Catching Cheating Students

Autor: Steven D. Levitt, Ming-Jen Lin
Rok vydání: 2019
Předmět:
Zdroj: Economica. 87:885-900
ISSN: 1468-0335
0013-0427
DOI: 10.1111/ecca.12331
Popis: 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.
Databáze: OpenAIRE