A Fuzzy Contextual Approach Towards Intelligent Educational Content Adaptation

Fuzzy contextual information is utilized within this paper in order to assist the process of educational multimedia content adaptation. Towards this scope, we extend on previous work in order to address the problem of educational personalization at a semantic level. In different previous works we have developed algorithms to address computationally efficient handling of fuzzy relations, and theory to address knowledge representation, thematic categorization and user profiling. In this work we take two further steps: first, we integrate ontologies in the original knowledge modeling approach and then we explain how these diverse algorithms and methodologies can be combined in order to approach a greater goal, that of educational content personalization. Prior work on Web-based educational content adaptation is now extended with semantic Web functionalities and features. The basis of this work is the role of context, as it improves the quality of the produced results, by utilizing fuzzy algebra, fuzzy sets and relations, towards efficient manipulation of the utilized user profiles. The novelty of the presented work is the ontological representation of contextual knowledge and its utilization within the personalized e-learning process.