Overview
- Uses TIMSS data collected from multiple countries across twenty years
- Employs a person-centered approach to explore student clusters using motivation and affect variables
- Uncovers meaningful clusters of students with consistent or more nuanced motivational profiles
- Identifies student profiles with inconsistent motivation scores, where self-confidence levels are closely aligned with average achievement
Part of the book series: IEA Research for Education (IEAR, volume 7)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
Keywords
- International large-scale educational assessments
- IEA
- Cross-cultural education research
- Achievement motivation
- Mathematics achievement
- Motivation, affect and attitudes
- School mathematics
- Cluster analysis
- TIMSS data
- Learning and achievement in mathematics
- Motivation profiles
- Mathematics self-confidence
- Enjoyment of mathematics
- Students value mathematics
- Trends in International Mathematics and Science Study
- Open Access
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Motivational Profiles in TIMSS Mathematics
Book Subtitle: Exploring Student Clusters Across Countries and Time
Authors: Michalis P. Michaelides, Gavin T. L. Brown, Hanna Eklöf, Elena C. Papanastasiou
Series Title: IEA Research for Education
DOI: https://doi.org/10.1007/978-3-030-26183-2
Publisher: Springer Cham
eBook Packages: Education, Education (R0)
Copyright Information: International Association for the Evaluation of Educational Achievement (IEA) 2019
Hardcover ISBN: 978-3-030-26182-5Published: 20 September 2019
Softcover ISBN: 978-3-030-26185-6Published: 11 September 2020
eBook ISBN: 978-3-030-26183-2Published: 03 September 2019
Series ISSN: 2366-1631
Series E-ISSN: 2366-164X
Edition Number: 1
Number of Pages: XI, 144
Number of Illustrations: 49 b/w illustrations, 1 illustrations in colour
Topics: Assessment, Testing and Evaluation, Educational Psychology, Statistics for Social Sciences, Humanities, Law, International and Comparative Education