How Data and Metadata Can Thwart Contract Cheating
Three years into my teaching career, I'm approaching 1,000 students taught. Even if I assume that 99 percent of them honestly did their own work, 1 that means that about ten students have cheated in some way.
Catching cheaters is the raison d'etre of sites such as Turnitin. Up until now, they have examined students' previous submissions. To wit, if there's a reasonable chance that David's midterm paper resembles others in Turnitin's database, then the site provides a probability that he has submitted work that isn't his own.
The intelligent use of data and metadata can at least partially combat writers-for-hire.
Is there a major problem with this retrospective approach? You betcha. Ours is an era of rampant contract cheating. On a personal level, at least two of my students in my analytics class clearly turned in work that they contracted others to do. Note to prospective cheaters: Correlation coefficients cannot be 2.0.
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