Abstract
A learning object (LO) is any entity or resource that can be used in computer-aided learning. Can be text, multimedia content, presentations, programs or any other type of digital content, usually available on web portals or distance learning systems. The LOs consulted by a student during a session of access to these portals are related to the research interests of the student for the duration of the session. This article proposes a model for recommending that explores this relationship by recommending LOs based on the analysis of similarity between historical sessions. The proposed model receives the sequence of LOs consulted during the current user session and sessions located whose sequences are similar to LOs consulted following the current session. LOs found in similar sessions are then recommended to the user. A prototype applied to a real scenario was developed and the results obtained showed the feasibility of the proposal.
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