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Novak, Matija; Joy, Mike; Kermek, Dragutin – ACM Transactions on Computing Education, 2019
Teachers deal with plagiarism on a regular basis, so they try to prevent and detect plagiarism, a task that is complicated by the large size of some classes. Students who cheat often try to hide their plagiarism (obfuscate), and many different similarity detection engines (often called plagiarism detection tools) have been built to help teachers.…
Descriptors: Plagiarism, Computer Software, Computer Software Evaluation, College Students
Source Code Plagiarism Detection in Academia with Information Retrieval: Dataset and the Observation
Karnalim, Oscar; Budi, Setia; Toba, Hapnes; Joy, Mike – Informatics in Education, 2019
Source code plagiarism is an emerging issue in computer science education. As a result, a number of techniques have been proposed to handle this issue. However, comparing these techniques may be challenging, since they are evaluated with their own private dataset(s). This paper contributes in providing a public dataset for comparing these…
Descriptors: Plagiarism, Computer Science Education, Comparative Analysis, Problem Solving
Cosma, Georgina; Joy, Mike; Sinclair, Jane; Andreou, Margarita; Zhang, Dongyong; Cook, Beverley; Boyatt, Russell – ACM Transactions on Computing Education, 2017
Perspectives of students on what constitutes source-code plagiarism may differ based on their educational background. Surveys have been conducted with home students undertaking computing and joint computing subject degrees at higher education institutions throughout the UK, China, and South Cyprus, and a total of 984 responses have been…
Descriptors: Foreign Countries, College Students, Plagiarism, Student Attitudes