In recent years researchers have been working to develop tools to filter the information available and give the users the content that is relevant to them. This paper presents a recommendation system developed on an agent architecture software based on a management content model in blended learning environments. It also uses clustering algorithms to find relevant information in the content, building a search space tailored to the interests of the learner. To validate the architecture proposed we worked with Action Research methodology and was developed a prototype system called SisMA in order to retrieve the information in the educational setting. To measure the effectiveness of the application and its impact on the learning process the system was tested in two scenarios. The results showed that the relevance of content and the profile generated by its work plan have had a positive effect on the learning process.

Peer Reviewed