A Knowledge Representation Model for Massive Open Online Course Platforms

Kiselev, Boris, Yakutenko, Viacheslav, Yuriev, Mikhail, Zhelbakov, Igor and Cunningham, Stuart (2017) A Knowledge Representation Model for Massive Open Online Course Platforms. In: 7th IEEE Int. Conference on Internet Technologies and Applications ITA-17, Wrexham, UK, 12-15 September 2017, Wrexham, UK.

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Abstract

This paper describes a knowledge model for the design of Massive Open Online Course (MOOC) platforms. It is based on our generic instructional engineering method called Knowledge Field of Educational Environment with Competence Boundary Conditions (KFEEC). KFEEC uses the ontology as a foundation for the knowledge representation model. It provides a flexible structure to the various self-paced e-learning system designs but appears to be overcomplicated for the MOOC platform. This paper describes the KFEEC method, the steps of adapting the KFEEC to the MOOC platform design, and the specification of the resulting knowledge model. This model is a core of the MOOC platform that will be developed in future work.

Item Type: Conference or Workshop Item (Poster)
Divisions: Applied Science, Computing and Engineering
Depositing User: Hayley Dennis
Date Deposited: 17 Dec 2018 11:50
Last Modified: 17 Dec 2018 11:50
URI: http://glyndwr.repository.guildhe.ac.uk/id/eprint/17365

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