The Global Research Landscape of AI in education: A Bibliometric analysis of Pathway Evolution and Frontier Issues

In recent years, research on Artificial Intelligence in Education (AIED) has progressed rapidly, making it essential to understand its research trends and developments to drive technological innovation and implementation in the education sector. Through a bibliometric analysis of 2,038 papers retrieved from the Web of Science database, we identified that China, the United States, Australia, and the United Kingdom are leading in this field. The bibliometric analysis reveals that the primary applications of artificial intelligence technologies in education include deep learning, machine learning, augmented reality, computer vision, and natural language processing (NLP). These technologies have been widely applied in various scenarios, such as intelligent tutoring systems, automated grading systems, and educational robots. Notably, generative AI technologies are advancing rapidly, sparking extensive discussions and controversies in education and other societal domains. Looking ahead, the development of education requires further cultivation of AI-driven thinking and the support of relevant policies to promote the deep integration of technology and education.