Global and Domestic Perspectives on AI in Education: A Knowledge Mapping Analysis Using CiteSpace

This study utilized CiteSpace to perform an extensive knowledge mapping analysis of 826 Chinese articles and 488 international publications on artificial intelligence in education, obtained from the China National Knowledge Infrastructure (CNKI) and Web of Science databases, spanning the years 2014 to 2024. The research employed visualization methods, such as co-citation analysis and network algorithms, to comprehensively assess research hotspots, key topics, and emerging trends in the field, both domestically and internationally. Research indicates that overseas studies prioritize the incorporation of AI technology in education and the development of theoretical frameworks, whereas domestic research focuses on the practical use of AI in curriculum development and educational administration. Despite these divergent perspectives, both international and domestic research entities share a mutual interest in the use and advancement of AI in education, especially in relation to personalized learning and educational equity. To promote AI in global education, Future research should prioritize AI-driven digital transformation and standardization in education, Interdisciplinary collaboration and leveraging big data analytics will enhance innovation and decision-making, Addressing ethical issues, privacy, and societal acceptance is crucial for equitable and sustainable educational development.