Volume 5 Number 12 (Dec. 2010)
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JSW 2010 Vol.5(12): 1363-1370 ISSN: 1796-217X
doi: 10.4304/jsw.5.12.1363-1370

Learning Ability Clustering in Collaborative Learning

Wen-Chih Chang1, Te-Hua Wang2, Mao-Fan Li3
1Department of Information Management, Chung Hua University, Taiwan
2Department of Information Management, Chihlee Institute of Technology, Taiwan
3Informatics Department, Taipei Medical University Hospital, Taiwan

Abstract—Collaborative learning promotes learning motivation which encourages the active participation and leads to good learning performance. In most cases, good grade is usually a good indicator of good learner. Teachers might classify learners into various groups according to their grade. As a result, learners with poor grades are easily depressed and self-distrust. In this paper, we integrate K-means clustering method and IRT forecasting process to solve the grouping issue in collaborative learning. With a better grouping solution, teachers then can adjust the learning materials adaptively and teach students according to the learning aptitude.

Index Terms—Learning ability, Item Response Theory, Kmeans, Collaborative Learning.


Cite: Wen-Chih Chang, Te-Hua Wang, Mao-Fan Li, "Learning Ability Clustering in Collaborative Learning," Journal of Software vol. 5, no. 12, pp. 1363-1370, 2010.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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