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Volume 7, Issue 3 (SEPTEMBER ISSUE 2026)
johepal 2026, 7(3): 28-50 |
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Hosseini A, Khademzadeh E. (2026). Governing Generative AI in Higher Education: Policy Archetypes, Cross-Regional Patterns, and an Adaptive Governance Framework. johepal. 7(3), 28-50. doi:10.66224/johepal.7.3.28
URL: http://johepal.com/article-1-1947-en.html
URL: http://johepal.com/article-1-1947-en.html
Abstract: (5 Views)
The emergence of Generative Artificial Intelligence is reshaping debates and practices surrounding higher education governance and compelling universities to develop policy responses. This study compares GenAI policies across 29 universities in North America, Europe, East and Southeast Asia, Oceania, and institutions in the Middle East, Africa, and Latin America. It examines four questions: which policy archetypes have emerged across major regions; what emerging or hybrid approaches appear beyond these archetypes; what governance principles underpin policy approaches; and how these findings can inform a governance framework for higher education institutions. Using qualitative content analysis with a hybrid inductive–deductive approach, the study identifies four dominant archetypes: Risk-Management and Compliance, Ethical-Framework and Rights-Based, Dialogic and Flexible, and Empowerment and Literacy-First. Emerging approaches are identified in China/East Asia, the Middle East, Africa, and Latin America, while hybrid approaches are observed in North America, reflecting variation in regulatory contexts, institutional resources, and educational practices. Across the sampled universities, three recurrent governance principles emerge: Mandatory Transparency, Ultimate Human Accountability, and Preservation and Cultivation of Critical Thinking. The study synthesizes these findings into a Tripartite Adaptive Governance Framework spanning strategic, operational, and cultural levels, offering a flexible basis for responsible, equitable, and pedagogically sound GenAI adoption.
Keywords: Generative AI, Higher Education Policy, Academic Integrity, AI Governance, Comparative Policy Analysis, Adaptive Governance
Type of Study: Research |
Subject:
Special
Received: 2026/05/24 | Accepted: 2026/09/13 | Published: 2026/09/30
Received: 2026/05/24 | Accepted: 2026/09/13 | Published: 2026/09/30
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