Minería de datos aplicada a la determinación de niveles de uso de la herramienta de inteligencia artificial y tecnología en instituciones de educación superior: caso de la Universidad Técnica de Machala, sección vespertina y nocturna.

Abstract

Abstract: This study analyzes the use of the internet and artificial intelligence tools among students at the Technical University of Machala, with the aim of identifying usage patterns, evaluating their impact on academic performance, and establishing relationships between variables that influence learning. Data were collected through surveys, followed by a cleaning and standardization process to ensure data quality. Exploratory factor analysis (EFA) was then applied, identifying key dimensions such as confidence in technology, use of digital platforms, and dependence on tools such as ChatGPT. Clustering techniques were then implemented, grouping students into three profiles: one with balanced technology use, another with high technology dependence and social media use, and a third with low digital use. Regression models were also incorporated to evaluate relationships between key variables. It was found that confidence in ChatGPT and the use of digital platforms are positively related to learning, but also to practices such as submitting copied work. It was also observed that men tend to use video games and YouTube more, while women tend to use social media and recreational chats. The results show a strong impact of technology on academic training, highlighting the need for awareness campaigns and ethical training on its proper use.