Design of a recommender system for intelligent classrooms based on multiagent systems

Dulce Rivero-Albarrán, Francklin Rivas-Echeverria, Laura Guerra, Brian Arellano, Stalin Arciniegas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Information Technology and Systems, ICITS 2018
EditorsAlvaro Rocha, Teresa Guarda
PublisherSpringer Verlag
Pages973-982
Number of pages10
ISBN (Print)9783319734491
DOIs
StatePublished - 2018
EventInternational Conference on Information Technology and Systems, ICITS18 - Libertad city, Ecuador
Duration: 11 Jan 201713 Jan 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume721
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Information Technology and Systems, ICITS18
Country/TerritoryEcuador
CityLibertad city
Period11/01/1713/01/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2018.

Keywords

  • Intelligent classrooms
  • Learning environments
  • Learning objects
  • Multiagent systems
  • Recommender system

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