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Research · Pedagogy

Generative AI in higher education assessment: a scoping review

Interactive Learning Environments (Taylor and Francis) · Ng, S. H. S., Chan, H. Y., Wong, J. H. K., Sam, L., Privitera, A. J. · Jan 2026

Key points

  1. Scoping review mapping generative AI in higher education assessment from June 2020 to February 2024 across 68 documents.
  2. It identifies generative AI roles spanning assessment design, grading, feedback and academic integrity.
  3. The evidence base remains nascent and unevenly distributed, with narrow disciplinary coverage and limited longitudinal data.

Summary

Published online 13 January 2026 in Interactive Learning Environments (Taylor and Francis), this scoping review by Ng, Chan, Wong, Sam and Privitera maps 68 documents on generative AI in higher education assessment from June 2020 to February 2024. It identifies four main roles for generative AI in assessment: design, grading, feedback and academic integrity. The review's finding that the evidence base is nascent and unevenly distributed is itself a key result for course leaders, confirming that assessment redesign decisions must be made with limited empirical guidance.

Source

Source: Interactive Learning Environments (Taylor and Francis) ↗ (Research)

Cite this item

Ng, S. H. S., Chan, H. Y., Wong, J. H. K., Sam, L. & Privitera, A. J. (2026). ‘Generative AI in higher education assessment: a scoping review’, Interactive Learning Environments (Taylor and Francis). Available at: https://www.tandfonline.com/doi/full/10.1080/10494820.2026.2614079

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