Minería de datos aplicada a la detección de patrones para el análisis de rendimiento académico de los estudiantes de la carrera de Ingeniería en Sistemas Computacionales de la Universidad Católica Santiago de Guayaquil.

Abstract

With the use of the Data Mining tool, patterns of academic performance were analyzed in the students, subjects and professors that allowed to elaborate a predictive model in benefit for the students, at the moment that they register in the semester, to indicate what is their probability of success, alert or failure based on their performance and the subjects they will take. For this research we used the KDD methodology that is based on the extraction of knowledge on a small or large amount of data, the Excel data mining tool was used for collection, data processing, and the development of the simulator that the model applied of prediction. In conclusion, the objective of this model is to show him through a traffic light the probability of success to the student based on his performance and the subjects to choose. There were 59 tests of which showed 16 false positives (27.12%) and 6 false negatives (10.17%).