Exploring the Landscape: A Bibliometric Analysis of 30-Most Cited Articles on ChatGPT in Education

Abstract

ChatGPT is a conversational AI model that offers unique opportunities for personalized learning, students’ engagement, and educational support. This study aims to investigate the influence of the top 30 most cited articles in the realm of ChatGPT in education. Employing a descriptive approach, bibliometric analysis was conducted on a combined dataset of 31 articles sourced from Web of Science and Scopus databases. Additionally, co-authorship and co-occurrence analyses were performed using VOSviewer (version 1.6.20) software. The findings reveal that the most cited papers were published between 2023 and 2024, with Healthcare, an open-access journal, emerging as the most cited platform. Notably, review articles garnered the highest number of citations, and authors predominantly hailed from developed nations. The literature dominantly focuses on the use of ChatGPT in medical education. Co-occurrence and co-authorship analyses highlight "ChatGPT" and "artificial intelligence" as the most frequently encountered keywords and no authors have published more than one paper. Lastly, a discussion, future suggestions and conclusion of the results was made which can serve as a key point for future research in the field.