Abstract
In this work it’s presented the description of a Recommender Systems to be used in a learning environment. For this, it’s defined the diverse recommendation methods that can be used: Content-based Recommendations, Collaboration recommendations and Hybrid Systems. It is proposed a Teaching agent design for obtaining the most appropriate learning objects based on Multiagent Systems framework composed of a Planning Agent, a Recommendation System and a Learning Object Management System; all of them collaborating on an intelligent platform. This design can be used in intelligent classrooms because it can adapt the environment and the teaching contents according to the needs of each student.
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The authors of this paper thank the support given by PUCESI to the project: Intelligent platform in educational environments case: PUCESI Student Office.
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Rivero-Albarrán, D., Rivas-Echeverria, F., Guerra, L., Arellano, B., Arciniegas, S. (2018). Design of a Recommender System for Intelligent Classrooms Based on Multiagent Systems. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_92
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