  Most successful Bayesian network (BN) applications to datehave been built
through knowledge elicitation from experts.This is difficult and time
consuming, which has lead to recentinterest in automated methods for learning
BNs from data. We present a case study in the construction of a BN in
anintelligent tutoring application, specifically decimal misconceptions.
Wedescribe the BN construction using expert elicitation and then investigate
how certainexisting automated knowledge discovery methods might support the BN
knowledge engineering process.
