A Bibliometric Lens on the Future: How AI continues to transform education institutions

Abstract

BACKGROUND: This extensive analysis examines the changing environment of AI in education using 1,480 Web of Science research publications. The goal is to map the academic landscape, highlight significant topics, and identify notable authors, nations, and documents to enable future study in this expanding subject. OBJECTIVE: The study seeks to explore AI’s influence on education and identify patterns and insights that might inform future research. METHODS: Bibliometric and content analytics are used to carefully extract data from the Web of Science Core Collection. To ensure completeness and relevance, 1,480 peer-reviewed papers from 2008 to 2023 were selected. RESULTS: The study identified six research clusters: AI Ethics and Innovation, Teaching Systems, Learning Experiences, Education Performance Enhancement via AI, Sustainable Development Goals in Education, and AI, Big Data, and Education. With the help of 107 universities, 310 keywords, and 160 authors from 37 different countries, these clusters are thriving islands in their respective fields. IMPLICATIONS: This study helps researchers, educators, and policymakers explore the literature and identify prospective research areas. It allows stakeholders to lead AI in education towards a more inclusive and enlightened future.