Student assessment using Bayesian nets

We describe OLAE as an assessment tool that collects data from students solving problems in introductory college physics, analyses that data with probabilistic methods that determine what knowledge the student is using, and flexibly presents the results of analysis. For each problem, OLAE automatically creates a Bayesian net that relates knowledge, represented as first-order rules, to particular actions, such as written equations. Using the resulting Bayesian network, OLAE observes a student's behavior and computes the probabilities that the student knows and uses each of the rules.