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The Analysis of TIMSS 2015 Data with Confirmatory Mixture Item Response Theory: A Multidimensional Approach

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  • Author(s): Saatcioglu, Fatima Munevver; Sen, Sedat
  • Language:
    English
  • Source:
    International Journal of Testing. 2023 23(4):257-275.
  • Publication Date:
    2023
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
    • Peer Reviewed:
      Y
    • Source:
      19
    • Education Level:
      Elementary Secondary Education
      Elementary Education
      Grade 4
      Intermediate Grades
    • Subject Terms:
    • Subject Terms:
    • Subject Terms:
    • Accession Number:
      10.1080/15305058.2023.2214648
    • ISSN:
      1530-5058
      1532-7574
    • Abstract:
      In this study, we illustrated an application of the confirmatory mixture IRT model for multidimensional tests. We aimed to examine the differences in student performance by domains with a confirmatory mixture IRT modeling approach. A three-dimensional and three-class model was analyzed by assuming content domains as dimensions and cognitive domains as item groups. We estimated the item performance differences among the students through structural parameters. There were 463 students from Turkey and 880 students from Canada who participated in the TIMSS 2015 4th-grade mathematics assessment. Results for Turkey indicated, students in Class 2 had better performance in knowing and reasoning compared to those in Classes 1 and 3. Students in Class 2 and Class 3 were similar in applying math concepts compared to students in Class 1. For the Canadian sample, students in Class 2 had better performance in knowing, applying, and reasoning compared to those in Class 1 and 3. Also, Class 3 students were better at applying domain than Class 1. Also, mean values were obtained for all content domains in the two countries. Confirmatory mixture IRT modeling approaches appear to differentiate students' mathematics competencies.
    • Abstract:
      As Provided
    • Publication Date:
      2023
    • Accession Number:
      EJ1401244