| Description: |
This study investigates the patterns, perceptions, and academic impacts associated with the use of generative artificial intelligence tools among students in higher education, particularly focusing on technically-oriented degree programs within the Spanish context. The primary objectives were to characterize student engagement with AI tools, evaluate their perceived educational utility and risks, examine the relationship between AI usage and academic performance, and identify gaps in institutional support and preparedness. A mixed-method approach was employed, starting with an extensive literature review to frame existing scholarly discussions around AI in educational settings. Subsequently, an exploratory survey was conducted, reaching students primarily from the Universitat Politècnica de Catalunya (UPC), specifically within the Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB). The survey explored usage patterns, motivations, concerns, and perceptions of institutional policies. A quantitative analysis using regression modeling was also carried out to preliminarily investigate correlations between AI usage and academic outcomes, although the sample size limited statistical robustness. Findings revealed widespread enthusiasm among students towards integrating AI tools, predominantly driven by perceived improvements in productivity, learning quality, and professional readiness. However, significant concerns were raised regarding ethical issues such as plagiarism, bias, and dependence on AI-generated content. The research also identified a pronounced misalignment between student expectations and institutional frameworks; notably, a majority of students reported unclear or insufficient institutional guidance on AI use. Regression models gave not statistically significant results, aligned with the ambivalence present in the existing literature. Ultimately, this research highlights critical gaps in policy clarity, institutional support, and pedagogical strategies regarding generative AI. It provides evidence-based recommendations for educators and policymakers, emphasizing the need for comprehensive AI literacy programs, clear ethical guidelines, and strategically integrated AI applications in higher education. Future research directions are suggested, advocating for more extensive, focused studies with larger and more diverse populations, as well as deeper consideration of social and gender equity dimensions in AI deployment. |