Data-driven Hint Generation from Peer Debugging Solutions

Data-driven methods have been a successful approach to generating hints for programming problems. However, the majority of previous studies are focused on procedural hints that aim at moving students to the next closest state to the solution. In this paper, I propose a data-driven method to generate remedy hints for BOTS, a game that teaches programming through a block-moving puzzle. Remedy hints aim to help students out of dead-end states, which are states in the problem from where no student has ever derived a solution. To address this, my proposed work includes designing debugging activities and generating remedy hints from students’ solutions to debugging activities.