Personalized Students' Profile Based On Ontology and Rule-based Reasoning

Nowadays, most of the existing e-learning architecture provides the same content to all learners due to ”one size fits for all” concept. E-learning refers to the utilization of electronic innovations to convey and encourage training anytime and anywhere. There is a need to create a personalized environment that involves collecting a range of information about each learner. Questionnaires are one way of gathering information on learning style, but there are some problems with their usage, such as reluctance to answer questions as well as guesses the answer being time consuming. Ontology-based semantic retrieval is a hotspot of current research, because ontologies play a paramount part in the development of knowledge. In this paper, a novel way to build an adaptive ontological student profile by analysis of learning patterns through a learning management system, according to the Felder-Silverman learning style model (FSLSM) and Myers-Briggs Type Indicator (MBTI) theory is proposed