rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Motivational Profiles in TIMSS Mathematics
    sub title: Exploring Student Clusters Across Countries and Time
  name:
    name part: Michaelides, Michalis P.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Brown, Gavin T. L.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Eklöf, Hanna.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Papanastasiou, Elena C.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XI, 144 pages 50 illustrations, 1 illustrations in color.)
  abstract: 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.
  table of contents: 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.
  note: by Michalis P. Michaelides, Gavin T. L. Brown, Hanna Eklöf, Elena C. Papanastasiou.
  note: Open Access
  subject:
    topic: Assessment
  subject:
    topic: Educational psychology
  subject:
    topic: Education-Psychology
  subject:
    topic: Statistics
  subject:
    topic: International education
  subject:
    topic: Comparative education
  subject:
    topic: Assessment, Testing and Evaluation
  subject:
    topic: Educational Psychology
  subject:
    topic: Statistics for Social Sciences, Humanities, Law
  subject:
    topic: International and Comparative Education
  classification: LC5225.A75
  classification: LB2822.75
  classification: 371.26
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: 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
  identifier: 9783030261832
  identifier: https://doi.org/10.1007/978-3-030-26183-2
  access condition: Open Access
  record info:
    record creation date: 190903
    record change date: 20230829020254.3
    record identifier: in00004423463