This paper emphasizes the significance of discussion forums in e-learning applications and the need for recommendations to help learners find relevant information within large or weakly structured forums. It presents a generic personalization framework and evaluates it using a recommender architecture for the e-learning-focused forum Comtella-D. The evaluation analyzes various sources of user feedback and the necessary level of user interaction to provide recommendations. The findings inform a personalization rule that selects the most suitable recommendation strategy based on user input data. The study concludes that collaborative filtering techniques can be effectively used in small data sets, such as e-learning discussion forums.
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Abel, Fabian, et al. "Recommendations in online discussion forums for e-learning systems." IEEE transactions on learning technologies 3.2 (2009): 165-176.
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