Working Paper: NBER ID: w21628
Authors: Steven D. Levitt; Mingjen 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.
Keywords: No keywords provided
JEL Codes: K42
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| seating proximity (C92) | likelihood of shared incorrect answers (C83) |
| students sitting next to each other (C92) | shared incorrect answers (Y10) |
| increased monitoring (E63) | reduced cheating behavior (C92) |
| random seat assignments (C78) | answer similarity (C59) |