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Engineering a Sustainable Future Through the Integration of Generative AI in Engineering Education

Author

Listed:
  • Javier Cañavate

    (Department of Chemical Engineering, Universitat Politècnica de Catalunya, BarcelonaTech, 08222 Terrassa, Spain)

  • Elisa Martínez-Marroquín

    (Faculty of Science and Technology, University of Canberra, Canberra, ACT 2617, Australia)

  • Xavier Colom

    (Department of Chemical Engineering, Universitat Politècnica de Catalunya, BarcelonaTech, 08222 Terrassa, Spain)

Abstract

Engineers’ work impacts society and the environment and plays a central role in delivering on the United Nations Sustainable Development Goals. However, developing sustainability skills in engineering programs competes with a dense technical curriculum and has proven challenging. The mainstream adoption of generative AI (GAI) tools has prompted a review of teaching and learning, with expanding possibilities as new use cases emerge. This study reviews the impact that GAI is having on engineering education and proposes a framework for the use of GAI to facilitate greater socio-enviro-technical integration in the engineering curriculum. Based on a scoping review of the literature and a conceptual analysis, this paper provides a forward-looking perspective. Artificial intelligence (AI) is also transforming the practice of engineering, triggering the need to adjust graduate attributes accordingly. The increased productivity expected with the rise of AI in the workplace can scale-up the impact of engineering developments and underscores the need for graduates’ sustainability skills. Furthermore, engineers have a prominent role in the development of AI systems. Therefore, in advocating for the need to enhance graduate’s sustainability skills, we emphasize understanding its limitations and the sustainability of AI systems to address the paradox of AI for sustainability and the sustainability of AI itself.

Suggested Citation

  • Javier Cañavate & Elisa Martínez-Marroquín & Xavier Colom, 2025. "Engineering a Sustainable Future Through the Integration of Generative AI in Engineering Education," Sustainability, MDPI, vol. 17(7), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3201-:d:1627794
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    References listed on IDEAS

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    1. Anne-Laure Ligozat & Julien Lefevre & Aurélie Bugeau & Jacques Combaz, 2022. "Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Life Cycle Assessment of AI Solutions," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    2. Mantoura Nakad & Linda Gardelle & Rami J. Abboud, 2024. "A Systematic Review of the Different Methods Assessing Sustainability Integration in Engineering Curricula," Sustainability, MDPI, vol. 16(11), pages 1-24, May.
    3. Agne Paulauskaite-Taraseviciene & Ingrida Lagzdinyte-Budnike & Lina Gaiziuniene & Vilma Sukacke & Laura Daniuseviciute-Brazaite, 2022. "Assessing Education for Sustainable Development in Engineering Study Programs: A Case of AI Ecosystem Creation," Sustainability, MDPI, vol. 14(3), pages 1-22, February.
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