Abstract
Nowadays, many platforms provide open educational resources to learners. So, they must browse and explore several suggested contents to better assimilate their courses. To facilitate the selecting task of these resources, the present paper proposes an intelligent tutoring system that can access teaching contents available on the web automatically and offers them to learners as additional information sources. In doing so, the authors highlight the description logic approach and its knowledge representation strength that underwrites the modulization, inference, and querying about a web ontology language, and enhanced traditional tutoring systems architecture using ontologies and description logic to enable them to access various data sources on the web. Finally, this article concludes that the combination of machine learning with the semantic web has provided a supportive study environment and enhanced the schooling conditions within open and distance learning.
Highlights
Every educational system aims to reduce the associated costs of the education process and increase the learners' assimilation level
The work described in this paper proposes a hybrid Intelligent Tutoring System (ITS) that allows the exploitation of existing Open Educational Resources (OER) from various sources on the web
The learning gain is a measure that indicates how much effect of such educational system on the schooling career of the learner, as it is calculated based on the ratio of obtained scores at the beginning and the end of the course
Summary
Every educational system aims to reduce the associated costs of the education process and increase the learners' assimilation level. On the other hand, embracing openness principles in e-learning has allowed people to freely access various data sources on the web. Many concepts have emerged aimed at democratizing knowledge and enabling free access to information sources for each person, among these are Open Pedagogy, Open Educational Resources (OER), and Practices (OEP). The adopted knowledge representation manner affects directly the effectiveness of such kind of systems. For this reason, caution must be taken when choosing a representation method. The progress of AI in the domain of solving problems and representing knowledge has added a certain amount of intelligence to educational systems
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