Family Cultural Capital and Student Achievement: Theoretical Insights from PISA (SpringerBriefs in Education) 9811544905, 9789811544903

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SPRINGER BRIEFS IN EDUC ATION

Cheng Yong Tan

Family Cultural Capital and Student Achievement Theoretical Insights from PISA 123

SpringerBriefs in Education

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Cheng Yong Tan

Family Cultural Capital and Student Achievement Theoretical Insights from PISA

123

Cheng Yong Tan The University of Hong Kong Hong Kong, Hong Kong

ISSN 2211-1921 ISSN 2211-193X (electronic) SpringerBriefs in Education ISBN 978-981-15-4490-3 ISBN 978-981-15-4491-0 (eBook) https://doi.org/10.1007/978-981-15-4491-0 © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 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 Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

This book is dedicated to my wife, Hwei Yin, the constant source of inspiration and support for my learning, and my son, Clyth, the epitome of a joyful learner.

Preface

I am thankful that my parents have arranged private piano lessons outside school for me. After attending these lessons, I have developed a stronger interest for music. Piano lessons also help me when I have music class in school. For example, if the school music teacher tells my class to label piano notes on an activity sheet, then my piano skills will be very useful. If my music teacher sees that I have filled in the notes correctly, she might think that I have a talent for music. She would then look upon me favourably and think I have a potential in learning and that I am very well-behaved. My friends might also have a good impression of me, so that they will regard me as their role model. They might even play with me more often as they respect me more. I might even have more opportunities to be elected as a class monitor, which has already happened, thanks to them. With the care of my teachers and friends, I feel happy going to school every day. Clyth, 8 years old

The except above from Clyth is illustrative of the myriad ways in which parents, especially middle-class parents, facilitate and contribute to their children’s learning. For example, Clyth’s after-school piano lessons not only enrich his musical learning at home, they also influence the way his teachers and friends perceive him. These perceptions then affect the learning and even leadership opportunities he has in school. However, while many of us will agree that parents will desire these positive conditions to occur, the truth is that, as the book will show, not all children are able to have the extra resources from their parents to benefit their school learning. Therefore, some children may have a headstart emanating from their cultural capital in their learning as compared to their peers. This book on the intricate relationship between cultural capital and students’ academic achievement is written for scholars, researchers, and graduate students specializing in the field of social stratification and reproduction, particularly cultural capital theory. More specifically, it will be useful to readers in four ways. First, it provides a useful one-stop overview of the state of quantitative research in cultural capital theory. Readers can survey the myriad ways cultural capital is

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conceptualized and measured by previous researchers, and use this information to inform their research design accordingly. For example, the book points the way forward on how different variables in the PISA data can be used as indicators of cultural capital and habitus. Second, readers can build on the discussion of salient theoretical issues pertaining to research in cultural capital theory to identify significant knowledge gaps that they can address in their research. For example, the empirical studies reviewed in the book demonstrate how cultural capital has assumed new forms in response to emerging social developments and continued to be instrumental in mediating the effects of social origins on students’ learning. This is exemplified by students’ access to and usage of information technology in their learning (digital divides) and by the emphasis on mathematics and science literacy attributed to parents’ familiarity with school evaluation standards and requirements of job markets in knowledge-based economies. Third, readers can read the studies on the specific aspects of cultural capital investigated and conduct further research (including the use of PISA data) to build on the results of these studies. These studies will also exemplify how they can investigate other aspects of cultural capital in their research. Lastly, readers can examine the results from studies on cultural capital effects in different socio-cultural-economic contexts and be sensitized to the role of field conditions in moderating cultural capital effects in their own research. Indeed, the book explores how international comparative studies have provided quantitative researchers with a means to compare the functioning of cultural capital across different sociocultural contexts indicative of social fields (e.g., societies differing in their socioeconomic gradients and cultural values). Hong Kong

Cheng Yong Tan

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Evolving Scholarship on Cultural Capital Theory and Students’ Academic Achievement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Aims of This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Important Research Questions We Should Be Asking . . . . . . . . 1.4 Overview of This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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2 Conceptual Diversity of Cultural Capital . . . . . . . . 2.1 Complexity of Cultural Capital . . . . . . . . . . . . . 2.1.1 Three States of Cultural Capital . . . . . . . 2.1.2 Beyond Highbrow Cultural Participation . 2.1.3 Proliferation of Indicators . . . . . . . . . . . . 2.1.4 Active Generation of Cultural Capital . . . 2.1.5 Habitus—the Glue of It All . . . . . . . . . . 2.2 Cultural Capital and Fields . . . . . . . . . . . . . . . . 2.2.1 Distinguishing Resources from Capital . . 2.2.2 Relational Value of Cultural Capital . . . . 2.2.3 Relational Stratification . . . . . . . . . . . . . 2.3 Cultural, Economic, and Social Capital . . . . . . . 2.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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3 Cultural Capital and PISA . . . . . . . . . . . . . . . . . . . . . 3.1 Influence of International Large-Scale Assessments 3.2 PISA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Influence of PISA . . . . . . . . . . . . . . . . . . . 3.2.2 Criticisms Against PISA . . . . . . . . . . . . . . 3.2.3 Strengths of PISA . . . . . . . . . . . . . . . . . . .

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3.3 Cultural Capital Variables and PISA Questions . . . . . . . . . . . . . . 3.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Interrogating the Cultural Capital–Students’ Achievement Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Myriad Aspects of Cultural Capital Varying in Importance . . 4.2 Cultural Capital in Nomological Framework . . . . . . . . . . . . 4.3 Conjunctive Effects of Cultural Capital . . . . . . . . . . . . . . . . 4.3.1 Synergistic Effects . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Moderating Effects of Students and Families’ Profiles 4.3.3 Offsetting Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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5 Comparing Cultural Capital Across Groups and Countries 5.1 Gender Gaps in Cultural Capital Effects . . . . . . . . . . . . . 5.2 Cross-National Differences in Cultural Capital Effects . . . 5.2.1 Moderating Effects of Masculinity . . . . . . . . . . . 5.2.2 Moderating Effects of Confucian Values . . . . . . . 5.2.3 Moderating Effects of Countries’ Socioeconomic Gradients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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6 Conclusion . . . . . . . . . . . . . . . . . . . 6.1 Revisiting Research Questions . . 6.2 Contributions to Theory . . . . . . 6.3 Implications for Practice . . . . . . 6.4 Limitations . . . . . . . . . . . . . . . . 6.5 Suggestions for Future Research 6.6 Concluding Remarks . . . . . . . . . References . . . . . . . . . . . . . . . . . . . .

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Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 1

Introduction

Abstract This chapter contextualizes the evolving scholarship on the relationships between cultural capital and students’ academic achievement. It cogently argues that while the extant field has benefited from the proliferation of research interrogating the relationships between cultural capital and students’ academic achievement, the knowledge base on cultural capital theory is still conspicuously wanting in terms of substantive clarification of the meaning and workings of the cultural capital construct. Therefore, this book is written to fill this knowledge gap. The present chapter delineates the aims of the book before inviting readers to reframe their research questions in order to advance the extant scholarship. These aims are namely, to elucidate the complexity of cultural capital as an explanatory heuristic in the examination of the relationship between students’ familial social origins and their academic achievement, to take stock of the emerging trajectory of sociologists employing quantitative methods to examine issues of educational inequality, and to contribute to the scholarship on cultural capital theory. Keywords Academic achievement · Cultural capital · Conceptualization · Educational inequality · Social reproduction

1.1 Evolving Scholarship on Cultural Capital Theory and Students’ Academic Achievement Cultural capital theory is one of the most comprehensive theoretical frameworks that educational scholars in the field of social inequality and reproduction have in their conceptual arsenal to elucidate the ontology relating students’ social origins with their school achievement. For example, Davies and Rizk’s (2018) systematic review of the extant literature found that cultural capital research in the United States has withstood the test of time, having evolved across three generations. The first generation of educational research scholars are essentially adherents of Bourdieu’s quintessential ideas published in the 1960s–1970s, namely that cultural capital comprises highbrow tastes, dispositions, and practices associated with individuals from higher socioeconomic status (SES) backgrounds, that cultural capital yields educational returns akin to economic forms of capital, that schools perpetuate © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 C. Y. Tan, Family Cultural Capital and Student Achievement, SpringerBriefs in Education, https://doi.org/10.1007/978-981-15-4491-0_1

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social reproduction because they reward students who possess cultural capital, and that schools’ evaluation masks this class bias behind the veneer of meritocracy and open competition. The second generation of educational research (1980s–2000s) is shaped by influential works by leading scholars as epitomized by DiMaggio (1982), DiMaggio and Mohr (1985), Lareau (2000, 2002), Lareau and Weininger (2003), and Collins (1998, 2004, 2008). More specifically, DiMaggio conceived cultural capital as individuals’ familiarity and consumption of highbrow culture (e.g., listening to classical music, appreciating literary works, and visiting museums) in a status attainment framework, and argued that any individuals, including those from lower SES families, can acquire and use cultural capital to achieve educational success and social mobility. Lareau focused on the parenting strategies of middle-class parents that are designed to align with school evaluation standards. She popularized the notion of “concerted cultivation” (Lareau, 2002) describing how these parents micro-manage their children’s daily lives and proactively engage school personnel to maximize their children’s learning. Concerted cultivation contrasts with the logic of “accomplishment of natural growth” held by working-class parents who are more concerned with satisfying children’s basic needs and decoupling the home from school. Collins differed from DiMaggio or Lareau in that he conceived cultural capital at the micro-level in faceto-face interactions in his theory of interaction ritual chains. More specifically, he associated cultural capital with individuals’ knowledge of basic vocabularies, ideas, styles, and particularistic artifacts that facilitates interactions in a group. Therefore, he, just as DiMaggio, regards cultural capital as a resource that students, even those from lower SES families, can leverage to succeed academically and experience social mobility. The third generation of educational research (in the last two decades) is characterized by scholastic pluralism that builds on, expands, and even integrates DiMaggio, Lareau, and Collins’ legacies. For example, researchers in the DiMaggio tradition have compared how highbrow cultural participation and other aspects of cultural capital contribute to student achievement (Evans, Kelley, & Sikora, 2014; Lund-Chaix & Gelles, 2014; Roose, 2015), employed Lareau’s idea of concerted cultivation in DiMaggio’s status attainment framework (Cherng, Calarco, & Kao, 2013; Kisida, Greene, & Bowen, 2014), examined outcomes beyond student achievement such as elite university admissions and persistence (Brooks, 2008; Davies, 2009; Dumais & Ward, 2010; Grayson, 2011; Khan, 2011; Sheng, 2014; Zimdars, Sullivan, & Heath, 2009), conducted international studies on cultural capital theory (Andersen & Jaeger, 2015; Evans et al., 2014; Marteleto & Andrade, 2014; Roose, 2015; Sheng, 2014), and examined how social class interacts with other variables such as gender or race to impact student outcomes (Christin, 2012; Lagaert, Van Houtte, & Roose, 2017).

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1.2 Aims of This Book Given this rapidly growing scholarship, there is an urgent need to take stock of the research to update our conceptualization of the construct of cultural capital and understanding on how it influences student outcomes. Accordingly, this book is written with three aims in mind. The first aim is to elucidate the complexity of cultural capital as an explanatory heuristic in the examination of the relationship between students’ familial social origins and their academic achievement. It debunks the myth that cultural capital is a singular construct operating independently from other factors to affect all students in the same way regardless of their demographic, familial, or broader socio-culturaleconomic contextual characteristics. The second aim is to take stock of the emerging trajectory of sociologists, including cultural capital theory scholars employing quantitative methods to examine issues of educational inequality. In this regard, the book underscores the potential of interrogating the rich data in Programme for International Student Assessment or PISA (a source of open-access “big data” in international large-scale assessment in educational research) to examine the relationships between different aspects of cultural capital and academic achievement of students from different countries. It hopes to achieve this by discussing how researchers have examined the intricate relationship between cultural capital and student learning using PISA data and the results of their investigations. The third aim is to contribute to the scholarship on cultural capital theory by presenting a conceptual framework that underscores the refined conceptualization of cultural capital and by discussing future research directions for cultural capital theory scholars. This conceptualization will inform future research examining the association between cultural capital and students’ academic achievement.

1.3 Important Research Questions We Should Be Asking In this discourse, the point of departure is that cultural capital is a useful conceptual heuristic for explaining the association between familial social origins and students’ academic achievement. Accordingly, we should progress from asking the exploratory research questions “Do students from more privileged family backgrounds (e.g., families with higher SES) perform better in school?” or “Does cultural capital contribute to students’ academic achievement?” to asking the following nuanced questions: • “Is there one singular cultural capital or are there different aspects of cultural capital that contribute to students’ academic achievement?” • “What aspects of cultural capital are more relevant in contemporary contexts such as knowledge-based economies?” • “What aspects of cultural capital are more important than others in affecting students’ academic achievement?”

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• “How does cultural capital benefit students in their learning?” • “How do students benefit from having more than one aspect of cultural capital?” • “Does cultural capital benefit all groups of students (e.g., boys versus girls, or students from different socio-cultural-economic contexts) similarly?”

1.4 Overview of This Book This book comprises six chapters. This chapter (the present chapter) provides an introduction to the scholarship and empirical research on cultural capital theory. It contextualizes the book in the evolving scholarship on the relationships between cultural capital and students’ academic achievement that has spanned three generations. It argues that while researchers, educators, and policymakers have benefited from the proliferation of research interrogating the relationships between cultural capital and students’ academic achievement, the field is conspicuously wanting in terms of substantial theoretical developments that are needed to further clarify the meaning and workings of the cultural capital construct. Addressing this knowledge gap is the key impetus for the publication of this book. Accordingly, this chapter delineates the aims of the book before inviting readers to reframe their research questions in order to advance the extant scholarship. Chapter 2 is devoted to a discussion on the conceptual diversity of cultural capital. It adopts two strategies to achieve this goal. The first is to argue for a more holistic, contemporary understanding of cultural capital that encompasses different manifestations of the construct beyond highbrow cultural consumption, to recognize that cultural capital can be actively generated by parents and children alike, and to nomologically reconcile cultural capital with the related transcendental variable of habitus. The second strategy to unpack the complexity of cultural capital is by examining it in the context of social fields in which it is recognized. This approach reminds us that familial “resources” are not necessarily valued “capital,” and that resources need to be converted to capital to profit their bearers in fields of competition. Furthermore, since the value of cultural capital is contingent on social relations in competitive fields, it can be inferred that there may be different aspects of cultural capital that are valued in different social fields. It is also noteworthy that the underlying relations in a field may be impervious to social change. Chapter 3 underscores the immense research possibilities for cultural capital researchers to harness the rich data in PISA to examine questions related to the cultural capital—students’ academic achievement relationships. It first affirms the emerging trajectory for sociologists, including scholars researching on cultural capital theory, to use quantitative methods and data from international large-scale assessments in their investigation of educational inequality. It then introduces PISA as a source of open-access “big data” in international large-scale assessment in educational research that can be exploited to examine the relationships between different

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aspects of cultural capital and academic achievement of students from different countries. In the discussion, it attempts to present an objective evaluation of the ubiquitous influence of PISA on education policies in many education systems worldwide and the criticisms against this developmental trajectory. After that, it outlines the benefits of PISA in contributing to educational development and scholarship. In particular, it methodologically summarizes the types of data pertaining to myriad cultural capital variables that PISA collects and makes available publicly for researchers to analyze. These data come from key survey instruments administered by PISA, namely Student Questionnaire, Student Information Communication Technology (ICT) Questionnaire, Student Educational Career (EC) Questionnaire, and Parent Questionnaire. This summary of PISA variables will be a useful resource for researchers open to exploring PISA data for their research on educational inequality. Chapter 4 elucidates the multitudinous ways in which cultural capital contributes to students’ academic achievement by illustrating how researchers have harnessed the rich data in PISA across the myriad cycles (from 2000 to 2015) to examine research questions pertaining to how cultural capital is associated with students’ reading, mathematics, and science achievement. There are three key insights that can be discerned from the research conducted by these researchers. First, cultural capital is a complex construct comprising various aspects that can be measured using different indicators. For example, cultural capital manifests in myriad ways in different societies, transcending the traditionally conceived highbrow cultural consumption to include parental familiarity with school evaluation standards and future job requirements in contemporary educational systems that value mathematics and science competencies and skills. The second insight highlights the importance of understanding the relationships between cultural capital and students’ academic achievement in a nomological framework. This framework includes some cultural capital aspects that are more proximal than others in affecting students’ academic achievement and recognizes how cultural capital may interact with habitus and social fields to affect students’ learning. The third insight is that different cultural capital variables may operate conjunctively, rather than separately, to influence students’ academic achievement. Indeed, different aspects of cultural capital may reinforce each other to synergistically benefit students’ learning, exhibit different patterns of association with students’ academic achievement depending on the profiles of students and their families, or even “cancel out” others in their effects. Chapter 5 complements the previous chapter by demonstrating other nuances of cultural capital. More specifically, it discusses results from published studies harnessing PISA data demonstrating how cultural capital levels and effects may vary across groups of students with various characteristics. These characteristics are namely, gender gaps and cross-national gaps in student achievement. In particular, cross-national differences comprise cultural attributes such as the degree of masculinity, influence of Confucian values, and socioeconomic gradients of countries. Results from these studies underscore the moderating influences of student-and societal-level factors in cultural capital–student achievement relationships.

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The last chapter, Chap. 6, synthesizes the materials presented in this book and summarizes the key contributions of the book to theoretical developments in cultural capital theory. In particular, it presents a conceptual framework that incorporates the rich, nuanced conceptualization of cultural capital, relationships between cultural capital and students’ academic achievement, and student and socio-cultural-economic moderators of these relationships. This conceptual framework can be used to inform further theoretical and empirical work interrogating the relationships between cultural capital and students’ academic achievement. Implications for practice for educators, parents, and policymakers are also discussed. The chapter ends with some suggestions for future research.

