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

doi:10.18687/laccei2018.1.1.259

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

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.

Original language	English
Title of host publication	16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Subtitle of host publication	Innovation, Education, and Inclusion
Publisher	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)	9780999344316
DOIs	https://doi.org/10.18687/laccei2018.1.1.259
State	Published - 2018
Event	16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology - Lima, Peru Duration: 18 Jul 2018 → 20 Jul 2018

Publication series

Name	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume	2018-July
ISSN (Electronic)	2414-6390

Conference

Conference	16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Country/Territory	Peru
City	Lima
Period	18/07/18 → 20/07/18

Bibliographical note

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

Keywords

Adaptive Systems
Artificial Neural Networks
E-Learning
Fuzzy Logic
Fuzzy Neural Systems
Hybrid architecture
Multiagent Systems

Access to Document

10.18687/laccei2018.1.1.259

Cite this

Alfaro, L., Rivera, C., Luna-Urquizo, J., Castañeda, E., & Fialho, F. (2018). Fuzzy neural system model for online learning styles identification, as an adaptive hybrid e-learning system architecture component. In 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Innovation, Education, and Inclusion (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2018-July). Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/laccei2018.1.1.259

Alfaro, L. ; Rivera, C. ; Luna-Urquizo, J. et al. / Fuzzy neural system model for online learning styles identification, as an adaptive hybrid e-learning system architecture component. 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Innovation, Education, and Inclusion. Latin American and Caribbean Consortium of Engineering Institutions, 2018. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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Alfaro, L , Rivera, C, Luna-Urquizo, J, Castañeda, E & Fialho, F 2018, Fuzzy neural system model for online learning styles identification, as an adaptive hybrid e-learning system architecture component. in 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Innovation, Education, and Inclusion. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2018-July, Latin American and Caribbean Consortium of Engineering Institutions, 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, Lima, Peru, 18/07/18. https://doi.org/10.18687/laccei2018.1.1.259

Fuzzy neural system model for online learning styles identification, as an adaptive hybrid e-learning system architecture component. / Alfaro, L.; Rivera, C.; Luna-Urquizo, J. et al.
16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Innovation, Education, and Inclusion. Latin American and Caribbean Consortium of Engineering Institutions, 2018. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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KW - Artificial Neural Networks

KW - E-Learning

KW - Fuzzy Logic

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KW - Hybrid architecture

KW - Multiagent Systems

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Alfaro L , Rivera C, Luna-Urquizo J, Castañeda E, Fialho F. Fuzzy neural system model for online learning styles identification, as an adaptive hybrid e-learning system architecture component. In 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Innovation, Education, and Inclusion. Latin American and Caribbean Consortium of Engineering Institutions. 2018. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/laccei2018.1.1.259

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

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Keywords

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