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Motivation and Analytics: Comparing Business and Engineering Students

Author

Listed:
  • Natalie M. Scala

    (Towson University, Towson, Maryland 21252)

  • Stella Tomasi

    (Towson University, Towson, Maryland 21252)

  • Andrea Goncher

    (Charles Sturt University, Bathurst, NSW 2795)

  • Karen M. Bursic

    (University of Pittsburgh, Pittsburgh, Pennsylvania 15260)

Abstract

Data analytics is a foundational topic for engineering as well as business students given its importance in subsequent coursework and curriculum. Many common, interdisciplinary analytical topics exist between the engineering and business fields; undergraduate students may approach learning those topics in various ways depending on program or major. This research examines differences in performance on analytics between engineering and business students that may be explained by differences in motivation and attitude. We use a survey and a lecture on trendlines with a common homework assignment to compare the two groups of students. Instructors of an engineering and a business course that incorporate analytics gave the same lecture on the use of spreadsheets to analyze trendline data, assigned the same individual homework assignment, and administered an end-of-module survey. The survey was built from the established MUSIC® Model of Academic Motivation. Analysis of the student data will address differences in motivation and how the program or major impacts student perception of analytical problem solving and contributes to performance on related assignments. We discuss quantitative and qualitative differences between engineering and business majors, concluding with a discussion of future work and some strategies for educators to use when teaching analytics.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:orited:v:19:y::i:1:p:1-11
    DOI: 10.1287/ited.2017.0187
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    References listed on IDEAS

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    1. Coleen R. Wilder & Ceyhun O. Ozgur, 2015. "Business Analytics Curriculum for Undergraduate Majors," INFORMS Transactions on Education, INFORMS, vol. 15(2), pages 180-187, January.
    2. Thomas A. Grossman, 2006. "Integrating Spreadsheet Engineering in a Management Science Course: A Hierarchical Approach," INFORMS Transactions on Education, INFORMS, vol. 7(1), pages 18-36, September.
    3. Tom Van Woensel & Marshall L. Fisher & Jan C. Fransoo, 2010. "Teaching Retail Operations in Business and Engineering Schools," INFORMS Transactions on Education, INFORMS, vol. 11(1), pages 29-34, September.
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    Cited by:

    1. Matthew D. Dean, 2020. "Using the Learning Assistant Model in an Undergraduate Business Analytics Course," INFORMS Transactions on Education, INFORMS, vol. 20(3), pages 125-133, May.
    2. Lisa Beck-Werz & Bernd Frick & Thomas Fritz & Fabian Lensing, 2022. "Understanding the impact of gender and migration on high-ability students’ behavior: Exploring behavioral differences in business, law, and engineering students throughout their academic careers," Working Papers Dissertations 83, Paderborn University, Faculty of Business Administration and Economics.
    3. 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.

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