ChatGPT: Empowering lifelong learning in the digital age of higher education
Integrity signals
Registry
Cites
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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?
Student-centred AI feedback mechanisms involve tasks like reflection prompts, AI-use reports, or annotated submissions, encouraging students to critically evaluate how and why they used generative AI tools.
“Student-centred AI feedback mechanisms involve tasks like reflection prompts, AI-use reports, or annotated submissions, encouraging students to critically evaluate how and why they used generative AI tools (Rawas, 2024; Tossell et al., 2024).”
From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Rawas, 2024
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References 11 · Cited by 310
- Authors
- Rawas, S.
- Affiliations
- Beirut Arab University (LB)
- Corresponding author
- Rawas, Soha
- ORCID
- Rawas, Soha
- Venue
- Education and Information Technologies
- Published
- 2023-08-09
- Volume
- 29
- Issue
- 6
- Pages
- 6895-6908
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4385702876
- Cited by
- 310
- References
- 11
- Citations by year
- 2026: 73 · 2025: 129 · 2024: 100 · 2023: 8
- FWCI
- 72.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Education and Information Technologies (publishedVersion)
- 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 › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- ChatGPT, large language models, artificial intelligence in education, higher education, lifelong learning, personalized learning recommendations, student cooperation, learning outcomes, AI ethics, AI implementation challenges, access to education
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.
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