Bayesian Networks For Competence-based Student Modeling

Adaptive learning technologies have been demonstrating effective by many types of adaptive educational systems (e.g., intelligent tutoring systems, adaptive hypermedia systems, adaptive assessment systems). NMC Horizon Report 2015 predicts that this kind of learning technologies would be deployed widely in higher education in four to five years. Recently, there is a trend of shifting the measurement of student’s performance from a knowledge-based model to a competence-based model. However, in literature, most adaptive educational systems employ student’s knowledge to build student models. In this paper, we propose to integrate competences in student models for adaptive learning technologies. We use Bayesian Networks to model student’s competences in addition to student’s knowledge. We describe a case study in the domain of object-oriented programming, which makes use of the proposed competencebased Bayesian Network model.