A Scoping Review of Generative AI Usage and Human Cognition in Education and Professional Practice: Dual-Edged Cognitive Impacts and a Governance Framework

Authors

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.

Keywords

Generative Artificial Intelligence Governance Framework Higher Education Human Cognition Scoping Review

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References

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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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Vol. 17 No. 3 (2026): September

Published

2026-09-11

License

Copyright (c) 2026 Kaneeka Vidanage, Manith Marapperuma, Shakya Dissanayake, Faiz Mohideen Mohamed Thassim Marikar

How to Cite

Vidanage, K., Marapperuma, M., Dissanayake, S., & Marikar, F. M. M. T. (2026). A Scoping Review of Generative AI Usage and Human Cognition in Education and Professional Practice: Dual-Edged Cognitive Impacts and a Governance Framework. Davao Research Journal, 17(3), 45-58. https://doi.org/10.59120/drj.v17i3.615

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