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Design of a Recommender System for Intelligent Classrooms Based on Multiagent Systems

  • Dulce Rivero-Albarrán
  • Francklin Rivas-Echeverria
  • Laura Guerra
  • Brian Arellano
  • Stalin Arciniegas
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 721)

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.

Keywords

Recommender System Intelligent classrooms Multiagent systems Learning objects Learning environments 

Notes

Acknowledgments

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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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Dulce Rivero-Albarrán
    • 1
    • 2
  • Francklin Rivas-Echeverria
    • 1
    • 2
  • Laura Guerra
    • 1
  • Brian Arellano
    • 1
  • Stalin Arciniegas
    • 1
  1. 1.Pontificia Universidad Católica del Ecuador, Sede Ibarra. Escuela de IngenieríaIbarraEcuador
  2. 2.Facultad de Ingeniería, Escuela de Ingeniería de SistemasUniversidad de Los AndesMéridaVenezuela

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