AI on Academic Integrity and Plagiarism Detection
Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) has introduced transformative advancements in academic integrity and plagiarism detection within educational institutions. This study explores how AI-driven tools are reshaping the landscape of academic honesty by enabling efficient and precise detection of plagiarised content, particularly in the face of sophisticated paraphrasing and AI-generated text. We analyse the effectiveness of traditional and AI-powered plagiarism detection tools, comparing their capabilities in recognising rephrased, translated, and synthetically generated content. Through a mixed-method approach, including quantitative tool performance analysis and qualitative insights from educators and students, the study assesses both the benefits and ethical challenges posed by AI in academic settings. Findings reveal that while AI significantly enhances detection accuracy, it raises concerns regarding dependency on automated assessments and ethical considerations in student evaluation. This research underscores the need for complementary human oversight and advocates for policy frameworks that guide the responsible integration of AI in academia.
Source: ASM Science Journal
Authors: Zhang Jing Bing, Wai Yie Leong
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4408899161