What Affect Future Use Intention? Unpacking Engineering Students’ Perceptions Toward Generative AI in Learning

• In Event: How Students Engage with GenAI: From Resistance to Empowerment

Abstract

Generative AI (GenAI) has revolutionized education by transforming how engineering students learn and enhance their ability to solve complex problems. Yet despite its potential, many students still have concerns toward using GenAI tools in learning contexts. To mitigate concerns and better empower students’ use of GenAI in engineering classrooms, this study proposes the four factors that likely influence future use intention, including pedagogical support, perceived beneficence, AI literacy, and ethical concerns. Through surveys (n=40) and interviews (n=12) with chemical-engineering undergraduates, the study validates that the four influential factors,both supportive and inhibitive—affect their future use intention. Based on these insights, we propose instructional strategies to empower students’ engagement with GenAI in learning.

Authors

• Daihan Xu, University College London

• Matheus de Andrade, University College London - IOE

• Diana Martin, University College London