Fuzzy neural system model for online learning styles identification, as an adaptive hybrid e-learning system architecture component

L. Alfaro, C. Rivera, J. Luna-Urquizo, E. Castañeda, F. Fialho

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

In the present work, we present a Fuzzy Neural System Model for online identification of Learning Styles which gives support for contents personalization. The model was developed to serve as a component for an Adaptive Hybrid E-Learning System Architecture, which focus on a high degree of customization and content adaptation. We proposal a Hybrid System model, in which techniques of Neural Networks, Fuzzy Logic and Case Based Reasoning are incorporated into the multiagent system. Finally, the authors present the architecture of the Fuzzy Neural System model, the results of the analysis of the model validation tests establishing conclusions and recommendations.

Idioma originalInglés
Título de la publicación alojada16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Subtítulo de la publicación alojadaInnovation, Education, and Inclusion
EditorialLatin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)9780999344316
DOI
EstadoPublicada - 2018
Evento16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology - Lima, Perú
Duración: 18 jul. 201820 jul. 2018

Serie de la publicación

NombreProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen2018-July
ISSN (versión digital)2414-6390

Conferencia

Conferencia16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
País/TerritorioPerú
CiudadLima
Período18/07/1820/07/18

Nota bibliográfica

Publisher Copyright:
© 2018 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

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