Volume 4 Number 2 (Apr. 2009)
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JSW 2009 Vol.4(2): 167-174 ISSN: 1796-217X
doi: 10.4304/jsw.4.2.167-174

Applying IRT to Estimate Learning Ability and K-means Clustering in Web based Learning

Wen-Chih Chang1 and Hsuan-Che Yang2

1Department of Information Management Chung Hua University, Hsin-Chu, Taiwan
2Department of Education Technology, Tamkang University, Taipei, Taiwan

Abstract—E-learning provides a convenient and efficient way for learning and enriching people’s lives. But there is no appropriate way to estimate and diagnose people when they learning with e-learning environment/system. For learning ability estimation issue, Item Response Theory which plays an important role in modern mental test theory is applied. Besides, K-means clustering method is also applied to cluster learner’s ability for remedying courses or enhancing courses. We integrate these two theories and propose a combination methodology to solve the estimation and diagnostic issues in e-learning environment. A web-based assist system is provided as well. Experimental data is collected with forty sophomore students studying “Business Data Communication” class at Dept. of Information Management in Chung Hua University in Taiwan. We illustrated the method to observe and estimate the variation of learner’s ability. This methodology and system could make some valuable contribution in e-learning related study and society.

Index Terms—E-learning, K-means cluster, Item Response Theory, Learner Ability, Assessment


Cite: Wen-Chih Chang and Hsuan-Che Yang, "Applying IRT to Estimate Learning Ability and K-means Clustering in Web based Learning," Journal of Software vol. 4, no. 2, pp. 167-174, 2009.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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