to a tool for ensuring that things that are built do not tilt in an unwanted way. Thus, one way of understanding norm in this sense is to see it as a means of quality assurance, making sure a professional standard is upheld. Of course, when it comes to more abstract matters, such as what quality assurance is in research and education, there is much debate. Looking at a conceptual analysis in the form of a philosophical investigation of the term norm, another differentiation than the one I proposed above emerges. In this context, norm is explained as denoting a “collective coverage of different kinds of rules of action and valuation bases”, and it is noted that common to all definitions is that they provide “action guidance” (Lübcke, 1988, p. 396, my translation). The five kinds of norms identified are: (1) classification, (2) logical or methodological, (3) behavioral, (4) moral, and (5) aesthetic. The first kind, classification norms, refer to rules for how to make distinctions. Some examples could be the criteria for being allowed to use the Ecolabel or the Organic Label of the EU, or the Swan Ecolabel of the Nordic countries. This kind of norm also plays an important role in science; for instance, criteria for labelling an animal as a mammal, vertebrate, or bird. The second kind, logical or methodological norms, are important in research, “serving to guide knowledge building” (Lübcke, 1988, p. 396, my translation). An example of a logical norm is that “one cannot, based on the claim that a class of individuals possess a particular property, draw the conclusion that every member of this class has this property”, and an example of a “methodological norm is that when testing a hypothesis, it should be tested on those cases in which it is most likely that it will be falsified” (Lübcke, 1988, p. 396, my translation). A further distinction could be made here between constitutive and regulatory principles, the former “defining what knowledge is” and the latter “aids, rules of thumb, which make it more likely to reach knowledge” (Lübcke, 1988, p. 396, my translation). Thus, phrased in the terminology of theory of science, we can say that the former concerns ontology (the nature of scientific knowledge) whereas the latter concerns epistemology (how we build scientific knowledge). The third kind, behavioral norms, denote rules for proper behavior (e.g., as researchers we respond to criticism of our work by taking it seriously, attempting to clarify our understanding, and offering

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potential counterarguments, rather than disregarding or responding emotionally to it). The fourth kind, moral norms, denote what “are traditionally taken to be general rules of conduct” (Lübcke, 1988, p. 397, my translation). Finally, the fifth kind, aesthetic norms, denote “rules for when works of art and other human products are beautiful” (Lübcke, 1988, p. 397, my translation). This philosophical investigation can help clarify different kinds of norms, and which are of relevance to discussions about norms in research as well. I will now leave this investigation and more freely discuss how I perceive that norms come into play in research and how we can relate to these facts. The purpose of this elaboration is to offer tools of mind (distinctions, conceptions, reasoning, and examples) to facilitate a more nuanced, informed, and qualified discussion of this important topic, which I consider to be a critical feature of methodology.

5.1.1 Norms for Research This topic, I argue, relates to the three last norms (3–5) in the philosophical investigation rendered above. While these kinds of norms may not appear relevant to our present discussion, they can in fact come into play in research. For example, a behavioral norm could involve trying to respond to criticism and questions raised by other scholars in relation to one’s research (peer review, viva), as mentioned; a moral norm concerns adhering to established principles of research ethics rather than merely what is stated in law; and an aesthetic norm could entail reviewers evaluating whether one’s theoretical argument is elegant and stringent. Hence, these kinds of norms are all potentially relevant to different parts of research activities and are not something that could reasonably be argued to question the status of whatever research is being discussed and evaluated. Hence, scientific work—research—is infused with norms. In fact, appropriating such norms constitutes an important part of being socialized into scientific practices through a research education.

5.1.2 Norms in Research and Norms in Drawing Conclusions from Research To make and discuss the important distinction between norms in research and norms in drawing conclusions from research, I will briefly exemplify using two—related— cases: the contested nature of education and social and cultural sustainability. When researchers argue for the value of, for instance, an educational theory (e.g., Play-Responsive Early Childhood Education and Care, or PRECEC; Pramling et al., 2019),2 they draw conclusions from research. Such argumentation actualizes norms. 2

Play-Responsive Early Childhood Education and Care (PRECEC) (Pramling, 2022; Pramling et al., 2019; Wallerstedt et al., 2021) is a theory of how education – or rather the holistic ambition

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It would be naive to presume that all ECEC stakeholders would appreciate/embrace this, or any other educational theory, as guiding ECEC practices generally. On the contrary, to continue with this particular example, there are strong forces driving an instruction-based, preparation-for-school rationale, which is disharmonious with the theory of PRECEC. It should be noted here that, while PRECEC as a theory is not normative, arguing for how children would benefit from teachers working from this particular theoretical conceptualization is. Another example of arguing for the merits of certain educational practices based on research involves promoting children’s agency as an important means and outcome/goal of ECEC, giving them the ability to voice their concerns, intentions, and wishes (perspectives). Yet other examples would entail arguing for the importance of working toward the equality between the sexes and all people’s equal value. As these examples indicate, what is at play is what kind of citizens we want to develop/have and what kind of society/world we envision as desirable (whoever “we” are). These are inherently political (and thus normative) issues. Researching educational processes is one thing, but conceptualizing educational aims is another. The latter is inherently valued and political in premising particular views regarding ideal/good citizens and societies/world. When engaging in debates on what would be desirable outcomes of participating in ECEC, and when discussing issues of sustainability, we need to keep in mind that these are contested (normative) issues. In regard to PRECEC, here serving as an example, it is important to maintain a distinction between discussing it as a theory of ECEC on the one hand and arguing for the benefits of working in ECEC in a way informed by this theory on the other. The soundness of the former can be accepted even if various stakeholders may envision premising other approaches and aims of ECEC. This distinction is also important to make when it comes to sustainable development: There are certain facts that cannot reasonably be denied. However, the conclusions we as individuals, groups, societies, and the world draw from these facts are often highly contested and politicized (normative).

