Integrating AI Ethics and Sustainability Through Experiential and Data-Driven Curriculum Innovation at PCCOE

Authors

  • Vivekanandan N. Department of Mechanical Engineering, Pimpri Chinchwad College of Engineering Pune, Maharashtra
  • Rajeswari K. Department of Computer Engineering, Pimpri Chinchwad College of Engineering, Pune

DOI:

https://doi.org/10.16920/jeet/2026/v39is2/26026

Keywords:

AI Ethics Education, Experiential Learning, Outcome-Based Assessment, Sustainability Literacy, Governance Competencies.

Abstract

A novel undergraduate course, Professional Ethics and Sustainability in the Age of AI, bridges critical gaps in engineering education by combining experiential learning with outcome-based assessment. Developed at Pimpri Chinchwad College of Engineering (PCCOE), the curriculum employs four research-grounded activities: historical case analyses of ethical disasters, TARES Test evaluations of AI advertisements, governance quizzes on surveillance systems, and multi-stakeholder role-plays about algorithmic grading. Interim results from 46-60 participants demonstrate significant competencies development: 91.3% of students recognize AI's ethical influence, 95.7% show heightened emotional awareness, with strong performance in persuasion literacy (M=4.40/5) and governance knowledge (M=9.43/10). Structured assessments reveal 81.8% attainment in ethical reasoning and 80.5% in communication/governance skills, while qualitative analysis uncovers sophisticated engagement with fairness, transparency, and accountability principles.

Built on Kohlberg's moral development theory, UNESCO's ESD framework, and IEEE's Ethically Aligned Design, the course uniquely integrates macro ethical principles with micro ethical skill-building. Final evaluations of the sustainability-focused AI mini-projects showed attainment levels of 82.4% for CO2 and 84.1% for CO4, completing the comprehensive outcomes-based assessment cycle.. This model offers engineering educators a replicable blueprint for cultivating professional judgment in AI ethics through three key innovations: (1) contextualized historical analogies, (2) measurable persuasion literacy benchmarks, and (3) stakeholder negotiation simulations that mirror real-world tech governance challenges. The demonstrated success of this active learning approach provides empirical support for transforming traditional ethics education in response to emerging technologies.

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Published

2026-02-18

How to Cite

N., V., & K., R. (2026). Integrating AI Ethics and Sustainability Through Experiential and Data-Driven Curriculum Innovation at PCCOE. Journal of Engineering Education Transformations, 39(Special Issue 2), 213–222. https://doi.org/10.16920/jeet/2026/v39is2/26026

Issue

Volume 39, Special Issue 2, January 2026

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

References

Aler Tubella, A., Mora-Cantallops, M., & Nieves, J. C. (2024). How to teach responsible AI in higher education: Challenges and opportunities. Ethics and Information Technology, 26(3). https://doi.org/10.1007/s10676-023-09733-7

Alshawi, A. (2021). Artificial intelligence for sustainability: Opportunities and challenges. Artificial intelligence and sustainable development (pp. 1–31). Wiley. https://doi.org/10.1002/9781119771524.ch1

An, Q., Yang, J., Xu, X., Zhang, Y., & Zhang, H. (2024). Decoding AI ethics from a user’s lens in education: A systematic review. Heliyon, 10(10), e39357. https://doi.org/10.1016/j.heliyon.2024.e39357

Barry, B. A., Sharp, R. R., & McGowan, M. L. (2025). Teaching the bioethics of information technologies and artificial intelligence in healthcare: Case-based learning for identifying and addressing ethical issues. International Journal of Ethics Education. https://doi.org/10.1007/s40889-025-00218-3

Coeckelbergh, M. (2020). AI Ethics. MIT Press. Deb, D., Taylor, G., Betz, S., Maddux, B. A. T., Ebert, C. E., Richardson, F. W., Couto, J. L. S., Jarrett, M. S., & Madjd-Sadjadi, Z. (2025). Enhancing university curricula with integrated AI ethics education: A comprehensive approach. In Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1 (pp. 248–254). Association for Computing Machinery. https://doi.org/10.1145/3641554.3701953

Dignum, M. (2019). Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. Springer.

Frodeman, R., Klein, J. T., & Mitcham, C. (Eds.). (2017). The Oxford Handbook of Interdisciplinarity (2nd ed.). Oxford University Press.

Gutierrez-Bucheli, L., Kidman, G., & Reid, A. (2021). Sustainability in engineering education: A review of learning outcomes. Journal of Cleaner Production, 330, 129734. https://doi.org/10.1016/j.jclepro.2021.129734.

Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds & Machines, 30(1), 99–120. https://doi.org/10.1007/s11023-020-09517-8.

Herkert, J. R. (2005). Ways of thinking about and teaching ethical problem solving: Microethics and macroethics in engineering. Science and Engineering Ethics, 11(3), 373–385. https://doi.org/10.1007/s11948-005-0006-3.

Hess, J. L., Kim, D., & Fila, N. D. (2023). Critical incidents in ways of experiencing ethical engineering practice. Studies in Engineering Education, 3(2), 1–30. https://doi.org/10.21061/see.80.

Hicks, A., & Kontar, W. (2024). The role of disasters and infrastructure failures in engineering education with analysis through machine learning. Journal of Civil Engineering Education, 150(4), 04024003. https://doi.org/10.1061/JCEECD.EIENG-2021.

Kohlberg, L. (1981). The philosophy of moral development: Moral stages and the idea of justice. Harper & Row.

Leydens, J., Lucena, J., & Riley, D. (2022, September 15). Engineering Education and Social Justice. In Oxford Research Encyclopedia of Education. Retrieved August 13, 2025, from https://oxfordre.com/education/view/10.1093/acrefore/9780190264093.001.0001/acrefore-9780190264093-e-1772.

Martin, D. A., Conlon, E., & Bowe, B. (2021). Using case studies in engineering ethics education: The case for immersive scenarios through stakeholder engagement and real-life data. Australasian Journal of Engineering Education, 26(1), 47–63. https://doi.org/10.1080/22054952.2021.1914297.

Martin, M. W., & Schinzinger, R. (2019). Ethics in engineering (3rd ed.). McGraw-Hill.

Matos, T., Santos, W., Zdravevski, E., Coelho, P. J., Pires, I. M., & Madeira, F. (2025). A systematic review of artificial intelligence applications in education: Emerging trends and challenges. Decision Analytics Journal, 15, 100571. https://doi.org/10.1016/j.dajour.2025.100571.

McSharry, P. E. (2023). Promoting AI ethics through awareness and case studies. In C. C. Corrigan, S. A. Asakipaam, J. J. Kponyo, & C. Luetge (Eds.), AI ethics in higher education: Insights from Africa and beyond (SpringerBriefs in Ethics). Springer, Cham. https://doi.org/10.1007/978-3-031-23035-6_6.

Memarian, B., & Doleck, T. (2022). Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review. Computers and Education: Artificial Intelligence, 5, 100152. https://doi.org/10.1016/j.caeai.2023.100152.

Shahriari, K., & Shahriari, M. (2017). IEEE standard review — Ethically aligned design: A vision for prioritizing human wellbeing with artificial intelligence and autonomous systems. In Proceedings of the 2017 IEEE Canada International Humanitarian Technology Conference (IHTC) (pp. 197–201). IEEE. https://doi.org/10.1109/IHTC.2017.8058187.

Silva, P. J., Felgueiras, C., Caetano, N., Martins, F., Onofrei, G., Blue, J., Sintejudeanu, M., Acitores, A., Cruz, F., Martín-Erro, A., Moreno Soriano, S., Davey, T., Collins, M., & Spada, D. (2025). Engineering education for a sustainable future – A systematic literature review and a perspective. In Proceedings of the International Conference on Engineering Education (pp. 1207–1215). Springer. https://doi.org/10.1007/978-981-96-5658-5_119.

United Nations. (2015). Transforming our world: The 2030 Agenda for Sustainable Development. United Nations.

Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11, 233. https://doi.org/10.1038/s41467-019-14108-y.

Whitbeck, C. (2011). Ethics in engineering practice and research (2nd ed.). Cambridge University Press.

Wiese, L. J., Patil, I., Schiff, D. S., & Magana, A. J. (2025). AI ethics education: A systematic literature review. Computers and Education: Artificial Intelligence, 8, 100405. https://doi.org/10.1016/j.caeai.2025.100405.

Williams, R. T. (2024). The ethical implications of using generative chatbots in higher education. Frontiers in Education, 8, 1331607. https://doi.org/10.3389/feduc.2023.1331607.

Zhuang, M., Long, S., Martin, F., & Castellanos-Reyes, D. (2025). The affordances of artificial intelligence (AI) and ethical considerations across the instruction cycle: A systematic review of AI in online higher education. The Internet and Higher Education, 67, 101039. https://doi.org/10.1016/j.iheduc.2025.101039.