Análisis de trayectorias de aprendizaje mediante las funciones de Buclicidad y Ramificación

Abstract

Among the opportunities for the design of educational technologies that integrate artifacts, interfaces and data analysis strategies, is to promote actions such as: assertive interventions during learning, recognition of learning trajectories, self-recognition of the students' process, better knowledge of the teacher about the student's process and better knowledge of the teacher about the consequences of his interventions. An alternative to the above actions is the design of representation systems for learning trajectories during structured problem solving. For a long time, teachers have used mathematical games to analyze aspects such as schema evolution, subitization, mathematization, etc. These games, generally physical, although there are also virtual ones, are not yet taking advantage of the benefits offered by data analytics within the field of learning analytics. The paper describes an analysis model designed in the Matlab program, which integrates data analytics to explore the learning trajectories of 10 subjects during the solution of the game called Four Horses. The research results are obtained from a series of videos (with informed consent) and verbal solution protocols developed by the players. With the analysis and interpretation of the results it was possible to identify the existing tendencies when solving this game and the usefulness of the Buclicity and Ramification functions to recognize in detail how a subject builds solution trajectories in structured mathematical games.