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The ever growing importance of e-learning over the last decade has triggered an explosion of resources available on the Web. Although this multiplicity of available resources can foster the development of a critical spirit, discernment and the student’s ability to weigh up the merits of different points of view, it can also induce disorientation in the search for the resources best suited to her/his needs and learning style. This issue has driven research into recommendation systems, already well known in fields such as e-commerce, applied to e-learning environments. However, in such environments the recommendations can only be efficacious if the system is able to deal with the many different factors involved in the learning process, such as the learning goal and the student’s cognitive features. This work proposes a recommendation strategy that combines, by adopting a hybrid cascade approach, two knowledge-based techniques that can take these factors into account in the recommendation process.


recommender system learning style personalised learning ontologies knowledge-based systems

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How to Cite
Di Bitonto, P., Laterza, M., Roselli, T., & Rossano, V. (2010). A recommendation method for e-learning environments: the rule-based technique. Journal of E-Learning and Knowledge Society, 6(3).

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