Dolos 2.0:在在线学习环境中实现无缝的源代码抄袭检测

Rien Maertens, P. Dawyndt, Bart Mesuere
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摘要

随着对编程技能需求的增加,越来越多的在线编程课程和评估成为趋势。虽然这使得教育者可以教更多的学生,但也为不诚实的学生行为打开了大门,比如抄袭其他学生的代码。当老师布置作业时,所有学生都为同一个问题写代码,源代码相似工具可以帮助打击抄袭。不幸的是,教师往往不使用这些工具来防止这种行为。为了应对这一挑战,我们开发了一种新的源代码抄袭检测工具,名为Dolos。Dolos是开源的,支持广泛的编程语言,并且被设计为用户友好的。它使教师能够通过使用快速算法和强大的可视化来检测、证明和防止编程课程中的抄袭。我们进一步介绍了Dolos的增强功能,并讨论了如何将其集成到现代计算机教育课程中,以应对在线学习和评估的挑战。通过降低教师在编程课程中发现、证明和防止抄袭的障碍,Dolos可以帮助保护学术诚信,确保学生诚实地获得成绩。
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Dolos 2.0: Towards Seamless Source Code Plagiarism Detection in Online Learning Environments
With the increasing demand for programming skills comes a trend towards more online programming courses and assessments. While this allows educators to teach larger groups of students, it also opens the door to dishonest student behaviour, such as copying code from other students. When teachers use assignments where all students write code for the same problem, source code similarity tools can help to combat plagiarism. Unfortunately, teachers often do not use these tools to prevent such behaviour. In response to this challenge, we have developed a new source code plagiarism detection tool named Dolos. Dolos is open-source, supports a wide range of programming languages, and is designed to be user-friendly. It enables teachers to detect, prove and prevent plagiarism in programming courses by using fast algorithms and powerful visualisations. We present further enhancements to Dolos and discuss how it can be integrated into modern computing education courses to meet the challenges of online learning and assessment. By lowering the barriers for teachers to detect, prove and prevent plagiarism in programming courses, Dolos can help protect academic integrity and ensure that students earn their grades honestly.
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