Cited by 208Artificial Intelligence in EducationAcademic integrity and plagiarismArtificial Intelligence in Healthcare and Education

ChatGPT in higher education - a synthesis of the literature and a future research agenda

Open access
Bhullar, Pritpal Singh, Joshi, Mahesh, Chugh, Ritesh·2024·Education and Information Technologies

Abstract

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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Integrity signals

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Crossref · 10.1007/s10639-024-12723-x

Cites

74 of 74 references verified0 citation errors · 0 not checkable

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  • Dependence on GenAI undermines critical thinking and reduces opportunities for deep learning.

    “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)

    Section 3.3.2 says ChatGPT could reduce students’ motivation to explore topics and draw conclusions independently. Section 3.4 warns of possible learning impediments and stresses the importance of critical thinking. These passages support a concern about learning, but they do not establish that dependence undermines critical thinking or specifically reduces opportunities for deep learning. (LLM, conf=0.82)

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  • Misuse of GenAI often stems from unclear guidance rather than intentional dishonesty.

    “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)

    Section 4.1 (Implications; page unavailable) calls for academic-integrity training and clearer institutional policies on appropriate and inappropriate AI use. Section 3.3.1 (Thematic clusters; page unavailable) likewise calls for clear boundaries. Neither passage says misuse often results from unclear guidance rather than intentional dishonesty. (LLM, conf=0.87)

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Cites

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Research works printed but not linked: 2

  1. Bajaj, Y., Kashiramka, S., & Singh, S. (2020). Application of capital structure theories: A systematic review. Journal of Advances in Management Research, 18(2), 173-199. https://doi.org/10.1108/ JAMR-01-2020-001. · DOI
  2. Neumann, M., Rauschenberger, M., & Schon, E-M. (2023). 2023 IEEE/ACM 5th International Workshop on Software Engineering Education for the Next Generation (SEENG), Melbourne, Australia, 2023, pp. 29-32, https://doi.org/10.1109/SEENG59157.2023.00010. · DOI · Paper page

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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
Locations
  • Education and Information Technologies (publishedVersion, cc-by)
  • Figshare (submittedVersion, cc-by)
Funders
Central Queensland University
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Safety Research › 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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