Matrix Factorization Feasibility for Sequencing and Adaptive Support in Intelligent Tutoring Systems

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.