Designing operational ethical frameworks for the use of generative AI in higher education
DOI:
https://doi.org/10.65835/aj.2026.2.15Keywords:
Generative artificial intelligence, ethics in higher education, operational framework, policy implementation, university governance.Abstract
This doctoral study developed and validated an Operational Ethical Framework (OEF-GAI) to guide the responsible use of Generative Artificial Intelligence (GAI) in higher education. Using a sequential mixed-methods approach (documentary analysis, case study, survey n=1,247, and Delphi method), it identified a critical gap between abstract ethical principles and their practical institutional application. Results showed that the university community demands practical guidance and training over mere prohibitions. The validated OEF-GAI responds with a three-layer architecture: Foundations (guiding principles), Operational Pillars (governance, practical instruments, training), and an Application Cycle for continuous improvement. It is concluded that the ethical integration of GAI requires institutionalizing processes of reflection and support, transforming the abstract dilemma into manageable practice that fosters responsible innovation.
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References
Bostrom, N., & Yudkowsky, E. (2014). The ethics of artificial intelligence. En K. Frankish & W. M. Ramsey (Eds.), The Cambridge Handbook of Artificial Intelligence (pp. 316–334). Cambridge University Press.
Chan, C. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, *20*(1), 38. https://doi.org/10.1186/s41239-023-00408-3
Cordón García, O. (2023). Inteligencia artificial en educación superior: Oportunidades y riesgos. RiiTE. Revista Interuniversitaria de Investigación en Tecnología Educativa, (15), 16–27. https://doi.org/10.6018/riite.591581
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Donaldson, L. (2001). The contingency theory of organizations. SAGE Publications.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... Vayena, E. (2018). AI4People: An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, *28*(4), 689–707.
Gallent-Torres, C., Zapata-González, A., & Ortego-Hernando, J. L. (2023). El impacto de la inteligencia artificial generativa en educación superior: Una mirada desde la ética y la integridad académica. RELIEVE. Revista Electrónica de Investigación y Evaluación Educativa, *29*(2). https://doi.org/10.30827/relieve.v29i2.29134
García-Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2024). The new reality of education in the face of advances in generative artificial intelligence. RIED. Revista Iberoamericana de Educación a Distancia, *27*(1), 9–39. https://doi.org/10.5944/ried.27.1.37716
González-Fernández, M. O., Romero-López, M. A., Sgreccia, N. F., & Latorre Medina, M. J. (2025). Marcos normativos para una IA ética y confiable en la educación superior: Estado de la cuestión. RIED. Revista Iberoamericana de Educación a Distancia, *28*(2). https://doi.org/10.5944/ried.28.2.43511
Guerra, M. (2024). Principios éticos de la educación con inteligencia artificial (IA). Tecnológico de Monterrey, Observatorio del Instituto para el Futuro de la Educación. https://observatorio.tec.mx/principios-eticos-de-la-educacion-con-inteligencia-artificial-ia/
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