Matrix Factorization Feasibility for Sequencing and Adaptive Support in Intelligent Tutoring Systems
نویسندگان
چکیده
Performance prediction has the potential of ameliorate the student model of an Intelligent Tutoring System by predicting whether a student mastered or not a specific set of skills. Recently, it has been shown, by means of a simulated learning process, how performance prediction methods based on Matrix Factorization can be used for continuous score prediction and for sequencing contents through a policy inspired by Vygotsky’s concept of the Zone of Proximal Development. In this paper we discuss the feasibility of the approach analysing a commercial system dataset. We evaluate performances of the score predictor and feasibility of the Vygotsky policy for sequencing tasks and providing adaptive support.
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