[ Análisis de Modelos Mentales Aplicado al Proceso de Aprendizaje ]
Volume 16, Issue 3, June 2016, Pages 528–532
Katya Martha Faggioni Colombo1, Mario Mata Villagomez2, Julio Bruce Novillo Granda3, and Fabiola Rosa Lopezdomínguez Rivas4
1 Facultad de Ciencias Matemáticas y Físicas, Universidad de Guayaquil, Guayaquil, Guayas, Ecuador
2 Facultad de Ciencias Administrativas, Universidad de Guayaquil, Guayaquil, Guayas, Ecuador
3 Escuela de Música, Universidad de las Artes, Guayaquil, Guayas, Ecuador
4 Facultad de Ciencias Administrativas, Universidad de Guayaquil, Guayaquil, Guayas, Ecuador
Original language: Spanish
Copyright © 2016 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.
Mental model representation using fuzzy graphs have recently grown in popularity for decision support and knowledge representation. Finding the most important node in the model has multiple applications. This paper presents a new model for static analysis in fuzzy graphs applied to the learning process. It makes use WA operators for the aggregation of the different centrality measures. This composite measure make possible to order the nodes and select the most important in a more integral way. WA operator brings flexibility to the model. A case study to show the applicability of the proposal is presented.
Author Keywords: mental model, fuzzy graph, static analysis, centrality measures, WA operator.
Volume 16, Issue 3, June 2016, Pages 528–532
Katya Martha Faggioni Colombo1, Mario Mata Villagomez2, Julio Bruce Novillo Granda3, and Fabiola Rosa Lopezdomínguez Rivas4
1 Facultad de Ciencias Matemáticas y Físicas, Universidad de Guayaquil, Guayaquil, Guayas, Ecuador
2 Facultad de Ciencias Administrativas, Universidad de Guayaquil, Guayaquil, Guayas, Ecuador
3 Escuela de Música, Universidad de las Artes, Guayaquil, Guayas, Ecuador
4 Facultad de Ciencias Administrativas, Universidad de Guayaquil, Guayaquil, Guayas, Ecuador
Original language: Spanish
Copyright © 2016 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
Mental model representation using fuzzy graphs have recently grown in popularity for decision support and knowledge representation. Finding the most important node in the model has multiple applications. This paper presents a new model for static analysis in fuzzy graphs applied to the learning process. It makes use WA operators for the aggregation of the different centrality measures. This composite measure make possible to order the nodes and select the most important in a more integral way. WA operator brings flexibility to the model. A case study to show the applicability of the proposal is presented.
Author Keywords: mental model, fuzzy graph, static analysis, centrality measures, WA operator.
Abstract: (spanish)
Los modelos mentales representados mediante grafos difusos han ganado en popularidad como soporte a la toma de decisiones y en la representación del conocimiento. La determinación del nodo más importante en un grafo difuso presenta múltiples aplicaciones como ayuda a la decisión. Sin embargo el análisis estático se ha centrado en la utilización de una sola medida de centralidad. En el presente artículo se describe un nuevo modelo para el análisis estático en modelos mentales aplicado al proceso de enseñanza. El mismo hace uso del operador para la agregación media ponderada de las distintas medidas de centralidad. Esta medida compuesta permite el ordenamiento de los nodos facilitando la selección de los conceptos más importantes de una forma más integral. La aplicabilidad de la propuesta es demostrada mediante un estudio de caso.
Author Keywords: modelo mental, grafo difuso, análisis estático, medidas de centralidad, operador WA.
How to Cite this Article
Katya Martha Faggioni Colombo, Mario Mata Villagomez, Julio Bruce Novillo Granda, and Fabiola Rosa Lopezdomínguez Rivas, “Analysis of Mental Models Applied to the Learning Process,” International Journal of Innovation and Applied Studies, vol. 16, no. 3, pp. 528–532, June 2016.
