Intelligent pedagogical model with kinesthetic-static immersion based on the neuro-linguistic programming approach (NLP)

Simón Choquehuayta Palomino, José Herrera Quispe, Luis Alberto Alfaro Casas, Blas Choquehuayta Llamoca

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, the authors propose a teaching/learning pedagogical model, based on an approach that uses neurolinguistic programming, educational data mining and haptic interaction. It also uses the theory of learning styles, which are identified with data mining techniques, clustering and the Farthest First algorithm, as well as a test of Neurolinguistic Programming. Depending on the results obtained, the teaching/learning strategies are defined, and the activities of an educational coaching are suggested, with the purpose of boosting the students' attention in the classroom, stimulating their communicative and psychomotor skills. The proposal was evaluated with a sample of students of regular basic education, to whom an instrument was applied before and after carrying out the tests of applying the plan of the teaching/learning activities. For this purpose, a multifunctional learning kit was constructed, which is a didactic and playful resource, applicable to the student's psychomotor area. The kit contains an application and a hardware device called "Tusuna-pad 1.0", which was implemented in the Unity games engine and was programmed using the C# language. The pedagogical model was validated with the participation of students of Regular Basic Education, considering pedagogical and computational aspects, results that were validated and duly analyzed. Finally, conclusions and recommendations for future work were established.

Original languageEnglish
Pages (from-to)564-573
Number of pages10
JournalInternational Journal of Advanced Computer Science and Applications
Volume10
Issue number11
DOIs
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019, Science and Information Organization.

Keywords

  • Educational data mining
  • Haptic interaction
  • Learning styles
  • Neuro-linguistic programming
  • Viral immersion

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