The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Integrating Generative AI in Education: How ChatGPT Brings Challenges for Future Learning and Teaching
Open accessOverview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Specifically, for educators, the need to learn about AI and address it in teaching brings extra requirements for their knowledge and skills [5].”
From AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities (2024) · cites this paper as [5]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, its rapid growth also raises important concerns about academic integrity, overreliance, and the reliability of AI-generated content, particularly when students use such tools without sufficient judgment or verification [3,25,26].”
From Engineering student perceptions of generative AI use in learning trust judgment and information seeking (2026) · cites this paper as [26]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Existing work shows that although these tools may strengthen autonomy, personalization, and learner confidence, excessive reliance may also create risks such as cognitive overload, reduced critical thinking, and weaker social learning [26].”
From Engineering student perceptions of generative AI use in learning trust judgment and information seeking (2026) · cites this paper as [26]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(2000) · Cited by 2,779
Cited by
Sorted by citations
The Impact of Artificial Intelligence (AI) on Students’ Academic Development
Vieriu, A. M., & Petrea, G. (2025) · Education Sciences · doi:10.3390/educsci15030343 · Cited by 493
Yu, H. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e24289 · Cited by 225
RetractedAlmogren, A. S., Al-Rahmi, W. M., & Dahri, N. A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e31887 · Cited by 250
Lavidas, K., Voulgari, I., Papadakis, S., Athanassopoulos, S., Anastasiou, A., Filippidi, A., Komis, V., & Karacapilidis, N. I. (2024) · Information · doi:10.3390/info15060314 · Cited by 181
Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study
Funa, A. A., & Gabay, R. A. E. (2024) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2024.101221 · Cited by 168
Metadata
- Authors
- Wu, Y.
- Affiliations
- University of California, Berkeley (US)
- Corresponding author
- Wu, Yi
- ORCID
- Wu, Yi
- Venue
- Journal of Advanced Research in Education
- Publisher
- Paradigm Academic Press Limited
- Published
- 2023-09
- Volume
- 2
- Issue
- 4
- Pages
- 6-10
- ISSN
- 2709-3980 (ISSN-L)
- OpenAlex
- W4379046986
- Cited by
- 124
- References
- 1
- Citations by year
- 2026: 27 · 2025: 62 · 2024: 33 · 2023: 2
- FWCI
- 29.11
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Advanced Research in Education (publishedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- generative AI, ChatGPT, artificial intelligence in education, future of learning, educational challenges, educational technology
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
