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Improving the Teaching of Hypothesis Testing Using a Divide-and-Conquer Strategy and Content Exposure Control in a Gamified Environment

Author

Listed:
  • David Delgado-Gómez

    (Department of Statistics, Universidad Carlos III, Getafe, 28903 Madrid, Spain)

  • Franks González-Landero

    (Edison Developments, 44002 Teruel, Spain)

  • Carlos Montes-Botella

    (Department of Statistics, Universidad Carlos III, Getafe, 28903 Madrid, Spain)

  • Aaron Sujar

    (Department of Statistics, Universidad Carlos III, Getafe, 28903 Madrid, Spain
    Department of Computer Engineering, Universidad Rey Juan Carlos, 28933 Madrid, Spain)

  • Sofia Bayona

    (Department of Computer Engineering, Universidad Rey Juan Carlos, 28933 Madrid, Spain
    Center for Computational Simulation, N/N Montepríncipe Avenue, Boadilla del Monte, 28660 Madrid, Spain)

  • Luca Martino

    (Signal Theory and Communication Department, Universidad Rey Juan Carlos, 28933 Madrid, Spain)

Abstract

Hypothesis testing has been pointed out as one of the statistical topics in which students present more misconceptions. In this article, an approach based on the divide-and-conquer methodology is proposed to facilitate its learning. The proposed strategy is designed to sequentially explain and evaluate the different concepts involved in hypothesis testing, ensuring that a new concept is not presented until the previous one has been fully assimilated. The proposed approach, which contains several gamification elements (i.e., points or a leader-board), is implemented into an application via a modern game engine. The usefulness of the proposed approach was assessed in an experiment in which 89 first-year students enrolled in the Statistics course within the Industrial Engineering degree participated. Based on the results of a test aimed at evaluating the acquired knowledge, it was observed that students who used the developed application based on the proposed approach obtained statistically significant higher scores than those that attended a traditional class ( p -value < 0.001), regardless of whether they used the learning tool before or after the traditional class. In addition, the responses provided by the students who participated in the study to a test of satisfaction showed their high satisfaction with the application and their interest in the promotion of these tools. However, despite the good results, they also considered that these learning tools should be considered as a complement to the master class rather than a replacement.

Suggested Citation

  • David Delgado-Gómez & Franks González-Landero & Carlos Montes-Botella & Aaron Sujar & Sofia Bayona & Luca Martino, 2020. "Improving the Teaching of Hypothesis Testing Using a Divide-and-Conquer Strategy and Content Exposure Control in a Gamified Environment," Mathematics, MDPI, vol. 8(12), pages 1-14, December.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:12:p:2244-:d:464979
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    References listed on IDEAS

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    1. Joan Garfield & Dani Ben‐Zvi, 2007. "How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics," International Statistical Review, International Statistical Institute, vol. 75(3), pages 372-396, December.
    2. Larreamendy-Joerns, Jorge & Leinhardt, Gaea & Corredor, Javier, 2005. "Six Online Statistics Courses: Examination and Review," The American Statistician, American Statistical Association, vol. 59, pages 240-251, August.
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    Cited by:

    1. Virginia Niculescu, 2022. "On Generalizing Divide and Conquer Parallel Programming Pattern," Mathematics, MDPI, vol. 10(21), pages 1-22, October.

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