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Academic Motivation in Introductory Business Analytics Courses: A Bayesian Approach

Author

Listed:
  • Stacey Vaziri

    (Department of Engineering Education, College of Engineering, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24601)

  • Baback Vaziri

    (Department of Computer Information Systems and Business Analytics, College of Business, James Madison University, Harrisonburg, Virginia 22807)

  • Luis J. Novoa

    (Department of Computer Information Systems and Business Analytics, College of Business, James Madison University, Harrisonburg, Virginia 22807)

  • Elham Torabi

    (Department of Computer Information Systems and Business Analytics, College of Business, James Madison University, Harrisonburg, Virginia 22807)

Abstract

The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically, the study will attempt to answer the questions of whether students’ scores on the MUSIC model predict or explain effort, academic performance, course rating, and instructor rating. A Bayesian approach to linear regression is used to determine and understand the impact of the MUSIC model components on the aforementioned output measures.

Suggested Citation

  • Stacey Vaziri & Baback Vaziri & Luis J. Novoa & Elham Torabi, 2022. "Academic Motivation in Introductory Business Analytics Courses: A Bayesian Approach," INFORMS Transactions on Education, INFORMS, vol. 22(2), pages 121-129, January.
    • Handle: RePEc:inm:orited:v:22:y:2022:i:2:p:121-129
    DOI: 10.1287/ited.2021.0247
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    References listed on IDEAS

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    1. Sinjini Mitra & Gerard Beenen, 2019. "A Comparative Study of Learning Styles and Motivational Factors in Traditional and Online Sections of a Business Course," INFORMS Transactions on Education, INFORMS, vol. 20(1), pages 1-15, September.
    2. Sinjini Mitra & Zvi Goldstein, 2018. "Impact of Supplemental Instruction on Business Courses: A Statistical Study," INFORMS Transactions on Education, INFORMS, vol. 18(2), pages 89-101, January.
    3. Natalie M. Scala & Stella Tomasi & Andrea Goncher & Karen M. Bursic, 2018. "Motivation and Analytics: Comparing Business and Engineering Students," INFORMS Transactions on Education, INFORMS, vol. 19(1), pages 1-11, September.
    4. Thomas A. Grossman & Vijay Mehrotra & Mouwafac Sidaoui, 2016. "A Student-Centered Approach to the Business School Management Science Course," INFORMS Transactions on Education, INFORMS, vol. 16(2), pages 42-53, January.
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    Cited by:

    1. Lui-Kwan Ng & Chung-Kwan Lo, 2022. "Flipped Classroom and Gamification Approach: Its Impact on Performance and Academic Commitment on Sustainable Learning in Education," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
    2. Matthew J. Drake, 2024. "Case Article—Creating a Brick Empire Through Data Visualization and Analytics," INFORMS Transactions on Education, INFORMS, vol. 24(3), pages 271-277, May.

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