Cited by 172Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationTechnology Adoption and User Behaviour

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

Registry

Crossref · 10.1016/j.nedt.2023.105796

Cites

13 of 13 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Citations

Cites

Show all 12 references

Research works printed but not linked: 1

  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

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Items 101–172 of 172

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
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
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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