5.1.3 Norms in the Semiotic Means of Research On a fundamental level, we could argue that the semiotic means of our communication—particularly our language—are not neutral. Rather, language as such contains perspectives on the world (Vološinov, 1929/1986). There is a perspective, or a norm if you will, inherent in the very means of our communication. Sometimes these perspectives are rather evident. Consider, for example, “nurse” and “male nurse”; sometimes referred to as educare, the integration of education and care—in ECEC can be inclusive of and responsive to play, when it comes into play. The theory provides a system of concepts for analyzing joint activities and how responsivity to differences and play can be coordinated in a mutual activity that is co-constituted by participants and in which they can participate from different experiences and with different resources.

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the addition of “male” makes it evident that in its non-specified form, the expectation is that whoever is referred to in this way is female. However, many times, the perspectivity (and thus its cultural normativity) is invisible to those who master the language. Making it visible requires analysis or other consciousness-raising practices such as translation. Leaving this excursion, we can conclude that in a very general sense, language as the semiotic means of our communication, even in science, is embedded with perspectives. However, this level of analysis is not relevant to our current concerns. Hence, when we make the distinction between normativity and non-normativity above, this level of description/analysis is disregarded. Making this important distinction in educational research and in discussions and research on sustainability, which we have made above, implies taking the more fundamental level of language perspectivity out of consideration (temporarily bracketing it). What is critical is what distinctions are relevant to a particular discussion (and level of analysis), and that every discussion and knowledge-building practice (being able to state or claim something) presumes something (premises, points of departure—which as such are not under scrutiny at the same time (Wittgenstein, 1969), even if it may be important to do this at other times during knowledge building and critical evaluation).

5.2 The Politics of Representation Norms that are inherent in the semiotic means of research also come to the fore in the naming and categorizing of participants in research. How we label, and thereby categorize, research participants—whether they be teachers collaborating with researchers and/or the children or other participants studied—can be understood as a matter of what has been referred to as the politics of representation (Mehan, 1993). This concept denotes the perspectivizing that is inherent in our terminology. It is important, I argue, that we represent preschool personnel in terms of “preschool teachers”—which is the professional denomination (in Sweden as well as many other countries)—rather than the more common “practitioner”. The problem with the latter is that it lives in a tradition of argumentation (Billig, 1996) where it stands in contrast to “theoretician”. There are other problems with these denominations for preschool personnel and researchers, respectively, but here I will only point to one that is particularly problematic. In an elaboration on the relationship between research and development of educational practice, Alexandersson (2006) argues, “when the teaching profession is labeled as a practical profession, this ends up far down on a professional hierarchy. Teacher can then, as a profession, be held back—economically as well as when it comes to influence over the development of [preschool or] school” (p. 357, my translation). That is, in referring to preschool teachers as “practitioners”, we unintentionally contribute to suppressing the recognition of the profession of preschool teacher as having a voice (or voices) in public debate and in driving the development of early childhood education and, in fact, even its recognition as a profession per se. When conducting research with preschool personnel—as is done, for example, in the project that generated PRECEC (see above) and in other approaches—how we

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label these participants is critical to how others perceive this group (and everything that goes along with it, such as societal status and salary) and how members of this group perceive themselves and their possibilities to develop collective agency. If we are to support young children through quality ECEC, in research we need to recognize the professionals who give them responsive and responsible acknowledgement, challenges, and support. A premise of the reasoning here about the politics of representation is that language is constitutive; that is, it does not merely refer to the pre-existing but is part of shaping what is referred to in certain ways, from a perspective (Pramling & Pramling Samuelsson, 2018). Consider some other examples: for instance, “free play”, a common term in discussions about ECEC. It implies that other play is “not-free” and therefore, within a more general tradition of argumentation (see also Kultti & Pramling, 2020) emphasizing the value of freedom, that free play is preferable to other forms of play. However, if play is reconstituted in terms of play “without” and “with” adult support, things begin to take on a different value. Not receiving support is arguably fundamentally counter to ECEC. Another common set of metaphors for speaking about development (and how ECEC relates to it) concern what is allegedly “natural”. Saying that some form of development is natural implies that other forms of development are “unnatural”. However, another term for “unnatural” that often serves as the contrast or binary to “natural” is “cultural”; hence, theorists may argue that culture is fundamental to the nature of human development—or in Rogoff’s elegant phrasing, “the cultural nature of human development” (Rogoff, 2003)—and thereby reconstitutes development. Not only are perspectives inherent in how we label—refer to—things; these labels also tend to be part of more encompassing traditions of argumentation and have implications for how we relate to what we refer to. Hence, we constitute not only the referents but also our relationships to them through our language (Shotter, 1993). Furthermore, implications are problematic from the point of view of scientific knowledge building, as they typically go unreflected on by speakers and thereby risk reproducing labels (images) that discriminate against groups and individuals (see also Chap. 2 of this book on the importance of explication). Returning to the kind of norm referred to as classification (Lübcke, 1988), it is arguably decisive that researchers, collectively in scientific analysis and debate, attempt to explicate premises for research (e.g., what categories of participants/research subjects are included/excluded); this also relates to a methodological norm (Lübcke, 1988) in research: the premise that there are empirically available a-theoretical data (which I criticized in Chap. 3). This is discussed in another context by Säljö (2021), who argues: The idea that there are entities that qualify as “ ‘raw’ pre-theoretical data” in itself is a strong pre-theoretical assumption that has played a considerable role in research on learning and development. Everyday observations of what appears to be obvious differences between people have been incorporated into research activities and later validated and “theorized.” An illustrative, although highly disturbing, example of this can be found in differential psychology and in the emergence of intelligence testing in the early 20th century. Here categories such as idiot, imbecile, moron, dull, borderline, average and so on were used to

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describe people on the basis of their performance on tests (Kamphaus et al., 2018, p. 58). Highly specialized claims were made regarding what constitutes the differences between people classified in each of these categories, and through the authority of research, such categories for understanding people were sanctioned and used for public communication, decision-making and for allocating resources to education. For instance, imbeciles and idiots were “ineducable” (Daniel, 1997, p. 121), and therefore investments into education for these groups could not be defended. (p. 2)

There is a reflexivity between cultural conceptions and scientific theorizing. In order not to further disadvantage groups of people, researchers need to critically analyze the norms that are invisible, because they can appear to be self-evident and thus beyond questioning. Keeping such a meta-level of reasoning alive, as manifest in the critical scrutiny of premises (norms) of scientific investigation, is arguably decisive in research ethics.

