A pilot study on logic proof tutoring using hints generated from historical student data.

Abstract

We have proposed a novel application of Markov decision processes (MDPs), a reinforcement learning technique, to automatically generate hints using historical student data. Using this technique, we have modified a an existing, non-adaptive logic proof tutor called Deep Thought with a Hint Factory that provides hints on the next step a student might take. This paper presents the results of our pilot study using Deep Thought with the Hint Factory, which demonstrate that hints generated from historical data can support students in writing logic proofs.