BAYESIAN NETWORKS IN EDUCATIONAL TESTING

In this paper we discuss applications of Bayesian networks to educational testing. Namely, we deal with the diagnosis of person's skills. We show that when modeling dependence between skills we can get better diagnosis faster. We present results of experiments with basic operations that use fractions. The experiments suggest that the test design can benefit from a Bayesian network that models relations between skills, not only in the case of an adaptive test but also when designing a fixed (non-adaptive) test.