References Andersen, I., & Jaeger, M. (2015). Cultural capital in context: Heterogeneous returns to cultural capital across schooling environments. Social Science Research, 87, 1943–1971. https://doi.org/ 10.1016/j.ssresearch.2014.11.015. Brooks, R. (2008). Accessing higher education: The influence of cultural and social capital on university choice. Sociology Compass, 2, 1355–1371. https://doi.org/10.1111/j.1751-9020.2008. 00134. Cherng, H., Calarco, J., & Kao, G. (2013). Along for the ride: Best friends’ resources and adolescents’ college completion. American Educational Research Journal, 50, 76–106. https://doi.org/ 10.3102/0002831212466689. Christin, A. (2012). Gender and highbrow cultural participation in the United States. Poetics, 40, 423–443. https://doi.org/10.1016/j.poetic.2012.07.003. Collins, R. (1998). The sociology of philosophies: A global theory of intellectual change. Cambridge: Belknap Press. Collins, R. (2004). Interaction ritual chains. Princeton, NJ: Princeton University Press. Collins, R. (2008). Violence. Princeton, NJ: Princeton University Press. Davies, S. (2009). Drifting apart? The institutional dynamics awaiting public sociology in Canada. Canadian Journal of Sociology, 34, 623–654. Davies, S., & Rizk, J. (2018). The three generations of cultural capital research: A narrative review. Review of Educational Research, 88(3), 331–365. https://doi.org/10.3102/0034654317748423. DiMaggio, P. (1982). Cultural capital and school success: The impact of status culture participation on the grades of U.S. high school students. American Sociological Review, 47, 189–201. https:// doi.org/10.2307/2094962. DiMaggio, P., & Mohr, J. (1985). Cultural capital, educational attainment, and marital selection. American Journal of Sociology, 90, 1231–1236. https://doi.org/10.1086/228209. Dumais, S., & Ward, A. (2010). Cultural capital and first-generation college success. Poetics, 38, 245–285. https://doi.org/10.1016/j.poetic.2009.11.011. Evans, M. D. R., Kelley, J., & Sikora, J. (2014). Scholarly culture and academic performance in nations. Social Forces, 92, 1573–1605. https://doi.org/10.1016/j.ssresearch.2015.02.005. Grayson, J. P. (2011). Cultural capital and academic achievement of first generation domestic and international students in Canadian universities. British Educational Research Journal, 37, 605–630. https://doi.org/10.1080/10573560903547452. Khan, S. (2011). Privilege: The making of an adolescent elite at St. Paul’s school. Princeton, NJ: Princeton University Press. Kisida, B., Greene, J., & Bowen, D. (2014). Creating cultural consumers: The dynamic of cultural capital acquisition. Sociology of Education, 87, 281–295. https://doi.org/10.1177/ 0038040714549076.

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Lagaert, S., Van Houtte, M., & Roose, H. (2017). Engendering culture: The relationship of gender identity and pressure for gender conformity with adolescents’ interests in the arts and literature. Sex Roles, 77, 482–495. https://doi.org/10.1007/s11199-017-0738-y. Lareau, A. (2000). Home advantage: Social class and parental intervention in elementary education. Lanham, MD: Rowman & Littlefield. Lareau, A. (2002). Unequal childhoods: Class, race, and family life. Berkeley, CA: University of California Press. Lareau, A., & Weininger, E. (2003). Cultural capital in educational research: A critical assessment. Theory and Society, 32, 567–606. Lund-Chaix, A., & Gelles, E. (2014). A cultural capital perspective of the effect of a governmentvoluntary sector partnership for enhancing access to post secondary education. Nonprofit and Voluntary Sector Quarterly, 43, 436–454. https://doi.org/10.1177/0899764012470028. Marteleto, L., & Andrade, F. (2014). The educational achievement of Brazilian adolescents: Cultural capital and the interaction between families and schools. Sociology of Education, 87, 16–35. https://doi.org/10.1177/0038040713494223. Roose, H. (2015). Signs of “emerging” cultural capital? Analysing symbolic struggles using class specific analysis. Sociology, 49, 556–573. https://doi.org/10.1177/0038038514544492. Sheng, X. (2014). Parental expectations relating to children’s higher education in urban China: Cultural capital and social class. Journal of Sociology, 50, 560–576. https://doi.org/10.1177/ 1440783312467096. Zimdars, A., Sullivan, A., & Heath, A. (2009). Elite higher education admissions in the arts and sciences: Is cultural capital the key? Sociology, 43, 648–666. https://doi.org/10.1177/ 0038038509105413.

Chapter 2

Conceptual Diversity of Cultural Capital

Abstract This chapter argues for a refined understanding and appreciation of the conceptual richness of the cultural capital construct. To this end, it elaborates on the complexity of the construct and its inextricable association with social fields. The construct sophistication of cultural capital is evident in its properties, namely being present in three states (objectified, institutionalized, and embodied), assuming different meanings beyond the original highbrow cultural consumption as explicated in Bourdieu’s early writings, being represented by a proliferation of indicators in research studies (e.g., home educational and cultural resources, cultural participation, parental involvement, reading habits, parent–child discussions, educational expectations, and parental educational attainment), being produced by individuals who know the rules of the game, and being conceptually coherent by virtue of the embodiment of habitus. The inextricable associations between cultural capital and social fields are underpinned by the need to convert cultural resources to cultural capital, relational value of cultural capital, and the idea of relational stratification. Keywords Academic achievement · Conceptualization · Cultural capital · Habitus · Social fields This chapter navigates the complex terrain pertaining to the conceptual diversity of cultural capital. It is divided into two broad sections. The first section interrogates the multidimensional characteristics of the cultural capital construct. The purpose of this section is to present the argument that it is more accurate to characterize cultural capital as a pluralistic, diverse, and multifaceted rather than a simplistic, unitary, decontextualized, and unidimensional construct. The second section of the present chapter summarizes the inextricable association between cultural capital and social field conditions. The purpose of this section is to underscore the importance of contextualization and relativity in cultural capital theory and to caution against analyzing the construct atomically and independently of other variables and sociocultural-economic contexts.

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 C. Y. Tan, Family Cultural Capital and Student Achievement, SpringerBriefs in Education, https://doi.org/10.1007/978-981-15-4491-0_2

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2.1 Complexity of Cultural Capital To understand and appreciate the complexity of cultural capital, we need to embrace a more holistic, contemporary understanding that encompasses different manifestations of the construct (including more than highbrow cultural participation), that recognizes that it can be actively generated by parents and children alike, and that reconciles it with the related transcendental variable of habitus. These points are elaborated in the following sections.

2.1.1 Three States of Cultural Capital First, cultural capital as conceptualized by Bourdieu (1986) is a multidimensional construct comprising three states: objectified, embodied, and institutionalized. Objectified cultural capital refers to home physical resources that are propitious to the development of the types of dispositions, values, perceptions, knowledge, and skills that are valued by teachers in schools. Embodied cultural capital represents the incorporation of the principles of social fields within the corporality of individuals in predispositions and propensities, and in physical features including body languages, intonation, and lifestyles. It is exemplified by values and attitudes conducive to learning, tastes and preferences for academic pursuits, and mastery of academic competencies and skills. These attributes are emphasized and rewarded in the formal school system, and teachers may perceive students demonstrating these characteristics as being more capable (Bourdieu, 1986). Institutionalized cultural capital is formed when embodied cultural capital is publicly recognized and acknowledged as a marker of social distinction. Cultural capital can thus be manifest (as in the objectified state) or symbolic (as in the embodied or institutionalized states).

2.1.2 Beyond Highbrow Cultural Participation Second, cultural capital may be construed as being limited to highbrow cultural participation or more broadly to include linguistic and cognitive habits, knowledge, and skills and familiarity with school evaluative standards (Lareau & Weininger, 2003). Advocates of the former position argue that cultural practices should be exclusionary, class-based (e.g., individuals from higher SES families enjoying beaux arts as compared to peers from lower SES families enjoying popular forms of mass culture), and that inclusion of variables otherwise corrodes the conceptual meaning of the cultural capital construct (Kingston, 2001). Advocates of the latter position, while agreeing that cultural capital must command value in the field, ask if highbrow cultural consumption is more legitimate and relevant than practices such as reading

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and parental involvement as markers of social distinction in inclusive, meritocratic societies (Farkas, Grobe, Sheehan, & Shuan, 1990; Reay, 2004a; Vryonides, 2007).

2.1.3 Proliferation of Indicators Third, it is not surprising that different manifestations of cultural capital, as evident in either the myriad states it can assume or the conceptual diversity characterizing the construct, have eventuated in a proliferation of indicators that researchers use to measure the construct (Tan, 2017a, b). Results on the associations between these indicators and students’ learning outcomes are mixed. These indicators include home educational and cultural resources (objectified form); (b) cultural participation, parental involvement in their children’s education, reading habits, parent–child discussions about cultural and school issues, and child or parental educational expectations for their children (embodied form); and (c) parental educational attainment (institutionalized form). Home educational resources include reading materials (books, encyclopedia, atlases, dictionaries, newspapers, and magazines), educational toys (soft toys for role-playing, push or pull toys), learning technologies (computers, educational software, Internet connection, records, and compact discs), and learning facilities (study desks, study areas) (Chiu & McBride-Chang, 2010; Claro, Cabello, San Martín, & Nussbaum, 2015; Hvistendahl & Roe, 2004; Iruka, Dotterer, & Pungello 2014). Researchers who employ a variety of indicators to measure home educational resources (e.g., study desk and place, computer, educational software, Internet connection) found that the access to such resources at home was associated with higher levels of students’ academic achievement (Claro et al., 2015; Iruka et al., 2014). In contrast, scholars who rely on a single indicator of home educational resources (e.g., number of books at home) fail to detect a significant relationship between the two variables (Hvistendahl & Roe, 2004). Home cultural resources comprise access to classical literature works, poetry books, and artworks at home. There are mixed results with regard to the contribution of these resources, with some studies reporting that the availability of home cultural resources is related to some domains of student achievement but not others (Chiu & McBride-Chang, 2010; Hvistendahl & Roe, 2004). Parents and children’s cultural practices are exemplified by students’ participation in extracurricular activities, and parents and children’s visits to venues such as museums, libraries and bookstores, zoos and farms, historical sites, art galleries, theaters, opera and ballet performances, and musical concerts (Hvistendahl & Roe 2004; Iruka et al., 2014). Students who have higher levels of cultural participation may have higher levels of academic achievement. To illustrate, secondary school students who participate in extracurricular activities have improved socio-emotional functioning as exemplified by higher levels of self-esteem, positive relations with peers, involvement in sociopolitical activities, educational aspirations, and perceived self-control in life, and lower levels of delinquency rates (Holland & Andre, 1987). The enhanced

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functioning contributes to students’ academic achievement. Students with higher levels of cultural participation may also do better in school because the determinants of cultural participation represent other attributes that are beneficial to academic achievement. To illustrate, Mudiappa and Kluczniok’s (2015) study found that parents’ possession of home cultural resources, parents’ educational aspirations for their children, parents’ reading habits, and parents reading to their children predicted their cultural participation. Nonetheless, the evidence on the relationship between cultural participation and student achievement is mixed, with learning benefits accruing to younger as opposed to older children (e.g., Iruka et al., 2014) and ethnic majority as opposed to minority students (Hvistendahl & Roe, 2004). Home reading habits are more strongly associated with parental educational levels than the reading socialization climate at home (Nagel & Verboord, 2012). Some studies found that home reading is positively related to student achievement (Yeo, Ong, & Ng 2014) while others reported a negative relationship between the two variables (Aram, Korat, & Hassunah-Arafat, 2013; Driessen, 2001). There are nuances to the pattern of results. For example, studies measuring reading with different indicators, such as parents teaching a child how to read, parent–child shared reading, child reading independently, parent–child reading informational materials together, and child asking to read or to be read (Yeo et al., 2014) are more successful in predicting students’ learning outcomes than studies relying on only one indicator, such as mother–child shared book reading (Aram et al., 2013) or parental reading behaviors (Driessen, 2001). Gauvain, Savage, and McCollum (2000) reported another interesting finding—that European-American and Hispanic second graders’ reading alone in the afternoon (but not evening) was related to their reading achievement. Parent–child discussions on cultural and school topics is another indicator of cultural capital. Topics discussed include highbrow culture, sociopolitical issues, children’s school programs and activities, children’s school progress and achievements, children’s educational plans, and even parental academic encouragement for children. Results on the relationship between parent–child discussions and student achievement are inconclusive, ranging from positive (Hvistendahl & Roe, 2004; Tramonte & Willms, 2010), non-significant (Lee & Bowen, 2006), to negative (Peng & Wright, 1994) relationships. Furthermore, older students (e.g., eighth graders; Hvistendahl & Roe, 2004; Tramonte & Willms, 2010) appeared to benefit more from parent–child discussions than younger students do (e.g., third to fifth graders; Lee & Bowen, 2006). Results are also more significant when student achievement is measured using test scores (Hvistendahl & Roe, 2004; Tramonte & Willms, 2010) as compared to teacher-reported grades (Lee & Bowen, 2006). Children’s own educational expectations (i.e., the highest educational level children expect themselves to attain) and parental educational expectations for their children are influenced by many factors. These factors include adolescent intellectual ability and prior academic achievement, adolescents’ academic interactions with parents and teachers, parental education, parental expectations of their children, parenting quality, and parental involvement (Marjoribanks, 1998; Rimkute, Hirvonen, Tolvanen, Aunola, & Nurmi, 2012). Compared to other cultural capital indicators, educational expectations exhibit one of the strongest positive associations

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with students’ learning outcomes (Hammouri, 2004; Lee & Bowen, 2006; Phillipson, 2009). Parental home involvement may include parents providing cognitive and academic stimulation, helping their children with homework, adopting achievement-oriented or autonomy-supportive practices, structuring the home environment, and providing emotional responsivity to their children (Iruka et al., 2014; Karbach, Gottschling, Spengler, Hegewald, & Spinath, 2013; Manolitsis, Georgiou, & Parrila, 2011; Peng & Wright, 1994; Puccioni, 2015; Yeo et al., 2014). Parents’ involvement signals their emphasis on their children’s academic achievement and compliance with teachers’ requests for parental participation (Lareau, 1987). Therefore, teachers may perceive parental involvement positively. However, results showed inconclusive results for the association between parental involvement and students’ learning outcomes, ranging from positive (Iruka et al., 2014; Yeo et al., 2014), non-significant (Manolitsis et al., 2011; Puccioni, 2015), mixed (Karbach et al., 2013), to negative (Peng & Wright, 1994) relationships. Parental home involvement conceptualized as engagement of and support for children in their learning (Yeo et al., 2014) appears to benefit student learning more than alternative conceptualizations of parental involvement as involving non-academic activities (Puccioni, 2015) or parental behaviors restricting student autonomy (Karbach et al., 2013). Parental school involvement includes parents communicating with schools, participating in school activities, attending parent meetings and parent–teacher conferences, volunteering at schools, visiting children in schools, and showing trust in schools (Clinton & Hattie, 2013; Johnson & Hull, 2014; Lee & Bowen, 2006; Moon & Lee, 2009; Niia, Almqvist, Brunnberg, & Granlund, 2015; Phillipson, 2009). Results on the association between parental school involvement and students’ learning outcomes are inconclusive, ranging from positive (Lee & Bowen, 2006), non-significant (Johnson & Hull, 2014; Moon & Lee, 2009), negative (Niia et al., 2015), to mixed (Clinton & Hattie, 2013; Phillipson, 2009) results. Studies conceptualizing parental school involvement as reactionary to unsatisfactory student school performance (Niia et al., 2015), and measuring parental school involvement using teacher (Niia et al., 2015) as opposed to parent data (Johnson & Hull, 2014; Moon & Lee, 2009), are more likely to report negative associations. Another nuanced finding is that studies measuring student achievement using test scores (Johnson & Hull, 2014; Moon & Lee, 2009) vis-à-vis teacher grades (Lee & Bowen, 2006) are more likely to report non-significant relationships. Some researchers use parental educational attainment as an indicator of cultural capital. Most studies showed a positive association between parental educational attainment and students’ learning outcomes (Baker, 2014, 2015; Baker, Cameron, Rimm-Kaufman, & Grissmer, 2012; Zhao, Valcke, Desoete, & Verhaeghe, 2012) although there are very few studies that reported contrary results (Zhao et al., 2012). Parental education benefits students’ learning outcomes through many mediating pathways, including cultural participation (Iruka et al., 2014), child behavioral regulation (Sektnan, McClelland, Acock, & Morrison, 2010), parenting, maternal language stimulation, home environment (Iruka et al., 2014; Myrberg & Rosén, 2009;

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Zadeh, Farnia, & Ungerleider, 2010), and children’s educational aspirations (Dubow, Boxer, & Huesmann, 2009). Results of a recently published meta-analysis (Tan, 2017b) involving 155 effect sizes related to 15 different cultural capital variables from 41 studies published between 1981 and 2015 showed that these myriad cultural capital variables had different effect sizes for students’ academic achievement. The 15 cultural capital variables were access to home educational resources, access to home cultural resources, children’s cultural participation, parent and child cultural participation together, children’s reading, parents’ reading, parent and child reading together, parent–child discussions, children’s educational expectations, parents’ educational expectations of their children, parental home involvement, parental school involvement, maternal education, paternal education, and parental education (e.g., higher of father or mother’s education). The effect size used in the analysis was Pearson’s correlation coefficient, r. Results of Tan’s (2017b) meta-analysis showed that the mean cultural capital effect size was significantly different from zero at .16. Seven of the effect sizes for specific cultural capital variables were significantly different from zero. These effect sizes ranged from small to medium. More specifically, home educational resources (r = 0.23), access to home cultural resources (r = 0.23), parents’ and children’s cultural participation (r = 0.17), parent–child discussions (r = 0.11), and maternal education (r = 0.29) had small effect sizes while parental educational expectations for children (r = 0.38) and parental education (r = 0.30) had medium effect sizes. The results affirm the contribution of cultural capital to students’ academic achievement and indicate that cultural capital is a multifaceted construct with some aspects having a greater effect than others on students’ academic achievement.

