Vinod, Gouri; (2025) Exploring Gen-Z Engineering Students' Views on AI Engineering: A US and UK Study. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

This thesis aims to explore the unique perspectives of Gen–Z engineering students— those born from the mid to late 1990s to the early 2010s—in the US and the UK, with supplemental input from current engineering faculty members, to examine how they navigate the challenges and opportunities presented by 21st–century, AI–integrated engineering education. The research introduces the term ‘AI engineering’ to encompass the wide range of AI topics and technologies within engineering that participants discuss throughout the project. By inquiring about students’ general views, awareness of ethical issues and biases associated with AI, and career aspirations, the thesis explores their responses regarding the current state of AI engineering. The study uses the concept of ‘fusion skills’—a combination of technical, professional, and ethical competencies—as a framework to highlight the skills necessary for an AI–driven engineering environment. As students continue to engage with AI, they see it as an extension of their own fusion skills, leading to more hybridisation rather than simply acquiring skills. Furthermore, the thesis argues that students’ current use of AI tools across disciplines positions AI engineering as interdisciplinary. This has led to an AI hybridisation triplex consisting of AI–human, AI–engineering student, and AI–engineer hybridisation. Through a bricolage analysis of semi–structured interviews with faculty (n=6) and standardised open–ended interviews with students (n=19) from both countries, emerging issues suggest that students are generally more open and enthusiastic about AI than faculty, who exhibit cautious optimism. By employing the fusion skills framework and the AI hybridisation triplex, the research also reveals how students across engineering disciplines engage with AI engineering in self–directed ways, while simultaneously being aware of its ethical issues. This reflects a more balanced view where the students understand AI’s potential and its shortcomings—with some even showing interest in AI engineering careers in the future.

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