A practical student model for a location-aware and context-sensitive Personalized Adaptive Learning System

Abstract

Student model is an essential component in any adaptive learning environment. Various student modelling approaches have been suggested in the literature that focus on learners' competencies, preferences and other personal attributes. However, there is a lack of a comprehensive student model that combines various aspects of student modelling while also considering the aspects of location and context awareness that are important for emerging ubiquitous learning environments. This paper proposes one such student model in the context of a personalized adaptive learning system, namely Personalized Adaptive Learning Dashboard (PALD), a compound student model bringing together various features of the overlay, fault, and stereotype models to provide a generic approach to modeling student with specific domain related knowledge.