5.3 Summary and Conclusions With the purpose of contributing to a feature of research methodology, in this conceptual analysis and discussion I have attempted to analyze norms in research in order to inform, nuance, and qualify collective reasoning. Clarifying, for example, communicative processes of teaching activities—that is, empirically identifying and conceptualizing how responsive actions have consequences for how activities proceed and how participants engage and change their participation and engagement in them—is not normative. However, arguing that a particular educational theory should ground educational practices is normative. Moreover, in a research field such as ECEC, it is in fact critical that researchers also contribute to the latter debate; but it is important to be clear when one is doing one or the other, and on what grounds one is doing it. When educational research is vaguely criticized as normative, this criticism disregards or does not recognize this distinction. Studying early education and care settings, such as kindergarten and preschools, means studying settings and practices infused with norms. These norms range from the overt and explicit (e.g., as stated in curricula and guidelines) to the implicit [e.g., the so-called hidden curriculum (Jackson, 1968; Tappan, 1998) and the ideology of the mundane (Shotter & Billig, 1998)]. However, studying normative institutions does not mean that the research is necessarily therefore normative. For example, a norm may be that play should be central to a particular ECEC system—but studying how play comes into play in this system is not, as a result, normative. It is possible to maintain an analytical stance. If we then, based on this research, draw the conclusion that play should be central to ECEC, a normative conclusion has been drawn (this does not indicate that it is an unwarranted claim). To restate: In a research field such as ECEC, it is arguably imperative that researchers also contribute to the latter discussion. ECEC personnel have the right to bear the fruits of research in this field, particularly as much research is funded by government agencies, through taxes.

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Even if we accept the premise that normativity, in different forms, is inherent in various parts of research, there are some forms of normativity that are contrary to a scientific approach. One form that is contrary to scientific investigation involves making claims about what participants should have done (or should not have done), rather than studying what they do and what this entails. Making claims about what participants should do (or should have done) is typified by the unfortunate problem generally referred to as “blame-the-teacher” accounts, which are problematic from both a scientific and an ethical perspective. “Blame-the-teacher” accounts entail claims about what the teacher should have done or should not have done, rather than what he or she did. These kinds of claims are problematic; not only from a scientifically analytical point of view in being based on what did not happen rather than what is empirically available, but also from a research ethics point of view. As researchers, we are dependent on the participation of teachers and children, and it is important to treat participants with respect. It is also crucial to remember that as researchers, we are in a very privileged position. We can look at activities from the outside, and using empirical data such as video recordings we can scrutinize activities repeatedly. Meanwhile, being a participant in an activity as it plays out, as teachers (and children) are, is an entirely different matter. As a participant in an activity, one does not have the privilege of taking a distant and reflective stance (see Erlandson, 2007, for an extensive elaboration on reflection and teaching action) but instead must respond in real time. Hence, as researchers we should be extremely careful not to value participants’ actions, especially in terms of what they did not do, should have done, or should not have done. Another form of normativity that is contrary to a scientific approach involves making claims about what entails good and bad quality preschool without clarifying how this distinction is made based on a theoretical point of view; or making claims about what entails good preschool by referring to the curriculum. Doing so means making claims about the nature of a preschool (its alleged quality) based on a normative document, and the resulting (underlying in the sense of implied, not explicated) reasoning can then be formulated thusly: Good quality preschool follows the curriculum. However, observing that work at a preschool relates to principles and goals as stated in the curriculum for preschool merely lets us know that the personnel do this part of their work. It says nothing—from a scientific point of view—about the quality of that preschool. In order for us to make scientifically legitimate claims about the quality of a preschool a systematic and explicated theoretical perspective needs to ground the analysis, so that it becomes clear how these claims are theoretically substantiated. For the integrity of scientific analysis, normative documents, such as the curriculum for preschool, need to be kept distinct from empirically grounded work on the nature of pedagogy and care in ECEC settings. Grounding claims about the quality of a preschool in the curriculum results in an evaluation rather than a research study.3 3

Closely aligned with, or rather part of, this point, which can be further explicated, is that a form of normativity that is problematic to research involves referring to normative documents (i.e., curricula, guidelines, and other political texts about what should be done and how) as if they are

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Research is infused with norms of various kinds, coming into play at different points of knowledge building. For a more nuanced and informed discussion of this, researchers need to be aware and make evident (explicit) when they engage with norms in one way or another—and on what basis—and when, despite studying normative institutions and practices, they maintain the analytical stance that is necessary for the integrity of scientific knowledge building. This is decisive for research (analytical integrity) and for research ethics.

5.3.1 Bad Research Is Unethical As there is an abundance of literature on the ethical considerations involved in conducting research with children, I will not reproduce these discussions here. Instead, as I have mentioned, I will limit my present discussion of research ethics to two features that are not commonly part of such discussions. One is what can be referred to as the politics of representation (Mehan, 1993; see this Sect. 5.2), and the other is what I will briefly point to here: the relationship between poorly conducted research and ethics. This relationship is mentioned in the document God forskningssed [Good research practice], published by the Swedish Research Council (Swe. Vetenskapsrådet) in 2017: A research report demonstrates bad research ethics when it has scientific deficiencies in regard to the precision of the research questions, uses erroneous methods or established methods incorrectly, systematically excludes observations that are not in line with the author’s thesis, handles non-response in a statistically unacceptable manner, or uses a design for the study that does not make it possible to answer the question. People’s time has been used in vain, and they may have been exposed to a certain degree of inconvenience, sometimes even suffering. Regardless, resources that could have been put to better use have been wasted. It is also not difficult to find examples that, through shallow correlations between ethnicity, crime, intelligence, education, etc., have led to the discrimination and stigmatization of individuals and groups. (Swedish Research Council, 2017, p. 16, my translation)

