Análisis del marco de competencias para estudiantes en el uso de inteligencia artificial IA utilizando minería de datos con la herramienta python. Caso de la UPS

Abstract

Abstract: This research aimed to analyze the level of knowledge, usage, and the ethical and academic implications of artificial intelligence among university students, in order to understand how these tools are employed to support learning and the completion of academic tasks. The study was conducted at a university in the city of Quito, using a structured survey administered to a sample of approximately 600 students. The CRISP-DM methodology was used to process the data, guiding the analysis through the following phases: problem understanding, data understanding, data preparation, modeling, evaluation, and deployment. Once the data were collected, they underwent cleaning, refinement, and transformation. Statistical, data mining, and machine learning techniques including factor analysis, clustering, tests of independence (such as the Chi-square test), and decision trees were applied to identify behavioral patterns and relationships among the variables under study. Ultimately, the results revealed two distinct student profiles based on their level of knowledge and use of artificial intelligence, highlighting differences in how these tools are utilized to support academic activities. It is concluded that the application of data mining techniques serves as an effective tool for understanding usage patterns within a university environment. These findings provide a foundation for designing pedagogical strategies that promote the critical, ethical, and responsible use of artificial intelligence, thereby strengthening the development of digital competencies in higher education.