2.1.4 Active Generation of Cultural Capital Fourth, to add to the complexity, cultural capital is not static in that individuals can actively generate more of it. Scholars of the concerted cultivation parenting strategy in the Lareau tradition epitomize this school of thought portraying middle-class parents as proactively seeking maximum benefits for their children’s learning by their parenting strategies and assertive engagement with school personnel. Researchers guided by the DiMaggio tradition take the contrarian perspective that highbrow cultural participation is valued by society and inexorably associate this form of cultural capital with higher SES families. Middle-class parents practicing concerted cultivation seek to maximize their home advantages for their children’s learning (instead of leaving it to chance) and strategically align their home practice with school evaluation (Lareau, 2002). They therefore not only facilitate their children’s learning of school materials which lower SES parents find difficult to accomplish, but also contribute to a secondary level of educational inequality (Boudon, 1974) when they intervene assertively in school matters, actively participate in school events, and effortlessly replicate school educational activities in the home domain (Lareau, 2000). Besides parents, children may also

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actively seek educational returns from the generation of their own, in addition to their parents’, cultural capital (Calarco, 2011, 2014; Chin & Phillips, 2004; Hadley, 2009; Morimoto & Friedland, 2013). For example, they may display the necessary temperaments or employ interaction strategies to gain teachers’ attention and secure learning benefits in class (Calarco, 2011, 2014; Chin & Phillips, 2004).

2.1.5 Habitus—the Glue of It All The conceptual diversity associated with cultural capital—different states of cultural capital, highbrow cultural participation and familiarity with schools’ evaluation standards, and active generation of cultural capital—is theoretically plausible when we consider the notion of habitus as the common denominator underlying different cultural capital manifestations in Bourdieu’s complete cultural capital theory. According to Bourdieu (1979, 1986), children need to be inculcated with the requisite habitus, enduring and transposable, for the intergenerational transmission of social privilege. Some scholars have deemed habitus as the most nebulous construct in cultural capital theory (Reay, 2004b; Winkle-Wagner, 2010). Habitus has been operationalized in myriad ways, including academic and career expectations, self-beliefs, and the value placed on education (Dumais, 2002; Gaddis, 2013; Horvat & Earl Davis, 2011; Reay, 1995). Most importantly, habitus is subliminal, thereby transcending categories of manifest attributes, and it operates as a matrix of perceptions, appreciations, and actions constituting a particular “lifestyle” (Bourdieu, 1977, 1979). It is both enabling—enabling individuals to conceive and generate different possible actions—yet constraining—in terms of limiting individuals’ perceptions of possibilities (Bourdieu 1990a). It is a product of an individual’s prior socialization and life history but is also malleable in response to new experiences (Bourdieu, 1990b; DiMaggio, 1979).

2.2 Cultural Capital and Fields The complexity of cultural capital can be appreciated when we examine it in the context of social fields in which it is recognized (Krarup & Munk, 2016). The inextricable association between cultural capital and fields cannot be overstated, given that individuals’ qualities are at best “resources,” and the resources need to be converted to “capital” that yield returns to their bearers in the field. Furthermore, since the value of cultural capital is contingent on social relations in the field, it can be inferred that there may be different forms of cultural capital that are valued in different fields. Social reproduction theorists also assert that underlying relations in fields are relatively impervious to social change (i.e., relational stratification). Therefore, we risk making wrong inferences on social mobility for students from lower SES families

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when we find associations between cultural capital and these students’ learning outcomes if we do not compare the distribution of this cultural capital for students from different SES families. These points are elaborated in the following sections.

2.2.1 Distinguishing Resources from Capital First, the distinction between resources and capital is neither pedantic nor semantic. Krarup and Munk (2016) cogently argued that researchers should shift their focus from independent effects of individual cultural resources to the social structure of these resources in the field. Only then will they be able to unpack and elucidate the social reality underpinning how these resources are invested, reconverted, and reproduced as cultural capital. Notwithstanding this argument, most researchers do not appear to examine cultural capital in the context of social fields (Sallaz & Zavisca, 2007; Savage & Bennett, 2005). For example, only nine percent of all articles published in four major American sociological journals citing Bourdieu are framed using his complete theory incorporating the concepts of cultural capital and fields, among others (Sallaz & Zavisca, 2007). When researchers analyze cultural capital variables in isolation, they are assuming that social forces can be alluded from the effects of the variables. However, social forces emanate from social structures, so the analytical paradigm must incorporate the dialectical relationship between particular resources of individuals (e.g., parents and students) and social structures. It, therefore, pays to heed Bourdieu’s (1984) cautionary note articulated in Distinction: the particular relations between a dependent variable (such as political opinion) and so-called independent variables such as sex, age and religion, or even educational level, income and occupation tend to mask the complete system of relationships which constitutes the true principle of the strength and form of the effects registered in any particular correlation. (p. 103)

2.2.2 Relational Value of Cultural Capital Second, attention on the nexus involving cultural capital and fields recognize that the value of cultural capital is contingent on social relations in the field (Bourdieu, 1985; Martin, 2011). Put another way, individuals are influenced not so much by their objective attributes as they are by their relative position in the social structure of the attributes. For example, students’ social class is not determined by their parents’ education, family income, and parents’ occupational status per se but by the relative distribution among these variables in society (Bourdieu, 1984). Having said that, individuals can exercise agency in their struggles to influence the social evaluation of the price of these demographic variables.

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Martin (2003) employed a gravity field to illustrate the idea of relational value of cultural capital. He argued that it is erroneous to say that heavier objects exhibit a greater falling velocity because of its larger mass or because of the influence from the gravity field per se. Rather, it is more accurate to conceive of the effect as a result of the interaction between the object and the gravity field. Therefore, It would be wholly mistaken to locate in any one of these factors [educational level and social origin] an ‘efficacy’ which only appears in a certain relationship and may therefore be cancelled out or inverted in another field or another state of the same field … because what is ultimately at stake … is the transformation of the price-forming mechanisms defining the relative values of the cultural productions associated with educational capital and social trajectory … (Bourdieu, 1984, p. 94)

Sometimes, the claim is made that specific aspects of cultural capital are “effective” because they are demonstrated to be correlated to students’ learning outcomes. This implies that these aspects of cultural capital are in themselves value generators in education. However, the fact may be that they are but means for the production of value that are sanctioned and rewarded in the education system (Krarup & Munk, 2016). In field theory, what relates the individuals’ cultural capital and the social space, together is habitus: the complicity between two states of the social… between the history objectified in the form of structures and mechanisms (those of the social space or of the fields) and the history incarnated in bodies in the form of habitus … (Bourdieu, 2000, p. 150f)

2.2.3 Relational Stratification Recognition of the role of fields in ascertaining the relative worth of cultural capital brings us to the third point—relational stratification. Relational stratification underscores the resilience of the underlying structure of relations in the midst of social changes in fields (Bourdieu, 1996). To illustrate, mass schooling has been implemented in many education systems worldwide in the recent decades. This development is accompanied by greater societal and family premium on education, more educational and cultural resources in homes, greater access to public libraries and online learning resources, and more private enrichment classes for all. The consequence is that more individuals across the SES spectrum have an opportunity to participate in formal education and even graduate from university. However, there is evidence that even in university education, students from higher SES families are more likely to take prestigious courses (e.g., medicine or law) within the same university or attend more prestigious universities (e.g., Ivy League universities in the United States or OxBridge in the UK) as compared to peers from disadvantaged families. Perfect educational equality is therefore a remote possibility because the scale for competition and comparison has moved for high-achieving students from privileged families to maintain their educational advantage and relative social standing (Munk, 2009).

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2.3 Cultural, Economic, and Social Capital While the focus of this book is on the role of cultural capital in students’ academic achievement, it is important to recognize non-cultural forms of capital in Bourdieu’s theory. Indeed, Bourdieu (1986) conceptualized family capital as comprising different yet related types, namely cultural, economic, and social capital. Economic capital, or what some refer to as family wealth, comprises familial net worth (current value of marketable assets less current value of liabilities) and financial wealth (net worth minus net equity in owner-occupied housing) (Wolff, 1998, 2002). Social capital, according to Bourdieu (1986), is “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance and recognition” (p. 248). Scholars such as Coleman (1988) and Putnam, Leonardi, and Nanetti (1993) have sought to further elucidate the concept of social capital. Waithaka (2014) identified social networks and social exchanges as the two key components of social capital. Social networks refer to the nexus of connections in an individual’s social relations while social support refers to exchanges between individuals eventuating in transfers of instrumental, symbolic, or informal resources. Configurations of the three forms of capital eventuate in families’ social positions as elucidated in Bourdieu’s family investment model comprising three orthogonal axes (Weininger, 2005). The first axis encapsulates the total volume of cultural, economic, and social capital a family possesses, so higher SES families (with the most resources) will be positioned at the top of the axis. The second axis recognizes differences in the composition of capital possessed characterizing class positions. The third axis captures the stability of change of the total volume and specific composition of capital possessed, so families can over time have more or less capital (upward or downward mobility, respectively) or have different combinations of capital (e.g., through acquisition of new forms of capital or conversion from one form of capital to another). Relatedly, Waithaka (2014) argued that higher SES parents can use a specific form of capital or a combination of more than one form of capital to benefit their children in educational and other outcomes. The three forms of capital are useful in identifying how social origins contribute to students’ academic achievement in different societal contexts. For example, possessing cultural capital in terms of familiarity with school evaluation standards and occupational demands of the job market benefits students in meritocracies (Tan, 2017c). In countries with lower socioeconomic inequality, students’ access to quality educational resources, made possible by the possession of economic capital, may be an important determinant of academic success. Conversely, students in more unequal countries need a combination of economic and non-economic capital (e.g., cultural capital) to excel academically (Tan, 2015). In more collectivistic societies (e.g., Confucian heritage cultures), the collective emphasis on learning reinforced by students’ network of family members, relatives, friends, and teachers (i.e., social capital) helps to motivate students to commit their time and energy to achieving academic success (Tan & Liu, 2018). In technologically advanced societies, students

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need both economic capital for accessing and cultural capital for harnessing the potential of information technology to negotiate the employment of technology to support their learning (Tan & Hew, 2017, 2018).

2.4 Concluding Remarks This chapter is dedicated to arguing for a refined understanding and appreciation of the conceptual richness of cultural capital. To achieve this aim, it has discussed two important characteristics of the construct, namely the complexity of cultural capital, and the inextricable association between cultural capital and social fields. The complexity of cultural capital is demonstrated by understanding it as comprising three states, as having myriad meanings beyond the original highbrow cultural consumption Bourdieu has articulated in his early writings, as being represented by a proliferation of indicators in research studies, as being promoted by active generation of the construct by relevant actors, and as being conceptually coherent by virtue of the embodiment of habitus. As for the inextricable associations between cultural capital and social fields, the chapter has discussed the importance of distinguishing cultural resources from cultural capital, relational value of cultural capital, and the idea of relational stratification as entrenching the cultural advantages of students from socioeconomically privileged families. Moving on, Chap. 3 addresses the potentialities for cultural capital researchers adopting quantitative, or at least mixed, methodologies to harness the rich data in PISA to examine questions related to the cultural capital—students’ academic achievement relationships.

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Chapter 3

Cultural Capital and PISA

Abstract This chapter highlights the immense research possibilities for cultural capital researchers to use PISA data to examine the relationships between cultural capital and students’ academic achievement. It recognizes the burgeoning trend of sociologists to employ quantitative methods and analyze data from international large-scale assessments in their research designs. It then introduces PISA as a source of openaccess “big data” in international large-scale assessment in educational research. It provides an objective evaluation of the influence of and criticisms against the role of PISA in education policymaking in many education systems worldwide. After that, it outlines the benefits of PISA in contributing to educational development and scholarship. In particular, it explicates the different cultural capital variables that are available for analysis from Student Questionnaire, Student ICT Questionnaire, Student EC Questionnaire, and Parent Questionnaire in PISA. This summary of PISA variables will be a useful resource for researchers open to exploring PISA data for their research on educational inequality. Keywords Academic achievement · Cultural capital · International large-scale assessment · PISA · Program for international student assessment · Quantitative · Research design This chapter recognizes the emerging trajectory of sociologists, including scholars researching on cultural capital theory, employing quantitative methods to examine issues of educational inequality and reproduction. In particular, it discusses the potential of interrogating the rich data in PISA (a source of open-access “big data” in international large-scale assessment in educational research) to examine the relationships between different aspects of cultural capital and academic achievement of students from different countries.

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 C. Y. Tan, Family Cultural Capital and Student Achievement, SpringerBriefs in Education, https://doi.org/10.1007/978-981-15-4491-0_3

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3.1 Influence of International Large-Scale Assessments International large-scale assessments (including PISA) have a tremendous impact on educational policymaking and practice (Heyneman & Lee, 2014). They influence educational practice in areas pertaining to pedagogy, teacher training, class size, hours of instruction, and technology use. Their impact is global, affecting both developed (e.g., Organization for Economic Cooperation and Development or OECD countries) and developing (e.g., sub-Sahara Africa and Latin America) regions and specific countries. In particular, they provide a cost-effective means for developing countries to improve their methods of assessments. They also enable researchers, policymakers, and educators to make generalizations about school system structures, identify specific research areas, and develop new research techniques and unravel new variables. Wagemaker (2014) affirmed the impact of international large-scale assessments by analyzing the proliferation in participation of different countries in these assessments; intense discourse on educational quality related to these assessments; changes in education policies, curriculum, and teaching in many education systems following these assessments; capacity-building of participants of these assessments and research endeavors involving data collected and analyzed in these assessments; and global and donor responses following these assessments.

3.2 PISA PISA measures “how well 15-year-old students approaching the end of compulsory schooling are prepared to meet the challenges of today’s knowledge societies” (OECD, 2012, p. 22). PISA assesses students on their ability to use their knowledge and skills to address real-life challenges instead of their mastery of the school curriculum (OECD, 2007). Each wave of PISA focuses on a major and two minor subject domains. For example, reading was allotted 60% of the testing time while mathematics and science were each allotted 20% of the testing time in PISA 2009 focusing on reading achievement (OECD, 2012). PISA’s sampling strategy is to target 15-year-old students in grade 7 or higher (OECD, 2012). It employs a two-stage stratified sampling design. In the first stage, a sample of at least 150 schools are selected within each country with the school’s probability of selection proportional to its size. In the second stage, a random sample of 35 15-year-old students are selected within each school identified in the first stage. A minimum of 4,500 students are selected within each country. To ensure representativeness, students or schools attended by students with severe intellectual/functional disabilities or with insufficient linguistic skills are excluded (OECD, 2014). PISA is conducted once every three years, with 43 participating countries in 2000 increasing to 72 countries in 2015.

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3.2.1 Influence of PISA Despite its influence on education policymaking, there has been no international assessment of student achievement as contentious as PISA. To illustrate, leading education researchers and educators published an open letter in The Guardian in the UK in 2014 to ask for the immediate suspension of PISA (Meyer et al., 2014). The letter’s authors cited problems with PISA, namely that PISA has narrowed the curriculum and promoted standardized testing in many countries, that it has motivated countries to adopt short-term fixes to improve their international rankings instead of enduring changes to teaching-learning, that it has failed to ensure democratic participation among countries, that it has eventuated in the formation of international profit-driven companies obsessed with testing, and that it has compromised teacher autonomy. The open letter then sparked further debates on the validity of PISA (Harris & Zhao, 2015; Sahlberg & Hargreaves, 2015). Sahlberg and Hargreaves (2015) published an open defense of PISA in The Washington Post in the United States, citing how PISA has informed education policy discussions; clarified how education systems should eschew market competition between schools, deemphasis on university-based training for teachers, and curricular standardization; underscored the importance of teacher professional autonomy and collaboration; and introduced equity as an important policy goal alongside quality of learning. Sahlberg and Hargreaves (2015) drew a fierce rebuttal from Harris and Zhao (2015) that is also published in The Washington Post. In their letter, Harris and Zhao (2015) reiterated their concerns about the validity and reliability of PISA data, the presumed homogeneity of students’ academic achievement in high-performing countries, and cultural insensitivity of standardized testing in PISA. Both detractors and supporters have to acknowledge that PISA has influenced public perceptions of national education systems worldwide since its inception in 2000 (Hopmann, Brinek, & Retzl, 2007). The impact of PISA is evident in PISA shocks in countries whose students did not perform well relative to peers in other countries, including Denmark (Egelund, 2008), Finland (Dobbins & Martens, 2012), Germany (Ertl, 2006), and Japan (Takayama, 2008), which often precipitate in educational reforms to raise standards and national competitiveness. To illustrate, Finland received the lion share of global attention when its students topped the rankings in PISA 2000, 2003, and 2006. Education researchers and policymakers tried to learn the critical success factors contributing to Finland’s educational success. Movies, books, and touring speakers introduced and promulgated the Finnish education model (Sahlberg, 2011; Wagner & Compton, 2011). However, when Finland was supplanted by Shanghai in the top rankings in PISA 2009 and 2012, the media concluded that the Finnish education system was dysfunctional and started looking to Shanghai to unravel the latter’s critical success factors (Cheng 2010; Sahlberg, 2013; Sellar & Lingard, 2013). Sellar and Lingard’s (2014) interviews with OECD, International Association for the Evaluation of Educational Achievement, and English and Australian education system personnel, and documentary analysis showed that OECD has been expanding PISA in terms of the scope of what it measures, the coverage of different countries,

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systems and schools, and its influence on education policy. OECD has also built on the PISA framework to investigate new areas as exemplified by the Programme for International Assessment of Adult Competencies and PISA-based Tests for Schools. Andreas Schleicher from PISA claimed in a testimony before the US Senate Education Panel in 2010 that the United States could gain tens of trillions of dollars in economic value if its students were to improve in their PISA performance to reach Poland’s standards (Dillon, 2010). Chester Finn, former US Assistant Secretary of Education, likened Shanghai students’ outstanding performance relative to US students’ in PISA 2009 to a Pearl Harbor Day attack and urged his country to improve its education system (Finn, 2010).

