Discovering and exploring cases of educational source code plagiarism with Dolos

被引:0
|
作者
Maertens, Rien [1 ]
Van Neyghem, Maarten [1 ]
Geldhof, Maxiem [1 ]
Van Petegem, Charlotte [1 ]
Strijbol, Niko [1 ]
Dawyndt, Peter [1 ]
Mesuere, Bart [1 ]
机构
[1] Univ Ghent, Dept Appl Math Comp Sci & Stat, Ghent, Belgium
基金
比利时弗兰德研究基金会;
关键词
Web app; Plagiarism; Source code; Academic dishonesty; Cheating; Learning analytics; Educational data mining; Online learning; Programming language;
D O I
10.1016/j.softx.2024.101755
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Source code plagiarism is a significant issue in educational practice, and educators need user-friendly tools to cope with such academic dishonesty. This article introduces the latest version of Dolos, a state-of-theart ecosystem of tools for detecting and preventing plagiarism in educational source code. In this new version, the primary focus has been on enhancing the user experience. Educators can now run the entire plagiarism detection pipeline from a new web app in their browser, eliminating the need for any installation or configuration. Completely redesigned analytics dashboards provide an instant assessment of whether a collection of source files contains suspected cases of plagiarism and how widespread plagiarism is within the collection. The dashboards support hierarchically structured navigation to facilitate zooming in and out of suspect cases. Clusters are an essential new component of the dashboard design, reflecting the observation that plagiarism can occur among larger groups of students. To meet various user needs, the Dolos software stack for source code plagiarism detection now includes a self-hostable web app, a JSON application programming interface (API), a command line interface (CLI), a JavaScript library and a preconfigured Docker container. Clear documentation and a free-to-use instance of the web app can be found at https://dolos.ugent.be. The source code is also available on GitHub.
引用
收藏
页数:7
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