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The academic integrity violations detection system for data science course on the MOOC-platform

机译:MOOC平台数据科学课程学术诚信违规检测系统

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Academic integrity violations (as plagiarism, answers sharing, etc) are major challenges for many high education institutions around the world. These challenges had become more urgent after wide adoption of e-learning approach by education community in form of MOOCs or SPOCs. Therefore, the usage of automatic academic integrity violation detection systems is highly advisable in case of courses with large enrollment and large amounts of machine- and peer-graded assignments. In this work, we share our experience how to overcome these challenges in such course - Introduction to Data Science. The brief description of the course and assignments structure will be given, after that we will highlight some features of the assignments for Data Science course that requires a bit more complex approach to plagiarism detection and we will discuss architecture of proposed system for academic integrity violations detection.
机译:学术诚信违规(作为抄袭,答案分担等)是世界各地许多高等教育机构的主要挑战。毕业区通过教育界以MOOCS或SPOC的形式广泛采用电子学习方法,这些挑战变得更加紧迫。因此,在具有大入学课程和大量机器和同伴分配的课程的情况下,可以使用自动学术诚信违规检测系统的使用。在这项工作中,我们分享我们的经验在这种课程中如何克服这些挑战 - 数据科学介绍。课程和分配结构的简要说明将得到给出,之后我们将突出数据科学课程作业的一些特征,这需要更复杂的抄袭检测方法,我们将讨论拟议的学术诚信违规检测系统的体系结构。

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