Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
An Evidential Model for Tracking Initiative in Collaborative Dialogue Interactions
User Modeling and User-Adapted Interaction
An Analysis of Initiative Selection in CollaborativeTask-Oriented Discourse
User Modeling and User-Adapted Interaction
Mixed initiative in dialogue: an investigation into discourse segmentation
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
A Simulated Student Can Improve Collaborative Learning
International Journal of Artificial Intelligence in Education
Tools for Authoring a Dialogue Agent that Participates in Learning Studies
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
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The aim of the project we discuss in this paper is to develop a computational model of peer learning. We present an extensive analysis of peer learning dialogues, analysis on which our computational model is based. Our model incorporates shifts of initiative as an identifier of knowledge co-construction. We have embedded this model in a peer-learning agent that collaborates with students to solve problems in the domain of computer science data structures.