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• W1566454014 abstract "The delivery of intelligent support for group work is a complex issue incollaborative learning environments. This particularly pertains to the constructionof effective groups and assessment of collaboration problems. This is because thecomposition of groups can be affected by several variables, and various methodsare desirable for ascertaining the existence of different collaboration problems.Literature has shown that current collaborative learning environments providelimited or no support for teachers to cope with these tasks. Considering this and theincreasing use of online collaboration, this research aims to explore solutions forimproving the delivery of support for group work in collaborative learningenvironments, and thus to simplify how teachers manage collaborative group work.In this thesis, three aspects were investigated to achieve this goal. The firstaspect emphasises on proposing a novel approach for group formation based onstudents‘ learning styles. The novelty and importance of this approach is theprovision of an automatic grouping method that can tailor to individual students‘characteristics and fit well into the existing collaborative learning environments.The evaluation activities comprise the development of an add-on tool and anundergraduate student experiment, which indicate the feasibility and strength of theproposed approach — being capable of forming diverse groups that tend to performmore effectively and efficiently than similar groups for conducting groupdiscussion tasks.The second focus of this research relates to the identification of majorgroup collaboration problems and their causes. A nationwide survey was conductedthat reveals a student perspective on the issue, which current literature fails toadequately address. Based on the findings from the survey, an XML-basedrepresentation was created that provides a unique perspective on the linkagesbetween the problems and causes identified.Finally, the focus was then shifted to the proposal of a novel approach fordiagnosing the major collaboration problems identified. The originality andsignificance of this approach lies in the provision of various methods for ascertaining the existence of different collaboration problems identified, based onstudent interaction data that result from the group work examined. The evaluationprocedure focused on the development of a supporting tool and severalexperiments with a test dataset. The results of the evaluation show that thefeasibility and effectiveness are sustained, to a great extent, for the diagnosticmethods addressed.Besides these main proposals, this research has explored a multi-agentarchitecture to unify all the components derived for intelligently managing onlinecollaborative learning, which suggests an overarching framework providingcontext for other parts of this thesis." @default.
• W1566454014 created "2016-06-24" @default.
• W1566454014 creator A5000890330 @default.
• W1566454014 date "2012-03-01" @default.
• W1566454014 modified "2023-09-23" @default.
• W1566454014 title "Intelligent support for group work in collaborative learning environments" @default.
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