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IEA Research for EducationA Series of In-depth Analyses Based on Data of the InternationalAssociation for the Evaluation of Educational Achievement (IEA)Markus BroerYifan BaiFrank FonsecaSocioeconomicInequality andEducationalOutcomesEvidence from Twenty Years of TIMSS

IEA Research for EducationA Series of In-depth Analyses Based on Dataof the International Association for the Evaluationof Educational Achievement (IEA)Volume 5Series EditorsSeamus Hegarty, University of Warwick, UK, and Chair of IEA Publicationsand Editorial CommitteeLeslie Rutkowski, Indiana University, USAEditorial BoardJohn Ainley, Australian Council for Educational Research, AustraliaKadriye Ercikan, University of British Columbia, CanadaEckhard Klieme, German Institute for International Educational Research(DIPF), GermanyRainer Lehmann, Humboldt University of Berlin, GermanyFou-Lai Lin, National Taiwan Normal University, Chinese TaipeiMarlaine Lockheed, Princeton University, USASarah Maughan, AlphaPlus Consultancy, UKCarina Omoeva, FHI 360, USAElena Papanastasiou, University of Nicosia, CyprusValena White Plisko, Independent Consultant, USAJonathan Plucker, John Hopkins University, USAFernando Reimers, Harvard Graduate School of Education, USADavid Rutkowski, Indiana University, USAJouni Välijärvi, University of Jyväskylä, FinlandHans Wagemaker, Senior Advisor to IEA, New Zealand

The International Association for the Evaluation of Educational Achievement (IEA)is an independent nongovernmental nonprofit cooperative of national researchinstitutions and governmental research agencies that originated in Hamburg,Germany, in 1958. For over 60 years, IEA has developed and conductedhigh-quality, large-scale comparative studies in education to support countries’efforts to engage in national strategies for educational monitoring and improvement.IEA continues to promote capacity building and knowledge sharing to foster innovationand quality in education, proudly uniting more than 60 member institutions, withstudies conducted in more than 100 countries worldwide.IEA’s comprehensive data provide an unparalleled longitudinal resource forresearchers, and this series of in-depth thematic reports can be used to shed lighton critical questions concerning educational policies and educational research.The goal is to encourage international dialogue focusing on policy matters andtechnical evaluation procedures. The resulting debate integrates powerfulconceptual frameworks, comprehensive datasets and rigorous analysis, thusenhancing understanding of diverse education systems worldwide.More information about this series at http://www.springer.com/series/14293

Markus Broer Yifan Bai Frank FonsecaSocioeconomic Inequalityand Educational OutcomesEvidence from Twenty Years of TIMSS

Markus BroerAmerican Institutes for ResearchWashington, DC, USAYifan BaiAmerican Institutes for ResearchWashington, DC, USAFrank FonsecaAmerican Institutes for ResearchWashington, DC, USAISSN 2366-1631ISSN 2366-164X (electronic)IEA Research for EducationISBN 978-3-030-11990-4ISBN 978-3-030-11991-1 (eBook)https://doi.org/10.1007/978-3-030-11991-1 International Association for the Evaluation of Educational Achievement (IEA) 2019. This book is anopen access publication.Open Access This book is licensed under the terms of the Creative Commons AttributionNonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), whichpermits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium orformat, as long as you give appropriate credit to the original author(s) and the source, provide a link to theCreative Commons license and indicate if changes were made.The images or other third party material in this book are included in the book’s Creative Commons license,unless indicated otherwise in a credit line to the material. If material is not included in the book’s CreativeCommons license and your intended use is not permitted by statutory regulation or exceeds the permitteduse, you will need to obtain permission directly from the copyright holder.This work is subject to copyright. All commercial rights are reserved by the author(s), whether the wholeor 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 orinformation storage and retrieval, electronic adaptation, computer software, or by similar or dissimilarmethodology now known or hereafter developed. Regarding these commercial rights a non-exclusivelicense has been granted to the publisher.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoes not imply, even in the absence of a specific statement, that such names are exempt from the relevantprotective 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 bookare believed to be true and accurate at the date of publication. Neither the publisher nor the authors or theeditors give a warranty, express or implied, with respect to the material contained herein or for any errorsor omissions that may have been made. The publisher remains neutral with regard to jurisdictional claimsin published maps and institutional affiliations.This Springer imprint is published by the registered company Springer Nature Switzerland AG.The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

