Motivational profiles in TIMSS mathematics : exploring student clusters across countries and time
This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from the IEA’s Trends in International Mathematics and Science Study (TIMSS) data. Statistical cluster analysis is used to identify groups of stude...
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| Format: | E-Book Buch |
| Sprache: | Englisch |
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Cham
SpringerOpen
2019
Springer Nature Springer International Publishing AG Springer International Publishing |
| Ausgabe: | 1 |
| Schriftenreihe: | IEA Research for Education |
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| ISBN: | 3030261824, 9783030261825, 9783030261832, 3030261832 |
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| Abstract | This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from the IEA’s Trends in International Mathematics and Science Study (TIMSS) data. Statistical cluster analysis is used to identify groups of students with similar motivational profiles, across grades and over time, for multiple participating countries. While motivational variables systematically relate to school outcomes, linear relationships can obscure the diverse makeup of student subgroups, each with varying combinations of motivation, emotions, and attitudes. In this book, a person-centered analysis of distinct and meaningful motivational profiles and their differences on sociodemographic variables and mathematics performance broadens understanding about the role that motivation characteristics play in learning and achievement in mathematics. Exploiting the richness of IEA’s TIMSS data from many countries, extracted clusters reveal consistent, as well as certain nuanced patterns that are systematically linked to sociodemographic and achievement measures. Student clusters with inconsistent motivational profiles were found in all countries; mathematics self-confidence then emerged as the variable more closely associated with average achievement. The findings demonstrate that teachers, researchers, and policymakers need to take into account differential student profiles, prioritizing techniques that target skill and competence in mathematics, in educational efforts to develop student motivation. |
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| AbstractList | This open access book presents a person-centred exploration of student profiles, using variables related to motivation to do school mathematics derived from the IEA's Trends in International Mathematics and Science Study (TIMSS) data. Statistical cluster analysis is used to identify groups of students with similar motivational profiles, across grades and over time, for multiple participating countries. While motivational variables systematically relate to school outcomes, linear relationships can obscure the diverse makeup of student subgroups, each with varying combinations of motivation, emotions, and attitudes. In this book, a person-centred analysis of distinct and meaningful motivational profiles and their differences on sociodemographic variables and mathematics performance broadens understanding about the role that motivation characteristics play in learning and achievement in mathematics. Exploiting the richness of IEA's TIMSS data from many countries, extracted clusters reveal consistent, as well as certain nuanced patterns that are systematically linked to sociodemographic and achievement measures. Student clusters with inconsistent motivational profiles were found in all countries; mathematics self-confidence then emerged as the variable more closely associated with average achievement. The findings demonstrate that teachers, researchers, and policymakers need to take into account differential student profiles, prioritizing techniques that target skill and competence in mathematics, in educational efforts to develop student motivation. [Publisher summary, ed] This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from the IEA's Trends in International Mathematics and Science Study (TIMSS) data. Statistical cluster analysis is used to identify groups of students with similar motivational profiles, across grades and over time, for multiple participating countries. While motivational variables systematically relate to school outcomes, linear relationships can obscure the diverse