A multifactor approach to student model evaluation

Authors:
Michael V. Yudelson;Olga P. Medvedeva;Rebecca S. Crowley
Affiliations:
Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, USA and School of Information Sciences, University of Pittsburgh, Pittsburgh, USA;Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, USA;Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, USA and Intelligent Systems Program, University of Pittsburgh, Pittsburgh, USA and Department of Path ...
Venue:
User Modeling and User-Adapted Interaction
Year:
2008

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Abstract

Creating student models for Intelligent Tutoring Systems (ITS) in novel domains is often a difficult task. In this study, we outline a multifactor approach to evaluating models that we developed in order to select an appropriate student model for our medical ITS. The combination of areas under the receiver-operator and precision-recall curves, with residual analysis, proved to be a useful and valid method for model selection. We improved on Bayesian Knowledge Tracing with models that treat help differently from mistakes, model all attempts, differentiate skill classes, and model forgetting. We discuss both the methodology we used and the insights we derived regarding student modeling in this novel domain.