Open AccessCatching Cheating Students
Author(s) -
Steven D. Levitt,
MingJen Lin
Publication year - 2015
Publication title -
ern: computational techniques (topic)
Language(s) - English
Resource type - Reports
DOI - 10.3386/w21628
Subject(s) - cheating , mathematics education , psychology , computer science , social psychology
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.
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