3.2.2 Criticisms Against PISA There are many criticisms against PISA. These criticisms relate to curricularPISA congruence, causality, contextualization, measurement, educational decisionmaking, accountability, and autonomy. First, student performance in PISA may be influenced by the extent of congruence between their national curriculum and what is tested in PISA (Solano-Flores & Wang, 2015). For example, the illustrations that accompany science test items in PISA may benefit Shanghai students more than American and Mexican students because the former are taught science concepts using illustrations to a greater extent than American or Mexican students are (Solano-Flores & Wang, 2015). Second, studies that attempt to identify factors that contribute to student performance in PISA may suffer from the issue of reverse causation because of the crosssectional nature of the data. For example, Artelt and Schneider’s (2015) analysis of PISA 2009 data found strong correlations among students’ knowledge and use of meta-cognitive strategies, and their reading achievement. However, the authors themselves acknowledged that it is equally possible that competent readers had greater knowledge and usage of these strategies instead of less proficient readers benefiting from the strategies. Third, Ercikan, Roth, and Asil (2015) demonstrated using PISA 2009 data for five countries with different levels of student reading achievement (Canada, ShanghaiChina, Germany, Turkey, and the US) that there are many factors influencing students’ reading performance. These factors include learning-related variables such as reading enjoyment and out-of-school enrichment activities and other contextual variables as exemplified by high school graduation rates and school disciplinary climate. Therefore, the researchers cautioned against a simplistic reliance of PISA rankings as indicators of educational quality and questioned the applicability of copying “best practices” from high-performing countries to improve student achievement. They argued that in establishing consequential validity, PISA must demonstrate that country scores are reliable, that country scores represent sufficient indicators of educational system quality across countries, and that student performance is homogenous within each country.

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Fourth, Rutkowski and Rutkowski (2016) highlighted problems with the sampling of participants (sampling errors), specifications of the achievement estimation model (measurement errors), and measurement of trends in student performance (linking errors) in PISA. For example, problems with sampling include poorly reported sample exclusion rates that may exceed international agreed thresholds and the inability of PISA’s sampling strategy to arrive at its intended sample. Problems with the achievement estimation model include poorly supported assumption of measurement invariance of its items across cultures and education systems, and the effects of missing and erroneous contextual background data on achievement estimates. Fifth, Tan and Dimmock (2018) averred that transnational influences such as PISA supplant national organizations to shape global educational reform agendas by emphasizing evidence-based policy and practice to rationalize education, promulgating standardized solutions to address all educational challenges, and implying that countries can achieve educational quality by pursuing international educational standards. Sixth, Labaree (2014) argued that PISA gives rise to an educational accountability system that reduces the aims of education to cognitive skills that are deemed to be economically useful but that may not have been taught in national curricula. Lastly, Meyer and Benavot (2013) cautioned sovereign countries against ceding their educational autonomy to PISA which promotes standardization in pedagogy, curriculum, and assessment.

3.2.3 Strengths of PISA The reservations against PISA must be balanced with the contributions it has made to educational research and policymaking. For example, Chiu (2015) unraveled from his analysis of PISA data how higher SES parents engage in rent-seeking that elevates their children’s mathematics achievement scores at the expense of those of less privileged children. He also found that students in countries with less family or school inequality had higher levels of achievement. However, the twist came in the form of the finding that rent-seeking behaviors adversely affect the achievement of all students, regardless of their family SES. Admittedly, these insights are not easily obtainable from primary studies involving only small samples of students. PISA examines both the quality and equity of students’ achievement outcomes (Schleicher, 2009). For the latter, it investigates within and between-school socioeconomic variation in student performance. This strategy enables PISA to ascertain the extent to which education systems moderate the relationships between students’ SES and achievement. To illustrate, Schleicher (2009) outlined ten lessons corresponding to fair and inclusive education design, practices, and resources drawn from ten countries that participated in PISA 2006 for improving equity in students’ educational outcomes. More specifically, countries can tweak the design of their education systems by minimizing early tracking and delaying it wherever possible, calibrating school choice, providing curricular alternatives and preventing student dropout in upper secondary education, and providing opportunities for lifelong learning to

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adults. In terms of fair and inclusive practices, countries can provide support for students facing learning difficulties and minimize student repetition of grades, foster school–home collaboration to help disadvantaged families, and accommodate learners’ diversity within the mainstream education system. As for fair and inclusive resourcing, countries can strengthen early childhood and basic education, be compensatory in the allocation of resources to needy students and schools, and set specific targets related to improving equity in education.

3.3 Cultural Capital Variables and PISA Questions An examination of the PISA survey instruments, namely student and parent questionnaires, shows that they contain many questions that tap into different aspects of cultural capital. These aspects include home educational and cultural resources; parental education; parent and child’s attitudes toward reading, learning mathematics, and learning science; educational expectations; cultural participation; parent–child academic and cultural discussions; supervision of child’s learning; parental provision of home support for the child’s learning; child’s engagement in reading, science, and mathematics learning activities beyond the school; and parental school involvement in the child’s education. PISA data on these variables coupled with data on students’ academic achievement provide immense opportunities for researchers examining the relationships between cultural capital and students’ academic achievement. The survey questions (Tables A.1–A.14 in Appendix) are discussed as follows. First, data for PISA 2000–2015 survey questions on students’ access to educational (e.g., quiet place to study) and cultural (e.g., poetry books) resources at home can be used as indicators of objectified cultural capital (Table A.1). Additionally, in PISA 2009 and 2012, students were asked about the frequency in which they used digital devices in different ways to support their learning outside of school (e.g., browsing the Internet for schoolwork or to follow up lessons). Data on students’ usage of information technology can be used in conjunction with those on their access to technology outside school to unravel how cultural capital is associated with students’ achievement in the digital domain (e.g., digital divides debate). Next, PISA 2000–2015 asked students (and parents in some waves) for information on their mother and father’s highest educational attainment (Table A.2). Data on parental educational attainment can be used to measure the institutionalized form of cultural capital. PISA also asked specific questions that correspond to the focal subject areas assessed in different waves. • For example, data on students’ attitudes toward reading (e.g., “I read only if I have to”) were collected in PISA 2000 and 2009 (Table A.3). In addition, data on parents’ reading attitudes (e.g., “Reading is one of my favorite hobbies”) were collected in PISA 2009.

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• Data on students’ attitudes toward learning mathematics (intrinsic and extrinsic motivation; e.g., “I do mathematics because I enjoy it”) were collected in PISA 2003 and 2012 (Table A.4). PISA 2012 also asked a question on students’ perceptions of their parents’ attitudes toward mathematics (e.g., “My parents believe it’s important for me to study mathematics”). There is another question for parents on their perceived need for mathematics skills in the job market in PISA 2012 (e.g., “Employers generally appreciate strong mathematics knowledge and skills among their employees”). • Data on students’ attitudes toward learning science (e.g., “Advances in usually improve people’s living conditions”) were collected in PISA 2006 and 2015 to correspond with the assessment focus in these waves (Table A.5). Parents were asked about their perceived need for science skills in the job market (e.g., “It is important to have good scientific knowledge and skills in order to get any good job in today’s world”). In PISA 2006 and 2015, students were also asked about their enjoyment in learning science (e.g., “I generally have fun when I am learning topics”) while parents were asked about their perceptions on the value of science to them and society (e.g., “I find that helps me to understand the things around me,” “Advances in usually bring social benefits”). These questions on students and parents’ attitudes toward learning (reading, mathematics, and science) provide data on embodied cultural capital and create possibilities for examining intergenerational transmission of learning attitudes. Students (in PISA 2003 and 2009) and parents (in PISA 2012) were asked questions on educational expectations for themselves and their children, respectively (Table A.6). Data from these questions can be used to measure habitus underpinning cultural capital. Students in PISA 2000 responded to a question asking them about their cultural participation (e.g., “Visited a museum or art gallery”; Table A.7). Data from this question enable researchers to examine students’ familiarity with highbrow arts as a form of cultural capital. Parents provided data on their academic and cultural discussions with their children (e.g., “Discuss how well my child is doing at school”) in PISA 2009, 2012, and 2015 (Table A.8). A similar question asked students on parent–child discussions in PISA 2000. Students responded to a question asking if their family members worked with them on their schoolwork together in PISA 2000 (Table A.9). Parents were asked about the nature of their home support for their children’s learning (Table A.10) when the latter were young (PISA 2009; e.g., “Read books”) and when the latter were adolescents (PISA 2015; e.g., “I am supportive of my child’s efforts at school and his/her achievements”). PISA collected information on students and parents’ engagement in different learning activities for reading, mathematics, and science. • In PISA 2000 and 2009, students responded to a question asking them about the amount of time they spent on reading, a question on the different genre (e.g.,

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magazines) of materials they voluntarily read, and another question asking them if they visited the library for different purposes (e.g., “Borrow books to read for pleasure”)—see Table A.11. Additionally, students were asked for their frequency of involvement in different reading activities (e.g., “Reading emails”) while parents provided data on the time they spent reading for their own enjoyment at home in PISA 2009. • Parents in PISA 2015 were asked about the frequency with which their child at 10 years old engaged in different science learning activities (e.g., “Watched TV programmes about science”). Students responded to a similar question on their science learning activities in PISA 2006. Table A.12 summarizes the contents of these questions. • Students provided information on the frequency with which they engaged in different mathematics learning activities (e.g., “I talk about mathematics problems with my friends”) in PISA 2012 (Table A.13). Parents responded to a question on their participation in different school-related activities (e.g., “Discussed my child’s behaviour with a teacher on my own initiative”) in PISA 2009, 2012, and 2015 (Table A.14). Data from these questions provide a measure of parents’ school involvement as a form of cultural capital.

3.4 Concluding Remarks This chapter has argued for the immense potentialities cultural capital researchers can exploit from harnessing the rich data in PISA to examine questions related to the cultural capital—students’ academic achievement relationships. These possibilities are congruent with the emerging trajectory of sociologists opening up their methodological repertoire to embrace quantitative methods and international largescale assessments in their research. It provides a critical evaluation of PISA, namely its influence of PISA on education policies in many parts of the world, the pushback from academics and educators it has inexorably invited, and its contributions to educational development and scholarship. With this context, the chapter then provides a summary of the types of data (from Student Questionnaire, Student ICT Questionnaire, Student EC Questionnaire, and Parent Questionnaire) pertaining to myriad cultural capital variables that PISA collects and makes available publicly for researchers to analyze. Scholars employing cultural capital theory as an explanatory heuristic for their research on educational inequality and reproduction will find this resource useful. Moving on, Chap. 4 will present a review of studies analyzing the relationships between cultural capital and students’ academic achievement using PISA data collected from different waves (2000–2015) and discuss key insights on the cultural capital construct gleaned from these studies.

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Sahlberg, P. (2011). Finnish lessons: What can the world learn from educational change in Finland?. New York, NY: Teachers College Press. Sahlberg, P. (2013, December 8). The PISA 2012 scores show the failure of “market based” education reform. Guardian. Retrieved March 11, 2019, from https://www.theguardian.com/ commentisfree/2013/dec/08/pisa-education-test-scores-meaning. Sahlberg, P., & Hargreaves, A. (2015, March 24). The tower of PISA is badly leaning. An argument for why it should be saved. The Washington Post. Retrieved March 11, 2019, from https://www.washingtonpost.com/news/answer-sheet/wp/2015/03/24/the-tower-of-pisa-isbadly-leaning-an-argument-for-why-it-should-be-saved/?utm_term=.aa1288c6f5b7. Schleicher, A. (2009). Securing quality and equity in education: Lessons from PISA. Prospects, 39, 251–263. https://doi.org/10.1007/s11125-009-9126-x. Sellar, S., & Lingard, B. (2013). Looking east: Shanghai, PISA 2009 and the reconstitution of reference societies in the global education policy field. Comparative Education, 49(4), 464–485. https://doi.org/10.1080/03050068.2013.770943. Sellar, S., & Lingard, B. (2014). The OECD and the expansion of PISA: New global modes of governance in education. British Educational Research Journal, 40(6), 917–936. https://doi.org/ 10.1002/berj.3120. Solano-Flores, G., & Wang, C. (2015). Complexity of illustrations in PISA 2009 science items and its relationship to the performance of students from Shanghai-China, the United States, and Mexico. Teachers College Record, 117(1), 1–18. Takayama, K. (2008). The politics of international league tables: PISA in Japan’s achievement crisis debate. Comparative Education, 44(4), 387–407. https://doi.org/10.1080/03050060802481413. Tan, C. Y., & Dimmock, C. (2018). National and transnational influences on school organization. In M. Connolly, D. H. Eddy-Spicer, C. James, & S. D. Kruse (Eds.), The SAGE handbook of School Organization (pp. 414–429). London: Sage. Wagemaker, H. (2014). International large-scale assessments: From research to policy. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and methods of data analysis (pp. 11–36). Boca Raton, FL: CRC. Wagner, T., & Compton, B. (2011). The Finland phenomenon: Inside the world’s most surprising school system [Video file]. Retrieved March 12, 2019, from http://www.2mminutes.com/products/ pc/viewPrd.asp?idProduct=22&idcategory=24.

Chapter 4

Interrogating the Cultural Capital–Students’ Achievement Relationships

Abstract This chapter reviews the published literature examining PISA data to derive three key insights on how cultural capital contributes to students’ academic achievement. The first insight provides support for the argument that cultural capital is a complex construct that can be measured using different indicators, that manifests in myriad ways in different societies, that have different influences on students’ learning, and that comprises both highbrow cultural consumption and parental familiarity with school evaluation standards and future job requirements. The second insight highlights the importance of understanding the relationships between cultural capital and students’ academic achievement in a nomological framework comprising cultural capital, habitus, and social fields. The third insight is that different cultural capital variables operate conjunctively, rather than separately, to influence students’ academic achievement. More specifically, they may be mutually reinforcing each other to engender synergy, exhibiting different patterns of association with students’ academic achievement depending on the profiles of students and their families, or compromising each other in their effects. Keywords Academic achievement · Cultural capital · Familiarity with school evaluation standards · Habitus · Highbrow culture · Indicators · Social fields This chapter complements the theoretical discussion characterizing earlier chapters (Chaps. 2 and 3) by discussing results from empirical studies that have elucidated the multitudinous ways in which cultural capital contributes to students’ academic achievement. More specifically, it illustrates how researchers have harnessed the rich data in different PISA waves (from 2000 to 2015) to examine research questions pertaining to how cultural capital is associated with students’ reading, mathematics, and science achievement. Examination of results from their published studies (Edgerton, Roberts, & Peter, 2013; Hartas 2015; Tan, 2015, 2017, 2018; Tan & Hew, 2017, 2018) reveals an emerging pattern of results that provide insights on the nuanced relationships between cultural capital and students’ academic achievement. Given the sampling focus of PISA, the results to be discussed in this and the next chapter must be read with the caveat that they may pertain more to secondary school students (fifteen-year-old) than kindergarten, primary, or university students. The following

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sections discuss three insights from studies that have employed PISA data to examine the association between cultural capital and students’ learning.

4.1 Myriad Aspects of Cultural Capital Varying in Importance The first insight is that cultural capital is a complex construct comprising various aspects, some of which are more important than others in contributing to students’ learning (Hartas, 2015; Tan, 2017). To illustrate, Hartas’ (2015) study exemplified the complex nature of cultural capital by demonstrating how some aspects of different aspects of cultural capital can influence others to ultimately benefit students’ achievement. Her study aimed to (a) understand changes in patterns of parental home and school involvement when students started formal schooling in primary schools and when they were 15 years old, and (b) examine how various cultural capital variables such as parental education, parental reading habits, parent–child interactions, parental support with child’s emergent literacy, school-based parental support, and home educational resources predicted parental literacy support when students were 15 years old. Hartas (2015) analyzed data from 58,653 parents in seven OECD countries, namely, Denmark, Germany, Hungary, Italy, Korea, New Zealand, and Portugal, who participated in PISA 2009. Data comprised parental educational qualifications, availability of home educational resources, parental reading habits, parental involvement with children’s learning at the start of primary school and when children were fifteen years old, considerations informing parental school choices, and parental school involvement. More specifically, parental reading habits were measured by items asking about parents’ attitudes toward reading and their reading habits. Parental involvement when the child was starting primary school was measured by items measuring parents doing various activities with their children. Parental involvement when the child was 15 years old comprised parents having conversations with their children on a variety of topics. Considerations informing parental school choices were measured by items asking parents about social/pastoral and academic factors that influenced their decisions. Parental school involvement was measured by items asking whether parents participated in their children’s school. Regression results showed that the cultural capital variables had different levels of influence on parental literacy support of their children, accounting for a total of 84% of the variance. The top three predictors were parent–child conversations, parental literacy support at primary school, and parental reading habits. The other predictors (parental education, home educational resources, social/pastoral considerations, academic considerations, and parental school involvement) were less influential. These results indicated that cultural capital is a complex construct comprising different aspects (parental educational qualifications, availability of home educational resources, parental reading habits, parental involvement with children’s learning at

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start of primary school and when children were fifteen years old, and parental school involvement) and that some aspects are more influential than others. They also suggested that some aspects of cultural capital (parent–child conversations, parental literacy support at primary school, and parental reading habits) are more proximal than others in facilitating students’ learning. Tan’s (2017) study provided further evidence that cultural capital can be measured in different ways and that different indicators vary in their relative effects on students’ learning. Additionally, it demonstrated that cultural capital can transcend the traditional conceptualization of highbrow cultural consumption to include parental familiarity with school evaluation standards and future job requirements. More specifically, his study aimed to address two specific issues: (a) whether students from higher SES families enjoy cultural advantages from parents’ familiarity with educational evaluation standards and knowledge about job markets beyond exclusive participation in elite status culture (e.g., student highbrow cultural appreciation, tastes, and participation) in their learning (Crosnoe & Muller, 2014; Gauld & Hukins, 1980; Ma, 2009) and (b) whether these cultural advantages benefit their achievement in nonlinguistic subjects with more objective performance evaluation (Acosta & Hsu, 2014; Archer, Dawson, DeWitt, Seakins, & Wong, 2015; Aschbacher, Ing, & Tsai, 2013; Hvistendahl & Roe, 2004; Osborne, Simon, & Collins, 2003). To achieve these aims, Tan (2017) examined the relationships between seven cultural capital variables indicative of parental familiarity with school evaluation standards and future job requirements, and students’ mathematics achievement. The study analyzed data pertaining to 96,591 fifteen-year-old students from 3,602 schools in eight countries who participated in PISA 2012. The countries comprised Chile, Hong Kong, Croatia, Hungary, Italy, Korea, Macau, and Mexico. The seven cultural capital variables examined were home educational resources; parental educational attainment and occupational status; parental expectations of their children’s educational attainment, future career in mathematics and school; and parental valuing of mathematics. In particular, parental educational expectations of their children pertained to whether parents expected their children to complete a theoretically oriented tertiary or postgraduate education. Parental mathematics career expectations of their children reflected data on whether parents expected their child to enter a mathematicsrelated career. Parental academic expectations of schools were measured using school principals’ responses on the extent of pressure the schools experienced from parents to achieve high academic standards. Parental perceived importance of mathematics was measured by parents’ responses on their perceived importance of the need to have good mathematics knowledge and skills to get good jobs and of employers’ appreciation of mathematics knowledge and skills in their employees. Results of three-level, fixed effect hierarchical linear modeling (HLM) showed that the seven cultural capital variables, though all significantly predicting students’ mathematics achievement, had different degrees of association with the outcome variable after controlling for student sex, school size, and countries’ level of economic development and cultural heritage. More specifically, parental educational expectations of their children, parental mathematics career expectations of their child, and

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parental academic expectations of schools were stronger predictors of students’ mathematics achievement as compared to other cultural capital variables, namely, access to home educational resources, parental education, parental occupational status, and parental perceived importance of mathematics. To summarize, Tan’s (2017) study provided support for the argument that cultural capital is a complex construct comprising different aspects (parental educational expectations of their children, parental mathematics career expectations of their child, parental academic expectations of schools, access to home educational resources, parental education, parental occupational status, and parental perceived importance of mathematics) and that some aspects (parental educational expectations of their children, parental mathematics career expectations of their child, and parental academic expectations of schools) contribute more than others to students’ mathematics achievement.

