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Thursday, May 24 • 10:40am - 11:30am
Data mining your past essays for new acts of plagiarism

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Recent experience with plagiarism detection services have shown a diminished capacity for finding all sources of cheating. In part, this is due to a number of  "defeat" strategies which are used to render low, often 0%, similiarity ratings. Detection is avoided by paying for a cloaking site to mask the copied material.

Since a significant source of copying of essays appears to be motivated by laziness, keeping a database of past assignments can help pinpoint the source of newly copied material. Over the last two years, I have developed some software which catalogues previous terms assignments. Key information from each paper is collected into a searchable index. Several different matching methods have been tested in order to find material which has been misappropriated from earlier work. This method has resulting in a significant increase in the detection of plagiarism and academic offences. The technology is ever evolving, and the presentation will focus on the types of comparisons, including which methods tend to reveal the most instances of academic offences.
The presentation will be interactive and participants will be encouraged to share their own experiences in tracking down plagiarism. The presentation requires no previous knowledge of plagiarism detection methods.

avatar for Jim Johnston

Jim Johnston

CEO, Paradynamics Testing Solutions
Jim is a Professor in the Lawrence Kinlin School of Business at Fanshawe College. In addition to teaching, Jim is interested in music, flying, politics and astronomy. Jim can be reached at jjohnston@fanshawec.ca or at jim@paradynamics.com.

Thursday May 24, 2018 10:40am - 11:30am EDT

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