A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application
Artificial Intelligence
2013-01-14 v1
Abstract
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.
Keywords
Cite
@article{arxiv.1301.2297,
title = {A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application},
author = {Ann Nicholson and Tal Boneh and Tim Wilkin and Kaye Stacey and Liz Sonenberg and Vicki Steinle},
journal= {arXiv preprint arXiv:1301.2297},
year = {2013}
}
Comments
Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001)