Artificial Intelligence in Education: Global Trends, Clusters, and Perspectives

Abstract

Integrating artificial intelligence (AI) in education has become a powerful force in transforming teaching practices and fostering personalized learning experiences. This study utilizes bibliometric analysis to investigate global trends and thematic clusters in AI in education, examining 11,779 publications spanning from 2010 to 2024. Using multiple correspondence analysis (MCA), the study identifies six main clusters, including adaptive learning technologies, ethical considerations, intelligent tutoring systems, future skills development, digital teaching tools, and interdisciplinary challenges. The findings underscore the prominence of adaptive and personalized learning systems as crucial areas of research focus, while also highlighting a growing concern regarding ethical issues such as algorithmic bias and accessibility. Additionally, emerging themes like the role of digital teachers and the societal impact of AI-driven education offer valuable insights into the progression of the field.