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

Authors :
Wu, Linjing
Liu, Qingtang
Zhou, Wanlei
Mao, Gang
Huang, Jingxiu
Huang, Huan
Source :
Technology, Knowledge & Learning; Dec2020, Vol. 25 Issue 4, p811-833, 23p
Publication Year :
2020

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22111662
Volume :
25
Issue :
4
Database :
Complementary Index
Journal :
Technology, Knowledge & Learning
Publication Type :
Academic Journal
Accession number :
146477761
Full Text :
https://doi.org/10.1007/s10758-018-9395-7