On the Development of Adaptive Web-based Learning Communities

M. Rigou (Greece)


Learning communities, adaptive, personalization, webmining, recommendations


Online learning communities may greatly benefit from incorporating adaptive features which take advantage of the knowledge and experiences of community members and use it to better serve each individual depending on personal preferences, goals and needs, as well as the history of activity in the community. This paper investigates the incorporation of adaptive features in online learning communities and focuses on deploying web mining techniques for this purpose. It presents a pilot system that experiments with the application of a number of adaptation forms and concludes with identifying some open issues and concerns in the domain of applying adaptiveness to web environments that host learning communities.

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