Diagnóstico del Proceso de Aprendizaje de Alumnos de Inteligencia Artificial mediante un Modelo Dinámico Bayesiano

One of the main objectives of Education for this century is to instill cognitive skills that ensure information research and comprehension through a critical reading. Not only are these skills desirable in any Engineering career, but they have also become critical in disciplines such as ‘Artificial Intelligence’, where innovations are given on a daily basis. In this sense, Bayesian Networks are a type of Intelligent System capable of identifying students' learning style. Nonetheless, they fail to represent the manner in which said knowledge evolves. Therefore, this paper proposes to apply a Dynamic Model in order to diagnose students' learning process and provide a better understanding of their behavior