makeup of student subgroups, each with varying combinations of motivation, emotions, and attitudes. In this book, a person-centered analysis of distinct and meaningful motivational profiles and their differences on sociodemographic variables and mathematics performance broadens understanding about the role that motivation characteristics play in learning and achievement in mathematics. Exploiting the richness of IEA's TIMSS data from many countries, extracted clusters reveal consistent, as well as certain nuanced patterns that are systematically linked to sociodemographic and achievement measures. Student clusters with inconsistent motivational profiles were found in all countries; mathematics self-confidence then emerged as the variable more closely associated with average achievement. The findings demonstrate that teachers, researchers, and policymakers need to take into account differential student profiles, prioritizing techniques that target skill and competence in mathematics, in educational efforts to develop student motivation. This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from the IEA’s Trends in International Mathematics and Science Study (TIMSS) data. Statistical cluster analysis is used to identify groups of students with similar motivational profiles, across grades and over time, for multiple participating countries. While motivational variables systematically relate to school outcomes, linear relationships can obscure the diverse makeup of student subgroups, each with varying combinations of motivation, emotions, and attitudes. In this book, a person-centered analysis of distinct and meaningful motivational profiles and their differences on sociodemographic variables and mathematics performance broadens understanding about the role that motivation characteristics play in learning and achievement in mathematics. Exploiting the richness of IEA’s TIMSS data from many countries, extracted clusters reveal consistent, as well as certain nuanced patterns that are systematically linked to sociodemographic and achievement measures. Student clusters with inconsistent motivational profiles were found in all countries; mathematics self-confidence then emerged as the variable more closely associated with average achievement. The findings demonstrate that teachers, researchers, and policymakers need to take into account differential student profiles, prioritizing techniques that target skill and competence in mathematics, in educational efforts to develop student motivation. |
| Author | Brown, Gavin T. L Papanastasiou, Elena C Michaelides, Michalis P Eklöf, Hanna |
| AuthorAffiliation | Umea University University of Nicosia University of Auckland University of Cyprus |
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| Notes | Includes bibliographical references Cham Switzerland: Springer International Publishing, 2019. Includes bibliographical references. xi, 144p. Title from title screen (viewed on 31/03/2020). Removed invalid ISBN/suffix "(PDF)". Electronic reproduction. Dordrecht: Springer, 2019. Requires the Libby app or a modern web browser. |
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| Snippet | This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from... This open access book presents a person-centred exploration of student profiles, using variables related to motivation to do school mathematics derived from... This open access book presents a person-centered exploration of student profiles, using variables related to motivation to do school mathematics derived from... |
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| SubjectTerms | Achievement motivation Assessment beteendevetenskapliga mätningar Cluster analysis Comparative education didactics of educational measurement Education Education: examinations and assessment Educational evaluation Educational psychology Educational systems and structures Education—Psychology International education Mathematics Mathematics -- Study and teaching Mathematics -- Study and teaching -- Psychological aspects Mathematics achievement Mathematics curriculum Mathematics education Mathematics teachers Mathematics teaching Motivation Motivation in education Nonfiction Secondary education Secondary school mathematics Social research and statistics Society and Social Sciences Sociology Sociology and anthropology Statistics Student motivation Trends in International Mathematics and Science Study Trends in International Mathematics and Science Study (TIMSS) |
