Mapping the landscape: generative AI in higher education assessment (2020-2024) - a scoping review

The emergence of Generative Artificial Intelligence (GAI) marks a paradigm shift in higher education, with the potential to transform assessment practices. Its disruptive capabilities offer both opportunities and challenges, prompting widespread debate about appropriate responses. Although recent reviews have synthesised research on GAI in higher education, methodological limitations, particularly the exclusion of grey literature, prevent a full understanding of this rapidly evolving field. To address this gap, the present scoping review maps the use of GAI in higher education assessment. Searches were conducted in ERIC, ProQuest, Scopus, and Web of Science for literature published between 1 June 2020 and 29 February 2024, including peer-reviewed articles and grey literature such as preprints and conference papers. This inclusive approach captured a comprehensive collection of both published and unpublished studies, the latter often overlooked in prior reviews. Documents were screened by three independent reviewers, and findings were synthesised narratively and in tables. A total of 68 documents met inclusion criteria, covering topics such as GAI’s role in assessment design, grading, feedback, and academic integrity. This review provides the most comprehensive global overview to date of early research on GAI in higher education assessment, highlighting both current practices and critical gaps for future investigation.