Discovering skill prerequisite structure through Bayesian estimation and nested model comparison

Identifying prerequisite relationships among skills is important for better student modeling in many educational systems. In this paper, we propose a new method to discover prerequisite structure from data using nested model comparisons in the context of Bayesian estimation. We evaluate our method with simulated data and real math test data.