Ontology-based learner modelling for supporting personalised e-Learning

Abstract

The rapid advancements in e-Learning technology enable each learner to have his/her own learning process based on his/her characteristics - this is called personalisation. Furthermore, recent developments in the field of semantic modelling have led to a renewed attention with focus on ontology-based e-learning systems. This paper describes learners' model ontology as a stage for creating personalised e-Learning systems based on learner's abilities, learning styles, prior knowledge and preferences. The learning style can be represented according to different models to support personalisation in different ways. User profile data is collected when the learner registers to the system and will be updated during the learning process. The system also uses Item Response Theory (IRT) for calculating learner's abilities in order to be more accurate.