Intelligent Technologies in E-Learning: Personalization and Interoperability

Abstract

Many educational systems are focused predominantly on such an organization of the learning process to be uniform for all learners. This approach is not the best for many learners, especially for those with various difficulties or interests. Strategies for personalization and adaptation can increase the tutoring quality and ensure efficient learning for groups of learners with different needs, goals, or interests. Intelligent technologies can enable the personalization of the learning process. However, no one system can contain all the knowledge needed for all learners, so interoperability between e-learning systems is of greater importance. Standards are needed for ensuring interoperability, but they are not sufficient. This paper first analyzes and classifies sources for learning on the Internet. The findings help to develop a knowledge model needed for a personalized recommendation of web-based sources, complementary to the learning content that a well-organized intelligent educational system can propose to learners. Having in mind specifics of the ontologies needed for modeling the learning domain, a model of the ontological repository for storing ontologies that can be useful for building intelligent educational systems is suggested. We also discussed mapping problems between ontologies and modeling e-learning standards.