TY - CHAP
T1 - Methodology
T2 - Cluster analysis of motivation variables in the TIMSS data
AU - Michaelides, Michalis P.
AU - Brown, Gavin T.L.
AU - Eklöf, Hanna
AU - Papanastasiou, Elena C.
N1 - Publisher Copyright:
© 2019, International Association for the Evaluation of Educational Achievement (IEA).
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - This chapter begins with a description of the IEA’s Trends in International Mathematics and Science Study (TIMSS) sampling framework. The research study was based on data from three cycles of TIMSS collected at grades four and eight from 12 jurisdictions (Australia, England, Hong Kong, Hungary, Iran, Japan, Norway, Ontario, Quebec, Singapore, Slovenia, and the USA) that participated at both grades in 1995, 2007, and 2015. The motivation variables available in each cycle of administration are outlined, together with how conceptually similar measures for value, enjoyment, and self-confidence in mathematics were constructed; descriptions of demographic and achievement measures used in the analysis are also provided. Two-step cluster analysis was used to create separate profiles of student motivation for each set of data. The characteristics of each motivational cluster were evaluated to ascertain whether differences in cluster membership were related to student background variables (such as sex, time on homework, parental education, and home resources) and mathematics achievement.
AB - This chapter begins with a description of the IEA’s Trends in International Mathematics and Science Study (TIMSS) sampling framework. The research study was based on data from three cycles of TIMSS collected at grades four and eight from 12 jurisdictions (Australia, England, Hong Kong, Hungary, Iran, Japan, Norway, Ontario, Quebec, Singapore, Slovenia, and the USA) that participated at both grades in 1995, 2007, and 2015. The motivation variables available in each cycle of administration are outlined, together with how conceptually similar measures for value, enjoyment, and self-confidence in mathematics were constructed; descriptions of demographic and achievement measures used in the analysis are also provided. Two-step cluster analysis was used to create separate profiles of student motivation for each set of data. The characteristics of each motivational cluster were evaluated to ascertain whether differences in cluster membership were related to student background variables (such as sex, time on homework, parental education, and home resources) and mathematics achievement.
KW - Cluster analysis
KW - Instrumentation
KW - Motivation scales
KW - TIMSS sampling
UR - http://www.scopus.com/inward/record.url?scp=85097975246&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-26183-2_3
DO - 10.1007/978-3-030-26183-2_3
M3 - Chapter
AN - SCOPUS:85097975246
T3 - IEA Research for Education
SP - 25
EP - 40
BT - IEA Research for Education
PB - Springer Nature
ER -