Understanding the impact of artificial intelligence on curriculum, instruction, and assessment in higher education: A systematic review

This preprint was a project carried out by the first author as a Research Associate with funding by the Learning Sciences and Psychological Studies in Education Hub in the School of Learning Development and Professional Practice, in the Faculty of Education and Social Work at the University of Auckland. The second and third authors provided guidance and supervision and contributed to the drafting of the manuscript.

The reference list for the final 34 papers in the review are available as *.ris file format for import into reference management software.

ABSTRACT

The emergence of artificial intelligence (AI) presents many opportunities and challenges to teaching and learning in higher education. However, compared to student-facing AI or administration-facing AI, little attention has been given to the impact of AI on faculty’s perspective or their curriculum, instruction, and assessment (CIA) practices. To address this gap, we conducted a systematic review of articles published within the first nine months following the release of ChatGPT. After screening following PRISMA guidelines, our review yielded 33 studies. The majority of these studies (n = 17) were conducted in Asia, and simulation and modelling were the most frequently used methods (n = 14). Thematic analysis of the studies resulted in four themes about the impact of AI on CIA triad: (a) generation of new material, (b) reduction of staff workload, (c) automation/optimisation of evaluation, and (d) challenges for CIA. Implications for future research and practices are proposed.