AI governance in higher education: A meta-analytic thematic review of current research trends, policy initiatives and knowledge gaps
Abstract
Research background: Artificial Intelligence (AI) is rapidly transforming higher education, presenting both opportunities and challenges for institutions. AI improves education through personalized learning, adaptive assessments, virtual tutoring, and generative support. However, these advancements also bring challenges that require vigilant governance to uphold academic integrity and ethical standards.
Purpose of the article: Given the complexities and potential impacts of AI in higher education, this study aims to provide a thematic review by synthesizing the available literature to shed light on research trends, initiatives, and knowledge gaps in AI governance. The literature also explores the background of AI integration into higher education, focusing on its applications, benefits, challenges, and implications for students, educators, and institutions.
Methods: This study followed PRISMA guidelines and used the Scopus database for data collection. After rigorous screening, 142 papers were selected for the final review. The bibliometric analysis was conducted using the R Studio Bibliometrix package, which generates various indicators like publication trends, author collaborations, keyword co-occurrences, and citation patterns. This approach offers a different perspective on data representation and analysis compared to VOSviewer.
Findings & value added: The study highlights that AI governance in higher education involves establishing guidelines, data protection, and privacy policies. Institutions like Swansea University and government agencies like the European Commission and the US Department of Commerce are adopting ethical frameworks to guide AI development and reserving funds for AI governance research. The research concluded that governments worldwide had recognized the need for AI integration in academic research and higher education for sustainable growth and had implemented comprehensive regulations.
Keywords
artificial intelligence, generative AI models, educational innovation, AI governance, higher education, SDG4
References
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