Analisis de Modelos Mentales Aplicado al Proceso de Aprendizaje/[ Analysis of Mental Models Applied to the Learning Process ]

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.