title: Decision-support and intelligent tutoring systems in medical education.
abstract: One of the challenges in medical education is to teach the decision-making process. This learning process varies according to the experience of the student and can be supported by various tools. In this paper we present several approaches that can strengthen this mechanism, from decision-support tools, such as scoring systems, Bayesian models, neural networks, to cognitive models that can reproduce how the students progressively build their knowledge into memory and foster pedagogic methods.
authors.affiliation: Department of Systems and Computer Engineering, Carleton University, Ottawa, Ont. monique_frize@carleton.ca
authors.forename: M
authors.initials: M
authors.lastname: Frize
authors.forename: C
authors.initials: C
authors.lastname: Frasson
mesh_terms: D001185:Artificial Intelligence; D001499:Bayes Theorem; D003657:Decision Making; D003661:Decision Support Techniques; D004501:Education, Medical / Q000379:methods*; D019359:Knowledge; D007858:Learning; D016571:Neural Networks, Computer; D013663:Teaching / Q000379:methods