| SubjectTermsDisplay | Education. Electronic books. Nonfiction. Sociology. |
| TableOfContents | Intro -- Foreword -- Acknowledgments -- Contents -- 1 Introduction to Motivational Profiles in TIMSS Mathematics -- 1.1 Motivation in Mathematics in Studies of Educational Achievement -- 1.2 A Person-Centered Approach to the Study of Motivation in TIMSS Mathematics -- 1.3 Potential to Expand the Current State of Research -- 1.4 Overview of This Book -- References -- 2 The Relationship of Motivation with Achievement in Mathematics -- 2.1 Introduction to Student Motivation -- 2.2 Theoretical Approaches to the Study of Motivation -- 2.2.1 Self-determination Theory -- 2.2.2 Expectancy-Value Theory -- 2.2.3 Self-efficacy Theory -- 2.2.4 Self-concept -- 2.2.5 Achievement Goal Theory -- 2.3 Measures of Motivation in TIMSS -- 2.4 The Relationship Between Motivation and Achievement -- 2.5 Self-reported Ratings of Motivation Across Education Systems -- 2.6 Self-reported Ratings of Motivation Across Ages -- 2.7 Another Approach to Studying the Motivation- Achievement Relationship -- References -- 3 Methodology: Cluster Analysis of Motivation Variables in the TIMSS Data -- 3.1 TIMSS Sampling -- 3.2 Jurisdictions Included in This Study -- 3.3 Instrumentation -- 3.3.1 Motivation Measures in the TIMSS 2015 Administration -- 3.3.2 Motivation Measures in the TIMSS 2007 Administration -- 3.3.3 Motivation Measures in the 1995 Administration -- 3.4 Other Variables Included in the Study -- 3.4.1 TIMSS Achievement Score Estimation -- 3.4.2 Other Variables of Interest -- 3.5 Analysis Technique -- References -- 4 Cluster Analysis Results for TIMSS 2015 Mathematics Motivation by Grade and Jurisdiction -- 4.1 Introducing the Person-Centered Approach -- 4.2 Cluster Analysis Results for the TIMSS 2015 Administration at Grade Four by Jurisdiction -- 4.2.1 Australia -- 4.2.2 Canada-Ontario -- 4.2.3 Canada-Quebec -- 4.2.4 England -- 4.2.5 Hong Kong -- 4.2.6 Hungary 4.2.7 Iran -- 4.2.8 Japan -- 4.2.9 Norway -- 4.2.10 Singapore -- 4.2.11 Slovenia -- 4.2.12 USA -- 4.3 Cluster Analysis Results for the TIMSS 2015 Administration at Grade Eight by Jurisdiction -- 4.3.1 Australia -- 4.3.2 Canada-Ontario -- 4.3.3 Canada-Quebec -- 4.3.4 England -- 4.3.5 Hong Kong -- 4.3.6 Hungary -- 4.3.7 Iran -- 4.3.8 Japan -- 4.3.9 Norway -- 4.3.10 Singapore -- 4.3.11 Slovenia -- 4.3.12 USA -- 5 Cluster Analysis Findings Over 20 Years of TIMSS -- 5.1 Summary of Cluster Analysis Results for Grade Four Samples -- 5.1.1 The TIMSS 1995 Administration -- 5.1.2 The TIMSS 2007 Administration -- 5.1.3 The TIMSS 2015 Administration -- 5.2 Summary of Cluster Analysis Results for Grade Eight Samples -- 5.2.1 The TIMSS 1995 Administration -- 5.2.2 The TIMSS 2007 Administration -- 5.2.3 The TIMSS 2015 Administration -- 5.3 Twenty-Year Patterns in TIMSS by Country and Grade -- 6 Insights from Motivational Profiles in TIMSS Mathematics -- 6.1 Examining the Role of Motivation in Educational Achievement -- 6.2 Clusters of Students Using Motivation Variables: A Person-Centered Approach -- 6.3 Motivation Clusters and Achievement -- 6.4 Motivation Clusters, and Student and Family Characteristics -- 6.5 Methodological Concerns -- 6.6 Concluding Remarks -- References -- Appendix A IBM SPSS Code for the Two-Step Cluster Analysis -- B TIMSS 1995 and 2007 Boxplots by Cluster for Each Jurisdiction -- B.1 Grade Four -- B.2 Grade Eight -- C TIMSS 1995 and 2007 Descriptive Statistics by Cluster for Each Jurisdiction -- C.1 Grade Four, TIMSS 1995 -- C.2 Grade Eight, TIMSS 1995 -- C.3 Grade Four, TIMSS 2007 -- C.4 Grade Eight, TIMSS 2007 |
| Title | Motivational profiles in TIMSS mathematics : exploring student clusters across countries and time |
| URI | https://cir.nii.ac.jp/crid/1130005509146021764 https://directory.doabooks.org/handle/20.500.12854/25886 http://library.oapen.org/handle/20.500.12657/22955 https://ebookcentral.proquest.com/lib/[SITE_ID]/detail.action?docID=5926956 https://search.informit.org/documentSummary;res=AEIPT;dn=225373 https://www.vlebooks.com/vleweb/product/openreader?id=none&isbn=9783030261832 http://link.overdrive.com/?titleID=10072075&websiteID= https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163032 |
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