Anti-plagiarism strategies: How to manage it with quality in large-scale thesis productions

Authors

  • Ken Larsson
  • Henrik Hansson

DOI:

https://doi.org/10.21913/IJEI.v9i2.893

Abstract

More than 400 students write their bachelor's or master's theses each year at the Department of Computer and Systems Sciences, Stockholm University. In order to support self-driven student thesis work and to reduce the burden on supervisors for feedback on basic skills, an IT support system called SciPro was developed. An important consideration in developing this system was to take actions to reduce plagiarism. Both prevention and detection were accomplished with the following: 1) prevention by policy guidelines, FAQ, face-to-face information, peer-reviews and transparency in the process of recurrent online thesis manuscript hand-ins; and 2) detection by automatic originality check of the final manuscript enabled by integration between SciPro and Turnitin. Explicit rules and regulations as well as frequent education about anti-plagiarism targeting both students and supervisors were also important parts of the prevention strategy. Current results include: 1) substantial improvements in policy development; 2) successful integration of anti-plagiarism software; and 3) recurrent educational activities for students and supervisors have raised the awareness of plagiarism issues at the department. Future development includes three new technical approaches in order to manage sophisticated antiplagiarism controls efficiently, with a quality standard not possible by other means, in large-scale thesis production: 1) automated and integrated (SciPro/Turnitin) recurrent anti-plagiarism controls of submitted thesis manuscripts at various stages in the thesis text production process; 2) automated anti-plagiarism controls of thesis texts submitted in SciPro by comparing consistency in style of writing between different versions of thesis manuscripts handed in by the same student during the process of producing the thesis text; and 3) an automated check of thesis manuscripts submitted to SciPro for identification of images/figures/illustrations/graphs copied from the Internet through integration of an image pattern recognition programme. These measures taken together will significantly increase thesis quality by verifying authenticity to a very high degree and systematising the anti-plagiarism procedures. They will also substantially reduce tedious, boring and immensely time consuming manual work for administrators and supervisors who need to guarantee that theses do not contain plagiarised texts or illustrations.

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Published

2013-11-30

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Articles