Luciana A. M. Zaina
ABSTRACT
In the last years, the adoption of recommender systems for improving user interaction has increased in e-learning applications. In the educational area, the recommendation of relevant and interesting content can attract the student's attention, motivating her/him during the learning-teaching process. It is very important, thus, to know learner preferences to suggest suitable contents to the students. The goal of this work is to present an approach to design the student interaction based on the recommendation of e-learning content, determining a more suitable relationship between learning objects and learning profiles. In our proposal, the learning profile is split into categories to attend different student preferences during the teaching-learning process: perception, presentation-format and participation. Our recommendation uses these categories to filter out the most suitable learning objects organized according to the IEEE LOM standard. We present a prototype architecture named e-LORS, over which we perform demonstrative experiments.
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