Generative AI and GenAI-resilient assessment: supporting the PGTA workforce

The use of postgraduate student teaching assistants (PGTAs) in higher education is an accepted practice, but potentially involves a ‘trade-off’ between increased academic support and teaching quality. While institutions can do much to build PGTA skills and competencies (Van Geyte and Hadjianastasis, 2021), it has also been argued that marking and the provision of feedback present particular challenges for inexperienced university teachers (Wald and Harland, 2018). This article explores this issue with reference to written coursework and Generative AI (also referred to as Gen AI or GAI). By situating and reviewing literature that considers PGTA perceptions of GAI, PGTA experiences of identifying work that has used GAI, and the implications of GAI-resilient assessment strategies for a PGTA workforce, I argue that the specific needs of PGTAs should be considered as part of the broader re-evaluation of assessment practices in higher education which the advent of GAI has accelerated.