Detecting and Preventing Cheating in Exams: Evidence from a Field Experiment

A-Tier
Journal: Journal of Human Resources
Year: 2024
Volume: 59
Issue: 1

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This work examines how to detect, document, and prevent plagiarism in exams. First, to identify and quantify plagiarism, we propose methods that compare similarities in multiple-choice answers between seat neighbors and nonneighbors. Second, we document cheating in undergraduate exams. Under baseline monitoring, at least 7.7 percent of the row-wise neighbor pairs plagiarized. Pairs composed of academically weaker students cheated more. Third, using a field experiment, we demonstrate that close monitoring eliminated cheating. By contrast, signing an honesty declaration doubled cheating relative to the control group. Complementary experiments suggest that the declaration backfired because it weakened the social norm of academic integrity.

Technical Details

RePEc Handle
repec:uwp:jhriss:v:59:y:2024:i:1:p:210-241
Journal Field
Labor
Author Count
3
Added to Database
2026-01-25