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Este trabajo aplica tecnicas de mineria de datos para estimar el riesgo de suspender la asignatura de Logica impartida en la ETSIINF UPM (Ingenieria Informatica), partiendo de las calificaciones obtenidas por el alumno dentro del proceso de evaluacion continua. Lo que se pretende es cuantificar la probabilidad de un alumno tiene de suspender conociendo las calificaciones obtenidas, por ejemplo, durante el primer mes de curso. El conjunto de datos estudiado son las notas (parciales y finales) de los alumnos en los anos anteriores. Se ha desarrollado una aplicacion web para que el alumno pueda ingresar las calificaciones obtenidas hasta el momento y saber que probabilidad tiene de aprobar finalmente la asignatura.---ABSTRACT---The present work uses data mining in order to estimate how likely it is that a student will fail the exam of Logic in the Computer Science Degree at the ETSIINF, UPM. This is done starting from his or her previous grades during the semester (continuous evaluation is used in this course). Previous knowledge used in the learning process comes in the form of grades obtained bystudents in previous years: based on this, data mining techniques extract relevant patterns and predict the probability for the current student to pass or fail. A web application has been developed, which allows a student to insert grades obtained so far (for example, during the first month) and see the probability to finally pass or fail the courseaccording to the results of previous years.

Estimación del riesgo de no superar una asignatura de evaluación continua mediante aprendizaje automático - [Estimating the risk of not passing a continuous evaluation module by machine learning]