Hence, conducting bad research—that is, research that does not adhere to the quality criteria of this tradition of knowledge building (see Chap. 4 of this book)—is also ethically problematic. This means that the logic of a study has to be carefully considered: Is there coherence between theory (theoretical premises), method of data generation, analysis, and the kinds of claims made? Thus, this entails additional importance to the scientific quality. This general point of the relationship between a study’s quality and its research ethics could also be discussed, among other things, in terms of the relationship between the study and a research field (or, potentially, research fields).

subsumed under research literature. These kinds of documents (published by government agencies, for example) do not have standing as scientific texts. There could certainly be reasons why it would be relevant to also refer to these kinds of documents in a research study, but explicit recognition of their status and the fact that they are distinct from research literature is imperative for the integrity of the research. Knowledge claims in research based on literature are restricted to scientific literature.

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Not only is it important to recognize previous studies of relevance to one’s investigation (cf. the maxim of researchers standing on the shoulders of giants)—arguably, it also implies the importance of critique in yet another way than is discussed in Chap. 2 of this book: Research that is potentially relevant to one’s investigation but is of poor quality should be critically scrutinized in order not to offer an unsound basis for further research. Referring to and thus by implication acknowledging previous studies that are of poor quality without clarifying these faults is in a sense unethical, as this research will then inform—and be carried forward through—subsequent research. Any such referral, of course, should not be done lightheartedly or with bad intentions but in a qualified and informed manner in the nature of collective knowledge building. (In the nature of scientific debate and knowledge building, the researchers whose work is criticized should, of course, be allowed to respond to this in subsequent issues of the journal in which the criticism is published.) A recurrent topic of this chapter has been the perspectivity of language and its implications, for instance, for research ethics. In the next chapter, I will deepen the discussion of the language practices of research.

References Alexandersson, M. (2006). Praxisnära forskning och läraryrkets vetenskapliga bas. In B. Sandin & R. Säljö (Eds.), Utbildningsvetenskap—ett kunskapsområde under formering (Educational science: A domain of knowing in formation) (pp. 355–376). Carlssons. Barnhart, R. K. (Ed.). (2004). Chambers dictionary of etymology. Chambers. Billig, M. (1996). Arguing and thinking: A rhetorical approach to social psychology (2nd ed.). Cambridge University Press. Daniel, D. M. (1997). The ineducable children of Leeds: The operation of the defective children and mental deficiency legislation in Leeds, 1900–29. Journal of Education Administration and History, 29, 121–141. Erlandson, P. (2007). Docile bodies and imaginary minds: On Schön’s Reflection-in-action (Göteborg Studies in Educational Sciences, 257). Acta Universitatis Gothoburgensis. Jackson, P. W. (1968). Life in classrooms. Holt, Rinehart, and Winston. Kamphaus, R. W., Winsor, A. P., Rowe, R. W., & Kim, S. K. (2018). A history of intelligence test interpretation. In D. Flanagan & E. M. McDonough (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (4th ed., pp. 56–70). Guildford Press. Kultti, A., & Pramling, N. (2020). Traditions of argumentation in teachers’ responses to multilingualism in early childhood education. International Journal of Early Childhood, 52, 267–280. Lübcke, P. (Ed.). (1988). Filosofilexikonet (Lexicon of philosophy). Forum. Mehan, H. (1993). Beneath the skin and between the ears: A case study in the politics of representation. In S. Chaiklin & J. Lave (Eds.), Understanding practice: Perspectives on activity and context (pp. 241–268). Cambridge University Press. Pramling, N., & Pramling Samuelsson, I. (2018). Pedagogies in early childhood education. In M. Fleer & B. van Oers (Eds.), International handbook on early childhood education (pp. 1311– 1322). Springer. Pramling, N., Wallerstedt, C., Lagerlöf, P., Björklund, C., Kultti, A., Palmér, H., Magnusson, M., Thulin, S., Jonsson, A., & Pramling Samuelsson, I. (2019). Play-responsive teaching in early

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childhood education. Springer. Open Access: https://link.springer.com/book/10.1007%2F978-3030-15958-0 Pramling, N. (2022). Educating early childhood education teachers for play-responsive early childhood education and care (PRECEC). In E. Loizou & J. Trawick-Smith (Eds.), Teacher education and play pedagogy: International perspectives (pp. 67–81). Routledge. Rogoff, B. (2003). The cultural nature of human development. Oxford University Press. Säljö, R. (2021). The challenges of capturing learning: Units of analysis in the study of human growth. Learning, Culture and Social Interaction, 31, 1–5. https://doi.org/10.1016/j.lcsi.2020. 100428 Shotter, J. (1993). Conversational realities: Constructing life through language. Sage. Shotter, J., & Billig, M. (1998). A Bakhtinian psychology: From out of the heads of individuals and into the dialogues between them. In M. Mayerfield Bell & M. Gardiner (Eds.), Bakhtin and the human sciences: No last words (pp. 13–29). Sage. Swedish Research Council. (2017). God forskningssed (Good research practice). Vetenskapsrådet. Tappan, M. B. (1998). Sociocultural psychology and caring pedagogy: Exploring Vygotsky’s “Hidden curriculum.” Educational Psychologist, 33(1), 23–33. Vološinov, V. N. (1986). Marxism and the philosophy of language (L. Matejka & I. R. Titunik, Trans.). Harvard University Press. (Original work published 1929). Wallerstedt, C., Pramling, N., & Lagerlöf, P. (2021). Triggering in play: Opening up dimensions of imagination in adult-child play. Learning, Culture and Social Interaction. https://doi.org/10. 1016/j.lcsi.2021.100497. Wittgenstein, L. (1969). On certainty/Über Gewissheit (G. E. M. Anscombe & G. H. von Wright, Eds.). Blackwell.

