Generative AI in Civic Education: A Multi-Case Study of Pedagogical Innovation and Governance in Higher Education

ShengYu Gu

doi:10.63313/EH.9055

Authors

ShengYu Gu School of Geography and Tourism, Huizhou University, Huizhou, China Author

DOI:

https://doi.org/10.63313/EH.9055

Keywords:

Generative artificial intelligence, Higher education, Civic education, AI governance

Abstract

The rapid diffusion of generative artificial intelligence (AI) is reshaping higher education, raising critical questions about its integration into civic reasoning, public judgment, and ethical learning. While existing studies have examined its pedagogical opportunities and risks, limited attention has been paid to practice-oriented institutional models that are both educationally effective and transferable. This study addresses this gap by examining how universities operationalize generative AI through the interaction of technology, pedagogy, and governance, and by identifying lessons for emerging institutions. Using a qualitative multiple-case study design, the study analyzes three international cases: Harvard University (USA), University College London (UK), and the University of Helsinki (Finland). Data were collected from institutional reports, policy documents, academic publications, and open-access course materials, and analyzed through thematic analysis. Drawing on digital governance theory, experiential learning theory, and political socialization in digital environments, the study develops a Technology-Pedagogy-Governance (TPG) framework for comparative analysis. The findings reveal three distinct but complementary institutional pathways. Harvard demonstrates AI-supported civic reasoning through its use as an analytical assistant; UCL highlights governance-centered design through differentiated assessment frameworks; and Helsinki emphasizes AI literacy and ethics as a foundation for civic competence through scalable open-access education. Across cases, effective practices converge on controlled AI integration, critical thinking-centered pedagogy, and explicit ethical governance. This study contributes by extending generative AI research into civic education, advancing institution-based analysis beyond abstract debates, and proposing a transferable AI-enhanced civic education model. It suggests that emerging universities should adopt a sequenced approach: prioritizing AI literacy, followed by bounded pedagogical integration, and supported by clear governance frameworks.

References

[1] Alam, A. (2026). Pedagogies in a Digitally Mediated World for the Future of Civic Education: Educating Youth for Hashtag Citizenship. In Youth Civic Engagement and Political Participation in Digital Spaces (pp. 55-92). IGI Global Scientific Publishing.

[2] Bezeriţă, L. (2025). SOME PECULIARITIES AND PERSPECTIVES OF THE FINNISH EDUCATION SYSTEM. Internal Auditing & Risk Management, 71(1), 77-85.

[3] Bo, N. S. W. (2025). OECD digital education outlook 2023: Towards an effective education ecosystem. Hungarian Educational Research Journal, 15(2), 284-289.

[4] Bowyer, B., & Kahne, J. (2020). The digital dimensions of civic education: Assessing the effects of learning opportunities. Journal of Applied Developmental Psychology, 69, 101162.

[5] Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101.

[6] Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in education and teaching international, 61(2), 228-239.

[7] Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International journal of educational technology in higher education, 20(1), 1-22.

[8] Gupta, V., & Nyamapfene, A. (2025). Generative AI in universities: Practices at UCL and other institutions, and the path forward. Internet Reference Services Quarterly, 29(1), 131-151.

[9] Helström, K. (2026). Case Study Methodology in Qualitative Research. In Approaches to Qualitative Research (pp. 141-147). Routledge.

[10] Kusumawardani, V., Agustin, D. A. C., & Permatasari, S. S. (2025). Social Media and Political Preferences Among Generation Z in the 2024 Indonesian General Election. Mediakita, 9(2), 246-269.

[11] Lee, T. S. C. (2025). Magic lines: Artist-teachers' preschool art studio curriculum design and implementation. In Arts and creativity in East and Southeast Asian preschools: Towards 'glocal'pedagogies (pp. 139-154). Singapore: Springer Nature Singapore.

[12] Liu, R., & Glave, C. Z. (2026). Justice, Equity, Diversity, and Inclusion in Artificial Intelligence and Childhood Education: A Critical Systematic Review. Journal of Research in Childhood Education, 40(1), 5-23.

[13] McKenna, T. J. (2025). Making Sense of Sensemaking: Designing Authentic K-12 STEM Learning Experiences. Teachers College Press.

[14] Mochizuki, Y., Bruillard, E., & Bryan, A. (2025). The ethics of AI or techno-solutionism? UNESCO's policy guidance on AI in education. British Journal of Sociology of Education, 1-22.

[15] Mott, R., & Haddad, B. (2025). A call to better Qual: A philosophical and methodological examination to advance case study research. Journal of Agricultural Education, 66(1), 41-41.

[16] Nguyen, H. (2025). Bringing AI into teaching: Understanding Vietnamese teachers' perspectives and pedagogical challenges. International Journal of Educational Methodology, 11(3), 335-347.

[17] Safdar, H., Hashmi, K., & Shah, M. A. (2026). Systematic Literature Review of the Governance of Integrity, Equity, Privacy, and Accountability in the Use of Artificial Intelligence Models in University Classrooms: Ethical Principles. Research Consortium Archive, 4(1), 311-333.

[18] Shaikh, S., Maroof, M. A., Kaskar, P., Girhe, P. B., Magar, A. V., & Sudhahar, W. (2026). Generative AI and Ethical Integration in K-12 and Higher Education: Policies, Pedagogy, and Practice. In Teacher Perspectives and Responsible Practice for Integrating AI in the Classroom (pp. 89-118). IGI Global Scientific Publishing.

[19] Tlili, A. (2025). Between Fear and Desire, the Monster Artificial Intelligence (AI): Analysis through the Lenses of Monster Theory. arXiv preprint arXiv:2508.08318.