Moderators of academic performance on the use of generative artificial intelligence
Integrity signals
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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?
High-performing students (assessed by CGPA) are inclined to utilize generative AI more strategically for research, writing and analytical reasoning.
“Academic achievement seems to mediate involvement, as high-performing students (assessed by CGPA) are inclined to utilize generative AI more strategically for research, writing and analytical reasoning (Marjerison et al., 2025).”
From <b>Beyond Access: Socioeconomic, Academic and Disciplinary Determinants of Generative AI Use in Higher Education</b> (2026) · cites this paper as Marjerison et al., 2025
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
Cognitive Load During Problem Solving: Effects on Learning
Sweller, J. (1988) · Cognitive Science · doi:10.1016/0364-0213(88)90023-7 · Cited by 11,048 · see citing works
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087 · see citing works
Chiu, T. K. F. (2024) · Educational technology research and development · doi:10.1007/s11423-024-10366-w · Cited by 235 · see citing works
Adopting AI: how familiarity breeds both trust and contempt
Horowitz, M. C., Kahn, L., Macdonald, J., & Schneider, J. (2024) · AI & SOCIETY · doi:10.1007/s00146-023-01666-5 · Cited by 135 · see citing works
Gustilo, L., Ong, E., & Lapinid, M. R. (2024) · International Journal for Educational Integrity · doi:10.1007/s40979-024-00153-8 · Cited by 89 · see citing works
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Zafar, S., Shaheen, F., & Khan, S. A. (2026) · Journal of Political Stability Archive · doi:10.63468/jpsa.4.2.17
- Authors
- Marjerison, R. K., Jun, J. Y., & Kim, J. M.
- Affiliations
- Wenzhou-Kean University (CN)
- Konkuk University (KR)
- Corresponding author
- Kim, Jong Min
- Venue
- Education and Information Technologies
- Published
- 2025-08-29
- Volume
- 30
- Issue
- 17
- Pages
- 24085-24107
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4413806743
- Cited by
- 3
- References
- 6
- Citations by year
- 2026: 3
- FWCI
- 1.93
- 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
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Keywords
- generative AI, academic performance, technology adoption, intention to use, Yerkes-Dodson law, inverted U-shaped relationship, academic integrity, AI familiarity, university students, artificial intelligence in 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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