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eLORM: learning object relationship mining‐based repository

Yang Ouyang (Networking Centre Laboratory, Department of Computer Science and Technology, Zhejiang University, Hangzhou, China)
Miaoliang Zhu (Networking Centre Laboratory, Department of Computer Science and Technology, Zhejiang University, Hangzhou, China)

Online Information Review

ISSN: 1468-4527

Article publication date: 11 April 2008

Abstract

Purpose

This paper aims to explore the feasibility of using web‐mining technology on learning object (LO) usage information to discover the LO relation pattern and provide valuable recommendations on related learning resources. Design/methodology/approach – This paper proposes three kinds of learning object relation patterns and gives a specific definition of each pattern based on analysing the learners' usage data stored in the learning object repository. These relation patterns can be used to make effective recommendations to learners.

Findings

LO usage data indicate the potential relation patterns between LOs. By using web‐mining technology on the usage data, it is possible to discover valuable relation patterns.

Originality/value

The authors propose a set of LO relation patterns and indicate how they are closely related to users' learning behaviour.

Keywords

Citation

Ouyang, Y. and Zhu, M. (2008), "eLORM: learning object relationship mining‐based repository", Online Information Review, Vol. 32 No. 2, pp. 254-265. https://doi.org/10.1108/14684520810879863

Publisher

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Emerald Group Publishing Limited

Copyright © 2008, Emerald Group Publishing Limited