Chapter 6

Scientific Language Practices

Abstract In this chapter, important language practices of science are discussed. A common but problematic feature of scientific language practices is nominalization (i.e., turning verbs into nouns), and its ensuing reification (turning the processes of learning, development, etc. into things) is particularly discussed and exemplified. The metaphorical nature of scientific language and why it is important to take a meta-perspective on this are also elaborated on.

6.1 Being Linguistically Responsive to the Dynamic Nature of the Phenomena and Processes of Educational Research Terminology in research is important for several reasons, including conceptual clarity, consistency of perspective (which is one aspect of being systematic), and ethics (on the last of these, see the discussion in Chap. 5 on the politics of representation). Scientific language is conceptual, which means that terms are theoretically specified. This theoretical specification (definition) implies that there will likely be several concepts for the same term, particularly if it is central to a field of investigation. In educational research such terms include learning, development, agency, and communication, as well as many others. Against the background of this realization, terms have to be conceptualized—or, phrased differently, theoretically situated. Another implication is that one has to be mindful of the perspective taken by the researchers whose work one builds upon, as they may use the same terms but—explicitly or implicitly—understand them from a different perspective from that taken in one’s own study. Therefore, when reviewing previous research, it is important to clarify not only what was studied, how this was done (method), and what the results were, but also the theoretical framing within which the research was conducted.1 1

When referring to previous research, it is important to avoid pooling references. This can be observed quite frequently, but is more common among some established researchers than PhD students (dissertations) as it presumes having a number of publications. Still, it is something one should learn to be mindful of already as a PhD student. An example is: “… is high preschool quality

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_6

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A particular terminological matter comes to the fore in conducting research on the phenomena and processes of educational and developmental science, such as learning, development, reasoning, thinking, arguing, and making sense. These are all central concerns in these fields of investigation, and are all processes. However, there is a long-standing and arguably dominant strand of research in these fields that transforms these (and other) processes into things (objects). This transformation is generally referred to as reification. Through a process of reification—which typically involves replacing verbs with nouns (Billig, 2008; Pramling, 2011), a process referred to as nominalization (Halliday & Martin, 1993)—things that are by nature dynamic, fleeting, and changing are reduced to static objects, localizable and delimited in space and time. Writing in the developmental research tradition of psychology, in a classic introduction to this field of study, Woodworth (1940) notes: Instead of “memory” we should properly say “remembering” or “O remembers”; instead of “sensation” we should say “seeing”, “hearing”, etc.; and instead of “emotion” we should say some one feels eager or angry or afraid. But, like other sciences, psychology finds it convenient to transform its verbs into nouns. Then what happens? We forget that our nouns are merely substitutes for verbs, and start hunting for the things denoted by the nouns – for substances, forces, faculties – but no such things exist; there is only the individual engaged in these different activities. Intelligence, consciousness, the “unconscious” belong with such terms as skill and speed. They are properly adverbs, the facts being that the individual acts intelligently, consciously, or unconsciously, skillfully, speedily. A safe rule, on encountering any abstract psychological noun, is to make it concrete by changing it into the corresponding verb or adverb. Much difficulty and unnecessary controversy can thus be avoided. (p. 18f., italics in original)

Recognizing the important difference in how we constitute our research objects (the very term “research object” is, of course, an example of reification), as something done or as something had (or not had, or had to a degree), has implications for how we conduct research and what images of people’s abilities ensue (Pramling, 2011) and, in the next turn, important implications for education and pedagogy (Pramling, 2006a). The are several problems with reification—due to nominalization (i.e., transforming verbs into nouns) or taking metaphors literally—in the context of scientific knowledge building in educational and developmental science. Constituting the phenomena of these research fields as objects means (Name, 2001, 2011, 2007, 2009, 2014, 2018)”. Writing in this way makes it unclear to the reader how the references are to be read. That is, one is left in the dark as to what the relationships between all these references are and why they are all needed: Do they all show the same thing—and if so, we may ask why we need more than one?; Do they show differences—a development—and if so, what differences/development? Furthermore, noting that the references range from research articles to conference proceedings to departmental reports, we may ask why it is not simply the “finished” text—the research article—that is referred to and what unique/additional contributions the other texts give. It could be argued that this kind of referencing practice—typically consisting of self-referencing—is not only opaque, and thus contrary to scientific writing practice (which should be distinct), but that it is also a form of promoting oneself rather than grounding and clarifying ideas/theory (see Roth & Cole, 2010, for an elaborate critical discussion of this kind of referencing practice; see also Matusov, 2011, for a contribution to this debate on referencing practices).

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. Transforming dynamic potentials into fixed entities, . Overgeneralizing potentially historically contingent descriptions of human nature, and . Being “misled” by language (Wittgenstein, 1953, §§ 94, 356) to put great effort and resources into trying to answer what may be futile research questions (Pramling, 2006a). To elaborate somewhat, transforming dynamic potentials into fixed entities (see also Säljö, 2002) is problematic because dynamic potentials (e.g., learning and development) are precisely the phenomena at the heart of these research fields. Overgeneralizing potentially historically contingent descriptions of human nature involves being rationally blind to how the phenomena being researched develop not only within individuals but also sociohistorically. Being misled by language, as it were—for example by taking metaphors literally—can result in entire research endeavors that can be argued to be futile. Some historical examples of this, I have argued elsewhere (Pramling, 2011), are research into what kind of computer man is (Hunt, 1971), building on the human-is-a-computer metaphor, and how big a chunk (Miller, 1956) is (Simon, 1974), the latter building on a verb being taken as a noun denoting some kind of object rather than an activity of sense making (Pramling, 2011). Reification is common in scientific language; it is, so to speak, inscribed in its language practices through how the objects(!) of study are constituted. In passing, it should be noted that reification as such is a case of reification (Billig, 2008); that is, a process is transformed into a thing, hiding from view, as it were, how this is done and by whom (and what the implications of the transformation are). One thing researchers do through reification is to make abstractions more readily cognizable, as Goatly (2011) argues. When abstractions are concretized into substances or objects and their qualities, they become things that can be created, transferred, and possessed; have impact and location; and have dimensions, forms, and parts. Transformed into things, the abstractions also become visually available for inspection. So how can we be mindful of reification? I suggest that the problems with reification imply the importance of keeping a meta-perspective alive throughout one’s reasoning, in order be able to distinguish the representational means (our language) from what we use them to represent. Such a meta-perspective can be nurtured by adopting a historical perspective (Pramling, 2006a); that is, it is important to read earlier (old) accounts of the same phenomenon one is investigating in one’s own research. Another way to try to be mindful of misplaced reification, as suggested by Woodworth (1940), as I have cited, is to attempt to reformulate accounts of, for example, mental phenomena, from nouns to verbs and see what happens to our reasoning; and to our research, we may add, as reification also has concrete consequences for how scientists design their investigations, including how they conduct and interpret experiments (see Pramling, 2011, for an elaboration and historical examples).

