Initializing Student Models using Dempster-Shafer Theory

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


Intelligent tutoring system, student modeling, scoring algorithm, Dempster-Shafer theory


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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