While the misuse of generative AI is certainly a growing concern for institutional integrity, traditional forms of academic misconduct, such as plagiarism, remain prevalent. The increasing sophistication of technology has changed the ‘usual forms of plagiarism’ we once knew, making it easier than ever for students to communicate in ways that challenge the integrity of assessments.
Unlike plagiarism, which involves directly copying someone else’s work, collusion happens when students work together in ways that undermine the principles of individual assessment, and the qualifications being awarded to them. This can include submitting identical assignments or sharing notes intended for individual work.
Institutions need a comprehensive approach that blends technology, policy, and educator intervention to highlight and prevent collusion effectively. We’ll use this blog post to explore educator strategies for prevention, tools for detection, and what collusion might look like in different scenarios.
What is student collusion and why does it matter?
Collusion differs from legitimate collaboration. While collaborative learning is encouraged in many academic settings, collusion crosses the line when it leads to unfair academic advantage. Examples include students submitting nearly identical essays when independent work was required, or working together to complete online exams designed to be taken alone.
Unchecked collusion has lasting consequences for both the student and the wider institution. For students, this type of academic dishonesty can lead to academic penalties, loss of learning opportunities, and even disciplinary actions that could impact future careers. For institutions, widespread collusion damages credibility, erodes trust in assessment processes, and diminishes the value of the qualifications granted. Recognizing these risks, institutions are taking steps to address collusion; for example, the International Baccalaureate plans to make unannounced visits to institutions to curb time-zone cheating.
Collusion can lead to an inequitable, unbalanced learning environment, whereby many students are working according to the policies laid out by the institution, while others are leveraging dishonest practices for gain. By proactively addressing this issue, institutions can uphold academic integrity and ensure fairness for all students.
Can students unintentionally engage in collusion?
Institutions are expected to take academic integrity seriously for the sake of their reputation and the protection of other students, but they must also consider the ethical dimensions of identifying collusion.
The lines are becoming blurred. Generative AI is becoming a constant figure in the education space, and online collaboration tools like WhatsApp, TikTok, and DropBox are on the rise. So how can we define what is acceptable group work and what is misconduct? Some students may engage in collusion without realizing they are violating academic policies, especially if expectations are not clearly outlined.
It’s important to consider intentionality when determining next steps. Was the institutional policy on collusion transparent enough? Did the educator make it clear how students should work together and how they should not? Clearly defining acceptable collaboration in course policies, reinforcing academic integrity in student orientation programs, and providing ongoing guidance can prevent unintentional collusion.
A study at an Australian university explored the fine line between collusion and collaboration, finding that collusion is a complex and unclear concept, with staff and students unsure about what constitutes acceptable collaboration. This confusion often led students to develop negative attitudes toward collaborative tasks (Sutherland, 2013).
A fair and balanced approach will build a culture of trust rather than fear between students and educators, ensuring that academic integrity remains a shared responsibility.
What strategies can educators use to identify student collusion?
Technology isn’t the only solution for student collusion. Faculty members are often the first to notice irregularities in student submissions, and their insights are invaluable in addressing the issue.
Monitor student work patterns
Educators are observant—enough to be able to recognize collusion by paying close attention to submission patterns. If multiple students submit near-identical work or exhibit writing styles that are inconsistent with their past submissions, this could signal collusion. Regular formative assessments and one-on-one discussions with students can help uncover inconsistencies and ensure accountability.
Encourage transparent group work
When assigning group projects, educators should establish clear structures for individual contributions. Tools like peer evaluation forms or contribution logs can help highlight where discrepancies may exist between students’ contributions, making it easier to identify potential collusion.
Conduct follow-up discussions
Ask students to explain their thought process and decision-making behind their work. Post-assessment debriefs can be a valuable strategy for identifying collusion. Sudden inconsistencies in explanations may indicate reliance on unauthorized assistance.
How can institutions adopt technology to highlight student collusion?
Educators can access a whole host of technologies to assist them with easily identifying collusion within their cohort. This includes similarity-checking software to highlight overlapping submissions and authorship analysis tools to track sudden shifts in writing style.
