Issue No. 02 - April-June (2010 vol. 3)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TLT.2009.40
Fabian Abel , Leibniz University of Hannover, Hannover
Ig Ibert Bittencourt , Federal University of Alagoas, Maceío
Evandro Costa , Federal University of Alagoas, Maceío
Nicola Henze , Leibniz University of Hannover, Hannover
Daniel Krause , Leibniz University of Hannover, Hannover
Julita Vassileva , University of Saskatchewan, Saskatoon
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.
Information filtering, user profiles and alert services, online information services.
N. Henze, F. Abel, I. I. Bittencourt, D. Krause, E. Costa and J. Vassileva, "Recommendations in Online Discussion Forums for E-Learning Systems," in IEEE Transactions on Learning Technologies, vol. 3, no. , pp. 165-176, 2009.