Conference Agenda

The accelerated integration of artificial intelligence (AI) tools, especially generative AI, is changing how learning takes place in higher education, and more specifically in engineering. These technologies open significant doors to support learning, solve complex problems, personalize instruction, and improve students’ cognitive efficiency. But their widespread and, in many cases, unregulated use has raised new concerns about academic integrity, excessive reliance on technology, the weakening of critical thinking, and ethical dilemmas regarding authorship and responsibility for learning. The article aims to explore the ethical use of AI among engineering students through an integrative review of recent scientific literature and empirical studies addressing student perceptions, practices, ethical frameworks, and institutional policies. An analytical-comparative review methodology is employed to identify usage patterns, benefits, emerging risks, and training needs related to AI literacy. The results show that, although engineering students have a positive attitude toward AI as a teaching support tool, they tend to normalize dangerous practices when no guidelines or ethical training are in place. Furthermore, the ethical use of AI is linked to the development of analytical skills, provided it is accompanied by pedagogical strategies, institutional policies, and an awareness of its limitations.

It is determined that the ethical use of AI in engineering education requires a comprehensive approach that combines regulatory frameworks, ethical and pedagogical literacy, and the redesign of teaching and assessment practices to leverage its benefits and minimize its risks.