Developing guidelines for the implementation of generative ai in higher education: A stakeholder-engaged approach

Date

2025-9-29

Author

Bekar, Eren

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Generative Artificial Intelligence (Gen-AI) is reshaping teaching, assessment, and research across universities. Yet many institutions lack actionable, value-sensitive guidance that safeguards integrity, equity, and privacy. This study developed comprehensive ethical guidelines for responsible Gen-AI integration in higher education, specifically within Social Sciences, addressing the urgent governance gap and ethical uncertainties impacting academic integrity, critical thinking, and digital equity. A qualitative investigation utilized deductive thematic analysis from three focus groups comprising Social Sciences academics and master’s/doctoral students. An initial 13 ethical values and principles, derived from meta-document analysis, guided the inquiry. Data analysis employed a “Real-Life Situation → Value-Related Concern → Solution/Policy Suggestion” schema. Thirteen ethical values and principles were consolidated into 8 core categories (e.g., Honesty and Transparency, Reliability, Equality). Findings showed consensus on Gen-AI disclosure and concerns about cognitive laziness and creativity erosion, alongside calls for unified institutional policies. Tensions arose from divergent stakeholder priorities (academic integrity vs. efficiency) and trade-offs between equitable access to paid tools and data privacy. Educators reported increased workload for verification and assessment. This research demonstrates the efficacy of a participatory, value-driven methodology in bridging abstract ethical principles with practical implementation. The framework offers a replicable model for institutions to foster responsible Gen-AI use. Recommendations include integrating clear Gen-AI usage policies in syllabus, mandating transparent disclosure, designing diversified assessments, providing institutional tool access, and establishing multi-layered governance frameworks.

Subject Keywords

Generative AI, Higher education, Ethics, Participatory design, Policy guidelines

URI

https://hdl.handle.net/11511/116154

Collections

Graduate School of Social Sciences, Thesis