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

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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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Acknowledgements

This research is supported by Chinese National Natural Science Foundation Project “Research on Deep Aggregation and Personalized Service Mechanism of Web Learning Resources based on Semantic” (Nos. 71704062, 61772012), Hubei Province Technology Innovation special projects “Key technologies and demonstration applications of Internet + Precision Education” (No. 2017ACA105), and Fundamental Research Funds for the Central Universities in Central China Normal University “Semantic analysis of MOOC comments and its application based on big data” (No. CCNU18QN022).

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Authors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Linjing Wu, Qingtang Liu, Gang Mao & Jingxiu Huang

  2. School of Information Technology, Deakin University, Melbourne, Australia

    Wanlei Zhou

  3. School of Education, South-Central University for Nationalities, Wuhan, Hubei, China

    Huan Huang

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  1. Linjing Wu
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  2. Qingtang Liu
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  4. Gang Mao
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Correspondence to Linjing Wu.

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Wu, L., Liu, Q., Zhou, W. et al. A Semantic Web-Based Recommendation Framework of Educational Resources in E-Learning. Tech Know Learn 25, 811–833 (2020). https://doi.org/10.1007/s10758-018-9395-7

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