Open Access Article

Generative AI and Educational Assessments: A Systematic Review

by Jian Zhao1, Elaine Chapman1 and Peyman G. P. Sabet1, 2

1 Graduate School of Education, The University of Western Australia
2 Global Curtin, Curtin University

Published in: Education Research and Perspectives, Volume 51, 31 December 2024, Pages 124-155;
DOI: 10.70953/ERPv51.2412006

Abstract

The launch of ChatGPT and the rapid proliferation of generative AI (GenAI) have brought transformative changes to education, particularly in the field of assessment. This has prompted a fundamental rethinking of traditional assessment practices, presenting both opportunities and challenges in evaluating student learning. While numerous studies have examined the use of GenAI in assessment, no systematic review has been conducted to synthesise the existing empirical evidence on this topic. Systematically reviewing 19 empirical studies published within 10 years, starting in 2014, this study assessed the current state of empirical evidence regarding GenAI in educational assessment practices and the future research directions required to advance this field. The findings were synthesised into four themes: (1) Educators’ perceptions of GenAI in assessment practices; (2) Students’ perceptions of GenAI in assessment practices; (3) Effectiveness of applying GenAI in assessment practices; and (4) Recommendations for leveraging GenAI in future assessment practices. The first three themes summarise the current empirical evidence, while the fourth theme identifies priorities for future research to guide the effective integration of GenAI into assessment practices.