4.2 Cultural Capital in Nomological Framework The second insight is that the relationships between cultural capital and students’ academic achievement are best understood using a complex nomological framework underscoring how cultural capital operates in concert with related concepts of habitus and fields to affect students’ learning (Edgerton et al., 2013). Edgerton and colleagues’ (2013) study clarified the roles of habitus and practice in a “structuredisposition-practice” model that explains the association between SES and students’ academic achievement. More specifically, their study aimed to, among other things, address two research questions. The first question asked if family SES influenced students’ habitus, academic practices, and academic achievement. The second question pertained to the relationships between students’ habitus, academic practices, and academic achievement. The study examined data relating to 21,948 fifteen-year-old students from 1,077 schools in ten provinces in Canada from two associated datasets, namely, the sample who participated in PISA 2003 and the 2003 Youth in Transition Survey. Family SES was measured using the highest level of parental education, highest parental occupation status, and availability of home possessions. Students’ habitus was measured by adding up students’ responses to questions asking about their expected years of schooling, dispositions toward teachers, and dispositions toward post-secondary education. Students’ academic practices were measured with items on students’ practices that contributed to academic achievement. Students’ academic achievement was measured using their PISA 2003 reading, mathematics, and science scores. Results of structural equation modeling showed that levels of students’ habitus and academic practices varied with their family SES and were differentially associated with their academic achievement. More specifically, students from higher SES families were more likely to exhibit higher levels of habitus and to be involved in academic practices. Students with higher levels of habitus, in turn, were more likely

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to exhibit more academic practices. Students’ habitus had a larger influence than their academic practices on academic achievement in all three subjects. Edgerton and colleagues’ (2013) study contributed to the literature in two ways. First, it provided a more comprehensive operationalization of habitus by including other aspects beyond students’ academic expectations (dispositions toward teachers and post-secondary education). Second, it incorporated the different, albeit related, concepts of “habitus” and “practice” to enable a more complete testing of Bourdieu’s cultural capital framework (i.e., structure as measured by SES affecting students’ habitus and academic practices, and habitus and practices influencing students’ academic achievement).

4.3 Conjunctive Effects of Cultural Capital The third insight is that different cultural capital variables operate conjunctively, rather than separately, to influence students’ academic achievement (Tan, 2015, 2018; Tan & Hew, 2017, 2018). This pattern of association happens in three ways.

4.3.1 Synergistic Effects First, the simultaneous presence of different aspects of cultural capital reinforces each other to synergistically benefit students’ learning, as demonstrated in Tan (2015) and Tan and Hew’s (2017) studies. Tan (2015) examined the moderating effects of parental education (institutionalized cultural capital) on the relationships (a) between home educational resources (objectified cultural capital) and students’ mathematics achievement and (b) between parental educational expectations (embodied cultural capital or habitus) and students’ mathematics achievement. More highly educated parents are expected to enhance the contribution of home educational resources to student learning for different reasons. First, they are more knowledgeable about where to purchase up-to-date and effective educational resources. Second, they may have more economic capacity to purchase costly resources (Giacquinta, Bauer, & Levin, 1993; Lareau, 2011). Third, they may be more pedagogically competent in harnessing these resources to support their children’s learning. More highly educated parents are also expected to moderate the relationship between their educational expectations of their children and the latter’s learning. This is because these parents have acquired the requisite dispositions that enable them to succeed in the educational field. Therefore, they are more equipped to imbue these dispositions in their children to enable the latter to replicate their educational success. The sample in Tan’s (2015) study comprised 73,178 students and their parents from ten economies who participated in PISA 2012. These countries were classified as medium socioeconomic gradient economies (Hong Kong, Italy, Macao, Mexico, and South Korea) and high socioeconomic gradient economies (Croatia, Chile,

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Portugal, Belgium, and Hungary). Students indicated the availability of educational resources at home. Parents’ educational expectations were measured using the highest level of education that parents expected their children to attain. Parents’ highest educational attainment was measured using fathers’ and mothers’ responses on their highest level of schooling completed. One-way analyzes of variance and post hoc comparisons showed that in all economies, students with higher parental education had higher levels of home educational resources than students with lower parental education. Results of HLM showed that, for all economies, home educational resources, parental academic expectations, and parental education were all positively associated with students’ mathematics achievement. In addition, the associations between home educational resources and achievement and between parental academic expectations and achievement were stronger for families with more highly educated parents. Another study that examined the reinforcing effects of different types of cultural capital on students’ achievement is Tan and Hew (2017). The authors interrogated the association between access to home information technology (IT) resources (a type of cultural capital) and mathematics achievement for students from families with different levels of other aspects of family capital (parental human, and home academic, and cultural resources). The social construction of technology perspective underscores the moderating role of students’ perceived affordances (Hutchby, 2001) on the relationship between their access to IT resources and learning, thereby challenging the presumed determinism of IT in affecting students’ achievement (Selwyn, 2012). The sample for the study comprised 144,395 students from 7,308 schools in 22 OECD economies, namely, Australia, Austria, Belgium, Canada, Switzerland, Chile, Denmark, Finland, France, United Kingdom, Hungary, Ireland, Italy, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Portugal, Slovak Republic, Sweden, and the US. Students indicated if they had access to home IT, educational, and cultural resources. Results of two-level HLM showed that students’ access to home IT resources were positively associated with their mathematics achievement, students whose mothers were more highly educated had higher levels of mathematics achievement, and students’ access to more home IT resources and more highly educated mothers additionally benefited their mathematics achievement. Tan and Hew’s (2017) study contributes to the scholarship on digital equity by employing Bourdieu’s (1986) theory of social stratification to more accurately differentiate students according to their stock of familial capital, and then interrogating the differentiated impact of IT access on their academic achievement. The results enable us to have a more nuanced understanding of the role of technology on students’ learning. The study demonstrates how the contribution of one aspect of cultural capital (in this case, access to home IT resources) to students’ academic achievement can be enhanced by having access to more educated parents.

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4.3.2 Moderating Effects of Students and Families’ Profiles The influence of a set of cultural capital variables on students’ learning also varies depending on the profiles of students and their families (Tan & Hew, 2018). Tan and Hew’s (2018) study addressed the issue of digital divides, comprising access to (first divide) and use of (second divide) information technology in the two related spheres (schools and at home) in influencing students’ mathematics achievement. The study was premised on Selwyn’s (2004) hierarchical framework of IT use comprising four stages: theoretical access to IT, actual use of IT, meaningful use of IT, and outcomes. The first stage, theoretical access to IT, refers to the formal provision of IT at home, in school, or the community accessible to individuals who may or may not use it. The second stage, actual use of IT, refers to individuals’ usage of IT in these settings. This usage may or may not eventuate in meaningful outcomes. The third stage, meaningful use of IT, refers to individuals exercising control and autonomy over technology and content to purposefully achieve desired outcomes. The last stage refers to the IT use culminating in short, medium, or long-term outcomes. The study examined data from 3,158 students from 1,030 schools in seven Confucian heritage cultures who participated in PISA 2012. These cultures comprised Hong Kong, Japan, Korea, Macau, Shanghai, Singapore, and Taipei. Cultural capitalrelated variables examined in the study were access to home IT resources, use of home IT resources, access to parental human resources, access to home educational resources, and access to home cultural resources. Students’ use of IT for learning at home measured the frequency of their computer use outside of school for different activities. Access to school IT resources measured principals’ perceptions on the extent to which the school’s capacity to provide instruction was hindered by the shortage of IT resources. Use of IT in mathematics lessons in school measured whether a computer had been used for teaching in their mathematics lessons within the last month. Results from latent class analysis showed that the sample could be classified into three latent classes. Class 1 (60.66%) was characterized by students who had least access to home IT resources, who were least likely to use home IT for learning, who attended schools with the least IT resources shortage, and whose mathematics teachers were least likely to use IT with student participation in their lessons. Class 2 (5.35%) was characterized by students who had the highest levels of home IT resources access, who moderately used home IT for learning, who attended schools with the least IT resources shortage, and whose mathematics teachers were most likely to use IT with student participation in their lessons. Class 3 (33.98%) was characterized by students who had the most access to home IT resources (similar to Class 2), who used home IT for learning most extensively, who attended schools with the worst IT resource shortage (similar to Class 1), and whose mathematics teachers were moderately likely to use IT with student participation in their lessons. Class 1 and 2 students had parents who did not differ in their mean educational levels while Class 1 and 3 students did not differ in their mean levels of access to cultural resources at home. In contrast, the three latent classes of students did not differ in their mean

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levels of access to home educational resources. Results of one-way ANOVA and post hoc tests showed that Class 2, Class 3, and Class 1 students had the lowest, average, and highest levels of mathematics achievement. The patterns of results for levels of students’ access to home IT, use of IT at home, access to parental human resources, access to home educational resources, access to home cultural resources, and mathematics achievement suggested that these myriad cultural capital variables contributed differently to students’ mathematics achievement for the three latent classes. The results also highlighted the importance of analyzing the combination of cultural capital variables, as opposed to focusing on the independent effect of specific variables, to ascertain the cultural capital-student achievement relationship.

4.3.3 Offsetting Effects Effects of some aspects of cultural capital “cancel out” those of others, so that there may not be discernible differences on students’ academic achievement when we examine different combinations of cultural capital variables (Tan, 2018; Tan & Hew, 2017). Tan’s (2018) study clarified the relationships among family SES, parental home and school involvement, and students’ science achievement. More specifically, it (a) examined the pattern of home and school involvement practices for parents of different SES backgrounds and (b) compared how the typology of involvement practices was associated with levels of students’ science achievement. The study analyzed data on family SES, home and school involvement practices, and students’ science achievement from 5,353 students and their parents in Hong Kong who participated in PISA 2015. More specifically, family SES was measured using the index of economic, social, and cultural status summarizing student data on their parents’ highest education level, parents’ highest occupational status, and home possessions. Home involvement was measured using parents’ responses on the frequency in which they or someone else in the family were involved in different activities related to their children’s social and educational development. School involvement was measured using parents’ responses on their participation in different school-related activities comprising parents’ communication with their child’s school and parents’ participation in their child’s school activities. Results of the three-step approach in latent class analysis (Asparouhov & Muthen, 2013; Vermunt, 2010) showed that there were three latent classes characterized by different levels of SES. Parents from Class 3 (lowest mean SES) had the lowest levels of home and school involvement. Parents from Class 1 (average mean SES) had average levels of home involvement and in school organization, but they were most involved in engaging teachers in discussions. Parents from Class 2 (highest SES) had the highest levels of involvement at home and in school organization, but they only moderately engaged teachers in discussions. Put together, these results did not support the assumption that parents from higher SES backgrounds were necessarily more involved in all aspects of their children’s

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learning. Results also showed that levels of students’ science achievement were not significantly different among the three classes. These findings provided evidence that higher SES parents are not necessarily more involved than lower SES parents in all aspects, and that higher levels of parental involvement (home and school) may not eventuate in higher levels of student achievement. The study indicated that the combination of cultural capital variables (parental home and school involvement) may be more pertinent than specific variables. Tan and Hew’s (2017) study provided further insights into how the presence of one form of cultural capital affects how students benefit from having other forms of cultural capital. Their results showed that students who had access to more home educational resources did not benefit from having simultaneous access to more home IT resources and more highly educated mothers. In contrast, students with access to less home educational resources benefited from having access to more home IT resources and highly educated mothers. Similarly, students who had access to more home cultural resources did not benefit from having simultaneous access to more home IT resources and more highly educated mothers. In contrast, students with access to less home cultural resources benefited from having access to more home IT resources and highly educated mothers. In summary, Tan and Hew’s (2017) study showed how the contribution of one aspect of cultural capital (in this case, access to home IT resources) to students’ academic achievement can be mitigated by the presence of other types of cultural capital (by having access to home educational or cultural resources).

4.4 Concluding Remarks Review of the pattern of results reported from the seven studies (Edgerton et al., 2013; Hartas, 2015; Tan, 2015, 2017, 2018; Tan & Hew, 2017, 2018) examining the relationships between cultural capital and students’ academic achievement using different waves of the PISA data provides three key insights on the complex nature of cultural capital construct. The first insight is that cultural capital is a complex construct comprising various aspects that can be measured using different indicators (Hartas, 2015). Indeed, cultural capital manifests in myriad ways in different societies, transcending the traditionally conceived highbrow cultural consumption to include parental familiarity with school evaluation standards and future job requirements in contemporary educational systems that value mathematics and science competencies and skills (Tan, 2017). Furthermore, some cultural capital aspects are more important and proximal than others in affecting students’ academic achievement (Hartas, 2015). The second insight is that the relationships between cultural capital and students’ academic achievement are best understood in the context of a complex nomological framework. It underscores cultural capital operating in concert with related concepts of habitus and fields to affect students’ learning (Edgerton et al., 2013). The third insight is that different cultural capital variables operate conjunctively, rather than separately, to influence students’ academic achievement (Tan, 2015, 2018;

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Tan & Hew, 2017, 2018). In some cases, the simultaneous presence of different aspects of cultural capital reinforces each other to synergistically benefit students’ learning (Tan, 2015; Tan & Hew, 2017). In other cases, the same cultural capital variables have different patterns of association with students’ academic achievement depending on the profiles of students and their families (Tan & Hew, 2018). Effects of some cultural capital also “cancel out” those of others, so that there may not be discernible differences on students’ academic achievement when we examine different combinations of cultural capital variables (Tan, 2018; Tan & Hew, 2017). Moving on, Chap. 5 will continue this journey of interrogating published studies to derive further insights on the nuances of cultural capital. More specifically, it shows using results of published studies harnessing PISA data on how cultural capital levels and effects may vary across groups of students and therefore, explain group differences.

References Acosta, S., & Hsu, H. Y. (2014). Shared academic values: Testing a model of the association between Hong Kong parents’ and adolescents’ perception of the general value of science and scientific literacy. Educational Studies, 40(2), 174–195. Archer, L., Dawson, E., DeWitt, J., Seakins, A., & Wong, B. (2015). ‘Science capital’: A conceptual, methodological, and empirical argument for extending Bourdieusian notions of capital beyond the arts. Journal of Research in Science Teaching, 52(7), 922–948. Aschbacher, P. R., Ing, M., & Tsai, S. (2013). Boosting student interest in science. Phi Delta Kappan, 95(2), 47–51. Asparouhov, T., & Muthen, B. O. (2013). Auxiliary variables in mixture modeling: A 3-step approach using Mplus (Mplus Web Notes: No: 15). Retrieved March 11, 2019, from https:// statmodel.com/examples/webnotes/AuxMixture_submitted_corrected_webnote. Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). New York, NY: Greenwood Press. Crosnoe, R., & Muller, C. (2014). Family socioeconomic status, peers, and the path to college. Social Problems, 61(4), 602–624. Edgerton, J. D., Roberts, L. W., & Peter, T. (2013). Disparities in academic achievement: Assessing the role of habitus and practice. Social Indicators Research, 114, 303–322. https://doi.org/10. 1007/s11205-012-0147-0. Gauld, C. F., & Hukins, A. A. (1980). Scientific attitudes: A review. Studies in Science Education, 7, 129–161. Giacquinta, J. B., Bauer, J. A., & Levin, J. E. (1993). Beyond technology’s promise: An examination of children’s educational computing at home. Cambridge: Cambridge University Press. Hartas, D. (2015). Patterns of parental involvement in selected OECD countries: Cross-national analyses of PISA. European Journal of Educational Research, 4(4), 185–195. https://doi.org/10. 12973/eu-jer.4.4.185. Hutchby, I. (2001). Technologies, texts, and affordances. Sociology, 35(2), 441–456. Hvistendahl, R., & Roe, A. (2004). The literacy achievement of Norwegian minority students. Scandinavian Journal of Educational Research, 48, 307–324. Lareau, A. (2011). Unequal childhoods: Class, race, and family life (2nd ed.). Berkeley, CA: University of California Press. Ma, Y. (2009). Family socioeconomic status, parental involvement, and college major choices— gender, race/ethnic, and nativity patterns. Sociological Perspectives, 52(2), 211–234.

