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Technology, Knowledge and Learning

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27-11-2018 | Original research

A Semantic Web-Based Recommendation Framework of Educational Resources in E-Learning

Authors: Linjing Wu, Qingtang Liu, Wanlei Zhou, Gang Mao, Jingxiu Huang, Huan Huang

Published in: Technology, Knowledge and Learning | Issue 4/2020

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Abstract

A big challenge in educational resources construction is the intelligent and personalized resource recommendation for learners. This paper proposes a semantic recommendation framework of educational resources based on semantic web and pedagogics. In this framework, a domain ontology is constructed to describe the knowledge structure of the domain. All the resources and user portfolio are described with ontology technology and resource description framework to support semantic inference. Based on the semantic resource organization, we made a set of reasoning rules based on pedagogics. These rules are made from the synthesis of the type of the knowledge, the internal structure of knowledge and learner’s learning performance. A case study was implemented on the course “theory and practice of database”. In this case, learners are recommended different learning materials according to the different knowledge structure and different learning performance. Three typical learning modes are proposed to describe the personalized learning experience. This framework can be used as a guide for teachers and resource designers.

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Title: A Semantic Web-Based Recommendation Framework of Educational Resources in E-Learning
Authors: Linjing Wu
Qingtang Liu
Wanlei Zhou
Gang Mao
Jingxiu Huang
Huan Huang
Publication date: 27-11-2018
Publisher: Springer Netherlands
Published in: Technology, Knowledge and Learning / Issue 4/2020
Print ISSN: 2211-1662
Electronic ISSN: 2211-1670
DOI: https://doi.org/10.1007/s10758-018-9395-7

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