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Analyzing User Behavior Distribution on E-Learning Platform with Techniques of Clustering

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Teng, C.W., Lin, C.S., Cheng, S.Y. & Heh, J.S. (2004). Analyzing User Behavior Distribution on E-Learning Platform with Techniques of Clustering. In R. Ferdig et al. (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2004 (pp. 3052-3058). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/13317.

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Conference Information

SITE

Society for Information Technology & Teacher Education International Conference (SITE) 2004
Atlanta, GA, USA
2004
ISBN 1-880094-52-5
  Richard Ferdig, Caroline Crawford, Roger Carlsen, Niki Davis, Jerry Price, Roberta Weber & Dee Anna Willis
AACE

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Authors

Chai-Wen Teng, Chia-Sheng Lin, Shun-Yung Cheng, Jia-Sheng Heh, MCSL, CYCU, TAIWAN, Taiwan

Abstract

Internet makes all the electronic information connected through communication networks. Users access these Internet resources with different behavior models. This research collects user actions on web and preprocesses these data for preparing data mining. These data have been transformed into Normalized-Distribution Matrix form, then using EM algorithm to group the users' behavior distribution into clusters. Teachers or system analysts easily retrieve these cluster's results. Teachers give proper advice to different cluster's students and system administrators adjust E-learning environment according to these outcomes. The experiment system shows IVC (Internet Virtual Community, http://ivc.cycu.edu.tw/) user behavior distribution.

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