Navigating Ethical Dilemmas in AI-Enhanced Education: A Critical Bibliometric Analysis of Global Research Trends and Collaboration Networks

With the rapid advancement of artificial intelligence (AI) in education, AI-enhanced learning is driving profound pedagogical shifts, offering personalized teaching and resource optimization while raising ethical concerns such as data privacy, algorithmic bias, intellectual property, transparency, and equity. Using bibliometric methods, the authors of this study systematically analyzed global research on AI ethics in education over the past decade, revealing its dynamic evolution. AI ethics in education research has grown exponentially, shifting from early technical feasibility studies to the ethical risks of generative AI in specific scenarios. However, research remains technology-centric, lacking focus on appropriate educational contexts. The international network is dominated by the United States, China, and European Union countries, with limited participation from developing nations. This study also examines ethical dilemmas and gaps in current research frameworks, aiming to provide insights for academics, policymakers, and future studies.