A learning social network with recognition of learning styles using neural networks

Authors:
Ramón Zatarain-Cabada;M. L. Barrón-Estrada;Viridiana Ponce Angulo;Adán José García;Carlos A. Reyes García
Affiliations:
Instituto Tecnológico de Culiacán, Culiacán Sinaloa, México;Instituto Tecnológico de Culiacán, Culiacán Sinaloa, México;Instituto Tecnológico de Culiacán, Culiacán Sinaloa, México;Instituto Tecnológico de Culiacán, Culiacán Sinaloa, México;Instituto Nacional de Astrofísica, Óptica y Electrónica, Puebla, México
Venue:
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Year:
2010

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Abstract

The implementation of an adaptive learning social network to be used as an authoring tool, is presented in this paper. With this tool, adaptive courses, intelligent tutoring systems and lessons can be created, displayed and shared in collaborative and mobile environments by communities of instructors and learners. The Felder-Silverman model is followed to tailor courses to the student's learning style. Self Organizing Maps (SOM) are applied to identify the student's learning style. The introduction of a social learning network to create, view and manage adaptive intelligent tutoring systems, and a novel method to identify the student's learning style, are the contributions of this paper.