Second Handbook of Academic Integrity
Integrity signals
Registry
Cites
Statistics
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?
Education scholars have advocated for teaching academic honesty as an ongoing skill that students develop throughout their academic journeys.
“Education scholars have advocated for teaching academic honesty as an ongoing skill that students develop throughout their academic journeys (Eaton, 2023).”
From Evolving intersections: AI, disability, and academic integrity in higher education (2025) · cites this paper as Eaton, 2023
Cited by
Sorted by citations
Evolving intersections: AI, disability, and academic integrity in higher education
Jafry, A., & Vorstermans, J. (2025) · New Directions for Teaching and Learning · doi:10.1002/tl.20629 · Cited by 6 · see citing works
Taptamat, N., Holt, M., McGrath, D., & McElligott, T. (2026) · Journal of University Teaching and Learning Practice · doi:10.53761/m1vv5t24
- Authors
- Eaton, S. E.
- Affiliations
- University of Calgary (CA)
- Corresponding author
- Sarah Elaine Eaton
- ORCID
- Sarah Elaine Eaton
- Venue
- Springer International Handbooks of Education
- Publisher
- Springer Nature Switzerland
- Published
- 2024
- ISSN
- 2197-1951
- 2197-196X
- OpenAlex
- W4389316797
- Cited by
- 35
- References
- 0
- Citations by year
- 2025: 7 · 2024: 6 · 2023: 19 · 2022: 1 · 2021: 1 · 2020: 1
- Type
- reference entry
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Decision Sciences › Information Systems and Management › Ethics in Business and Education
- Social Sciences › Political Science and International Relations › Academic Freedom and Politics
- Keywords
- academic integrity, academic ethics, higher education, research integrity
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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