Plagiarism detection while assessing online student work is a necessary task for professors, whether it is an on-ground, online, or hybrid course. By using dropboxes for assessing online student work, faculty may integrate programs that compare a student’s submission with Internet content as well as previously submitted work by this and other students. These programs not only detect “cut and pasted” content, but also “recycled” work that has been submitted previously, either by this student in question or some other student.
Plagiarism is a very serious issue that must be addressed while assessing online student work, as well as when assessing work of traditional students in face-to-face courses. Use of dropboxes that require electronic submission of work is key to plagiarism detection while assessing online student work, and the same strategy can also be used with traditional students. By having students submit work electronically, you can make use of programs like Turnitin, Safe Assign, Plagiarism Detector, See Sources, Plagiarism Checker, Viper, and Essay Rater, which detect plagiarism. By requiring electronic submission, you also may simply cut and paste passages into search engines for browsers and library databases to compare similarity. While the “cut and paste” method works as a quick check to detect non-attributed sources, it can be tedious to use and it does not compile a comprehensive report showing percentage of originality; it also does not check university databases for previously submitted work, so “recycled” work is not detected.
Over 70% of all undergraduate students admit to submitting plagiarized work at some point in their degree program. The problem is not limited to undergraduates, however. Sadly, I’ve had graduate and even doctoral students who were expelled from their programs for incidents of plagiarism. Plagiarism is even rampant in professions, as several famous researchers, military leaders, authors, musicians, and politicians have become embroiled in scandals in which their books, speeches, reports, theses, and dissertations were shown to be plagiarized. There are even websites dedicated to humiliating and publicizing incidents of plagiarism by academics and famous persons, such as TheFamousPlagiarists.com or WarOnPlagiarism.org.
As the use of plagiarism detection tools have become more prevalent and well known, students have developed strategies to attempt to “game” these systems. This requires additional work on the part of the professor to stay ahead of the students attempts to submit work that is not theirs. Some students will attempt to use html code to find and replace certain letters (such as a Cyrillic “e” which looks nearly identical to a regular “e”) throughout the document. You can detect and defeat this strategy by simply “revealing codes” in the document or copying/pasting it into an RTF editor to strip the codes, then paste it into a blank document file and resubmit to the plagiarism detection program. Another technique is to submit work as an image-based PDF file, rather than a text-based PDF, MS Word, or text-based PDF. You may either refuse to accept the work in improper format or attempt to type passages into a search box to ascertain originality of the source.
One final strategy that I recommend is checking to see what sort of paper-sharing sites exist for the course that you are teaching. Google your university name and the course identifier and you may discover “shared” answer keys for exams as well as shared papers and discussion question responses on sites like CourseHero.com, StudyBlue.com, Pinterest.com, HomeworkSavior.com, LearningAce.com, Reddit, and Chegg.com. These sites place most of the content behind a firewall or in image form, so that non-subscribers cannot access it – nor can plagiarism detection programs. The most important strategy for plagiarism detection is to make your expectations clear to students and to uniformly enforce stated policies, without exception.