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6.2 Metaphors for Talking About the Empirical Basis of Research Recurrently in this book, I emphasize the metaphorical nature of language. The language of science generally, at least if seen from a historical perspective, and the language used to speak about the empirical basis of research, to use a specific case, are no exceptions to this. A rather commonsense way of writing about the basis of one’s research is to formulate it in terms of data collection. This is problematic, because empirical data are not there beforehand to be found and collected (as some kind of objects; cf. above on reification). Rather, as researchers, we transform the world we observe into empirical data. We do this through some method of registration/observation. This entails some degree of transformation, however subtle. Therefore, rather than talking about collecting data, it makes more sense to talk about generating empirical data. This metaphor—generating—implies a more dynamic activity, and indicates that the researcher does something in transforming the fleeting and shifting world into a representational form (e.g., through transcripts) that can be systematically scrutinized and analyzed. Empirical data are not there to be collected; rather, we generate data through our methods of investigation (observation, interviews, etc.). This perspective also implies that the world does not speak for itself and that empirical data are not neutral. The latter point implies the importance of being mindful of how data are generated and what theoretical premises and conceptual resources guide this part of the research.

6.3 Some Final Words on the Importance of Being Attentive to Terminology While I have emphasized throughout this book the importance of being mindful of the terminology in one’s discourse, and how keeping a meta-perspective alive throughout one’s exploration and reporting is pivotal to a scientific stance, it should be acknowledged that we can do this only to an extent. In order to communicate and make claims, we have to presume things that we cannot—at the same time continuously—question and analyze. Hence, some modesty is recommended. Still, supporting other scholars, and oneself, by paying attention to the terms and concepts we employ in research is an important part of the collective, critical, and informed work referred to as scientific.

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References Billig, M. (2008). The language of critical discourse analysis: The case of nominalization. Discourse & Society, 19(6), 783–800. Goatly, A. (2011). The language of metaphors (2nd ed.). Routledge. Halliday, M. A. K., & Martin, J. R. (1993). Writing science: Literacy and discursive power. University of Pittsburgh Press. Hunt, E. B. (1971). What kind of computer is man? Cognitive Psychology, 2, 57–98. Matusov, E. (2011). Too many references, just cut a few and it will be perfect: APA versus Chicago (Commentary). Mind, Culture, and Activity, 18, 58–66. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97. Pramling, N. (2006a). Minding metaphors: Using figurative language in learning to represent (Göteborg Studies in Educational Sciences, 238). Acta Universitatis Gothoburgensis. Open Access: http://hdl.handle.net/2077/16798 Pramling, N. (2011). Possibilities as limitations: A study of the scientific uptake and moulding of G. A. Miller’s metaphor of chunk. Theory & Psychology, 21(3), 277–297. Roth, W.-M., & Cole, M. (2010). The referencing practices of Mind, Culture, and Activity: On citing (sighting?) and being cited (sighted?). Mind, Culture, and Activity, 17, 93–101. Säljö, R. (2002). My brain’s running slow today—The preference for “things ontologies” in research and everyday discourse on human thinking. Studies in Philosophy and Education, 21, 389–405. Simon, H. A. (1974). How big is a chunk? Science, 183, 482–488. Wittgenstein, L. (1953). Philosophische untersuchungen/Philosophical investigations (G. E. M. Anscombe, Trans.). Blackwell. Woodworth, R. S. (1940). Psychology: A study of mental life (12th ed.). Methuen.

Chapter 7

Coda: Summary and the Importance of Being Mindful of Pareidolia

Abstract In this final chapter the key insights from the book are summarized, and a metaphor is introduced and developed for conceptualizing what is argued to be a key competence in a researcher: the ability to distinguish between how we know (or epistemology) and what we know (ontology, making reality claims).

To end1 this introduction to methodology for early childhood education and care research, I will do two things (as it were; cf. the reasoning above on reification): (i) summarize what I consider the key lessons to learn from this introduction and (ii) suggest and somewhat illuminate a metaphor for what I have argued constitutes a key competence in a researcher. To summarize this book, I first listed and elaborated (including presenting the etymology of) important scientific terminology. Throughout the book, I have particularly emphasized the importance and functions of theory in scientific knowledge building. Given the systematic nature of theory—that its constituting concepts are systematically related and defined in relation to each other—I clarified and motivated the problems with combining theories, or parts of theories. In the context of this discussion, I also illuminated the concept of unit of analysis and the importance of coherence between the different parts of research (theory, research questions, method, analysis, representation of empirical data, and knowledge claims). A key point of this book has been to argue that research is an argumentative set of practices: The world does not simply present itself. This argument reminds us of the importance of being aware of the contributions made by the researcher to knowledge building, by taking a theoretical perspective and everything this entails.

