Recommendations in Online Discussion Forums for E-Learning Systems

Authors:
Fabian Abel;Ig Ibert Bittencourt;Evandro Costa;Nicola Henze;Daniel Krause;Julita Vassileva
Affiliations:
Leibniz University of Hannover, Hannover;Federal University of Alagoas, Maceío;Federal University of Alagoas, Maceío;Leibniz University of Hannover, Hannover;Leibniz University of Hannover, Hannover;University of Saskatchewan, Saskatoon
Venue:
IEEE Transactions on Learning Technologies
Year:
2010

Citing 0
Cited 4

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Abstract

In this paper, we outline the importance of discussion fora for e-learning applications. Due to a weak structure or size of the discussion forum, recommendations are required in order to help learners finding relevant information within a forum. We present a generic personalization framework and evaluate the framework based on a recommender architecture for the e-learning focused discussion forum Comtella-D. In the evaluation, we examine different sources of user feedback and the required amount of user interaction to provide recommendations. The outcomes of the evaluation serve as source for a personalization rule, which selects the most appropriate recommendation strategy based on available user input data. We furthermore conclude that collaborative filtering techniques can be utilize successfully in small data sets, like e-learning related discussion fora.