Generative AI policies in higher education for human-centered learning: A qualitative thematic analysis of documents
Article
Andrienko-Genin, T, Sayegh, G. (2026). Generative AI policies in higher education for human-centered learning: A qualitative thematic analysis of documents
. East European Journal of Psycholinguistics, 13(1), 54-83. 10.29038/eejpl.2026.13.1.and
Andrienko-Genin, T, Sayegh, G. (2026). Generative AI policies in higher education for human-centered learning: A qualitative thematic analysis of documents
. East European Journal of Psycholinguistics, 13(1), 54-83. 10.29038/eejpl.2026.13.1.and
. This article examines the evolving landscape of generative artificial intelligence (AI) policies in universities and colleges, situating them within broader knowledge systems and frameworks of human intelligence. The study employs a reflexive thematic analysis of AI policy documents to map the current landscape of generative AI policies in higher education. The data corpus consists of three main sources: (1) global recommendations and position papers issued by international organizations and accrediting bodies; (2) scholarly generalizations of policy statements and frameworks from higher education institutions; and (3) institutional-level disciplinary syllabi AI policy statements presented in Crowdsourced Syllabus Statements on AI Tools. Documents were selected based on relevance to generative AI, higher education, and policy development. Case studies from leading universities illustrate diverse policy approaches, ranging from strict restrictions on AI-assisted assignments to integrative strategies embedding AI literacy and ethical considerations into curricula. By mapping these policy landscapes, this article contributes to an understanding of how higher education organizes, shares, and applies knowledge in the age of generative AI. It argues that successful AI integration depends on flexible governance, ongoing stakeholder dialogue, and institutional capacity to adapt policies in response to rapidly evolving technologies. In doing so, higher education institutions not only safeguard academic integrity but also shape the societal norms of responsible AI use for future generations.
