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Addressing the Challenges of AI-Generated Assignment Submissions in Education: Insights and Strategies

Year: 2025

Type: article

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.

Source: Journal of Data Science

DOI: 10.6339/25-jds1208

Authors: Shuyi Wang, Longxin Xu, Junchen Liu, Yujia Zhai

Institution: Tianjin Normal University

Language: English

Topic: Academic integrity and plagiarism

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: diamond

Funder: National Office for Philosophy and Social Sciences