Bibliometric Analysis of Studies on Artificial Intelligence in Environmental and Health Education

Abstract

While the use of artificial intelligence in education is a prominent area of research, it has also become a collaborative application for educational institutions. These institutions are working to develop AI-based systems to enhance existing educational frameworks. Accordingly, this study conducts a bibliometric analysis of research on artificial intelligence in environmental and health education published between 2020 and 2024 (the past five years), using the Web of Science database. VOSviewer software was employed for the analysis. A search of the Web of Science database using these criteria yielded 640 studies. An examination of the publication distribution by year reveals a notable concentration of publications in 2024. In terms of country-specific contributions, the leading contributors were China, the United States, and England. The most prolific authors in the field were identified as Ai Koyanagi, Brendon Stubbs, and Joseph Firth. In terms of document and citation numbers within journals, the "Journal of Medical Internet Research" emerged as the most prominent. The most frequently cited keywords included "Artificial Intelligence," "Health Education," followed by "Machine Learning," "COVID-19," and "ChatGPT." These findings offer valuable insights into recent advancements in artificial intelligence research within the fields of environmental and health education. This study is anticipated to help researchers identify key trends and offer guidance for future investigations in the field.