The Use of Artificial Intelligence in Detecting Plagiarism in Electronic Examinations: A Comparison Between Traditional and Modern Systems

This paper examines the utilisation of artificial intelligence (AI) in detecting plagiarism within electronic examinations, presenting a comparative analysis of traditional and modern systems. Traditional systems address plagiarism detection through techniques such as text matching and fundamental statistical content analysis. In contrast, contemporary AI-powered systems employ more sophisticated methods, including machine learning and the analysis of writing patterns, thereby enabling the identification of plagiarism even in instances involving minor textual modifications. Moreover, modern systems offer the ability to monitor plagiarism in real time during the examination process, rendering them markedly more effective and accurate in combating academic dishonesty. Despite the numerous advantages afforded by artificial intelligence, several challenges persist, including the protection of student privacy and the assurance of tool accuracy.