Learning to Grade Student Programs in a Massive Open Online Course


We study the problem of automatically evaluating the quality of computer programs produced by students in a very large, online, interactive programming course (or “MOOC”). Automatically evaluating interactive programs (such as computer games) is not easy because such programs lack any sort of well-defined logical specification. As an alternative, we devise some simple statistical approaches to assigning a score to a student-produced code.

Proceedings of the IEEE International Conference on Data Mining