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STEM Education

2026, Volume 6, Issue 6: 1036-1056. doi: 10.3934/steme.2026042
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Engineering students' engagement with generative AI: Perceptions, practices, and implications for learning and teaching

  • 1.
    School of Electrical, Mechanical and Biomedical Engineering, University of Technology Sydney, Ultimo, Australia; Anna.LidforsLindqvist@uts.edu.au
  • 2.
    Centre for Teaching and Learning, Southern Cross University, Gold Coast, Australia; zach.quince@scu.edu.au

  • Academic Editor: Feng-Kuang Chiang
  • Published: 12 October 2026

  • Generative artificial intelligence (GenAI) is rapidly transforming the way students learn, create, and demonstrate knowledge in higher education. While universities are developing policies and guidelines, less is known about how students in specific disciplines perceive and use these tools. Here, we provide an explorative case comparison study and investigate engineering students' engagement with GenAI across two Australian universities. A survey of 131 students examined reported GenAI use, perceived benefits and challenges, and awareness of institutional policy and training across two cohorts with different demographic and curricular contexts. Our results showed broad awareness and adoption of GenAI, with differences between cohorts in reported frequency and purposes of use, as well as in perceptions of policy training. Students reported benefits in idea generation and efficiency while identifying challenges related to accuracy, content relevance, and ethical use. Our findings suggest that GenAI literacy development should be gradual, discipline-specific, integrated into coursework, and guided by clear communication about the ethical use of GenAI. The study highlights the importance of aligning institutional strategies with students lived experiences of GenAI in learning.

    Citation: Anna Lidfors Lindqvist, Zachery Quince. Engineering students' engagement with generative AI: Perceptions, practices, and implications for learning and teaching[J]. STEM Education, 2026, 6(6): 1036-1056. doi: 10.3934/steme.2026042

    Related Papers:

  • Generative artificial intelligence (GenAI) is rapidly transforming the way students learn, create, and demonstrate knowledge in higher education. While universities are developing policies and guidelines, less is known about how students in specific disciplines perceive and use these tools. Here, we provide an explorative case comparison study and investigate engineering students' engagement with GenAI across two Australian universities. A survey of 131 students examined reported GenAI use, perceived benefits and challenges, and awareness of institutional policy and training across two cohorts with different demographic and curricular contexts. Our results showed broad awareness and adoption of GenAI, with differences between cohorts in reported frequency and purposes of use, as well as in perceptions of policy training. Students reported benefits in idea generation and efficiency while identifying challenges related to accuracy, content relevance, and ethical use. Our findings suggest that GenAI literacy development should be gradual, discipline-specific, integrated into coursework, and guided by clear communication about the ethical use of GenAI. The study highlights the importance of aligning institutional strategies with students lived experiences of GenAI in learning.



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  • Authors' biographies Dr Anna Lidfors Lindqvist is a Senior Lecturer in the School of Electrical, Mechanical and Biomedical Engineering at the University of Technology Sydney (UTS), Australia. She specialises in applied mechanical design projects and engineering education. Her research in engineering education focuses on innovative assessment methods, studio learning, formative assessment, and feedback literacy to enhance student learning and professional skill development. She actively collaborates with industry and academia to bridge the gap between education and engineering practice; Dr. Zach Quince is a senior lecturer in Teaching and Learning at Southern Cross University. His expertise includes biomedical engineering curriculum development, professional engineering skills development, and ethical GenAI use in higher education. He has led the development of digital technology integration and GenAI. His research focuses on graduate employability and industry-aligned skills. A recipient of multiple teaching awards, he has secured grants for projects on GenAI in education and professional skill development
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  • © 2026 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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