模拟相似性以维护编程学术诚信

IF 2.1 Q1 EDUCATION & EDUCATIONAL RESEARCH

Informatics in Education Pub Date : 2024-04-22 DOI:10.15388/infedu.2024.21

Oscar Karnalim

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引用次数: 0

摘要

程序设计专业的学生需要了解抄袭和串通行为。因此，我们开发了一个评估提交系统来提醒学生注意此事。每一份提交的材料都会与其他材料进行比较，任何并非巧合的相似之处都会连同可能的原因一并报告。该系统还采用了游戏化的方式，鼓励学生尽早提交独特的作品。不过，该系统可能会带来不必要的压力，因为巧合的相似之处仍会被报告。此外，该系统并没有明确涵盖自我抄袭行为。我们重新审视了该系统，并将重点转移到报告学生自己提交的模拟相似性上，而不是报告不同提交的实际相似性。根据我们对 390 名学生进行的评估和五个准实验，使用模拟相似性的学生对抄袭和串通（尤其是自我抄袭）的认识略有提高。他们对这一问题的认识在一定程度上是可以接受的（约 75%），而且他们看到了我们的评估提交系统的好处。

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Simulating Similarities to Maintain Academic Integrity in Programming

Programming students need to be informed about plagiarism and collusion. Hence, we developed an assessment submission system to remind students about the matter. Each submission will be compared to others and any similarities that do not seem a result of coincidence will be reported along with their possible reasons. The system also employs gamification to promote early and unique submissions. Nevertheless, the system might put unnecessary pressure as coincidental similarities can still be reported. Further, it does not specifically cover self-plagiarism. We revisit the system and shift our focus to report simulated similarities from student own submission instead of reporting actual similarities across submissions. According to our evaluation with 390 students and five quasi-experiments, students with simulated similarities are slightly more aware of plagiarism and collusion, self-plagiarism in particular. Their awareness of the matter is somewhat acceptable (around 75%) and they see the benefits of our assessment submission system.

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来源期刊

Informatics in Education EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

6.10

自引率

3.70%

发文量

审稿时长

20 weeks

期刊介绍： INFORMATICS IN EDUCATION publishes original articles about theoretical, experimental and methodological studies in the fields of informatics (computer science) education and educational applications of information technology, ranging from primary to tertiary education. Multidisciplinary research studies that enhance our understanding of how theoretical and technological innovations translate into educational practice are most welcome. We are particularly interested in work at boundaries, both the boundaries of informatics and of education. The topics covered by INFORMATICS IN EDUCATION will range across diverse aspects of informatics (computer science) education research including: empirical studies, including composing different approaches to teach various subjects, studying availability of various concepts at a given age, measuring knowledge transfer and skills developed, addressing gender issues, etc. statistical research on big data related to informatics (computer science) activities including e.g. research on assessment, online teaching, competitions, etc. educational engineering focusing mainly on developing high quality original teaching sequences of different informatics (computer science) topics that offer new, successful ways for knowledge transfer and development of computational thinking machine learning of student''s behavior including the use of information technology to observe students in the learning process and discovering clusters of their working design and evaluation of educational tools that apply information technology in novel ways.