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A general architecture for intelligent tutoring of diagnostic classification problem solving.

Crowley, Rebecca S and Medvedeva, Olga (2003) A general architecture for intelligent tutoring of diagnostic classification problem solving. AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium. 185 - 189. ISSN 1942-597X

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We report on a general architecture for creating knowledge-based medical training systems to teach diagnostic classification problem solving. The approach is informed by our previous work describing the development of expertise in classification problem solving in Pathology. The architecture envelops the traditional Intelligent Tutoring System design within the Unified Problem-solving Method description Language (UPML) architecture, supporting component modularity and reuse. Based on the domain ontology, domain task ontology and case data, the abstract problem-solving methods of the expert model create a dynamic solution graph. Student interaction with the solution graph is filtered through an instructional layer, which is created by a second set of abstract problem-solving methods and pedagogic ontologies, in response to the current state of the student model. We outline the advantages and limitations of this general approach, and describe it's implementation in SlideTutor - a developing Intelligent Tutoring System in Dermatopathology.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Crowley, Rebecca S
Medvedeva, Olga
Date: 2003
Date Type: Publication
Journal or Publication Title: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Publisher: American Medical Informatics Association (AMIA)
Page Range: 185 - 189
Schools and Programs: School of Medicine > Biomedical Informatics
Refereed: Yes
ISSN: 1942-597X
Article Type: Research Article
MeSH Headings: Artificial Intelligence; Cognition; Computer Graphics; Computer-Assisted Instruction; Humans; Models, Educational; Problem Solving; Programming Languages; Software; Teaching--methods
Other ID: NLM PMC1479898
PubMed Central ID: PMC1479898
PubMed ID: 14728159
Date Deposited: 29 Aug 2012 20:15
Last Modified: 01 Nov 2017 14:03


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