A Scoping Review of Generative AI Usage and Human Cognition in Education and Professional Practice: Dual-Edged Cognitive Impacts and a Governance Framework
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Abstract
The use of Generative Artificial Intelligence (Gen-AI) across education, healthcare, ethics, and professional practice is rapidly increasing. This growth has sparked a polarized debate, with Gen-AI viewed either as a powerful cognitive augmenter or as a potential threat to critical thinking, creativity, and independent reasoning. To examine this issue, the review scope was defined using the PRISMA-ScR guidelines, Joanna Briggs Institute (JBI) methodology, and the Population–Concept–Context (PCC) framework. A systematic literature search was conducted across PubMed, IEEE Xplore, ACM Digital Library, Springer, and Wiley Online Library. Only English-language publications published between 2020 and 2025 were considered. Following multi-stage screening, duplicate removal, eligibility assessment, and human verification, 107 peer-reviewed articles were included in the final analysis. Among the selected studies, 42% focused on university education, 23% on school education, 16% on medical education, 11% on ethics and moral responsibilities, and 8% on professional training. Synthesis of the findings led to two major conceptual contributions. First, the Cognitive Impact Taxonomy (CIT) provides a structured approach for assessing Gen-AI’s influence on fluid and crystallized intelligence, key cognitive processes, and the trajectory of cognitive impacts leading to severity assessment. Second, the Integrated Cognitive Symbiosis Framework (ICSF) introduces a three-layer governance model to support responsible and cognitively healthy Gen-AI adoption. Together, the CIT–ICSF pipeline offers educators, institutional leaders, and policymakers a practical mechanism to maximize the benefits of Gen-AI while mitigating potential long-term cognitive risks.
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References
Adnin, R., Pandkar, A., Yao, B., Wang, D., and Das, M. (2025) Examining student and teacher perspectives on undisclosed use of generative AI in academic work. In: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, pp 1–17. ACM, New York, NY, USA. https://doi.org/10.1145/3706598.3713393
Al-Abri, A. (2025). Exploring ChatGPT as a virtual tutor: A multi-dimensional analysis of large language models in academic support. Education and Information Technologies, 30(12), 17447-17482.https://doi.org/10.1007/s10639-025-13484-x
Alabsi, H., Almotairi, M., Alyami, M., Alqahtani, Y., Obeidat, R., and Almansour, F. (2025) Can ChatGPT serve as a cognitive stimulus? A proposed model for assessing the impact on graduate students' perceptions of cognitive and developmental skills. In: Advances in Intelligent Systems and Computing, 461–468. Springer Nature Switzerland, Cham
Alaswad, S., Kalganova, T., and Awad, W. (2025). Developing a Framework for Using Large Language Models for Viva Assessments in Higher Education. In 2024 International Conference on IT Innovation and Knowledge Discovery (ITIKD) (pp. 1-7). IEEE. https://doi.org/10.1109/ITIKD63574.2025.11005250.
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Copyright (c) 2026 Kaneeka Vidanage, Manith Marapperuma, Shakya Dissanayake, Faiz Mohideen Mohamed Thassim Marikar

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