An examination of the efficacy of the plagiarism detection software program Turnitin
| dc.contributor.advisor | Li, Jia | |
| dc.contributor.advisor | Owen, Michael | |
| dc.contributor.author | Walchuk, Kevin | |
| dc.date.accessioned | 2016-12-22T16:24:33Z | |
| dc.date.accessioned | 2022-03-29T20:00:16Z | |
| dc.date.available | 2016-12-22T16:24:33Z | |
| dc.date.available | 2022-03-29T20:00:16Z | |
| dc.date.issued | 2016 | |
| dc.degree.discipline | Education and Digital Technologies | en |
| dc.degree.level | Master of Education (MEd) | en |
| dc.description.abstract | This research examined the effectiveness of the plagiarism detection program Turnitin in identifying clearly copied, verbatim textual material from peer reviewed and published academic journal articles. It also considered both the effectiveness and appropriateness of tasking plagiarism detection programs, such as Turnitin, with the responsibility of identifying semantic plagiarism, defined for this purpose as the plagiarism of the meaning of text. | en |
| dc.description.sponsorship | University of Ontario Institute of Technology | en |
| dc.identifier.uri | https://hdl.handle.net/10155/717 | |
| dc.language.iso | en | en |
| dc.subject | Plagiarism | en |
| dc.subject | Semantic plagiarism | en |
| dc.subject | Plagiarism detection | en |
| dc.subject | Turnitin | en |
| dc.subject | Cheating | en |
| dc.title | An examination of the efficacy of the plagiarism detection software program Turnitin | en |
| dc.type | Master's Project | en |