Abstract
In this chapter, we present an approach for recommendation of learning materials to students in an e-learning environment. Our aim is to increase the current system’s personalization capabilities for students in different scenarios making use of recommendation techniques. The recommendation is produced considering learning materials’ properties, student’s profile and the context of use. In addition, the process of recommendation is improved through students´ collaboration. In the context of this work, a learning material is a link to a Web page or a paper available on the Web and previously stored in a private repository. The process of collaboration occurs during student’s evaluations of the recommendations. These student´s evaluations are used by the system to produce new recommendations for other students. The main features of the recommendations aspects are described and some examples are also used to discuss and illustrate how to provide this personalization.
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Lichtnow, D., Gasparini, I., Bouzeghoub, A., de Oliveira, J.P.M., Pimenta, M.S. (2011). Recommendation of Learning Material through Students´ Collaboration and User Modeling in an Adaptive E-Learning Environment. In: Daradoumis, T., Caballé, S., Juan, A.A., Xhafa, F. (eds) Technology-Enhanced Systems and Tools for Collaborative Learning Scaffolding. Studies in Computational Intelligence, vol 350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19814-4_12
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DOI: https://doi.org/10.1007/978-3-642-19814-4_12
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