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

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Bibliographic Details
Title: Exploring the Landscape: A Bibliometric Analysis of 30-Most Cited Articles on ChatGPT in Education
Language: English
Authors: Kashinath Boral (ORCID 0009-0003-1327-6719), Krishna Kanta Mondal (ORCID 0009-0006-9680-6050), Aparna Saikia (ORCID 0009-0007-2239-7386)
Source: International Journal of Education in Mathematics, Science and Technology. 2024 12(6):1583-1602.
Availability: International Journal of Education in Mathematics, Science and Technology. Necmettin Erbakan University, Ahmet Kelesoglu Education Faculty, Meram, Konya, 42090, Turkey. e-mail: ijermst@gmail.com; Web site: https://www.ijemst.net/index.php/ijemst/index
Peer Reviewed: Y
Page Count: 21
Publication Date: 2024
Document Type: Journal Articles
Information Analyses
Descriptors: Bibliometrics, Citation Analysis, Artificial Intelligence, Computer Software, Technology Integration, Teaching Methods, Research Reports, Periodicals, Electronic Publishing, Authors, Information Retrieval, Foreign Countries, Databases
ISSN: 2147-611X
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.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1465716
Database: ERIC
Description
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.
ISSN:2147-611X