A recent study highlights that almost half of students in Europe are concerned about plagiarism detection software, prompting them to engage in counterproductive academic practices. The researchers suggest clearer guidelines and better educational practices to mitigate these issues.
Nearly half of high school and university students in seven European countries are troubled by the use of plagiarism detection software in education, according to a recent study published in the International Journal for Educational Integrity. The findings suggest that these concerns may lead to counterproductive academic behaviors and misdirected learning.
The research, led by the University of Copenhagen’s Department of Food and Resource Economics, aimed to understand students’ anxiety regarding text-matching software (TMS) in Switzerland, Denmark, Hungary, Ireland, Lithuania, Portugal and Slovenia.
“It’s paradoxical that a technology intended to ensure academic integrity is causing unnecessary worries among students. Our research clearly shows that uncertainty about how the software operates, how it’s used and what constitutes plagiarism leads to worries and counterproductive writing practices,” lead author Mads Goddiksen, a postdoc researcher in the University of Copenhagen’s Department of Food and Resource Economics, said in a news release.
In the study, 47% of high school students and 55% of undergraduate participants expressed worries about being monitored by plagiarism detection tools. Their fears extend beyond the possibility of being caught cheating.
The students revealed that these concerns affect their academic habits, such as refusing to reuse sources from previous work or excessively paraphrasing content to evade detection by the software. Some even resort to extreme measures like including up to 90 footnotes in a 12-page paper.
“The biggest issue isn’t the worry itself, but that students lose focus on writing well and ethically. Instead, it becomes about avoiding the software flagging something as problematic. This affects the quality of both their assignments and overall education,” added Goddiksen.
The study’s findings point to a significant misunderstanding about how plagiarism detection software works. Many students incorrectly believe that the software independently determines what counts as plagiarism, leading them to alter their writing styles unnecessarily.
“There’s nothing inherently wrong with paraphrasing or reproducing content from other sources in an assignment – this is largely what academic writing involves, as long as it’s done transparently. However, today, such practices may pop up in plagiarism checks because the software identifies similarities in phrases and formulations. This makes students nervous and renders the software ineffective if used on its own,” Goddiksen added.
To combat these issues, the researchers argue that educational institutions need to provide clearer guidelines and consistent practices regarding plagiarism detection software.
“The technology can be a helpful tool for identifying potential issues, but it requires institutions to communicate clearly about it and ensure that instructors and students understand the software’s limitations,” Goddiksen added.
The study suggests more instruction on academic writing and citation practices, as well as clarifications from educators on what constitutes plagiarism in specific assignments.
“We propose a combination of instruction and clearer procedures for how to use the software. Educators need to step in and explain where the boundaries for plagiarism are for specific assignments and how they use the software. This won’t just alleviate concerns but serve to ensure that the technology supports learning rather than hindering it,” co-author Mikkel Willum Johansen, an associate professor in the Department of Science Education at the University of Copenhagen, said in the news release.
The research, based on 3,424 survey responses and 36 interviews, also highlights emerging challenges related to AI-generated text detection tools. These tools can suggest whether content was produced by AI, but their reliability is questionable.
“The problem is that these systems can only suggest whether something appears to be generated by AI but they cannot say so with certainty,” added Johansen. “Unlike plagiarism detection software, they lack an original text for comparison. For this reason, AI-detection systems are highly unreliable. This underscores the importance of institutions having clear procedures and a consensus on how to use the technology, so that we avoid penalizing students unfairly.”
The study underscores the need for balanced and informed use of technology in education to ensure it enhances, rather than hinders, student learning.