Even learning management systems (LMS) data can analyze submission trends via timestamps and IP addresses, as well as student performance data to identify outliers or concerning patterns indicative of more widespread collusion.
Nicholls and Lewis (2017) note, “Sometimes roommates using the same Wi-Fi router take the class together so this isn’t necessarily a sign of collusion. However, if two or more students normally log in with different IP addresses, but suddenly are using the same IP address and starting exams at nearly the same time, it suggests [unauthorized] collaboration.”
How can Turnitin help educators spot student collusion?
Turnitin’s suite of academic integrity tools offers valuable insights into potential collusion cases, too. The Turnitin Similarity Report highlights patterns that may indicate unauthorized collaboration between students.
Turnitin automatically excludes papers submitted by the same student to the same assignment, preventing previous drafts from skewing similarity scores.
If you’re a Turnitin instructor seeking guidance on checking for student collusion, the next part of this blog post will guide you through the process of configuring the right Similarity Report settings to quickly identify submission irregularities:
- Search options: The standard and institutional paper repository must be selected to compare student work against previous submissions. If "no repository" is selected, a collusion check cannot take place.
- Paper storage settings: Storing student papers in the standard or institutional repository allows future comparisons to detect collusion.
- Excluding small sources: If instructors choose to exclude a large percentage or number of words from similarity reports, they may miss cases of collusion. Turnitin can exclude small sources starting at nine words, allowing meaningful similarities to be flagged.
- User enrollment: Make sure your students submit to Turnitin with the same user profile (e.g. not as a non-enrolled user) to avoid being classified as separate students in Turnitin. This can cause work to be flagged as self-plagiarism rather than collusion.
What are some practical examples of student collusion?
Identifying collusion without technology requires a keen eye for unusual similarities in student work. Some common scenarios include:
Cross-course or inter-institutional collusion
Students in different sections, different courses, or even different institutions sharing answers and submitting matching content. This can happen in several ways:
- Maria took the course last semester and shares her completed assignments with Liam, who is taking the same course this term. Liam submits Maria’s work as his own.
- Two students in different sections of the same course receive identical assignments. They collaborate on their responses and submit near-identical work, despite being graded separately.
- A group of students from different institutions takes an online exam with similar questions. They create a shared document with answers and use it to complete their assessments.
Overlap in group work or individual submissions
In group assignments, students may produce work collaboratively but then submit it as individual work, crossing the line into collusion if the content is shared or reused inappropriately. This blurs the line between acceptable collaboration and collusion and can manifest itself in the following ways:
- A group of students works together on a project but later submits highly similar individual reports, despite instructions to create their reports individually.
- Two students complete a lab experiment together but submit nearly identical reports with minimal individual analysis.
- A student shares their partially completed essay with a peer for “feedback,” but the peer incorporates large sections of the original text into their own submission.
Other types of collusion include the use of shared resources without attribution, such as sharing notes, drafts, or research material that isn’t intended for group use. In addition to this, students may collude via peer reviews either by giving inflated or false feedback to help a peer succeed without doing the required work.
Institutional approaches to address collusion
Students need clear guidelines on what constitutes acceptable collaboration. Comprehensive academic integrity policies which filter down to course syllabi should include explicit definitions and examples of student collusion, reinforcing the importance of individual work.
Classroom discussions can further clarify these policies, giving students opportunities to ask questions and understand expectations. Institutions should provide clear definitions of collusion, reinforce policies in student orientations, and ensure faculty receive training on academic integrity.
Overview: Taking proactive steps to maintain academic integrity
Collusion poses a significant challenge to academic integrity, but with the right strategies, institutions can effectively address and prevent it. A combination of educator vigilance, clear policies, and technological tools can help highlight irregular patterns while maintaining a level of fairness for students.
By encouraging open conversations about academic integrity, rewarding original work, and reinforcing the importance of ethical academic behavior, this can reduce the likelihood of collusion occurring in the first place.
As Smith (2025) rightly points out, “No matter the underlying cause, whenever a student’s academic integrity is in question, always begin by assuming best intentions. While reasons are potentially many, focusing on how to address the underlying issue(s) is more important because this understanding tends to lead to more substantive results.”
Equip your institution with the right tools and strategies to tackle academic collusion head-on.