Title: An investigation into knowledge discovery in collaborative learning communities

Authors: Jian Liao, Minhong Wang, Yanyan Li, Ronghuai Huang

Addresses: Faculty of Education, Division of Information and Technology Studies, The University of Hong Kong, Pokfulam Road, Hong Kong; E-Learning School, South West University, 400715, Chongqing, China. ' Faculty of Education, Division of Information and Technology Studies, The University of Hong Kong, Pokfulam Road, Hong Kong. ' Knowledge Science and Engineering Institute, School of Education Technology, Beijing Normal University, 100875, Beijing, China. ' Knowledge Science and Engineering Institute, School of Education Technology, Beijing Normal University, 100875, Beijing, China

Abstract: While collaborative community is applied comprehensively in school learning and organisational training, research on collaborative learning process is emerging. Traditional statistical methods make it difficult to perform large volume in-depth analysis on interaction regulations and mechanisms in collaborative communities, especially when bottom-up analysis is required. In this study, data-mining methodology is addressed to discover knowledge from large-scale and real interaction data in collaborative learning communities. We propose to use Knowledge Discovery in Databases (KDD) approach for knowledge discovery in collaborative communities. A case study of role discovery in collaborative learning is developed to demonstrate the usefulness of the approach.

Keywords: CSCL; computer-supported collaborative learning; communities of practice; CoP; collaborative communities; knowledge discovery; data mining; e-learning; internet; online learning; electronic learning.

DOI: 10.1504/IJIEM.2009.023929

International Journal of Internet and Enterprise Management, 2009 Vol.6 No.2, pp.177 - 192

Published online: 20 Mar 2009 *

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