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Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literatureand its implications. International Journal of Science Education, 25(9), 1049–1079. Selwyn, N. (2004). Reconsidering political and popular understandings of the digital divide. New Media & Society, 6(3), 341–362. Selwyn, N. (2012). Making sense of young people, education and digital technology: The role of sociological theory. Oxford Review of Education, 38(1), 81–96. Tan, C. Y. (2015). The contribution of cultural capital to students’ mathematics achievement in medium and high socioeconomic gradient economies. British Educational Research Journal, 41(6), 1050–1067. Tan, C. Y. (2017). Do parental attitudes toward and expectations for their children’s education and future jobs matter for their children’s school achievement? British Educational Research Journal, 43(6), 1111–1130. Tan, C. Y. (2018). Socioeconomic status, involvement practices, and student science achievement: Insights from a typology of home and school involvement patterns. American Educational Research Journal, 56(3), 899–924. Tan, C. Y., & Hew, K. F. (2017). Information technology, mathematics achievement, and educational equity in developed economies. Educational Studies, 43(4), 371–390. Tan, C. Y., & Hew, K. F. (2018). The impact of digital divides on student mathematics achievement in Confucian heritage cultures: A critical examination using PISA 2012 data. International Journal of Science and Mathematics Education. Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18, 450–469. https://doi.org/10.1093/pan/mpq025.

Chapter 5

Comparing Cultural Capital Across Groups and Countries

Abstract This chapter complements the previous chapter by demonstrating other nuances of cultural capital. It continues the review of the extant literature where researchers have taken advantage of the rich data on cultural capital and students’ academic achievement in PISA datasets to examine research questions pertaining to how different aspects of cultural capital are associated with students’ reading, mathematics, and science achievement. More specifically, it discusses results from published studies harnessing PISA data demonstrating how cultural capital levels and effects may vary across groups of students with various characteristics. These characteristics are namely, gender gaps and cross-national gaps in student achievement. In particular, cross-national attributes are exemplified by the degree of masculinity and Confucian values, and socioeconomic gradients of countries. Results from these studies underscore the moderating influences of student-and societal-level factors in the cultural capital-student achievement relationship. Keywords Academic achievement · Confucian · Cultural capital · Gender · Masculinity · Socioeconomic gradient This chapter continues the review of the extant literature where researchers have taken advantage of the rich data on cultural capital and students’ academic achievement in PISA datasets to examine research questions pertaining to how cultural capital is associated with students’ reading, mathematics, and science achievement. However, it departs from the previous chapter in that it focuses on studies where researchers have examined how cultural capital levels and effects may vary across groups of students and therefore, explain group differences. These group differences are namely, gender gaps (Brozo et al., 2014; Chiu & McBride-Chang, 2006) and cross-national gaps (Brozo, Shiel, & Topping, 2007/2008; Chiu & Chow, 2010; Sebastian, Moon, & Cunningham, 2017; Tan, 2015; Tan & Liu, 2018) in students’ achievement. Cross-national differences are related to cultural attributes such as the degree of masculinity and influence of Confucian values, and socioeconomic gradients of countries. Results from these studies underscore the moderating influences of student-and societal-level factors in the cultural capital-student achievement relationship. The following sections discuss results from empirical studies using PISA data that demonstrate these moderating effects. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 C. Y. Tan, Family Cultural Capital and Student Achievement, SpringerBriefs in Education, https://doi.org/10.1007/978-981-15-4491-0_5

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5.1 Gender Gaps in Cultural Capital Effects Two studies analyzing PISA data alluded to gender gaps for cultural capital effects (Brozo et al., 2014; Chiu & McBride-Chang, 2006). First, Brozo and colleagues’ (2014) study illustrated how students’ reading engagement explained the gender gap in reading achievement in five countries. The study analyzed data from students from Finland, Germany, Ireland, Korea, and the US who participated in PISA 2009. Students’ reading engagement was measured using three variables, namely their enjoyment of reading, the time they spent reading for enjoyment, and the diversity of texts they read. Both students’ print and digital reading literacies were assessed. Results showed that, compared to boys, girls had significantly higher levels of overall reading engagement, as measured by their enjoyment of reading, the time they spent reading for enjoyment, and the diversity of texts they read. Girls also had higher levels of reading achievement as compared to boys. More specifically, girls had significantly higher levels of reading enjoyment than boys, especially in Finland and Germany. In terms of time spent reading for enjoyment, girls spent more time reading than boys did in all countries except Korea. With regard to print reading diversity, girls read more widely than boys in all countries except Germany. The pattern of results for digital reading was more nuanced. Girls (vis-à-vis boys) read more diverse types of texts in Korea and the US while the opposite pattern of results was found for Finland and Germany. There was no significant gender difference in reading diversity in Ireland. Brozo and colleagues’ (2014) study provided evidence on how boys and girls had different levels of cultural capital (in this case, reading engagement) that contributed to the gender gap in reading achievement. Chiu and McBride-Chang (2006) examined a plethora of variables to ascertain which of these explained gender differences in reading achievement across 41 countries. Their study had four specific research questions on (a) the extent to which parents’ economic and educational attainments were associated with students’ reading achievement; (b) whether the number of books at home explained differences in students’ reading achievement; (c) the extent to which students’ reading interest was associated with their reading achievement, and (d) gender differences in students’ reading achievement. The sample comprised 193,841 students from 41 countries who participated in PISA 2000. The following variables were analyzed: Student gender; country-level gross domestic product (GDP) per capita; family SES measured using maternal and paternal years of schooling and their highest occupational status; number of books at home; and students’ reading enjoyment. Results of three-level HLM showed that first, girls had higher mean levels of reading achievement than boys. Gender explained 1.9% of the reading achievement variance. Next, Log GDP per capita, family SES, schoolmates’ SES, number of books at home, and students’ reading enjoyment were all significant predictors of students’ reading achievement. Lastly, among these independent variables, only students’ reading enjoyment mediated the gender effect in reading achievement. More

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specifically, students’ reading enjoyment explained 42% of the individual gender difference in reading achievement and 21% of the school-level gender effect. Chiu and McBride-Chang’s (2006) study clarified that boys and girls have different levels of students’ reading engagement, as an aspect of cultural capital, and the extent to which this cultural capital variable explains student-and school-level gender differences in reading achievement.

5.2 Cross-National Differences in Cultural Capital Effects Brozo, Shiel, and Topping’s (2007/2008) and Sebastian and colleagues (2017) demonstrated using PISA data that the contribution of cultural capital to students’ learning vary across countries. More specifically, Brozo and colleagues’ (2007/2008) study examined the relationship between students’ reading engagement and achievement in three English-speaking countries, namely Ireland, UK, and US, using data from PISA 2000 and 2003. The authors focused on students’ reading engagement because of its demonstrated association with reading literacy (Kirsch et al., 2002). For example, students who are motivated to read do in turn read more, and reading benefits their vocabulary and comprehension skills (Stanovich, 1986). In PISA, students’ reading engagement is conceptualized as comprising three components. The first component is students’ diversity of reading which pertains to the frequency with which they read six types of text (magazines, comics, fiction books, nonfiction books, email, and webpages). The second component is students’ frequency of leisure reading on a daily basis. The third component is students’ attitudes toward reading. Brozo and colleagues’ (2007/2008) analysis showed a differentiated pattern of results across the three countries. In Ireland, students had overall high reading achievement (ranked 5th in 2000 and 6th in 2003). Students’ frequency of daily reading was strongly related to their reading achievement. Students’ attitudes toward reading were related to their reading achievement. In the UK, student had overall high reading achievement (ranked 7th) but not reading engagement (ranked lower than Nordic countries). Therefore, the association between reading engagement and achievement was not strong. In the US, students’ overall reading engagement was a strong predictor of their reading achievement. To illustrate, they ranked 20th in their levels of reading engagement, 24th in their reading diversity, and 15th in their ability to interpret and retrieve information from text. These results showed that the relationship between reading engagement, as an aspect of cultural capital, and reading achievement varied across the three countries. In another study, Sebastian and colleagues (2017) examined principal and parent survey data to ascertain whether parental school involvement was associated with students’ mathematics achievement. The sample comprised parents and principals from seven countries (Chile, Croatia, Hong Kong-China, Hungary, Korea, MacaoChina, and Portugal) who participated in PISA 2012. Results of factor analyzes

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showed that parental school involvement comprised three factors: parent-initiated involvement, teacher-initiated involvement, and parental volunteering at school. Results of HLM showed that for the entire sample, parent-initiated school involvement was not associated with students’ mathematics achievement while teacher-initiated school involvement and parental volunteering at school were negatively associated with students’ mathematics achievement. Parent-initiated school involvement was negatively associated with students’ mathematics achievement in Macao-China and Portugal. It was not significantly related with students’ mathematics achievement in the other five countries. Teacher-initiated school involvement was negatively associated with students’ mathematics achievement in Croatia, Hungary, Macao-China, and Portugal. It was not significantly related to students’ mathematics achievement in the other four countries. Parental volunteering at school was negatively associated with students’ mathematics achievement in Croatia, Macao-China, and Portugal. It was not significantly related to students’ mathematics achievement in the other four countries. The different pattern of association between parental school involvement (comprising parent-initiated school involvement, teacher-initiated school involvement, and parental volunteering at school) and students’ mathematics achievement for different countries provided support for the argument that national contexts may moderate the contribution of cultural capital (in this case, parental school involvement) to students’ academic achievement. Both Brozo and colleagues (2007/2008) and Sebastian and colleagues’ (2017) studies clearly showed cross-national differences in cultural capital influences on students’ learning. What these researchers did not accomplish is to identify what caused these differences. In contrast, results from other studies indicated that these differences are partly explained by masculinity values (Chiu & Chow, 2010), Confucian values (Tan & Liu, 2018), and countries’ socioeconomic gradients (Tan, 2015). Results from these studies are discussed next.

5.2.1 Moderating Effects of Masculinity Chiu and Chow’s (2010) study examined how cultural contexts might moderate the association between students’ extrinsic motivation and their reading achievement. In particular, the authors reasoned that masculine cultures with clearly defined gender roles discourage girls from aspiring to join traditionally masculine careers. The circumscribed ambitions of girls demotivate them from learning, thereby dampening the academic competition for girls as well as for boys. Boys, in turn, also get demotivated in their learning. Therefore, the authors argued that the association between students’ extrinsic motivation and their reading achievement is lower in more masculine cultures. The authors analyzed data from 193,841 students in 41 countries who participated in PISA (exact wave not discernible from article). Students’ extrinsic motivation was measured using their responses to items asking about their motivation to study to

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increase their job opportunities, ensure that their future is financially secure, and get a good job. Results of HLM showed that the association between students’ extrinsic motivation and their reading achievement was more negative in more masculine cultures. These results provide support for the argument that social fields (in this case, cultural context) moderate the relationship between students’ cultural capital (extrinsic motivation) and their academic achievement.

5.2.2 Moderating Effects of Confucian Values Tan and Liu (2018) tested the proposition that sociocultural values moderate the relationship between cultural capital and students’ achievement. More specifically, their study aimed to (a) compare the association between cultural capital and students’ reading achievement in a unique group of countries—Confucian heritage cultures (CHCs)—and non-CHCs with comparable levels of educational and economic development; and (b) identify specific cultural capital variables that had the strongest relationship with students’ reading achievement in CHCs. The study was designed to challenge the assumption that cultural capital benefits student achievement in the same way in different societies. Indeed, there are different reasons why this assumption may not hold. First, different indicators are needed to measure cultural capital in different contexts (Caro, Sandoval-Hernandez, & Ludtke, 2013; Rutkowski & Rutkowski, 2013). Second, societies have different levels of educational and economic development which moderate student learning experiences (e.g., student learning may benefit from access to qualified teachers, quality school educational materials, updated school infrastructure, and school autonomy in economically developed countries; Byun, Schofer, & Kim 2012; Hanushek & Woessmann, 2017; Heyneman & Loxley, 1983; Ker, 2016; Lee, 2014; Little & Rolleston, 2014; Mourshed, Chijioke, & Barber, 2010; Zhang, Khan, & Tahirsylaj, 2015). Third, students’ learning opportunities are either facilitated or circumscribed by national curricular emphasis on specific subject areas (e.g., favoring mathematics and science over liberal arts to prepare students for knowledge-based economies; Dennis, 2000; Tan, 2013). The last reason is that sociocultural values on education affect students’ motivation to learn. For example, CHCs are characterized by the belief that effort may compensate the absence of innate intelligence in learning, that learning yields long-term benefits as contrasted with short-term hedonistic pursuits, and that academic achievement represents the discharge of filial responsibility toward parents (Chan, Bowes, & Wyver, 2009; French, French, & Li, 2015; Li, Costanzo, & Putallaz, 2010; Sun, 2011; Wang, Harding, & Mai, 2012). Therefore, Tan and Liu (2018) expected family advantages such as cultural capital to have a smaller impact on student achievement in CHCs as compared to non-CHCs. The sample for the study comprised 32,981 students and 875 school principals in six CHCs (Singapore, Hong Kong, Taipei, Korea, Macau, and Japan) and 83,527 students and 3,468 school principals in nine non-CHCs (Switzerland, Netherlands,

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Estonia, Finland, Canada, Poland, Belgium, Germany, and Australia) who participated in PISA 2012. These countries were selected for analysis because they had comparably high levels of student academic achievement and national income. Students’ objectified cultural capital was measured using student responses on their access to home educational and cultural resources. Students’ institutional cultural capital was measured using student responses to questions asking about their fathers’ and mothers’ highest educational levels. Results of t-test comparisons between CHCs and non-CHCs showed that levels of paternal education, maternal education, and home educational and cultural resources were lower in CHCs than in non-CHCs. However, the mean levels of students’ reading achievement were higher in CHCs than in non-CHCs. Controlling for student sex, levels of school autonomy in decision-making, and country GDP, results of HLM showed that objectified cultural capital, namely home educational and cultural resources, was more important than institutionalized cultural capital, namely paternal and maternal education, for students’ reading achievement in CHCs. This pattern of results contrasted with that for non-CHCs where paternal and maternal education and home educational resources had roughly similar degrees of association with students’ reading achievement, and only access to home cultural resources appeared to be more strongly related to students’ reading achievement than parental education. The results suggested that CHCs and non-CHCs constitute different social fields that moderate the functioning of cultural capital (home educational and cultural resources, paternal and maternal education) for students’ learning.

5.2.3 Moderating Effects of Countries’ Socioeconomic Gradients Tan’s (2015) study compared the pattern of results for the moderating effects of parental education (institutionalized cultural capital) on the relationships between home educational resources (objectified cultural capital) and students’ mathematics achievement and between parental educational expectations (embodied cultural capital or habitus) and students’ mathematics achievement between medium and high socioeconomic gradient countries. The association between cultural capital and students’ academic achievement was expected to be stronger in higher socioeconomic gradient countries for two reasons. First, countries with higher socioeconomic gradients may have education systems that are horizontally segregated (Willms, 2010); that is, schools vary in terms of the socioeconomic profiles of students they admit. In particular, higher SES schools offer higher instructional quality, higher curricular relevance and comprehensiveness, more instructional time and more challenging assignments (Willms, 2010). Students from higher SES families are more likely to excel in these schools because of their access to home educational resources and more highly educated parents who can help them use these resources optimally (Willms, 2002). The second reason is that countries with higher socioeconomic gradients may

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have education systems that are vertically segregated (Willms, 2010); that is, schools provide different educational offerings to students according to their academic abilities (e.g., streaming and tracking). Parents may then be able to form more accurate educational expectations of their children’s academic abilities. Data analyzed pertained to the availability of home educational resources, parents’ educational expectations of their children, and parents’ highest educational attainment. Results of one-way analyzes of variance and post hoc comparisons showed that in medium and high socioeconomic gradient economies, students with higher parental education had higher levels of home educational resources and parental expectations than students with lower parental education. Results of HLM for medium and high socioeconomic gradient economies showed that home educational resources, parental academic expectations, and parental education were all positively associated with students’ mathematics achievement. The interactive terms involving home educational resources and parental education and involving parental academic expectations and parental education were significant. A comparison of the effects (main and interactive) of cultural capital on students’ mathematics achievement in medium and high socioeconomic gradient economies in Tan’s (2015) study showed that these effects explained more student achievement variance in high (7.45%) than in medium (2.82%) socioeconomic gradient economies. The main effects for parental educational expectations, and interaction effect between parental educational expectations and parent education were stronger in high as compared with medium socioeconomic gradient economies.

5.3 Concluding Remarks Review of the pattern of results reported from the seven studies provides insights on how cultural capital can be used as a conceptual heuristic to explain gender (Brozo et al., 2014; Chiu & McBride-Chang, 2006) and cross-national (Brozo et al., 2007/2008; Chiu & Chow, 2010; Sebastian et al., 2017; Tan, 2015; Tan & Liu, 2018) differences in students’ academic achievement. In particular, cross-national differences comprise cultural attributes such as the degree of masculinity (Chiu & Chow, 2010), influence of Confucian values (Tan & Liu, 2018), and socioeconomic gradients (Tan, 2015). Differences in levels of cultural capital and the association between cultural capital and students’ academic achievement among different groups of students point to yet another facet characterizing the complexity of the cultural capital construct in addition to the need for multiple indicators to measure the construct (Hartas, 2015; Tan, 2017a, b), the complex nomological framework underpinning the relationships between cultural capital and students’ academic achievement (Edgerton, Roberts, & Peter, 2013; Hartas, 2015), and the conjunctive effects of different cultural capital variables on students’ academic achievement (Tan, 2015, 2018; Tan & Hew, 2017, 2018) as discussed in the previous chapter. Moving on, the next (and last chapter) is devoted to synthesizing the materials discussed in Chaps. 1, 2, 3, 4 and

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this chapter. It will also summarize the key contributions of the book to theoretical developments in cultural capital theory and outline implications for practice.

References Brozo, W. G., Shiel, G., & Topping, K. (2007/2008). Engagement in reading: Lessons learned from three PISA countries. Journal of Adolescent & Adult Literacy, 51(4), 304–315. https://doi.org/ 10.1598/jaal.51.4.2. Brozo, W. G., Sulkunen, S., Shiel, G., Garbe, C., Pandian, A., & Valtin, R. (2014). Reading, gender, and engagement: Lessons from five PISA countries. Journal of Adolescent & Adult Literacy, 57(7), 584–593. https://doi.org/10.1002/jaal.291. Byun, S.-Y., Schofer, E., & Kim, K.-K. (2012). Revisiting the role of cultural capital in East Asian educational systems: The case of South Korea. Sociology of Education, 85(3), 219–239. Caro, D. H., Sandoval-Hernandez, A., & Ludtke, O. (2013). Cultural, social, and economic capital constructs in international assessments: An evaluation using exploratory structural equation modelling. School Effectiveness and School Improvement, 25(3), 433–450. Chan, S.-M., Bowes, J., & Wyver, S. (2009). Chinese parenting in Hong Kong: Links among goals, beliefs and styles. Early Child Development and Care, 179(7), 849–862. Chiu, M., & Chow, B. W. Y. (2010). Culture, motivation, and reading achievement: High school students in 41 countries. Learning and Individual Differences, 20, 579–592. Chiu, M. M., & McBride-Chang, C. (2006). Gender, context, and reading: A comparison of students in 43 countries. Scientific Studies of Reading, 10(4), 331–362. Dennis, D. (2000). The role of historical studies in mathematics and science educational research. In A. E. Kelly & R. A. Lesh (Eds.), Handbook of research design in mathematics and science education (pp. 799–814). Mahwah, NJ: Lawrence Erlbaum. Edgerton, J. D., Roberts, L. W., & Peter, T. (2013). Disparities in academic achievement: Assessing the role of habitus and practice. Social Indicators Research, 114, 303–322. https://doi.org/10. 1007/s11205-012-0147-0. French, J., French, A., & Li, W.-X. (2015). The relationship among cultural dimensions, education expenditure, and PISA performance. International Journal of Educationa Development, 42, 25– 34. Hanushek, E. A., & Woessmann, L. (2017). School resources and student achievement: A review of cross-country economic research. In M. Rosen, K. Y. Hansen, & U. Wolff (Eds.), Cognitive abilities and educational outcomes: A festschrift in honour of Jan-Eric Gustafsson (pp. 149–171). Cham: Springer. Hartas, D. (2015). Patterns of parental involvement in selected OECD countries: Cross-national analyses of PISA. European Journal of Educational Research, 4(4), 185–195. https://doi.org/10. 12973/eu-jer.4.4.185. Heyneman, S., & Loxley, W. A. (1983). The effect of primary-school quality on academic achievement across twenty-nine high- and low-income countries. American Journal of Sociology, 88(6), 1162–1194. Ker, H. W. (2016). The impacts of student, teacher- and school-level factors on mathematics achievement: An exploratory comparative investigation of Singaporean students and the USA students. Educational Psychology, 36(2), 254–276. Kirsch, I., de Jong, J., Lafontaine, D., McQueen, J., Mendelovits, J., & Monseur, C. (2002). Reading for change: Performance and engagement across countries. Paris: Organisation for Economic Co-operation and Development. Lee, J. (2014). Universal factors of student achievement in high-performing Eastern and Western countries. Journal of Educational Psychology, 106(2), 364–374.

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Li, Y., Costanzo, P., & Putallaz, M. (2010). Maternal socialization goals, parenting styles, and social-emotional adjustment among Chinese and European American young adults: Testing a mediation model. The Journal of Genetic Psychology, 171(4), 330–362. Little, A., & Rolleston, C. (2014). School quality counts: Evidence from developing countries. Oxford Review of Education, 40(1), 1–9. Mourshed, M., Chijioke, C., & Barber, M. (2010). How the world’s most improved school systems keep getting better. Retrieved March 11, 2019, from https://www.mckinsey.com/~/media/ mckinsey/industries/social%20sector/our%20insights/how%20the%20worlds%20most% 20improved%20school%20systems%20keep%20getting%20better/how_the_worlds_most_ improved_school_systems_keep_getting_better.ashx. Rutkowski, D., & Rutkowski, L. (2013). Measuring socioeconomic background in PISA: One size might not fit all. Research in Comparative and International Education, 8(3), 259–278. Sebastian, J., Moon, J.-M., & Cunningham, M. (2017). The relationship of school-based parental involvement with student achievement: A comparison of principal and parent survey reports from PISA 2012. Educational Studies, 43(2), 123–146. https://doi.org/10.1080/03055698.2016. 1248900. Stanovich, K. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360–407. Sun, M.-T. (2011). Educational research in Mainland China: Current situation and Developmental trends. Comparative Education, 47(3), 315–325. Tan, C. Y. (2013). Organizational legitimacy of the Singapore Ministry of Education. Oxford Review of Education, 39(5), 590–608. Tan, C. Y. (2015). The contribution of cultural capital to students’ mathematics achievement in medium and high socioeconomic gradient economies. British Educational Research Journal, 41(6), 1050–1067. Tan, C. Y. (2017a). Conceptual diversity, moderators, and theoretical issues in quantitative studies of cultural capital theory. Educational Review, 69(5), 600–619. Tan, C. Y. (2017b). Examining cultural capital and student achievement: Results of a meta-analytic review. Alberta Journal of Educational Research, 63(2), 139–159. Tan, C. Y. (2018). Socioeconomic status, involvement practices, and student science achievement: Insights from a typology of home and school involvement patterns. American Educational Research Journal, 56(3), 899–924. Tan, C. Y., & Hew, K. F. (2017). Information technology, mathematics achievement, and educational equity in developed economies. Educational Studies, 43(4), 371–390. Tan, C. Y., & Hew, K. F. (2018). The impact of digital divides on student mathematics achievement in Confucian heritage cultures: A critical examination using PISA 2012 data. International Journal of Science and Mathematics Education. Tan, C. Y., & Liu, D. (2018). What is the influence of cultural capital on student reading achievement in Confucian as compared to non-Confucian heritage societies? Compare: A Journal of Comparative and International Education, 48(6), 896–914. Wang, Y., Harding, R., & Mai, L.-W. (2012). Impact of cultural exposure on young Chinese students’ adaptation in a UK business school. Studies in Higher Education, 37(5), 621–639. Willms, J. D. (2002). Ten hypotheses about socioeconomic gradients and community differences in children’s developmental outcomes. Quebec, Canada: Human Resources Development. Willms, J. D. (2010). School composition and contextual effects on student outcomes. Teachers College Record, 112(4), 1008–1037. Zhang, L., Khan, G., & Tahirsylaj, A. (2015). Student performance, school differentiation, and world cultures: Evidence from PISA 2009. International Journal of Educational Development, 42, 43–53.

Chapter 6

Conclusion

Abstract This concluding chapter synthesizes the materials presented in the preceding chapters (Chaps. 1–5) and summarizes the key contributions of the book to theoretical developments in cultural capital theory. It juxtaposes these findings with the set of research questions that are presented in the introductory chapter. It then presents a conceptual framework incorporating three salient properties characterizing cultural capital that are derived from the burgeoning extant scholarship. These properties relate to the rich and nuanced attributes underpinning the conceptualization of cultural capital, student and socio-cultural-economic moderators of the relationships between cultural capital and students’ academic achievement, and effects of different combinations of cultural capital variables on students’ academic achievement. This conceptual framework can be used to inform further theoretical and empirical work interrogating the relationships between cultural capital and students’ academic achievement. Implications for practice for educators, parents, and policymakers are also discussed. The chapter also presents a list of research questions that need to be addressed in future research in order to further unpack the cultural capital construct, especially with respect to its nomological framework, and take the field forward. It ends with some suggestions for future research. Keywords Academic achievement · Conceptual framework · Cultural capital · Moderators · PISA · Program for international student assessment The aim of this concluding chapter is to synthesize the theoretical developments and research evidence presented in earlier chapters and update our understanding of the relationships between cultural capital and students’ academic achievement. It achieves this by first revisiting the research questions posed in Chap. 1. Next, it outlines how the present book has contributed in terms of theoretical developments in cultural capital theory. In particular, it summarizes insights from the scholarship in a conceptual framework comprising three salient properties characterizing the complexity of cultural capital theory. After that, it briefly discusses implications for practice particularly for policymakers, school leaders, and educators. The chapter ends with suggestions for future research.

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 C. Y. Tan, Family Cultural Capital and Student Achievement, SpringerBriefs in Education, https://doi.org/10.1007/978-981-15-4491-0_6

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6.1 Revisiting Research Questions In Chap. 1, I argue for a more nuanced and pointed approach to understanding the relationships between cultural capital and students’ academic achievement. This approach culminates in a series of research questions that collectively frame the discourse on the topic. In this concluding chapter, I will address these research questions to elucidate the complex nature of the cultural capital construct. Research question: “Is there one singular cultural capital or are there different aspects of cultural capital that contribute to students’ academic achievement?”

The emerging evidence base suggests that cultural capital is far from being a unitary, singular construct. It can exist in three states, namely, embodied, objectified, and institutionalized states (Bourdieu, 1986). Furthermore, it can be represented by different forms beyond highbrow cultural consumption as exemplified by parental familiarity with school evaluation standards and future job requirements in contemporary knowledge-based economies (Farkas, Grobe, Sheehan, & Shuan, 1990; Lareau & Weininger, 2003; Reay, 2004a; Tan, 2017a; Vryonides, 2007). Furthermore, cultural capital can be measured using different indicators (including children’s access to home educational and cultural resources, parent–child cultural participation, parent– child home reading habits, parent–child discussions on cultural and school topics, educational expectations of children by parents or children themselves, parental home and school involvement, and parental educational attainment; Tan 2017b, c). These myriad manifestations are underpinned by students’ worldviews, styles, and preferences known as habitus (Bourdieu, 1977, 1979, 1986, 1990a, 1990b; DiMaggio, 1979; Dumais, 2002; Gaddis, 2013; Horvat & Earl Davis, 2011; Reay, 1995, 2004b; Winkle-Wagner, 2010). Research question: “What aspects of cultural capital are more relevant in contemporary contexts such as knowledge-based economies?”

Students have immense educational and job opportunities in science, technology, engineering, and mathematics in knowledge-based economies. In these contexts, cultural capital such as parental familiarity with evaluation standards and job market requirements may be more relevant than highbrow cultural consumption (Tan, 2017a). This cultural capital includes students’ access to home educational resources, parental education, parental occupational status, parental educational expectations of their children, parental mathematics career expectations of their children, parental academic expectations of their children’s schools, and parental perceived importance of mathematics. Research question: “What aspects of cultural capital are more important than others in affecting students’ academic achievement?”

Results of empirical studies showed that the associations between cultural capital and students’ academic achievement vary for different aspects of cultural capital (Tan, 2017b, c). For example, in Tan’s (2017c) meta-analysis comparing the effect sizes of 15 different aspects of cultural capital, results showed that parental educational

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expectations of their children and parental education were more important than students’ access to home educational and cultural resources, parent and child cultural participation, parent–child discussions, and maternal education. Research question: “How does cultural capital benefit students in their learning?”

Adherents of the Lareau’s tradition of concerted cultivation assert that middle-class parents can and are proactively seeking maximum benefits for their children’s learning by their parenting strategies and engagement with school personnel. To achieve this, they strategically align their home practice with school evaluation, such as facilitating their children’s learning of school materials, intervening assertively in school matters, actively participating in school events, and effortlessly replicating school educational activities in the home domain (Lareau, 2000). Furthermore, students can display the necessary temperament or employ interaction strategies to gain teachers’ attention and secure learning benefits in class (Calarco, 2011, 2014; Chin & Phillips, 2004), thereby generating yet another source of cultural capital. In unraveling the workings of cultural capital, it is also important to recognize the structure-disposition-practice nexus as demonstrated by Edgerton, Roberts, and Peter’s (2013) study. More specifically, Edgerton and colleagues’ analysis showed that students from higher SES families (structure) were more likely to exhibit higher levels of habitus (dispositions) and be involved in academic practices. Students with higher levels of habitus, in turn, were more likely to exhibit more academic practices. Interestingly, students’ habitus had a larger influence than their academic practices on academic achievement. Research question: “How do students benefit from having more than one aspect of cultural capital?”

It may appear intuitive to expect that students will always benefit from having more, rather than fewer, aspects of cultural capital for their academic achievement. However, a review of published studies showed that cultural capital variables may operate conjunctively, rather than separately, to influence students’ academic achievement (Tan, 2015, 2018; Tan & Hew, 2017, 2018). There can be various scenarios representing different patterns of association involving multiple cultural capital variables. These include different aspects of cultural capital reinforcing each other to synergistically benefit students’ learning (Tan, 2015; Tan & Hew, 2017), the same cultural capital variables exhibiting different patterns of association with students’ academic achievement depending on the profiles of students and their families (Tan & Hew, 2018), and even effects of some cultural capital variables offsetting those of others (Tan, 2018; Tan & Hew, 2017). Research question: “Does cultural capital benefit all groups of students (e.g., boys versus girls, or students from different socio-cultural-economic contexts) similarly?”

Results from published studies showed that cultural capital may have different patterns of association with students’ academic achievement depending on their demographics (e.g., gender; Brozo et al., 2014; Chiu & McBride-Chang, 2006) and sociocultural-economic contextual attributes such as the degree of masculinity (Chiu &

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Chow, 2010), influence of Confucian values (Tan & Liu, 2018), and socioeconomic gradients (Tan, 2015) in different countries.

6.2 Contributions to Theory The theorizing and discussion on cultural capital in this book builds on key tenets underpinning decades of scholarship highlighting the role of cultural capital in social reproduction. More specifically, it adopts the conceptualization of cultural capital as comprising three states (objectified, institutionalized, and embodied). It is also allied with the existing scholarship recognizing habitus as the common denominator underlying different states of cultural capital. Lastly, it affirms how cultural capital assumes various forms in different contexts (social fields) to transmit socioeconomic advantages intergenerationally. At the same time, this book presents evidence that demonstrates how quantitative researchers have operationalized their analytical strategy with PISA data to empirically examine these tenets of cultural capital theory. First, it points the way forward on how different variables in the PISA data can be used as indicators of cultural capital and habitus. It also demonstrates how cultural capital has assumed new forms in response to emerging social developments and continues to be instrumental in mediating the effects of social origins on students’ learning. This is exemplified by students’ access to and usage of information technology in their learning (digital divides; Tan & Hew, 2017, 2018) and by the emphasis on mathematics and science literacy attributed to parents’ familiarity with school evaluation standards and requirements of job markets in knowledge-based economies (Tan, 2017a). Lastly, it explores how international comparative studies have provided quantitative researchers with a means to compare the functioning of cultural capital across different sociocultural contexts indicative of social fields (e.g., societies differing in their socioeconomic gradient in Tan (2015) and Confucian versus non-Confucian societies in Tan and Liu (2018)). The book makes two important contributions to the scholarship on the role of cultural capital in explaining social inequality and reproduction in students’ academic achievement. The first contribution is that it has presented empirical evidence that cultural capital is a complex construct comprising multiple diverse aspects with varying patterns of association with students’ academic achievement. The evidence reviewed also suggests that the relationships between cultural capital and students’ academic achievement are far from simple; they implicate related constructs such as habitus and fields in a nomological network of influences, and they may vary according to students’ demographics and field conditions. In addition, there are indications that the combination of different aspects of cultural capital may not necessarily eventuate in higher levels of students’ academic achievement. More specifically, while there may be synergetic effects, these multiple aspects may influence students’ academic achievement differently depending on their individual and familial profiles, or even

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Complex attributes of cultural capital Comprising multiple aspects/diverse indicators underpinned by habitus Interactions among structure, dispositions, and practice

Cultural capital

Effects for combinations of different cultural capital aspects Different relative effects Synergistic effects Offsetting effects

Moderation of cultural capital effects by Students’ demographics Familial profiles Socio-cultural-economic contexts

Fig. 6.1 Complexity of cultural capital construct

“cancel out” each other in their effects. Figure 6.1 summarizes this complexity in the cultural capital construct. The second contribution is that the book has highlighted the prospect of using PISA data to interrogate the associations between students’ cultural capital and academic achievement. This possibility is consonant with the trend of more sociologists, including those researching on social inequality and reproduction, embracing quantitative methodologies to examine big data in their quantitative or mixed methods research design. Indeed, the book has systematically summarized the research questions that can be addressed with PISA data and the types of cultural capital variables that are available for research. These variables span the almost two decades of PISA administration from 2000 to 2015 and pertain to students’ reading, mathematics, and science learning across scores of participating countries in the world. Researchers can, therefore, harness the many positive attributes of PISA—publicly available data, large samples involved, plethora of cultural capital variables and other variables that can serve as controls in analytical models, availably of comparable data for different countries, and six waves of comprehensive data (2000–2015; 2018 data due to be released soon). This book has discussed how previous studies employing PISA data have contributed to theoretical advances in cultural capital theory but much more can be done to analyze PISA data to further develop the theory.

