Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    UID:
    b3kat_BV046190294
    Format: 1 Online-Ressource (xi, 144 Seiten) , Diagramme
    ISBN: 9783030261832
    Series Statement: IEA research for education volume 7
    Note: Open Access
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26182-5
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26184-9
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-26185-6
    Language: English
    Subjects: Sociology
    RVK:
    Keywords: Schulleistungsmessung ; Testergebnis ; Testauswertung
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    UID:
    almahu_9948170421302882
    Format: XI, 144 p. 50 illus., 1 illus. in color. , online resource.
    Edition: 1st ed. 2019.
    ISBN: 9783030261832
    Series Statement: IEA Research for Education, A Series of In-depth Analyses Based on Data of the International Association for the Evaluation of Educational Achievement (IEA), 7
    Content: 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.
    Note: 1. Introduction to Motivational Profiles in TIMSS Mathematics -- 2. The Relationship of Motivation with Achievement in Mathematics -- 3. Methodology: Cluster Analysis of Motivation Variables in the TIMSS Data -- 4. Cluster Analysis Results for TIMSS 2015 Mathematics Motivation by Grade and Jurisdiction -- 5. Cluster Analysis Findings Over 20 Years of TIMSS -- 6. Insights from Motivational Profiles in TIMSS Mathematics -- Appendix A -- Appendix B -- Appendix C.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783030261825
    Additional Edition: Printed edition: ISBN 9783030261849
    Additional Edition: Printed edition: ISBN 9783030261856
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    UID:
    almahu_9949602272102882
    Format: 1 online resource (149 pages)
    Edition: 1st ed.
    ISBN: 9783030261832
    Series Statement: IEA Research for Education Series ; v.7
    Note: 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.
    Additional Edition: Print version: Michaelides, Michalis P. Motivational Profiles in TIMSS Mathematics Cham : Springer International Publishing AG,c2019 ISBN 9783030261825
    Language: English
    Keywords: Electronic books.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    UID:
    almahu_9949595416102882
    Format: 1 online resource (XI, 144 p. 50 illus., 1 illus. in color.)
    Edition: 1st ed. 2019.
    ISBN: 3-030-26183-2
    Series Statement: IEA Research for Education, A Series of In-depth Analyses Based on Data of the International Association for the Evaluation of Educational Achievement (IEA), 7
    Content: 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.
    Note: 1. Introduction to Motivational Profiles in TIMSS Mathematics -- 2. The Relationship of Motivation with Achievement in Mathematics -- 3. Methodology: Cluster Analysis of Motivation Variables in the TIMSS Data -- 4. Cluster Analysis Results for TIMSS 2015 Mathematics Motivation by Grade and Jurisdiction -- 5. Cluster Analysis Findings Over 20 Years of TIMSS -- 6. Insights from Motivational Profiles in TIMSS Mathematics -- Appendix A -- Appendix B -- Appendix C. , English
    Additional Edition: ISBN 3-030-26182-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    UID:
    edoccha_9959151211702883
    Format: 1 online resource (XI, 144 p. 50 illus., 1 illus. in color.)
    Edition: 1st ed. 2019.
    ISBN: 3-030-26183-2
    Series Statement: IEA Research for Education, A Series of In-depth Analyses Based on Data of the International Association for the Evaluation of Educational Achievement (IEA), 7
    Content: 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.
    Note: 1. Introduction to Motivational Profiles in TIMSS Mathematics -- 2. The Relationship of Motivation with Achievement in Mathematics -- 3. Methodology: Cluster Analysis of Motivation Variables in the TIMSS Data -- 4. Cluster Analysis Results for TIMSS 2015 Mathematics Motivation by Grade and Jurisdiction -- 5. Cluster Analysis Findings Over 20 Years of TIMSS -- 6. Insights from Motivational Profiles in TIMSS Mathematics -- Appendix A -- Appendix B -- Appendix C. , English
    Additional Edition: ISBN 3-030-26182-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    UID:
    edocfu_9959151211702883
    Format: 1 online resource (XI, 144 p. 50 illus., 1 illus. in color.)
    Edition: 1st ed. 2019.
    ISBN: 3-030-26183-2
    Series Statement: IEA Research for Education, A Series of In-depth Analyses Based on Data of the International Association for the Evaluation of Educational Achievement (IEA), 7
    Content: 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.
    Note: 1. Introduction to Motivational Profiles in TIMSS Mathematics -- 2. The Relationship of Motivation with Achievement in Mathematics -- 3. Methodology: Cluster Analysis of Motivation Variables in the TIMSS Data -- 4. Cluster Analysis Results for TIMSS 2015 Mathematics Motivation by Grade and Jurisdiction -- 5. Cluster Analysis Findings Over 20 Years of TIMSS -- 6. Insights from Motivational Profiles in TIMSS Mathematics -- Appendix A -- Appendix B -- Appendix C. , English
    Additional Edition: ISBN 3-030-26182-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Did you mean 9783030216825?
Did you mean 9783030231125?
Did you mean 9783030061821?
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages