Testing of support tools for plagiarism detection

Tomas Foltynek*, Dita Dlabolova, Alla Anohina-Naumeca, Salim Razi, Julius Kravjar, Laima Kamzola, Jean Gabriel Guerrero Dib, Ozgur Celik, Debora Weber-Wulff

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

There is a general belief that software must be able to easily do things that humans find difficult. Since finding sources for plagiarism in a text is not an easy task, there is a wide-spread expectation that it must be simple for software to determine if a text is plagiarized or not. Software cannot determine plagiarism, but it can work as a support tool for identifying some text similarity that may constitute plagiarism. But how well do the various systems work? This paper reports on a collaborative test of 15 web-based text-matching systems that can be used when plagiarism is suspected. It was conducted by researchers from seven countries using test material in eight different languages, evaluating the effectiveness of the systems on single-source and multi-source documents. A usability examination was also performed. The sobering results show that although some systems can indeed help identify some plagiarized content, they clearly do not find all plagiarism and at times also identify non-plagiarized material as problematic.
Original languageEnglish
Article number46
Pages (from-to)1-31
Number of pages31
JournalInternational Journal of Educational Technology in Higher Education
Volume17
Issue number1
DOIs
Publication statusPublished - 1 Dec 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

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