Initializing Student Models using Dempster-Shafer Theory

S. Sonamthiang, K. Naruedomkul (Thailand), and N. Cercone (Canada)

Keywords

Intelligent tutoring system, student modeling, scoring algorithm, DempsterShafer theory

Abstract

Students bring preconceptions into learning situations. If their prior understanding is not engaged, they may fail to grasp new concepts. We present a pretest scoring algorithm to initialize a student model. Initializing student a model can reveal student background knowledge with respect to the domain content. Dempster-Shafer theory was applied to cope with uncertainty factors in using a test which included incomplete data and students’ unsolicited behaviors. Many concepts may be needed to answer one question correctly; therefore questions of the pretest can be used as sensors that collect evidence of student preconceptions. The system is stand-alone and easily employable by any intelligent tutoring system. The applicability of our approach was demonstrated by using the scoring result with an overlay student model.

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