A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application
Abstract
Most successful Bayesian network (BN) applications 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 intelligent tutoring application, specifically decimal 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.
Cite
Text
Nicholson et al. "A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application." Conference on Uncertainty in Artificial Intelligence, 2001.Markdown
[Nicholson et al. "A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application." Conference on Uncertainty in Artificial Intelligence, 2001.](https://mlanthology.org/uai/2001/nicholson2001uai-case/)BibTeX
@inproceedings{nicholson2001uai-case,
title = {{A Case Study in Knowledge Discovery and Elicitation in an Intelligent Tutoring Application}},
author = {Nicholson, Ann E. and Boneh, Tal and Wilkin, Tim A. and Stacey, Kaye and Sonenberg, Liz and Steinle, Vicki},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2001},
pages = {386-394},
url = {https://mlanthology.org/uai/2001/nicholson2001uai-case/}
}