Cited by 279Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationEducational Technology and Pedagogy

RETRACTED: The application and challenges of ChatGPT in educational transformation: New demands for teachers' roles

Open access
Yu, Hao·2024·Heliyon

Abstract

With the rapid development of information technology, artificial intelligence has demonstrated great potential in promoting educational transformation. In November 2022, the release of the artificial intelligence product ChatGPT attracted widespread attention, particularly in the field of education, sparking heated discussions among scholars. As a language processing tool, ChatGPT can not only answer user questions but also complete user-specified tasks and even continuously optimize task performance. However, while possessing powerful features, ChatGPT also has some shortcomings that need improvement, such as the accuracy of answering questions, data pollution issues, ethical and safety concerns, and the risk of knowledge plagiarism. In the process of promoting school education reform, the application of ChatGPT brings both opportunities and challenges. Moreover, ChatGPT's emergence offers teachers an opportunity to reflect on their professional value and sets higher demands for them.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.heliyon.2024.e24289This paper is marked retracted.

Cites

87 of 87 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Yu, H.
Affiliations
Shaanxi Normal University (CN)
Corresponding author
Yu, Hao
ORCID
Yu, Hao
Venue
Heliyon
Publisher
Elsevier BV
Published
2024-01
Volume
10
Issue
2
Pages
e24289
ISSN
2405-8440 (ISSN-L)
OpenAlex
W4390674638
Cited by
225
References
65
Citations by year
2026: 33 · 2025: 104 · 2024: 88
FWCI
84.60
Type
journal article
Language
en
Status
Retracted
Open access
Locations
  • Heliyon (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China
  • Beijing Normal University (ICER201902)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
Keywords
ChatGPT, educational transformation, teacher role, artificial intelligence in education, school education reform, contaminated data, retracted article

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.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review