Motivational profiles in TIMSS mathematics : exploring student clusters across countries and time / Michalis P. Michaelides, Gavin T. L. Brown, Hanna Eklöf, Elena C. Papanastasiou.
2019
QA11.2
Linked e-resources
Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Motivational profiles in TIMSS mathematics : exploring student clusters across countries and time / Michalis P. Michaelides, Gavin T. L. Brown, Hanna Eklöf, Elena C. Papanastasiou.
ISBN
9783030261832 (electronic book)
3030261832 (electronic book)
9783030261825
3030261832 (electronic book)
9783030261825
Published
Cham, Switzerland : SpringerOpen, [2019]
Language
English
Description
1 online resource (xi, 144 pages) : illustrations.
Item Number
10.1007/978-3-030-26183-2 doi
Call Number
QA11.2
Dewey Decimal Classification
510.71
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 19, 2019).
Series
IEA research for education ; v. 7.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
All Resources