ForewordIEA’s mission is to enhance knowledge about education systems worldwide and toprovide high-quality data that will support education reform and lead to betterteaching and learning in schools. In pursuit of this aim, it conducts, and reports on,major studies of student achievement in literacy, mathematics, science, citizenship,and digital literacy. IEA studies, most notably TIMSS, PIRLS, ICCS, and ICILS,have set the benchmark for international comparative studies in education.These well-established studies have generated vast datasets encompassingstudent achievement, disaggregated in a variety of ways, along with a wealth ofcontextual information which contains considerable explanatory power. The numerousreports that have emerged from them represent an invaluable contribution to thecorpus of educational research.Nevertheless, IEA’s goal of supporting education reform needs something more:deep understanding of education systems and the many factors that bear on studentlearning advances through in-depth analysis of the global datasets. IEA has longchampioned such analyses and facilitates scholars and policymakers in conductingsecondary analysis of the datasets. So IEA provides software such as the InternationalDatabase Analyzer to encourage the analysis of their datasets, support numerouspublications, including a peer-reviewed journal – Large-Scale Assessment in Education– dedicated to the science of large-scale assessment and publishing articles thatdraw on large-scale assessment databases; and organize a biennial internationalresearch conference to nurture exchanges between researchers working withIEA data.The IEA Research for Education series represents a further effort by IEA tocapitalize on these unique datasets, so as to provide powerful information forpolicymakers and researchers. Each report focuses on a specific topic and isproduced by a dedicated team of leading scholars on the theme in question. Teamsare selected on the basis of an open call for tenders; there are two such calls a year.Tenders are subject to a thorough review process, as are the reports produced. (Fulldetails are available on the IEA website.)v

viForewordThis fifth volume in the series is concerned with socioeconomic inequality andeducational outcomes. Socioeconomic status is a key variable in social scienceresearch. It is especially important to the understanding of educational inequalityand how best to address it. There is a substantial literature on the links betweenstudents’ educational achievement and their family background. Despite this,challenges in measuring socioeconomic status and identifying its impact persist.This book draws on data collected over 20 years in the IEA Trends inInternational Maths and Science Study (TIMSS) and scrutinizes studentachievement levels in relation to their socioeconomic status. Besides achievementdata, TIMSS has been collecting background information from students, teachers,and school principals. Using a modified version of the TIMSS home educationalresources index, the authors have identified tentative patterns in the changes overtime. Specifically, they have established which countries have seen greatereducational inequality attributable to family background and which have seen areduction. They also identify which countries have managed to increase theacademic performance of disadvantaged students over the period and those whichhave not.There are no easy answers to the challenges posed by the educationalunderachievement of students from disadvantaged backgrounds. It remains,however, one of the most significant issues facing societies and their educationsystems. While family background is a critical variable, the authors properly pointout that macro-level factors such as gross national wealth per person, totalexpenditure on education, and degree of centralization of the education system allplay a part. What this book does offer is a data-driven focus on the effects ofsocioeconomic status on educational outcomes and a methodology for deepernational investigation across the many cycles of TIMSS. Both researchers andpolicymakers will find it suggestive in terms of exploring national contexts moreprecisely and devising policy actions to ameliorate educational underachievement.Future publications in the series will examine trends to evaluate the success ofcountries in strengthening teacher quality, and reducing educational inequality, andsystematically investigate differences in use, perceptions, and capabilities in usingcomputer technologies by student gender.Seamus HegartyLeslie RutkowskiSeries editors

Contents123Socioeconomic Inequality and Educational Outcomes:An Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15A Review of the Literature on Socioeconomic Status andEducational Achievement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2.1Socioeconomic Status and Related Constructs and Measures . . . .2.2Family SES and Student Achievement . . . . . . . . . . . . . . . . . . . .2.3Differences in Education Systems and Changes Over Time . . . . .2.3.1Homogeneous Versus Heterogeneous . . . . . . . . . . . . . .2.3.2Centralized Versus Decentralized . . . . . . . . . . . . . . . . .References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78911111315.19202325262627303031Methodology: Constructing a Socioeconomic Index for TIMSSTrend Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3.1TIMSS Data and Sample Characteristics . . . . . . . . . . . . . . . . . . .3.2Construction of a Proxy Measure for Socioeconomic Status . . . . .3.2.1Components of the SES* Measure . . . . . . . . . . . . . . . .3.2.2Multiple Imputation of Missing Values . . . . . . . . . . . . .3.2.3The SES* Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3.2.4Defining High- and Low-SES* Groups . . . . . . . . . . . . .3.3Analytic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3.3.1Plausible Values and Imputed Datasets . . . . . . . . . . . . .3.3.2Measuring Educational Inequality . . . . . . . . . . . . . . . . .3.3.3Country-Level Indicators in the Educational Systemsand the Macroeconomic Context . . . . . . . . . . . . . . . . . .References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32. 33vii

