Addressing the Challenges of AI-Generated Assignment Submissions in Education: Insights and Strategies
Shuyi Wang, Lin Xu, Junchen Liu, Yujia Zhai
Abstract
The rapid development of artificial intelligence (AI) tools, particularly generative models, has introduced significant challenges in academic assessment. Students increasingly rely on AI to complete assignments, complicating the evaluation of their true understanding and effort. This paper examines the limitations of AI detection tools, the inadequacies of traditional teaching methods in this context, and the potential for responsibly integrating AI into educational practices. Drawing on insights from educators and recent developments in AI, the paper proposes strategies for adapting assessment methods to ensure academic integrity while embracing technological advancements. The findings underscore the need for a balanced approach that leverages AI’s benefits while mitigating its risks.