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ChatGPT in higher education - a synthesis of the literature and a future research agenda
Open accessAbstract
ChatGPT has emerged as a significant subject of research and exploration, casting a critical spotlight on teaching and learning practices in the higher education domain. This study examines the most influential articles, leading journals, and productive countries concerning citations and publications related to ChatGPT in higher education, while also shedding light on emerging thematic and geographic clusters within research on ChatGPT’s role and challenges in teaching and learning at higher education institutions. Forty-seven research papers from the Scopus database were shortlisted for bibliometric analysis. The findings indicate that the use of ChatGPT in higher education, particularly issues of academic integrity and research, has been studied extensively by scholars in the United States, who have produced the largest volume of publications, alongside the highest number of citations. This study uncovers four distinct thematic clusters (academic integrity, learning environment, student engagement, and scholarly research) and highlights the predominant areas of focus in research related to ChatGPT in higher education, including student examinations, academic integrity, student learning, and field-specific research, through a country-based bibliographic analysis. Plagiarism is a significant concern in the use of ChatGPT, which may reduce students’ ability to produce imaginative, inventive, and original material. This study offers valuable insights into the current state of ChatGPT in higher education literature, providing essential guidance for scholars, researchers, and policymakers.
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“Bhullar, Joshi, & Chugh (2024) warn that such dependence undermines critical thinking and reduces opportunities for deep learning.”
From Generative AI-Enhanced Oral Exams in Economics Education (2026) · cites this paper as Bhullar, Joshi, & Chugh (2024)
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“Scholars such as Bhullar, Joshi, & Chugh (2024), Cassidy (2023), Eke (2023), and Plata, De Guzman, & Quesada (2023) further argue that misuse often stems from unclear guidance rather than intentional dishonesty, underscoring the need for explicit institutional policies.”
From Generative AI-Enhanced Oral Exams in Economics Education (2026) · cites this paper as Bhullar, Joshi, & Chugh (2024)
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Metadata
- Authors
- Bhullar, P. S., Joshi, M., & Chugh, R.
- Affiliations
- Maharaja Ranjit Singh Punjab Technical University (IN)
- Central Queensland University (AU)
- Corresponding author
- Chugh, Ritesh
- Venue
- Education and Information Technologies
- Published
- 2024-05-02
- Volume
- 29
- Issue
- 16
- Pages
- 21501-21522
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4396592436
- Cited by
- 139
- References
- 73
- Citations by year
- 2026: 67 · 2025: 59 · 2024: 13
- FWCI
- 52.42
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Education and Information Technologies (publishedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Funders
- Central Queensland University
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- ChatGPT, generative AI in education, higher education teaching and learning, academic integrity, plagiarism, student engagement, learning environment, student examinations, research agenda
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