A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application

Most successful Bayesian network (BN) ap­ plications to date have been built through knowledge elicitation from experts. This is difficult and time consuming, which has lead to recent interest in automated methods for learning BNs from data. We present a case study in the construction of a BN in an intel­ ligent tutoring application, specifically dec­ imal misconceptions. We describe the BN construction using expert elicitation and then investigate how certain existing automated knowledge discovery methods might support the BN knowledge engineering process.