This study analyses the use of artificial intelligence (AI) tools by university students in science and engineering disciplines, based on a survey conducted with a sample of 94 participants. The objective was to identify usage patterns and their relationship with variables such as academic performance, perceived learning, ethics, trust, knowledge, and recommendation. Descriptive statistics and association tests such as chi-square, along with Phi and Cramér’s V coefficients, were used to assess the strength of relationships between categorical variables. The results show that most students have used AI tools for academic purposes, with a positive perception in terms of learning and knowledge. Significant associations were found between AI use and variables such as learning and knowledge while others such as academic performance and trust did not show statistical significance. Minor differences were observed based on gender, although not statistically significant. These findings suggest a growing interest and normalization of AI use in technical education contexts, where perceptions of usefulness and ethical considerations play a more prominent role than academic performance per se. The implications of these results are discussed within the framework of designing pedagogical and training strategies for the responsible integration of AI in higher education.

Keywords: Artificial intelligence, university students, science and engineering, academic use of AI, academic ethics, self-directed learning.