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Can we rely on text originality check systems?

Can we rely on text originality check systems?.

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Can we rely on text originality check systems?

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  1. Canwerely on text originality check systems?

  2. TOCS limited ability to detect plagiarism means that we cannot wholly rely on a technical system to detect plagiarism and cheating. Instead, additional strategies against plagiarism and cheating are needed. Examples of such strategies are the use of recurrent drafts, peer reviews, portfolio methods and new exam designs.

  3. Canwerely on text originalitycheck systems?Evaluationofthree systems used in highereducation and suggestion of a new methodological testapproachFrey Appelgren Heyman, Mattias Olofsson, Henrik Hansson, Jan Moberg, Ulf Olsson

  4. To whichdegreedoesoriginality check systems detectplagiarism? Whichoriginality check system is best suited for a universitylecturer’sneeds?

  5. The studywasconducted in conjunctionwith the procurementof the new national agreementfor originality check systems at Swedish Universities and Stockholm University'sown tests. • Three systems weresubmittedfor tenders in the national procurement in 2011 and thereforeselected in thisstudy.

  6. GenuineText- Developer: Knownet AB Turnitin- Developer: iParadigms Urkund – Developer: Prio Infocenter AB

  7. The followingaspectswereevaluated: • 1. Time for searching • 2. Identificationofplagiarised text • 3. The design of the originalityreport

  8. The followingaspectswere not evaluated: • Howthe systems handletables, images or source code • Easytouse as standalone • Howto save the reportwithcomments for storing in anothersystem • EasytouseintegratedwithLMS • Howtointegratewith LMS

  9. To assess the effectivenessof the text matching systems toidentifyplagiarisedreferences, we: usedpiecesof text from longer texts wehave chosen. The extractswerecombined in sevendocumentsand thensubmitted.

  10. The selectionofthe test texts (references) wasmadeusingfour different selectionmethods: • Selectionfrom the University librarycollectionsincludingdatabases by librarians • Randomselectionof texts • Selectionofdisciplinespecific texts obtained from different universitydepartments • Selectionof relevant material from websites

  11. FindingsTimerequired for text matchingidentificationresults

  12. FindingsResultofsearch

  13. FindingsResultgraphicevaluation

  14. Conclusion 1Data suggestTurnitin as the best suitedoriginality check system for the needsofuniversitylecturers. This system wassuperior in terms of all three major areas evaluated: a) timefor searching, b) identificationofplagiarised text, and c) the design of the originalityreport.

  15. Conclusion 2The systems canonlyfindsomeof the plagiarised texts thatwere in the test documents. 20 (12%), 63 (38%) and 84 (50%) identifiedplagiarised texts of 167 possiblemeansthatthese systems cannot be consideredreliablesearchengines.If this is a big problem or not depends on whetherlecturersexpectthat the systems willfindmorethanwhattheyareactuallydoing.

  16. Conclusion3Originality check systems limitedabilitytodetectplagiarismmeansthatwecannotwhollyrely on a technical system todetectplagiarism and cheating. Instead, additionalstrategiesagainstplagiarism and cheatingareneeded. Examplesofsuchstrategiesare the useofrecurrent drafts, peerreviews, portfolio methods and new exam designs.

  17. NextstudyOriginality check system as oneofseveral softwares to support the academicwriting process

  18. http://www.su.se/plagieringshandboken

  19. Källa: http://www.su.se/plagieringshandboken

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