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Who’s Cheating? Mining Patterns of Collusion from Text and Events in Online Exams

Author

Listed:
  • Catherine Cleophas

    (Institute for Business Management, Kiel University, Kiel 24098, Germany)

  • Christoph Hönnige

    (Institute for Political Science, Leibniz University Hanover, Hanover 30167, Germany)

  • Frank Meisel

    (Institute for Business Management, Kiel University, Kiel 24098, Germany)

  • Philipp Meyer

    (Institute for Political Science, Leibniz University Hanover, Hanover 30167, Germany)

Abstract

As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams’ digital output also enables computer-aided detection of collusion patterns. This paper presents two simple data-driven techniques to analyze exam event logs and essay-form answers. Based on examples from exams in social sciences, we show that such analyses can reveal patterns of student collusion. We suggest using these patterns to quantify the degree of collusion. Finally, we summarize a set of lessons learned about designing and analyzing online exams.

Suggested Citation

  • Catherine Cleophas & Christoph Hönnige & Frank Meisel & Philipp Meyer, 2023. "Who’s Cheating? Mining Patterns of Collusion from Text and Events in Online Exams," INFORMS Transactions on Education, INFORMS, vol. 23(2), pages 84-94, January.
    • Handle: RePEc:inm:orited:v:23:y:2023:i:2:p:84-94
    DOI: 10.1287/ited.2021.0260
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    References listed on IDEAS

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