While AI has the potential to streamline assessment development in higher education, there are concerns about its reliability, fairness, and potential to perpetuate bias. This study sought to understand the perceptions of academics and teaching and learning (T&L) specialists on the use of AI tools and large language models on assessment development, whether the private HE institution (PHEI) needs to change how it assesses students, and the types of assessments to be created. This topic is extremely relevant, as many higher education institutions (HEIs) are entering unchartered territory, and there is scant credible evidence on the prior‐implementation reporting and evaluation of AI integration into assessment practices. Forty academics and T&L specialists at a PHEI in South Africa shared their perceptions. The study revealed two key themes: (a) AI use and (b) reconceptualizing assessments and T&L structures, indicating the need for HEIs to understand the synergies between AI and assessment practices.
No takes yet. Share an insight, caveat, or question.
Pramjeeth et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: