Minería de datos aplicada al análisis de los usos de la tecnología y el rendimiento académico de las universidades ecuatorianas

Abstract

Abstract: The present degree work applies data mining using the KDD methodology (Knowledge Discovery in Databases) to a dataset that collects information from 31 Ecuadorian universities, the total record of dataset is 10952 students. The purpose is to investigate the influence of the use of the Internet on academic performance. It also seek to clarify cause-effect relationships between the student s socioeconomic levels and the use of technology in their academic and leisure or entertainment activities. To achieve these objectives, predictive and descriptive data mining techniques are applied, such as Cluster Analysis, Factorial Analysis, Decision Trees, Logistic Regression, among others; with which we look for patterns and categorizations that allow describing the underlying structures of the data set with which it is counted.