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 language | English |
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Title of host publication | Information Science and Management Engineering |
Publisher | WITPress |
Pages | 1373-1378 |
Number of pages | 6 |
ISBN (Print) | 9781845648282 |
DOIs | |
Publication status | Published - 2013 |
Publication series
Name | WIT Transactions on Information and Communication Technologies |
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Volume | 46 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