1

The word “coda”, of Latin origin, literally means tail and typically denotes the final part of something (e.g., a text).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 N. Pramling, Methodology for Early Childhood Education and Care Research, SpringerBriefs in Education, https://doi.org/10.1007/978-3-031-24174-1_7

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7.1 Pareidolia and Conclusions In the field of human psychology, there is a phenomenon known as pareidolia. Etymologically, pareidolia [Παρειδωλ´ια] stems from the ancient Greek para [παρ α] ´ meaning beside, instead and eidolon [ε‡δωλoν], image. The concept of pareidolia means illusory perception or experiencing patterns in random information. Reported examples of pareidolia include perceiving animals in clouds, faces in natural objects (tree trunks, rocks) and, which may be the most famous examples, the face of Jesus on a piece of toast and the so-called Face on Mars. Besides such visual perception (and typically face pareidolia),2 auditory perception is also included, perhaps the most famous example being preachers/pastors perceiving hidden (allegedly more specifically satanic) messages in rock records played backward(!) (Davis, 2005). So, the reader may ask, what does all this talk about illusory perception have to do with the topic of the present book, research methodology? The reason I mention this concept is that I will suggest that it can serve as a metaphor for raising awareness of what I argue is a key competence in a researcher.3 In the context of this book’s topic, I argue that pareidolia can serve as a metaphor for the inability to perceive one’s own perspective as a perspective—or, if you will, to recognize that process of sense making; that is, that even as researchers we make sense of what we encounter (perceive) (a basic condition of being a human being, Bruner, 1990) rather than merely processing information (as if we were computers/information processors). An inability to recognize this feature of knowledge building—that we make sense, ideally in terms of the theoretical perspective we take in our study—implies ascribing what are, in fact, features of sense making to the world we investigate. This inability to distinguish, unfortunately, is often evident in studies taking a so-called critical perspective,4 in which claims are made about unveiling (and similar metaphors) and uncovering how things really are (as if this did not imply taking a perspective, albeit a different one than that allegedly being unveiled). To quote some examples, as rendered in the meta-text in Cohen et al. (2017): “reveals”, “revealing”, “uncover”, “expose”, as it were the “smokescreen” to see how it (that is, “reality”) “really is”. Please note that I do not claim that work 2

You can read more about the phenomenon of face pareidolia—perceiving faces where there are none—and the neuroscientific investigation into this in the somewhat unfortunately titled research article “Women are Better at Seeing Faces where there are None: an ERP study of face pareidolia” (Proverbio & Galli, 2016; see also Zhou & Meng, 2020). 3 Sometimes pareidolia is restricted to the notion of perceiving faces where there are none, seeing this as an example of apophenia [Aπ oϕ šνια]; that is, “the human tendency to perceive meaningful patterns from random data” (Zhou & Meng, 2020, p. 1). Hence, the terms “pareidolia” and “apophenia” are often used interchangeably. However, it is more common to see face pareidolia as a special case of pareidolia more generally. No distinction will be made here between these terms, as it is not important to the metaphorical way I use the term “pareidolia”. 4 Note that so-called critical theories are not more critical—in the sense of critique in scientific knowledge building (see Chapter 2)—than other theories. Rather, critical theories are used with an ambition to change the status quo (and in this sense are closely adjacent to action research and other practice-near research approaches).

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informed by a “critical perspective” generally indicates this fallacy of recognizing the theoretical perspective as a perspective. What I suggest is more limited in scope: When one uncritically employs terminology like that exemplified here (revealing, uncovering, etc.)—that is, without a meta-perspective recognizing the perspectivity inherent in this—this fallacy occurs. There is a parallel to such pareidolia in what is typically referred to as anthropomorphism. This concept denotes ascribing non-human entities human traits, such as voluntary remembering, problem solving, and reasoning. One of many legacies from developmental psychologist Jean Piaget is that anthropomorphism (and more generally animism, believing that non-living entities—clouds for example—are alive) is characteristic of children’s thinking (Piaget, 1926/1951). However, the empirical and analytical grounding of this claim has been criticized in subsequent research (Pramling, 2006b; Pramling & Säljö, 2015; Thulin & Pramling, 2009; cf. also Aronsson & Hundeide, 2002; Sommer et al., 2010). Ascribing human characteristics to non-human entities is common not only in everyday discourse—for instance, saying about a computer that is processing slowly that it is thinking or, in reference to a table that a child has run into, “stupid table” or “it hit you”—but also, unfortunately (and especially during the last decade) in research, in so-called post-humanist thinking whereby not only humans but also things, literally objects, are ascribed agency and intention. There may be a point in arguing in such a way, as a mode of thinking (what if ), to find new ways of thinking and perhaps solving problems (e.g., concerning sustainable development). However, without an explicit awareness (a meta-perspective) clarifying that this is a metaphorical way of reasoning (as if it were) rather than, when not presenting such a meta-perspective, making reality claims (as a matter of fact; how it is), such claims fall outside the scope of science and should not be regarded as contributions to this project of collective knowledge building. Reasoning as if one were a participant in an event in which no person could actually take part in is a productive mode of collaboratively reasoning and thinking through problems in research. A fascinating example of this is reported by Ochs et al. (1996), who studied physicists engaged in understanding subatomic particles and showed that they reasoned as if they themselves were in that position. In doing this, they frequently used what Ochs et al. refer to as an “indeterminate reference”, more specifically “one that combines a personal animate pronominal subject (e.g., ‘I’) with an inanimate physical event predicate (e.g., ‘am in the domain state’)” (p. 358). Ochs et al. elaborate: The referent constructed in these utterances appears to be neither exclusively the physicist nor the object of inquiry but rather a blended identity that blurs the distinction between the two. Such utterances cannot, of course, be literally understood as indexing events in which physicists participate. Nevertheless, they appear to be completely unproblematic for the physicist interlocutors. Indeed, no one ever stops an interaction to ask, “What do you mean ‘I’m in the domain state’?” or “How could you possibly ‘go below in temperature’?” Moreover, they are also ubiquitous in our data. (p. 339f., italics in original)

This mode of speaking as if the researcher were an actor in the observed event is not taken literally by participants; that is, no interlocutor from this thought figure draws

