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

Authors

  • Kaneeka Vidanage General Sir John Kotelawala Defense University
  • Manith Marapperuma General Sir John Kotelawala Defense University
  • Shakya Dissanayake General Sir John Kotelawala Defense University
  • Faiz Mohideen Mohamed Thassim Marikar General Sir John Kotelawala Defense University

DOI:

https://doi.org/10.59120/drj.v17i3.615

Keywords:

Generative Artificial Intelligence, Governance Framework, Higher Education, Human Cognition, Scoping Review

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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Author Biographies

  • Kaneeka Vidanage, General Sir John Kotelawala Defense University

    Faculty of Computing, Sri Lanka

  • Manith Marapperuma, General Sir John Kotelawala Defense University

    Faculty of Computing, Sri Lanka

  • Shakya Dissanayake, General Sir John Kotelawala Defense University

    Faculty of Computing, Sri Lanka

  • Faiz Mohideen Mohamed Thassim Marikar, General Sir John Kotelawala Defense University

    Staff Development Centre, Sri Lanka

References

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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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Published

2026-08-08

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