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.Econ exams at Canterbury, at least, are well monitored with random seat allocation, and have been so for a number of years. I wonder what the amount of cheating is.
Tuesday, 13 October 2015
Catching cheating students
There is a new NBER working paper out on Catching Cheating Students by Steven D. Levitt and Ming-Jen Lin. The abstract reads,