Towards data-driven mastery learning

Abstract

We have developed a novel data-driven mastery learning system to improve learning in complex procedural problem solving domains. This new system was integrated into an existing logic proof tool, and assigned as homework in a deductive logic course. Student performance and dropout were compared across three systems: The Deep Thought logic tutor, Deep Thought with integrated hints, and Deep Thought with our data-driven mastery learning system. Results show that the data-driven mastery learning system increases mastery of target tutor-actions, improves tutor scores, and lowers the rate of tutor dropout over Deep Thought, with or without provided hints.