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Insights from motivational profiles in TIMSS mathematics
Department of Psychology, University of Cyprus, Nicosia, Cyprus.
The University of Auckland, Auckland, New Zealand.
Umeå University, Faculty of Social Sciences, Department of applied educational science, Departement of Educational Measurement.ORCID iD: 0000-0002-4630-6123
Department of Education, University of Nicosia, Nicosia, Cyprus.
2019 (English)Book (Refereed)
Abstract [en]

A person-centered cluster analysis approach to the study of motivation in IEA’s Trends in International Mathematics and Science Study (TIMSS) mathematics has revealed interesting profiles of students across key motivational constructs. Between four and six different clusters were extracted from each sample analyzed. Unsurprisingly, some clusters had consistent motivation scores, but in almost every jurisdiction, there were clusters of students with inconsistent score distributions between the contributing motivational constructs. The clusters were systematically different on various external variables, such as mean mathematics achievement, gender composition, and the level of home resources available to students. The study also presents a novel way of looking at the relative importance of enjoyment of, confidence in, and value for mathematics, and the association of these motivation variables with achievement and other demographic characteristics at the cluster level. When motivation scores were mixed rather than consistent, there was a uniform achievement advantage enjoyed by the groups of students who had higher scores for confidence in mathematics over enjoyment of, or value for mathematics. This approach revealed that gender and socioeconomic background are not independent of cluster membership. Typically, clusters with high confidence values were comprised of more boys than girls, and students from better resourced homes. The findings can be linked to relevant literature on motivation in mathematics. Educational efforts to develop student motivation need to take into account differential student profiles and prioritize techniques that target skill and competence in mathematics.

Place, publisher, year, edition, pages
Springer Nature, 2019. , p. 114
Series
IEA Research for Education Series, ISSN 2366-1631, E-ISSN 2366-164X ; 7
Keywords [en]
Cluster analysis, Educational achievement, Family characteristics, Mathematics competence, Mathematics motivation, Student characteristics, Student motivation profiles
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Didactics
Identifiers
URN: urn:nbn:se:umu:diva-203461DOI: 10.1007/978-3-030-26183-2_6Scopus ID: 2-s2.0-85097982775ISBN: 978-3-030-26182-5 (print)ISBN: 978-3-030-26183-2 (electronic)OAI: oai:DiVA.org:umu-203461DiVA, id: diva2:1728439
Available from: 2023-01-18 Created: 2023-01-18 Last updated: 2023-01-18Bibliographically approved

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Eklöf, Hanna

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf