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 Estatal de Quevedo

Abstract

Abstract: This work was related to data mining applied to determine the levels of use of tools and technologies of artificial intelligence in higher education institutions: case of the Universidad Técnica Estatal de Quevedo. The objective was to analyze how university students use technology through the application of the CRISP-DM method. Data mining techniques are applied to discover trends on their behavior and to build profiles on the usage of technological tools. In this research, typical practices, usage of online content and ways of usage were assessed with a question that was made to the students from where reports were gathered that were subsequently processed and analyzed with the R program. Methods like 'the elbow method', silhouette measure, and k-means clustering algorithm were used to identify significant clusters within the study population. The results key trends proved tools in the use technological such and significant differences between groups of students, concluding that mismanagement of these tools can yield addictive behaviors thus underscoring the need to advocate responsible balanced use of technology especially within educational environments.