Minería de datos aplicada a la determinación de los niveles de uso de las herramientas de inteligencia artificial y la tecnología en instituciones de educación superior: caso de la Universidad Técnica de Machala, Sección Matutina.

Abstract

Abstract: This research explores the use of technology, artificial intelligence tools, and internet trust among students at the Technical University of Machala. The objective is to identify behavioral patterns and usage profiles of technological tools using data mining techniques. The CRISP DM methodology was implemented to identify underlying structures in the set of variables. Exploratory Factor Analysis (EFA) was used. Data clustering was performed using the unsupervised learning algorithm k-means. Data was collected through a physical survey on the UTMACH campus from a sample of 600 students from different faculties. Data were processed using the R programming language in the RStudio development environment. The results revealed key trends regarding addictions, the use of technological tools, internet trust, and significant differences between student groups. It is concluded that the students are in excellent academic condition, but improper use of these technological tools, the internet, and devices could lead to addictive behaviors. The findings were complemented with interpretable simple linear regression models, which allowed for the validation of specific significant relationships between variables.