Cheating and Signaling

The Chronicle of Higher Education has an article on cheating in online courses and some of the high-tech measures being used to detect such cheating:

As the students proceeded, they were told whether each answer was right or wrong.

Mr. Smith figured out that the actual number of possible questions in the test bank was pretty small. If he and his friends got together to take the test jointly, they could paste the questions they saw into the shared Google Doc, along with the right or wrong answers. The schemers would go through the test quickly, one at a time, logging their work as they went. The first student often did poorly, since he had never seen the material before…The next student did significantly better, thanks to the cheat sheet, and subsequent test-takers upped their scores even further. They took turns going first.

…”So the grades are bouncing back and forth, but we’re all guaranteed an A in the end,” Mr. Smith told me. “We’re playing the system, and we’re playing the system pretty well.”

…A method under consideration at MIT would analyze each user’s typing style to help verify identity, Mr. Agarwal told me in a recent interview. Such electronic fingerprinting could be combined with face-recognition software to ensure accuracy, he says. Since most laptops now have Webcams built in, future online students might have to smile for the camera to sign on.

Some colleges already require identity-verification techniques that seem out of a movie. They’re using products such as the Securexam Remote Proctor, which scans fingerprints and captures a 360-degree view around students, and Kryterion’s Webassessor, which lets human proctors watch students remotely on Web cameras and listen to their keystrokes.

The cheater-detector arms-race is interesting but also makes me think about the signaling theory of education. Cheating works best if the signaling model is true. If education were all about increasing productivity and if employers could measure productivity then cheating would be a waste of time. As illustrated by Mr. Smith, however, at least some students care about the A that cheating produces more than the knowledge that learning produces. Mr. Smith must believe either that education (in at least this class) doesn’t increase productivity or that employers don’t learn about productivity. Employers have big incentives to learn about productivity so my bet is on the former.

If students perceive the situation correctly we also have an interesting hypothesis: students should cheat more in those courses that offer the least productivity gains. Studies on cheating find mixed results across major, with some finding that business majors cheat more and others not, but these studies are cross sectional, i.e. across individuals. A better test of the theory that I propose would look at cheating by the same individuals across courses. Absences should also be higher in courses with lower productivity gains.