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iGLS: intelligent grouping for online collaborative learning

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Liu, Shuangyan, Joy, Mike and Griffiths, Nathan (2009) iGLS: intelligent grouping for online collaborative learning. In: IEEE International Conference on Advanced Learning Technologies, Riga, Latvia, July 15-17, 2009. Published in: ICALT: 2009 IEEE International Conference on Advanced Learning Technologies pp. 364-368.

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Official URL: http://dx.doi.org/10.1109/ICALT.2009.41

Abstract

One of the factors that affect successful collaborative learning is the composition of collaborative groups. Due to the lack of intelligent grouping according to learners' pedagogic needs in current online collaborative learning environments, developing intelligent grouping according to individual learners' cognitive characteristics is highly desired. In this paper, we propose a new approach to supporting intelligent grouping based on learners' learning styles. Our approach achieves the balance of different levels of learning styles in group composition. We demonstrate how it can fit into current activity-based collaborative learning environments and how it could be applied in a real world application.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
L Education
Divisions: Faculty of Science > Computer Science
Journal or Publication Title: ICALT: 2009 IEEE International Conference on Advanced Learning Technologies
Publisher: IEEE
ISBN: 978-1-4244-4482-3
Editor: Aedo, I and Chen, NS and Sampson, D and Zaitseva, L and Kinshunk, X
Date: 2009
Number of Pages: 5
Page Range: pp. 364-368
Identification Number: 10.1109/ICALT.2009.41
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Conference Paper Type: Paper
Title of Event: IEEE International Conference on Advanced Learning Technologies
Type of Event: Conference
Location of Event: Riga, Latvia
Date(s) of Event: July 15-17, 2009
URI: http://wrap.warwick.ac.uk/id/eprint/6493

Data sourced from Thomson Reuters' Web of Knowledge

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