Monitoring computer-based collaborative problem solving
Journal of Artificial Intelligence in Education
Modelling Dialogue and Beliefs as a Basis for Generating Guidance in a CSCL Environment
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Using Dialogue Features to Predict Trouble During Collaborative Learning
User Modeling and User-Adapted Interaction
Some useful tactics to modify, map and mine data from intelligent tutors
Natural Language Engineering
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Our goal is to build and evaluate a web-based, collaborative distance-learning system that will allow groups of students to interact with each other remotely and with an intelligent agent that will aid them in their learning. The agent will follow the discussion and interact when it detects learning trouble of some sort, such as confusion about the problem they are working on or a participant who is dominating the discussion or not interacting with the other participants. In order to recognize problems in the dialogue, we are first examining the role that a participant is playing as the dialogue progresses. In this paper we discuss group interaction during collaborative learning, our representation of participant roles, and the statistical model we are using to determine the role being played by a participant at any point in the dialogue.