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the conclusion that this is how it is. The mode of reasoning remains epistemology, and is not mistaken for ontology. This as-if mode of reasoning is functional for the researchers to collaboratively make sense of observations and how they may be explained (cf. Fleer, 2014), but it remains a mode of talking and reasoning. The ability to distinguish between how something is talked about and what is being referred to is crucial for a researcher to have. In contrast to the Ochs et al. (1996) example, the inability to distinguish between the mode of thinking (as if ) and making reality claims (as is), as I argue is typically done in post-human reasoning, more specifically constitutes a case of what I have suggested elsewhere in this book be seen as an “ontologization”. This term denotes displacing epistemology in ontology and thus reconstituting the former as the latter. To continue with the example of post-human thinking: The problem with claims (rather than what-if thought figures) about the intentions, agency, etc. of things is not only that the perspective (the philosophy) is conflated with what the claims are made about (the world), but also that in the application of one of the principles as formulated in a core concept of science—Ockham’s razor—it falls short of the alternative. According to the principle of Ockham’s razor, when confronted with two (or more) alternative explanations of the same observation (or phenomenon), we should always prioritize the one that presumes less. In the context of the present example, if we have the alternatives of presuming, for example, that learning can be understood without versus with the presumption that objects in the proximity of the learner also understand, think, have intentions (and that this has implications for the learner’s learning), we should go for the one that does not presume the latter. Put bluntly, the simpler explanation wins. Returning to the matter of pareidolia, the relation and distinction between pareidolia and ontologization can be elaborated thusly. As I use the term here, pareidolia serves as a metaphor for the researcher’s (i.e., the perceiver’s/knowledge builder’s) inability to distinguish between what lies in his or her perceiving/knowledging and what lies in the phenomena and processes perceived/knowledged (understood). When something that is a feature of the perspective (theory) is displaced in the world being investigated, what I call an ontologization occurs. This is a form of fallacy, whereby epistemology is misplaced into, and receives standing as, ontology. Phrased differently, as used in this book, pareidolia denotes the inability to see one’s own perspective as a perspective, whereas ontologization denotes the process of ascribing epistemological distinctions to studied reality. However, keeping in mind the lessons regarding reification (see Chap. 6), rather than ontologization, ontologizing would be the preferable denomination for this process. To end this book I return to the issues of metaphors and thinking as if , which were highlighted, among other places, when I discussed theory as a map. Theorizing could be construed as a form of as-if thinking. As Vaihinger (1924/2001) argues, such thinking is in fact indicative of not only scientific knowledge but also the nature of consciousness. He argues that the latter is better understood as molding and formative than in terms of the traditional metaphor of the mind as a mirror reflection (cf. Rorty, 1979, for a critical elaboration on this long-standing metaphor for understanding and the nature of learning). The purpose of our knowledge, Vaihinger argues, is “not the

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portrayal of reality–this would be an utterly impossible task–but rather to provide us with an instrument for finding our way about more easily in this world” (Vaihinger, 1924/2001, p. 15, my italics). The latter metaphor constitutes knowledge as action and as a resource for orienting ourselves in the world. Here, orienting could denote, for example, how we can support children in making sense of the world, themselves, and each other; how a (minority) language can be made into a developmental asset for learning another (typically majority) language; how to increase the likelihood that members of the growing generation will be able to think in new ways (promoting imagination); how to remember more forcefully than what we happen to remember by our nature; and many other important matters. Through research, we generate and develop powerful forms of knowing, with intellectual and material consequences; but this knowing should not be conflated with the world. Cognizance of the contributions we as researchers make in knowledge building, and of the fact that the world and its phenomena and processes can be constituted in different ways from different theoretical points of view (systematic perspectives), is an important reminder of the dynamic relationship between knowing and what it is we know something about.

References Aronsson, K., & Hundeide, K. (2002). Relational rationality and children’s interview responses. Human Development, 45(3), 174–186. Bruner, J. S. (1990). Acts of meaning. Harvard University Press. Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education. Routledge. Davis, E. (2005). IV (33 1/3, no. 17). Continuum. Fleer, M. (2014). A digital turn: Post-developmental methodologies for researching with young children. In M. Fleer & A. Ridgway (Eds.), Visual methodologies and digital tools for researching with young children (International Perspectives on Early Childhood Education and Development, 10) (pp. 3–11). Springer. Ochs, E., Gonzales, P., & Jacoby, S. (1996). “When I come down I’m in the domain state”: Grammar and graphic representation in the interpretive activity of physicists. In E. Ochs, E. A. Schegloff, & S. A. Thompson (Eds.), Interaction and grammar (pp. 328–369). Cambridge University Press. Piaget, J. (1951). The child’s conception of the world (J. Tomlinson & A. Tomlinson, Trans.). Savage, MD: Littlefield Adams. (Original work published 1926). Pramling, N. (2006). ‘The clouds are alive because they fly in the air as if they were birds’: A reanalysis of what children say and mean in clinical interviews in the work of Jean Piaget. European Journal of Psychology of Education, 21(4), 453–466. Pramling, N., & Säljö, R. (2015). The clinical interview: The child as a partner in conversations versus the child as an object of research. In S. Robson & S. F. Quinn (Eds.), International handbook of young children’s thinking and understanding (pp. 87–95). Routledge. Proverbio, A. M., & Galli, J. (2016). Women are better at seeing faces where there are none: An ERP study of face pareidolia. Social Cognitive and Affective Neuroscience, 1501–1512. Rorty, R. (1979). Philosophy and the mirror of nature. Princeton University Press. Sommer, D., Pramling Samuelsson, I., & Hundeide, K. (2010). Child perspectives and children’s perspectives in theory and practice (International Perspectives on Early Childhood Education and Development, 2). Springer.

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Thulin, S., & Pramling, N. (2009). Anthropomorphically speaking: On communication between teachers and children in early childhood biology education. International Journal of Early Years Education, 17(2), 137–150. Vaihinger, H. (2001). The philosophy of “as if”: A system of the theoretical, practical, and religious fictions of mankind (6th rev. ed., C. K. Ogden, Trans.). Routledge. (Original work published 1924). Zhou, L.-F., & Meng, M. (2020). Do you see the “face”? Individual differences in face pareidolia. Journal of Pacific Rim Psychology, 14, e2. https://doi.org/10.1017/prp.2019.27