Cited by 337Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationEducation and Communication Studies

Preparing for AI-enhanced education: conceptualizing and empirically examining teachers’ AI readiness

Wang, Xinghua, Li, Linlin, Tan, Seng Chee, Yang, Lu, Lei, Jun·2023·Computers in Human Behavior

Integrity signals

Registry

Crossref · 10.1016/j.chb.2023.107798

Cites

67 of 67 references verified0 citation errors · 0 not checkable

Statistics

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

Claims the paper makes

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Claims other papers make about this one

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Cites

Flagged first, then by citations

2 of the 69 references couldn’t be matched to a known paper.

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Authors
Wang, X., Li, L., Tan, S. C., Yang, L., & Lei, J.
Affiliations
  • Qingdao University (CN)
  • Nanyang Technological University (SG)
  • Ningbo University (CN)
Corresponding author
  • Wang, Xinghua
  • Lei, Jun
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2023-09
Volume
146
Pages
107798
ISSN
0747-5632 (ISSN-L)
OpenAlex
W4367189069
Cited by
336
References
69
Citations by year
2026: 128 · 2025: 122 · 2024: 76 · 2023: 10
FWCI
78.85
Type
journal article
Language
en
Open access
closed
Locations
  • Computers in Human Behavior (publishedVersion)
  • NIE Digital Repository (National Institute of Education, Nanyang Technological University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Education › Education and Communication Studies
Keywords
AI readiness, teachers, artificial intelligence in education, teacher job satisfaction, AI ethics, primary school teachers

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 ›

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