Testing of support tools for plagiarism detection

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dc.authoridGuerrero-Dib, Jean/0000-0003-3150-9363
dc.authoridWeber-Wulff, Debora/0000-0002-7335-6548
dc.authoridRazi, Salim/0000-0003-2136-4391
dc.authoridFoltynek, Tomas/0000-0001-8412-5553
dc.authoridCELIK, Ozgur/0000-0002-0300-9073
dc.authoridHenek Dlabolova, Dita/0000-0002-6316-3750
dc.authoridAnohina-Naumeca, Alla/0000-0001-7993-5842
dc.contributor.authorFoltynek, Tomas
dc.contributor.authorDlabolova, Dita
dc.contributor.authorAnohina-Naumeca, Alla
dc.contributor.authorRazi, Salim
dc.contributor.authorKravjar, Julius
dc.contributor.authorKamzola, Laima
dc.contributor.authorGuerrero-Dib, Jean
dc.date.accessioned2025-01-27T21:19:20Z
dc.date.available2025-01-27T21:19:20Z
dc.date.issued2020
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractThere 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.
dc.description.sponsorshipHTW Berlin
dc.description.sponsorshipThis research did not receive any external funding. HTW Berlin provided funding for openly publishing the data and materials.
dc.identifier.doi10.1186/s41239-020-00192-4
dc.identifier.issn2365-9440
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85088576086
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1186/s41239-020-00192-4
dc.identifier.urihttps://hdl.handle.net/20.500.12428/28554
dc.identifier.volume17
dc.identifier.wosWOS:000552264700001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofInternational Journal of Educational Technology in Higher Education
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20250125
dc.subjectText-matching software
dc.subjectSoftware testing
dc.subjectPlagiarism
dc.subjectPlagiarism detection tools
dc.subjectUsability testing
dc.titleTesting of support tools for plagiarism detection
dc.typeArticle

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