Web-Based Learning Under Tacit Mining of Various Data Sources

Authors

DOI:

https://doi.org/10.3991/ijet.v16i16.23405

Keywords:

Intelligent tutoring system, open educational resource, description logics, data access

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.

Author Biography

Abdelouahab Belazoui, University of Batna 2

Associate Professor in Computer Science Department of Pharmacy Faculty of Medicine - University of Batna 2 (Algeria)

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Published

2021-08-23

How to Cite

Belazoui, A., Telli, A., & Arar, C. (2021). Web-Based Learning Under Tacit Mining of Various Data Sources. International Journal of Emerging Technologies in Learning (iJET), 16(16), pp. 153–168. https://doi.org/10.3991/ijet.v16i16.23405

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Papers