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  • 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
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  • 2
    UID:
    gbv_1778514405
    Format: 1 Online-Ressource (144 p.)
    ISBN: 9783030261832
    Series Statement: IEA Research for Education
    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: English
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    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
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  • 4
    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
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  • 5
    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
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  • 6
    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
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