viii45ContentsSocioeconomic Achievement Gaps: Trend Results for EducationSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.1Overall Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.1.1Increasing SES* Achievement Gap . . . . . . . . . . . . . . . .4.1.2Decreasing SES* Achievement Gap . . . . . . . . . . . . . . .4.2Education System Specific Findings . . . . . . . . . . . . . . . . . . . . . .4.2.1Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.2Hong Kong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.3Hungary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.4Islamic Republic of Iran . . . . . . . . . . . . . . . . . . . . . . . .4.2.5The Republic of Korea . . . . . . . . . . . . . . . . . . . . . . . . .4.2.6Lithuania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.7New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.8Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.9Russian Federation . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.10 Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.11 Slovenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.12 Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4.2.13 United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Trends in Socioeconomic Achievement Gaps in the MacroeconomicContext: Discussion and Future Research . . . . . . . . . . . . . . . . . . . . .5.1Summary of the Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5.2Relating the Findings to Country-Level Indicators in theEducational Systems and the Macroeconomic Context . . . . . . . . .5.2.1Tentative Pattern 1: Reductions in the AchievementGap Tend to Accompany Improvements in OverallTIMSS Performance . . . . . . . . . . . . . . . . . . . . . . . . . . .5.2.2Tentative Pattern 2: Education Systems ThatObserved Increases in Achievement Gaps Tendto be Decentralized . . . . . . . . . . . . . . . . . . . . . . . . . . .5.2.3Tentative Pattern 3: Education Systems ThatReduced Investment in Education Tended to Observean Increased Mathematics Achievement Gap . . . . . . . . .5.3Limitations of the Study and Recommendations forFuture Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5.4What Have We Learned from Twenty Years of TIMSS Data? . . .References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Appendix Sensitivity Check . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A.1 Index Sensitivity Check . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .A.2 Cut-off Sensitivity Check . . . . . . . . . . . . . . . . . . . . . . . . . . . . .References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35353636414144464850525456586163656769. 71. 72. 73. 73. 77. 77. 78. 79. 80.81818283

Chapter 1Socioeconomic Inequality and EducationalOutcomes: An IntroductionAbstract International large-scale assessments may be used to understand differencesin average student performance across countries over time. Differences in achievementare associated with students’ background characteristics and, while the most salientbackground variables may differ across education systems, a substantial amount of thevariance in student achievement is normally explained by family socioeconomic status(SES). Family SES is thus considered an important factor in education research, butthere are still challenges regarding how to best measure SES operationally. In additionto measuring student achievement, the IEA’s Trends in International Mathematics andScience Study (TIMSS) has been collecting background information from students,their teachers, and principals at four-year intervals since 1995. This study uses datafrom the IEA’s TIMSS grade eight mathematics and science assessments to examinechanges in the achievement gaps between high- and low-SES students between 1995and 2015 for 13 education systems, as operationalized by a modified version of theTIMSS home educational resources index. The performance of disadvantaged studentsmay also be tracked over time. These measures explain a sizeable amount of variationin the TIMSS achievement scores and, in conjunction with data on the countries’education systems and other macroeconomic indicators, can provide country-specificanalyses and an across-country synthesis.Keywords Achievement gaps · Educational inequality · International large-scaleassessment · Socioeconomic status (SES) · Student achievement · Trend analysis ·Trends in International Mathematics and Science Study (TIMSS) · Australia ·Hong Kong · Hungary · Islamic Republic of Iran · Lithuania · New Zealand ·Norway · Republic of Korea · Russian Federation · Singapore · Slovenia ·Sweden · United States International Association for the Evaluation of Educational Achievement (IEA) 2019M. Broer et al., Socioeconomic Inequality and Educational Outcomes, IEA Research forEducation 5, https://doi.org/10.1007/978-3-030-11991-1 11

21Socioeconomic Inequality and Educational Outcomes: An IntroductionEducational inequality is a central theme in education research due to its strongassociation with the attainment of educational qualifications and social positions in asociety, which more importantly mirrors inequality in a society (Breen and Jonsson2005). Ferreira and Gignoux (2011) described the difference between two types ofinequality (as well as methods for measuring them): (1) inequality of outcomes,which can be expressed simply as the degree of variability in the outcome measure,and (2) inequality in opportunity, which can be described as the degree to whichfamily background and other pre-determined personal characteristics determine aperson’s educational outcomes (including, for example, differential access to betterresourced schools). Our study focuses on the second type of inequality, andspecifically on the degree to which family socioeconomic status (SES) is related toeducational outcomes as measured in the Trends in International Mathematics andScience Study (TIMSS). When we write about inequality or educational inequalityfurther on in the report, especially in the results section, it should be interpreted as“educational inequality in opportunity due to SES.” Researchers have madesubstantial contributions to the understanding of how SES relates to studentperformance (Lee and Burkam 2002). Sociological theories have been proposedand tested regarding how economic, social, and cultural capital in the family oforigin can help transmit advantages from one generation to the next (Bourdieu 1986;Coleman 1988, 1990; Lareau 2011).Over the last few decades, the emergence of international comparative assessmenthas provided an opportunity for researchers and policymakers to not only trackstudent performance within their own education system but also to compare theirsystem’s performance with that of other participating education systems. Prior tothis, researching the inequality of educational outcomes depended on using differentdata sets from the various education systems to make comparisons across societies(Shavit and Blossfeld 1993). However, student performance results frominternational comparative assessments, such as IEA’s TIMSS and Progress inInternational Reading Literacy Study (PIRLS), and the Program for InternationalStudent Assessment (PISA) run by the Organisation for Economic Cooperation andDevelopemt (OECD), are

Fou-Lai Lin, National Taiwan Normal University, Chinese Taipei Marlaine Lockheed, Princeton University, USA . technical evaluation procedures. The resulting debate integrates powerful conceptual frameworks, comprehensive datasets and rigorous analysis, thus . International Maths

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