Literaturnachweis - Detailanzeige
Autor/inn/en | Cheers, Hayden; Lin, Yuqing; Yan, Weigen |
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Titel | Identifying Plagiarised Programming Assignments with Detection Tool Consensus |
Quelle | In: Informatics in Education, 22 (2023) 1, S.1-19 (19 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1648-5831 |
Schlagwörter | Plagiarism; Assignments; Computer Software; Computer Science Education; Identification; Programming; Scores; Case Studies; Undergraduate Students; Comparative Analysis |
Abstract | Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work presents a semi-automatic approach that enables the indication of suspicious assignment submissions by analysing source code similarity scores among the submissions. The proposed approach seeks the consensus of multiple source code plagiarism detection tools in order to identify program pairs that are consistently evaluated with high similarity. A case study is presented to demonstrate the use of the proposed approach. The results of this case study indicate that it can accurately identify assignment submissions that are suspicious of plagiarism. (As Provided). |
Anmerkungen | Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |