This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
COMET: A Collaborative Tutoring System for Medical Problem-Based Learning
July/August 2007 (vol. 22 no. 4)
pp. 70-77
Siriwan Suebnukarn, Thammasat University Dental School
Peter Haddawy, Asian Institute of Technology
The Collaborative Medical Tutor (COMET) is an intelligent tutoring system for medical problem-based learning (PBL). COMET emulates live human-tutored medical PBL sessions as much as possible while also letting students participate collaboratively from disparate locations. COMET uses Bayesian networks to model both individual and group student knowledge and activity. Generic domain-independent tutoring algorithms use these student and group models to generate tutoring hints. COMET incorporates a multimodal interface that integrates text and graphics in a rich communication channel between the students and the system and among students in the group. A comparison of learning outcomes shows that students using the COMET system achieved significantly higher clinical-reasoning gains than students in human-tutored sessions. This article is part of a special issue on intelligent educational systems.
Index Terms:
intelligent tutoring systems, computer-supported collaborative learning, Bayesian networks, medicine, problem-based learning, empirical evaluation
Citation:
Siriwan Suebnukarn, Peter Haddawy, "COMET: A Collaborative Tutoring System for Medical Problem-Based Learning," IEEE Intelligent Systems, vol. 22, no. 4, pp. 70-77, July-Aug. 2007, doi:10.1109/MIS.2007.66
Usage of this product signifies your acceptance of the Terms of Use.