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Factor Structure of Student Science-Learning Motivation: Evidence from TIMSS U.S. Data

Author

Listed:
  • Fa Zhang

    (Department of Education, Open University of China, Beijing 100039, China
    Department of Foundations of Education, Virginia Commonwealth University, Richmond, VA 23284, USA)

  • Christine L. Bae

    (Department of Foundations of Education, Virginia Commonwealth University, Richmond, VA 23284, USA)

  • Michael D. Broda

    (Department of Foundations of Education, Virginia Commonwealth University, Richmond, VA 23284, USA)

  • Alison C. Koenka

    (Jeannine Rainbolt College of Education, The University of Oklahoma, Norman, OK 73019, USA)

Abstract

We investigated the structure of science motivation among a nationally representative sample of grade 8 students in the United States from the TIMSS dataset. Drawing on an integrative conceptual model of motivation, the following constructs from situative expectancy-value theory (SEVT) and self-determination theory (SDT) were examined through confirmatory factor analyses, including self-concept, task value (intrinsic and utility value), and sense of relatedness, to test the underlying factor structure of motivation. Internal validity evidence was established, which showed that a four-factor model fits the data significantly better than a three-factor model and one-factor model. This study contributes to the current literature by providing evidence of the four dimensions of motivation in a manner that is theoretically aligned with SEVT and SDT, and validated using the TIMSS dataset. The student’s sense of relatedness as a key interpersonal facet of learning motivation is highlighted in this study.

Suggested Citation

  • Fa Zhang & Christine L. Bae & Michael D. Broda & Alison C. Koenka, 2023. "Factor Structure of Student Science-Learning Motivation: Evidence from TIMSS U.S. Data," Sustainability, MDPI, vol. 15(17), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:13230-:d:1232307
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    References listed on IDEAS

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