Method for test results analysis of e-learning based on rough set theory

Yiwei Zhang, Lihua Zhang

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Abstract

In order to improve personalized service of e-learning systems, this paper introduces a method of attribute value reduction algorithm and decision rules generation based on rough set theory. This work analyzes e-learners' online test results and creates decision tables via expanding information of all the examination questions. The rough set based algorithm generates rules, which are used to evaluate the degree of e-learners master the knowledge, to provide personalized feedback, and to make the e-learners select instructional resources more specifically.

Original languageEnglish
Title of host publicationInformation Science and Management Engineering
PublisherWITPress
Pages1373-1378
Number of pages6
ISBN (Print)9781845648282
DOIs
Publication statusPublished - 2013

Publication series

NameWIT Transactions on Information and Communication Technologies
Volume46 VOLUME 2
ISSN (Print)1743-3517

Keywords

  • Data mining
  • Online test
  • Rough set
  • Rules generation

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Zhang, Y., & Zhang, L. (2013). Method for test results analysis of e-learning based on rough set theory. In Information Science and Management Engineering (pp. 1373-1378). (WIT Transactions on Information and Communication Technologies; Vol. 46 VOLUME 2). WITPress. https://doi.org/10.2495/ISME20131772