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A Recommender System Based on Cognitive Map for Smart Classrooms

  • Jose Aguilar
  • Priscila Valdiviezo-Diaz
  • Guido Riofrio
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 721)

Abstract

In this paper, we propose a Fuzzy Cognitive Maps (FCMs) to recommender Learning Resources in a Smart Classroom. We have proposed a Smart Environment for a Classroom in previous works, based on Multi-agent Systems, called SaCI. One of its agents is a recommender system of Learning Resources. In this paper, we define this recommender system using Fuzzy Cognitive Maps. Our recommender system exploits the knowledge, learns, discovers new information, infers preferences, among other thing. For that, it uses five types of knowledge from SaCI: students, learning resources, topics, context and criticism. The performance results of our recommender system based on FCMs are very encouraging.

Keywords

Cognitive maps Smart Classroom Recommender system 

Notes

Acknowledgment

Dr. Aguilar has been partially supported by the Prometeo Project of the Ministry of Higher Education, Science, Technology and Innovation of the Republic of Ecuador. This work has been partially supported by the UTPL Project entitled: “Medios de Gestión de Servicios (Middleware) Inteligentes para Entornos de Aprendizaje Virtual”.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.CEMISID, Departamento de ComputaciónUniversidad de Los AndesMéridaVenezuela
  2. 2.UTPLLojaEcuador
  3. 3.Dpto. de Ciencias de la Computación y ElectrónicaUniversidad Técnica Particular de LojaLojaEcuador

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