Aunque las matemáticas son importantes para el desarrollo educativo, las evaluaciones internacionales reportan un índice de reprobación mayor a 50%. Esta necesidad mundial ha propiciado el desarrollo de estudios sólidos para gestionar el conocimiento. Sin embargo, carece de una metodología que brinde soporte para implementar un sistema que gestione ese conocimiento. En el presente trabajo proponemos una metodología que guíe la implementación de un sistema de gestión de conocimiento de los estudiantes sobre el dominio de matemáticas de nivel universitario. La metodología incluye 5 fases con actividades específicas que han sido obtenidas de la literatura y de la experiencia de los autores. La metodología ha sido validada mediante un estudio de caso en una universidad de México.
The representing of a student’s knowledge in an academic discipline plays an important role in boosting the student’s skills. To support stakeholders in the educational domain, it is necessary to provide them with robust assessment strategies that facilitate the teaching-learning process. Student´s mastery is determined by the degree of knowledge, which demonstrates objectively, on the topics included in the different areas that make up an academic discipline. Although there is a wide variety of techniques to represent knowledge, particularly Knowledge Graph technique is becoming relevant due to the structured approach and benefits it offers. This paper proposes a method that classifies and weights the nodes (topics) of a Knowledge Graph of a disciplinary area, which is analyzed through a case study. The method has two approaches: avoid exhaustive evaluation of the nodes and weight the nodes with adequate precision. Method´s application is illustrated by a case study. As results, a Knowledge Graph is obtained with its classified and weighted nodes through the application of the proposed method, in which 100% of the topics have been impacted through the objective evaluation of 20.8% representing 10 nodes. It is concluded that the proposed method has potential to be used in the representation and management of knowledge, being necessary to improve phases’ iteration to condition number of objective nodes.
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