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6.3 Implications for Practice There are two sets of implications for practice. The first is that parents can ascertain what may be more important and relevant to foster their children’s academic achievement according to their children’s gender and the particular socio-cultural-economic contexts their children are learning in. For example, parents may wish to strategically focus on the aspects of cultural capital that appear to have a greater influence on students’ academic achievement than others, such as holding and communicating higher levels of educational expectations for their children. If the focus is to enhance students’ mathematics achievement, parents may also clarify and communicate their expectations for their children’s mathematics career and work with school principals and their children’s teachers to raise their academic expectations of their children’s school. These parental strategies may be able to compensate for some but not all of the influence of social origins for lower-SES students due to the hysteresis effect (Hardy, 2012). More specifically, some scholars adhering to the social reproduction hypothesis averred that habitus is inherently associated with higher SES, is reinforced by school gatekeepers, and is not easily emulated by lower-SES students. Hysteresis thus represents the structural tendencies that these students have to confront in their school learning. The second is that policymakers, school principals, teachers, and researchers can work together to analyze the publicly available PISA data to clarify what contributes to students’ academic achievement in different subjects such as mathematics, reading, and science. These different stakeholders can play different roles. For example, policymakers may be interested to know the parent or home contributing factors that are more malleable and work with researchers and school personnel to analyze the variables of interest in PISA before sharing the findings with parents, especially those from less privileged families. This collaboration may be more cost-efficient than the alternative scenario where time and effort have to be devoted to preparing elaborate research proposals and bidding for competitive research grants whose results are not determinate.

6.4 Limitations There are three key limitations that merit discussion. The first limitation pertains to the focus of the discussion on how familial cultural capital explains parental influence on students’ learning. Notwithstanding the salience of family resources and socialization, the exegesis of social reproduction is incomplete if we do not examine how school processes act in concert to legitimate the practices of high-SES families as efficacious and valuable, and thereby rewarding students from these families at the expense of peers from disadvantaged families (Schmidt, Burroughs, Zoido, & Houang, 2015). These school processes comprise teaching resources and methods, assessment modes, school progression systems, expectations of students’ learning

6.4 Limitations

63

behaviors (Caro, Lenkeit, & Kyriakides, 2016; Gao, 2014; Hopkins & Reynolds, 2002; Lipowsky et al., 2009; Schmidt et al., 2015), and even the elaborated codes emphasized by teachers (Bernstein, 1964). The second limitation arises from the lack of ethnic or racial information in PISA data that restricts researchers’ ability to investigate the interaction between social class and ethnicity/race. Indeed, Lareau and Horvat’s (1999) study of the involvement of parents of third-grade students demonstrated the complexities involved— how Black parents’ skepticism toward schools, fueled by their concerns about racial discrimination, was anathema to teachers’ expectations of deference from these lower-SES parents. Researchers using PISA data have to contend with potential intra-country heterogeneity in their research design and complement the quantitative analysis with qualitative data. The third limitation relates to the increasingly globalized nature of cultural capital that is not captured in PISA. Jarvis’ (2019) study highlighted the globalized dimension of cultural capital. His study of locally and foreign-educated Koreans found that her university-educated participants differed in their relative possession of global and local cultural capital, and that graduates were more successful at work when they exhibited mastery of both types of resources. There is also evidence that universities have legitimated cosmopolitanism as a desirable embodied cultural capital and used academic qualifications to signal the inculcation of such attributes to prospective employers (Igarashi & Saito, 2014). Existing PISA data have yet to incorporate these emerging conceptualizations, so cultural capital researchers have to focus on more traditional forms of cultural capital.

6.5 Suggestions for Future Research Notwithstanding the advances in our understanding of the association between cultural capital and students’ academic achievement (e.g., Davies & Rizk, 2018), the knowledge base on cultural capital theory is still evolving and tentative. Indeed, the complexity of the cultural capital construct foreshadows many research questions that remain to be addressed in future research. These questions are exemplified by the following, and some of the questions can be at least partially addressed using the different waves of PISA data on cultural capital and students’ learning variables: • What is the nexus of nomological relationships among diverse cultural capital variables and how do these variables contribute to students’ academic achievement? • How do the cultural capital-academic achievement relationships compare for students from different age groups, gender, and other individual and familial demographic variables? • What is the pattern of cultural capital-academic achievement relationships for specific countries and how do the patterns of relationships compare across different countries (differing in dimensions beyond those examined in previous studies)?

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• How does the pattern of relationships between cultural capital and students’ academic achievement compare across time in the context of sociocultural changes? • What is the pattern of relationships between cultural capital and students’ nonachievement learning variables such as their learning progress and non-academic learning outcomes?

6.6 Concluding Remarks This concluding chapter has summarized the key findings on the complexity of cultural capital as discussed in the first five chapters of the book. In particular, it has juxtaposed these findings with the set of research questions that are presented in Chap. 1 and presented them as a set of three salient properties characterizing cultural capital derived from the burgeoning extant scholarship in Fig. 6.1. These properties are, namely, attributes of cultural capital, moderators for the relationships between cultural capital and students’ academic achievement, and effects of combinations of cultural capital variables on students’ academic achievement. The chapter has also presented a list of research questions that need to be addressed in future research to further unpack the complexity of the cultural capital construct, especially with respect to its nomological framework, and take the field forward.

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Tan, C. Y. (2015). The contribution of cultural capital to students’ mathematics achievement in medium and high socioeconomic gradient economies. British Educational Research Journal, 41(6), 1050–1067. https://doi.org/10.1002/berj.3187. Tan, C. Y. (2017a). Do parental attitudes toward and expectations for their children’s education and future jobs matter for their children’s school achievement? British Educational Research Journal, 43(6), 1111–1130. https://doi.org/10.1002/berj.3303. Tan, C. Y. (2017b). Conceptual diversity, moderators, and theoretical issues in quantitative studies of cultural capital theory. Educational Review, 69(5), 600–619. Tan, C. Y. (2017c). Examining cultural capital and student achievement: Results of a meta-analytic review. Alberta Journal of Educational Research, 63(2), 139–159. Tan, C. Y. (2018). Socioeconomic status, involvement practices, and student science achievement: Insights from a typology of home and school involvement patterns. American Educational Research Journal, 56(3), 899–924. Tan, C. Y., & Hew, K. F. (2017). Information technology, mathematics achievement, and educational equity in developed economies. Educational Studies, 43(4), 371–390. https://doi.org/10.1080/ 03055698.2016.1277137. Tan, C. Y., & Hew, K. F. (2018). The impact of digital divides on student mathematics achievement in Confucian heritage cultures: A critical examination using PISA 2012 data. International Journal of Science and Mathematics Education. https://doi.org/10.1007/s10763-018-9917-8. Tan, C. Y., & Liu, D. (2018). What is the influence of cultural capital on student reading achievement in Confucian as compared to non-Confucian heritage societies? Compare: A Journal of Comparative and International Education, 48(6), 896–914. https://doi.org/10.1080/03057925. 2017.1369392. Vryonides, M. (2007). Social and cultural capital in educational research: Issues of operationalisation and measurement. British Educational Research Journal, 33, 867–885. Winkle-Wagner, R. (2010). Foundations of educational inequality: Cultural capital and social reproduction. ASHE Higher Educational Report, 36, 1–21.

Appendix

See Tables A.1, A.2, A.3, A.4, A.5, A.6, A.7, A.8, A.9, A.10, A.11, A.12, A.13, A.14 Table A.1 Home educational and cultural resources in PISA questionnaires Respondents

PISA waves

Survey questions

Similar questions in other PISA waves

Student

2015

ST011 Which of the following are in your home (Yes, No) • A desk to study at • A room of your own • A quiet place to study • A computer you can use for school work • Educational software • A link to the Internet • Classic literature (e.g., ) • Books of poetry • Works of art (e.g., paintings) • Books to help with your school work • • A dictionary • Books on art, music, or design

Q21 (PISA 2000 Student questionnaire) Q17 (PISA 2003 Student questionnaire) Q13 (PISA 2006 Student questionnaire) Q20 (PISA 2009 Student questionnaire) Q7 (PISA 2009 Parent questionnaire) Q25 (PISA 2012 Student questionnaire)

ST013 How many books are there in your home? There are usually about of shelving. Do not include magazines, newspapers, or your schoolbooks • 0–10 books • 11–25 books • 26–100 books • 101–200 books • 201–500 books • More than 500 books

Q7 (PISA 2000 Student questionnaire) Q19 (PISA 2003 Student questionnaire) Q15 (PISA 2006 Student questionnaire) Q22 (PISA 2009 Student questionnaire) Q27 (PISA 2012 Student questionnaire)

(continued)

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2020 C. Y. Tan, Family Cultural Capital and Student Achievement, SpringerBriefs in Education, https://doi.org/10.1007/978-981-15-4491-0

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Appendix

Table A.1 (continued) Respondents

PISA waves

Survey questions

Similar questions in other PISA waves

Student (ICT questionnaire)

2015

IC001 Are any of these devices available for you to use at home? (Yes, and I use it; Yes, but I don’t use it; No) • Desktop computer • Portable laptop or notebook • (e.g. , ) • Internet connection • Printer • USB (memory) stick • , e.g.

Q1 (PISA 2009 ICT questionnaire) Q(unnumbered; PISA 2012 ICT questionnaire)

IC010 How often do you use digital devices for the following activities outside of school? (Never or hardly ever; Once or twice a month; Once or twice a week; Almost every day; Every day) • Browsing the Internet for schoolwork (e.g. for preparing an essay or presentation) • Browsing the Internet to follow up lessons, e.g. for finding explanations • Using e-mail for communication with other students about schoolwork • Using e-mail for communication with teachers and submission of homework or other schoolwork • Using social networks for communication with other students about schoolwork (e.g. , ) • Using social networks for communication with teachers (e.g. , ) • Downloading, uploading or browsing material from my school’s website (e.g. time table or course materials) • Checking the school’s website for announcements, e.g. absence of teachers • Doing homework on the computer • Doing homework on a mobile device • Downloading learning apps on a mobile device • Downloading science learning apps on a mobile device

Q9 (PISA 2009 ICT questionnaire) Q(unnumbered; PISA 2012 ICT questionnaire)

Appendix

69

Table A.2 Parental educational attainment in PISA questionnaires Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Student

2015

ST005 What is the completed by your mother? • • • • • She did not complete

Q12 (PISA 2000 Student questionnaire) Q11 (PISA 2003 Student questionnaire) Q6 (PISA 2006 Student questionnaire) Q10 (PISA 2009 Student questionnaire) Q14 (PISA 2012 Student questionnaire)

ST006 Does your mother have any of the following qualifications? (Yes, No) • • • •

Q14 (PISA 2000 Student questionnaire) Q12 (PISA 2003 Student questionnaire) Q7 (PISA 2006 Student questionnaire) Q11 (PISA 2009 Student questionnaire) Q10 (PISA 2009 Parent questionnaire) Q15 (PISA 2012 Student questionnaire)

ST007 What is the completed by your father? • • • • • He did not complete

Q13 (PISA 2000 Student questionnaire) Q13 (PISA 2003 Student questionnaire) Q9 (PISA 2006 Student questionnaire) Q14 (PISA 2009 Student questionnaire) Q19 (PISA 2012 Student questionnaire)

ST008 Does your father have any of the following qualifications? (Yes, No) • • • •

Q15 (PISA 2000 Student questionnaire) Q14 (PISA 2003 Student questionnaire) Q10 (PISA 2006 Student questionnaire) Q15 (PISA 2009 Student questionnaire) Q9 (PISA 2009 Parent questionnaire) Q20 (PISA 2012 Student questionnaire) Q(unnumbered; PISA 2012 Parent questionnaire)

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Appendix

Table A.3 Attitudes toward reading in PISA questionnaires

.

Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Student

2009

Q24 How much do you agree or disagree with these statements about reading? (Strongly disagree, Disagree, Agree, Strongly agree) • I read only if I have to • Reading is one of my favourite hobbies • I like talking about books with other people • I find it hard to finish books • I feel happy if I receive a book as a present • For me, reading is a waste of time • I enjoy going to a bookstore or a library • I read only to get information that I need • I cannot sit still and read for more than a few minutes • I like to express my opinions about books I have read • I like to exchange books with my friends

Q35 in PISA 2000 Student questionnaire

Parent

2009

Q6 How much do you agree or disagree with these statements about reading? (Strongly agree, Agree, Disagree, Strongly disagree) • Reading is one of my favorite hobbies • I feel happy if I receive a book as a present • For me, reading is a waste of time • I enjoy going to a bookstore or a library

Appendix

71

Table A.4 Attitudes toward learning mathematics in PISA questionnaires Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Student

2012

Q41 Thinking about your views on mathematics: to what extent do you agree with the following statements? (Strongly agree, Agree, Disagree, Strongly disagree) • I enjoy reading about mathematics • Making an effort in mathematics is worth it because it will help me in the work that I want to do later on • I look forward to my mathematics lessons • I do mathematics because I enjoy it • Learning mathematics is worthwhile for me because it will improve my career • I am interested in the things I learn in mathematics • Mathematics is an important subject for me because I need it for what I want to study later on • I will learn many things in mathematics that will help me get a job

Q30 in PISA 2003 Student questionnaire

Q42 Thinking about how people important to you view mathematics: How strongly do you agree with the following statements? (Strongly agree, Agree, Disagree, Strongly disagree) • My parents believe it’s important for me to study mathematics • My parents believe that mathematics is important for my career • My parents like mathematics Parent

2012

Q We are interested in what you think about the need for mathematics skills in the job market today. How much do you agree with the following statements? (Strongly agree, Agree, Disagree Strongly disagree) • It is important to have good mathematics knowledge and skills in order to get any good job in today’s world • Employers generally appreciate strong mathematics knowledge and skills among their employees • Most jobs today require some mathematics knowledge and skills • It is an advantage in the job market to have good mathematics knowledge and skills

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Appendix

Table A.5 Attitudes toward learning science in PISA questionnaires Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Student

2006

Q18 How much do you agree with the statements below? (Strongly agree, Agree, Disagree, Strongly disagree) • Advances in usually improve people’s living conditions • is important for helping us to understand the natural world • Some concepts in help me see how I relate to other people • Advances in usually help improve the economy • I will use in many ways when I am an adult • is valuable to society • is very relevant to me • I find that helps me to understand the things around me • Advances in usually brings social benefits • When I leave school there will be many opportunities for me to use

Parent

2006

Q4 We are interested in what you think about the need for science skills in the job market today. How much do you agree with the following statements? (Strongly agree, Agree, Disagree, Strongly disagree) • It is important to have good scientific knowledge and skills in order to get any good job in today’s world • Employers generally appreciate strong scientific knowledge and skills among their employees • Most jobs today require some scientific knowledge and skills • It is an advantage in the job market to have good scientific knowledge and skills

Student

2015

ST094 How much do you disagree or agree with the statements about yourself below? (Strongly disagree, Disagree, Agree, Strongly agree) • I generally have fun when I am learning topics • I like reading about • I am happy working on topics • I enjoy acquiring new knowledge in • I am interested in learning about

Q16 in PISA 2006 Student questionnaire

Parent

2015

PA033 How much do you agree with the following statements? (Strongly agree, Agree, Disagree, Strongly disagree) • is important to help us to understand the natural world • is valuable to society • is very relevant to me • I find that helps me to understand the things around me • Advances in usually bring social benefits

Q6 in PISA 2006 Parent questionnaire

Appendix

73

Table A.6 Educational expectations in PISA questionnaires Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Parent

2012

Q Which of the following do you expect your child to complete? (Please tick as many as apply.) • • • • • •

Q23 in PISA 2003 (Student questionnaire) Q5 (PISA 2009 Student EC questionnaire)

Table A.7 Cultural participation in PISA questionnaires Respondents

PISA years

Survey questions

Student

2000

Q18 During the past year, how often have you participated in these activities? (Never or hardly ever, Once or twice a year, About 3 or 4 times a year, More than 4 times a year) • Gone to the • Visited a museum or art gallery • Attended a popular music concert • Attended an opera, ballet or classical symphony concert • Watched live theatre • Attended sporting events

Table A.8 Parent-child discussions in PISA questionnaires Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Parent

2015

PA003 How often do you or someone else in your home do the following things with your child? (Never or hardly ever, Once or twice a year, Once or twice a month, Once or twice a week, Every day or almost every day) • Discuss how well my child is doing at school • Spend time just talking to my child • Ask how my child is performing in science class • Discuss with my child how science is used in everyday life • Discuss options with my child

Q19 (PISA 2000 Student questionnaire) Q8 (PISA Parent questionnaire 2009) Q(unnumbered; PISA Parent questionnaire 2012)

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Appendix

Table A.9 Schoolwork supervision in PISA questionnaires Respondents

PISA years

Survey questions

Student

2000

Q20 How often do the following people work with you on your ? (Never or hardly ever, A few times a year, About once a month, Several times a month, Several times a week) • Your mother • Your father • Your brothers and sisters • Grandparents • Other relations • Friends of your parents

Table A.10 Parental home support in PISA questionnaires Respondents

PISA years

Survey questions

Parent

2009

Q3 When your child attended the first year of , how often did you or someone else in your home undertake the following activities with her or him? (Never or hardly ever, Once or twice a month, Once or twice a week, Every day or almost every day) • Read books • Tell stories • Sing songs • Play with alphabet toys (for example: blocks with letters of the alphabet) • Talk about things you had done • Talk about what you had read • Play word games • Write letters or words • Read aloud signs and labels

Parent

2015

PA004 Thinking about , to what extent do you agree with the following statements? (Strongly disagree, Disagree, Agree, Strongly agree) • I am interested in my child’s school activities • I am supportive of my child’s efforts at school and his/her achievements • I support my child when he/she is facing difficulties at school • I encourage my child to be confident

Appendix

75

Table A.11 Reading activities in PISA questionnaires Respondents

PISA years

Survey questions

Similar questions in other PISA waves

Student

2009

Q23 About how much time do you usually spend reading for enjoyment? • I do not read for enjoyment • 30 min or less each day • More than 30 min to less than 60 min each day • 1–2 h each day • More than 2 h each day

Q34 in PISA 2000 Student questionnaire

Q25 How often do you read these materials because you want to? (Never or almost never, A few times a year, About once a month, Several times a month, Several times a week) • Magazines • Comic books • Fictions (novels, narratives, stories) • Non-fiction books • Newspapers

Q36 in PISA 2000 Student questionnaire

Q26 How often are you involved in the following reading activities? (I don’t know what it is, Never or almost never, Several times a month, Several times a week, Several times a day) • Reading emails •