An educational recommender system based on argumentation theory

You are free to use the manuscript version of your article for internal, educational or other purposes of your own institution, company or funding agency[EN] Recommender Systems aim to provide users with search results close to their needs, making predictions of their preferences. In virtual learning environments, Educational Recommender Systems deliver learning objects according to the student's characteristics, preferences and learning needs. A learning object is an educational content unit, which once found and retrieved may assist students in their learning process. In previous work, authors have designed and evaluated several recommendation techniques for delivering the most appropriate learning object for each specific student. Also, they have combined these techniques by using hybridization methods, improving the performance of isolated techniques. However, traditional hybridization methods fail when the learning objects delivered by each recommendation technique are very different from those selected by the other techniques (there is no agreement about the best learning object to recommend). In this paper, we present a new recommendation method based on argumentation theory that is able to combine content-based, collaborative and knowledge-based recommendation techniques, or to act as a new recommendation technique. This method provides the students with those objects for which the system is able to generate more arguments to justify their suitability. It has been implemented and tested in the Federation of Learning Objects Repositories of Colombia, getting promising results.This work was partially developed with the aid of the doctoral grant offered to Paula A. Rodriguez by 'Programa Nacional de Formacion de Investigadores - COLCIENCIAS', Colombia and partially funded by the COLCIENCIAS project 1119-569-34172 from the Universidad Nacional de Colombia. It was also supported by the by the projects TIN2015-65515-C4-1-R and TIN2014-55206-R of the Spanish government and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politecnica de Valencia.Rodríguez, P.; Heras, S.; Palanca Cámara, J.; Poveda, JM.; Duque, N.; Julian Inglada, VJ. (2017). An educational recommender system based on argumentation theory. AI Communications. 30(1):19-36. https://doi.org/10.3233/AIC-170724S193630