Are Teachers Assessing Work Written by Students or by AI? A Rapid Literature Review of Research on Detecting Content Generated by Generative AI

Abstract

The rapid emergence of generative artificial intelligence (GenAI) in academic settings has led to growing concerns about its impact on writing and assessment practices. This paper reviews the latest literature on detecting GenAI-generated content and explores the challenges and potential solutions faced by educators. This study identifies various GenAI detection tools and analyses their strengths, weaknesses, and effectiveness across different writing contexts. It also discusses the growing complexity of GenAI outputs, including modifications by humans or other AI systems, which complicate detection efforts. The findings highlight the importance of adopting multifaceted approaches to evaluation, combining detection tools with expert human judgement to ensure academic integrity. Additionally, the results of this study suggest that pedagogical models need to evolve to accommodate the use of GenAI, advocating for a shift toward promoting critical thinking, creativity, and real-world problem solving. This review provides insights into how educators can adapt their teaching strategies and assessment methods in response to the increasing prevalence of GenAI tools in education.