The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Chatting or cheating? The impacts of ChatGPT and other artificial intelligence language models on nurse education
Overview
Integrity signals
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Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Restrictive approaches limit GenAI use, particularly in assess ments, emphasising verification requirements and traditional skill development”
From Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review (2025) · cites this paper as Choi et al., 2023
In the citing paper
“Additionally, with the rapid advancements in nursing research and the advent of new diseases and medications, nursing professionals are challenged to quickly adapt to evolving medical knowledge, make accurate decisions in real-case scenarios, and master complex nursing skills (1, 17, 26–28).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [1]
In the citing paper
“Scholars caution that generative AI’s potential to foster misinformation, over-reliance, and reduced critical judgment could undermine the ethical foundations of nursing education if left unchecked [12].”
From From adoption to interaction: examining human-GenAI engagement patterns, ethical tensions, and educational trade-offs in nursing education (2026) · cites this paper as [12]
In the citing paper
“professional behavioral learning in nursing requires students to engage in hands-on practice in authentic or simulated clinical environments, mastering various nursing skills through practical operation and repeated training, such as patient care, surgical nursing, and intravenous infusion, rather than relying solely on dialogue interactions with AI chatbots (1).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [1]
In the citing paper
“Numerous researchers have forecasted how ChatGPT will affect various areas, including the educational system Choi et al. (2023), Lim et al. (2023) (12 publications).”
From Decoding ChatGPT: A taxonomy of existing research, current challenges, and possible future directions (2023) · cites this paper as Choi et al. (2023)
In the citing paper
“These include the dissemination of false information and references [12, 23, 61, 85], biased reinforcement [47, 50], compromised academic integrity [18, 40, 66, 74], and the potential decline in students' skills [43, 61, 64, 74].”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [12]
Citations
Cites
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079
ChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842
ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.9 · Cited by 1,806
ChatGPT is fun, but not an author
Thorp, H. H. (2023) · Science · doi:10.1126/science.adg7879 · Cited by 1,437
ChatGPT and other large language models are double-edged swords
Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023) · Radiology · doi:10.1148/radiol.230163 · Cited by 1,008
Pavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972
Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning
Mhlanga, D. (2023) · Sustainable Development Goals Series · doi:10.1007/978-3-031-37776-1_17 · Cited by 718
Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse?
O’Connor, S., & ChatGPT (2023) · Nurse Education in Practice · doi:10.1016/j.nepr.2022.103537 · Cited by 585
“What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter
Taecharungroj, V. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7010035 · Cited by 489
Flanagin, A., Bibbins-Domingo, K., Berkwits, M., & Christiansen, S. L. (2023) · JAMA · doi:10.1001/jama.2023.1344 · Cited by 420
The future of medical education and research: Is ChatGPT a blessing or blight in disguise?
Arif, T. B., Munaf, U., & Ul-Haque, I. (2023) · Medical Education Online · doi:10.1080/10872981.2023.2181052 · Cited by 317
Research works printed but not linked: 1
- Gilson, 2023, How does CHATGPT perform on the United States medical licensing examination? The implications of large language models for medical education and knowledge assessment, JMIR Med. Educ., 9
Cited by
Sorted by citations
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784
Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions
Abd-alrazaq, A., AlSaad, R., Alhuwail, D., Ahmed, A., Healy, P. M., Latifi, S., Aziz, S., Damseh, R., Alabed Alrazak, S., & Sheikh, J. (2023) · JMIR Medical Education · doi:10.2196/48291 · Cited by 722
La nueva realidad de la educación ante los avances de la inteligencia artificial generativa
García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2023) · RIED-Revista Iberoamericana de Educación a Distancia · doi:10.5944/ried.27.1.37716 · Cited by 238
Empowering education development through AIGC: A systematic literature review
Chen, X., Hu, Z., & Wang, C. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12549-7 · Cited by 232
Duong, C. D., Vu, T. N., & Ngo, T. V. N. (2023) · The International Journal of Management Education · doi:10.1016/j.ijme.2023.100883 · Cited by 249
Metadata
- Authors
- Choi, E. P. H., Lee, J. J., Ho, M.-H., Kwok, J. Y. Y., & Lok, K. Y. W.
- Affiliations
- University of Hong Kong (HK)
- Corresponding author
- Choi, Edmond Pui Hang
- Venue
- Nurse Education Today
- Publisher
- Elsevier BV
- Published
- 2023-06
- Volume
- 125
- Pages
- 105796
- ISSN
- 0260-6917 (ISSN-L)
- OpenAlex
- W4324364344
- Semantic Scholar
- 77a3a61e96029a7c0d29133a082d814ac79d4430
- Cited by
- 172
- References
- 12
- Citations by year
- 2026: 27 · 2025: 44 · 2024: 60 · 2023: 41
- FWCI
- 40.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nurse Education Today (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- ChatGPT, generative AI, nursing education, university students, technology acceptance model, effort expectancy, performance expectancy, intention to use, knowledge sharing, academic dishonesty, AI adoption in education
- MeSH terms
- Artificial Intelligence, Education, Nursing, Educational Status, Humans, Language
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