Authoring Neuro-fuzzy Tutoring Systems for M and E-Learning

Zataraín-Cabada, Ramón; Barrón-Estrada, M. L.; Sandoval, Guillermo; Osorio, Moisés; Urías, Eduardo; Reyes-García, Carlos A.

doi:10.1007/978-3-540-88636-5_74

Cited by 8 publications

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“…With the idea of giving learners a more protagonist role, many efforts have been done recently to capture the way students learn in order to model their learning style [7,8,9,10]. The ILSQ questionnaire is used to calculate learning styles with the support of Bayesian Networks, Linear Temporal Logic, or Neuro-Fuzzy Systems.…”

Section: Introductionmentioning

confidence: 99%

A Learning Social Network with Recognition of Learning Styles Using Neural Networks

Zataraín-Cabada

Barrón-Estrada

Angulo

et al. 2010

Advances in Pattern Recognition

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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.

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Section: Introductionmentioning

confidence: 99%