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Catching Cheating Students

Author

Listed:
  • Steven D. Levitt
  • Ming-Jen Lin

Abstract

We develop a simple algorithm for detecting exam cheating between students who copy off one another’s exam. When this algorithm is applied to exams in a general science course at a top university, we find strong evidence of cheating by at least 10 percent of the students. Students studying together cannot explain our findings. Matching incorrect answers prove to be a stronger indicator of cheating than matching correct answers. When seating locations are randomly assigned, and monitoring is increased, cheating virtually disappears.

Suggested Citation

  • Steven D. Levitt & Ming-Jen Lin, 2015. "Catching Cheating Students," NBER Working Papers 21628, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21628
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    Cited by:

    1. Le Maux, Benoît & Necker, Sarah, 2023. "Honesty nudges: Effect varies with content but not with timing," Journal of Economic Behavior & Organization, Elsevier, vol. 207(C), pages 433-456.
    2. Erich Battistin, 2016. "How manipulating test scores affects school accountability and student achievement," IZA World of Labor, Institute of Labor Economics (IZA), pages 295-295, September.
    3. Kelum A. A. Gamage & Roshan G. G. R. Pradeep & Erandika K. de Silva, 2022. "Rethinking Assessment: The Future of Examinations in Higher Education," Sustainability, MDPI, vol. 14(6), pages 1-15, March.

    More about this item

    JEL classification:

    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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