@INPROCEEDINGS{IUI07,
  author = {Amershi, S. and Conati, C.},
  title = {Unsupervised and Supervised Machine Learning in User Modeling for
	Intelligent Learning Environments},
  booktitle = {Proceedings of the 2007 International Conference on
Intelligent User
	Interfaces},
  year = {2007},
  pages = {72--81},
  month = {July},
  abstract = {In this research, we outline a user modeling framework
that uses both
	unsupervised and supervised machine learning in order to reduce development
	costs of building user models, and facilitate transferability. We
	apply the framework to model student learning during interaction
	with the Adaptive Coach for Exploration (ACE) learning environment
	(using both interface and eye-tracking data). In addition to demonstrating
	framework effectiveness, we also compare results from previous research
	on applying the framework to a different learning environment and
	data type. Our results also confirm previous research on the value
	of using eye-tracking data to assess student learning.}
}