A semantic approach for situation-aware ubiquitous learner support

Abstract

This paper thoroughly introduces a semantic web approach for supporting decision making in ubiquitous learning environment. Probabilistic ontology will be proposed to reduce inaccuracy, randomness, and incompleteness and will support automated reasoning to support the learner choice of the learning intention, strategy, media and resource according to the predicted learning situation. The multi-entity Bayesian networks (MEBNs) was used for modelling the knowledge and analysing the content in context-aware ubiquitous learning. In fact, MEBNs offer a rigorous framework for knowledge representing and reasoning with probabilistic inference. Finally, a case study has been presented confirming the effectiveness of the proposed model.