[ Sistema para la selección del método pedagógico en sistemas tutores inteligentes ]
Volume 20, Issue 2, May 2017, Pages 643–651
Ivelisse Teresa Machín Torres1
1 Ingeniera, Facultad de Ciencias Técnicas, Departamento Ingeniería, Universidad José Martí Pérez, Isidro González # 26 entre Ave Libertad y Agramonte, Sancti -Spíritus, Cuba
Original language: Spanish
Copyright © 2017 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The pedagogical method selection is relevant to guarantee adaptability and to personalize each method, while working with intelligent tutorial systems. The objective of this research is just to develop a hybrid system for the pedagogical method selection for an intelligent tutorial system that contributes to knowledge management and strengthens the multiple specific intelligences of each student, in the teaching–learning process. The proposed hybrid system has two components, a genetic algorithm and a neuro fuzzy network, Mamdani Anfis style. The hybrid approach interprets the rules base of a fuzzy system in neural networks terms, where the net simulates a fuzzy inference system of Mamdani type. The learning algorithm works modifying its structure and/or parameters, that is to say, because of neuronal inclusion or exclusion and weight adaptability. The neuro fuzzy network learns in a supervised way, through the Levenberg–Marquardt algorithm. An experiment was applied in order to measure system effectiveness, considering decrease in wrong attempts doing an exercise as a success criterion. The result allows us to confirm that the selection of the pedagogical method generated by the proposal is useful, so it can contribute in a positive way to the programming teaching. This new system enables teaching under in a personalized learning style, taking into account the students characteristics.
Author Keywords: genetic algorithm, learning style, neuro fuzzy network, tutor modeled, object-oriented programming.
Volume 20, Issue 2, May 2017, Pages 643–651
Ivelisse Teresa Machín Torres1
1 Ingeniera, Facultad de Ciencias Técnicas, Departamento Ingeniería, Universidad José Martí Pérez, Isidro González # 26 entre Ave Libertad y Agramonte, Sancti -Spíritus, Cuba
Original language: Spanish
Copyright © 2017 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The pedagogical method selection is relevant to guarantee adaptability and to personalize each method, while working with intelligent tutorial systems. The objective of this research is just to develop a hybrid system for the pedagogical method selection for an intelligent tutorial system that contributes to knowledge management and strengthens the multiple specific intelligences of each student, in the teaching–learning process. The proposed hybrid system has two components, a genetic algorithm and a neuro fuzzy network, Mamdani Anfis style. The hybrid approach interprets the rules base of a fuzzy system in neural networks terms, where the net simulates a fuzzy inference system of Mamdani type. The learning algorithm works modifying its structure and/or parameters, that is to say, because of neuronal inclusion or exclusion and weight adaptability. The neuro fuzzy network learns in a supervised way, through the Levenberg–Marquardt algorithm. An experiment was applied in order to measure system effectiveness, considering decrease in wrong attempts doing an exercise as a success criterion. The result allows us to confirm that the selection of the pedagogical method generated by the proposal is useful, so it can contribute in a positive way to the programming teaching. This new system enables teaching under in a personalized learning style, taking into account the students characteristics.
Author Keywords: genetic algorithm, learning style, neuro fuzzy network, tutor modeled, object-oriented programming.
Abstract: (spanish)
La selección del método pedagógico es fundamental para garantizar la adaptabilidad y personalización cuando se trabaja con Sistemas Tutores Inteligentes. El objetivo del presente trabajo es desarrollar un sistema híbrido para la selección del método pedagógico para un Sistema Tutor Inteligente que contribuya a la gestión del conocimiento y potencie las inteligencias múltiples específicas de cada estudiante, en el proceso enseñanza-aprendizaje. El sistema híbrido propuesto consta de dos componentes, un algoritmo genético y una red neurodifusa estilo Mamdani Anfis. El enfoque híbrido interpreta la base de reglas de un sistema difuso en términos de una red neuronal, donde la red simula un sistema de inferencia difusa del tipo Mamdani. El algoritmo de aprendizaje trabaja modificando su estructura y/o parámetros, es decir por inclusión o exclusión de neuronas y por adaptación de pesos. La red neurodifusa aprende en modo supervisado, a través del algoritmo de Levenberg –Marquardt. Se aplicó un experimento con el objetivo de medir la efectividad del sistema, tomando como criterio de éxito la disminución de la cantidad de intentos incorrectos necesarios para realizar un ejercicio. Los resultados permiten afirmar que la selección del método pedagógico generada por la propuesta tiene utilidad, pues puede contribuir de forma positiva a la enseñanza de la programación. Este novedoso sistema permite enseñar bajo un estilo de aprendizaje personalizado, considerando la inclusión de características del estudiante.
Author Keywords: algoritmo genético, estilos de aprendizaje, modelado del tutor, red neurodifusa, programación orientada a objetos.
How to Cite this Article
Ivelisse Teresa Machín Torres, “System for selection of pedagogical method in intelligent tutorial systems,” International Journal of Innovation and Applied Studies, vol. 20, no. 2, pp. 643–651, May 2017.
