When we talk about academic integrity in universities, we often focus on preventing plagiarism and cheating. But what if our very approach to enforcing these standards is unintentionally creating barriers for some of our most vulnerable students?
My recent research explores how current academic integrity policies and practices can negatively affect neurodivergent students—those with conditions like ADHD, dyslexia, Autism, and other learning differences. Our existing systems, structures, and policies can further marginalize students with cognitive differences.
The Problem with One-Size-Fits-All
Neurodivergent students face unique challenges that can be misunderstood or ignored. A dyslexic student who struggles with citation formatting isn’t necessarily being dishonest. They may be dealing with cognitive processing differences that make these tasks genuinely difficult. A student with ADHD who has trouble managing deadlines and tracking sources is not necessarily lazy or unethical. They may be navigating executive function challenges that affect time management and organization. Yet our policies frequently treat these struggles as potential misconduct rather than as differences that deserve support.
Yet our policies frequently treat these struggles as potential misconduct rather than as differences that deserve support.
The Technology Paradox for Neurodivergent Students
Technology presents a particularly thorny paradox. On one hand, AI tools such as ChatGPT and text-to-speech software can be academic lifelines for neurodivergent students, helping them organize thoughts, overcome writer’s block, and express ideas more clearly. These tools can genuinely level the playing field.
On the other hand, the same technologies designed to catch cheating—especially AI detection software—appear to disproportionately flag neurodivergent students’ work. Autistic students or those with ADHD may be at higher risk of false positives from these detection tools, potentially facing misconduct accusations even when they have done their own work. This creates an impossible situation: the tools that help are the same ones that might get students in trouble.
Moving Toward Epistemic Plurality
So what’s the solution? Epistemic plurality, or recognizing that there are multiple valid ways of knowing and expressing knowledge. Rather than demanding everyone demonstrate learning in the exact same way, we should design assessments that allow for different cognitive styles and approaches.
This means:
Rethinking assessment design to offer multiple ways for students to demonstrate knowledge
Moving away from surveillance technologies like remote proctoring that create anxiety and accessibility barriers
Building trust rather than suspicion into our academic cultures
Designing universally, so accessibility is built in from the start rather than added as an afterthought
What This Means for the Future
In the postplagiarism era, where AI and technology are seamlessly integrated into education, we move beyond viewing academic integrity purely as rule-compliance. Instead, we focus on authentic and meaningful learning and ethical engagement with knowledge.
This does not mean abandoning standards. It means recognizing that diverse minds may meet those standards through different pathways. A student who uses AI to help structure an essay outline isn’t necessarily cheating. They may be using assistive technology in much the same way another student might use spell-check or a calculator.
Call to Action
My review of existing research showed something troubling: we have remarkably little data about how neurodivergent students experience academic integrity policies. The studies that exist are small, limited to English-speaking countries, and often overlook the voices of neurodivergent individuals themselves.
We need larger-scale research, global perspectives, and most importantly, we need neurodivergent students to be co-researchers and co-authors in work about them. “Nothing about us without us” is not just a slogan, but a call to action for creating inclusive academic environments.
Key Messages
Academic integrity should support learning, not create additional barriers for students who already face challenges. By reimagining our approaches through a lens of neurodiversity and inclusion, we can create educational environments where all students can thrive while maintaining academic standards.
Academic integrity includes and extends beyond student conduct; it means that everyone in the learning system acts with integrity to support student learning. Ultimately, there can be no integrity without equity.
Read the whole article here: Eaton, S. E. (2025). Neurodiversity and academic integrity: Toward epistemic plurality in a postplagiarism era. Teaching in Higher Education. https://doi.org/10.1080/13562517.2025.2583456
Sarah Elaine Eaton, PhD, is a Professor and Research Chair in the Werklund School of Education at the University of Calgary, Canada. Opinions are my own and do not represent those of my employer.
I am always excited to hear about new work that showcases postplagiarism. Imagine my dismay when I read a new article, published in an (allegedly) peer-reviewed journal, that foregrounded the tenets of postplagiarism, but was rife with fabricated sources, including references to work attributed to me, but that I never wrote.
I have opted not to ‘name and shame’ the authors. Anyone who is curious enough need only do an Internet search to find the offending article and those who wrote it.
Instead, I prefer to take a more productive approach. Here I provide a brief timeline of the development of postplagiarism as both a framework and a theory:
The book begins with a history of plagiarism. Then, I discuss plagiarism in modern times. In the concluding chapter I contemplate the future of plagiarism. Building on the scholarship of Rebecca Moore Howard, I proposed that the age of generative artificial intelligence (Gen AI) could launch us into a post-plagiarism era in which human-AI hybrid writing becomes the norm.
2024: Dr. Rahul Kumar (Brock University, Canada) and I launch our website, http://www.postplagiarism.com. We provide open access resources free of charge. Thanks to the generosity of colleagues and friends who speak multipole language, we offer translations of the postplagiarism infographic in multiple languages.
Also, in this year, Rahul Kumar begins a study to test the tenets of postplagiarism.
If you see references to our work on postplagiairsm as we have conceptualized it that pre-date our work, dig deeper to see if the work is real. There are now fabricated sources published on the Internet that do not — and never did — exist.
Imitation is flattery, as the saying goes. This quip has been used as a way to dismiss plagiarism concerns, as students learn to imitate great writers by quoting them without attribution. The saying digs deep into cultural and historical understandings that are beyond the scope of a blog post. What I can say is that in the postplagiarism era, fabrication is not the new flattery.
One of the tenets of postplagiarism is that humans can relinquish control over what they write to an AI, but we do not relinquish responsibility. The irony of seeing fabricated references about postplagiarism in fabricated is as absurd as it is puzzling. There is no need to fabricate references to post plagiarism, especially since we provide numerous free and open access to resources and research on the topic.
Sarah Elaine Eaton, PhD, is a Professor and Research Chair in the Werklund School of Education at the University of Calgary, Canada. Opinions are my own and do not represent those of my employer.
The first time I heard about decriminalizing the language and processes we use to address cases of plagiarism and other forms of academic misconduct; I was riveted. It was at an academic integrity conference in Richmond, Virginia and the lead presenter was Dr. James Earl Orr, who presented together with students on how a developmental and supportive approach to academic misconduct case management can help lead students towards academic success while still holding them responsible for their behaviour. James Earl Orr, writing together with Karita Orr, published an excellent article on using restorative practices to resolve academic integrity violations.
When I was writing the University of Calgary’s academic integrity Handbook for Academic Staff and Teaching Assistants, I took the opportunity to apply what I had learned from listening to Dr. Orr at conferences and reading his work by including a section on how to decriminalize the language we use to talk about academic misconduct.
Academic integrity violations are rarely criminal in nature and yet, much of the language we use when addressing plagiarism and academic cheating is legalistic, setting the stage for criminalizing student behaviour. One step towards taking a more learner-centred approach to misconduct is to decriminalize the language we use to talk about breaches of academic integrity.
Front cover of the Student Academic Integrity Faculty Handbook, published by the Taylor Institute for Teaching and Learning at the University of Calgary
“We know that words matter and the language we use is important. A full list of terms related to academic misconduct is available in our policy. It should be noted that the terms “academic integrity” and “academic misconduct” are not interchangeable.
Academic integrity is about acting ethically in teaching, learning and research contexts. We do not report, investigate or manage cases of academic integrity. We report, investigate and manage cases of academic misconduct.
Academic misconduct is what happens when individuals do not act with integrity. This is currently the language used in our policy and procedures. When speaking and writing about academic misconduct, we can use the terms “breaches of integrity or “violations of integrity” as synonyms for academic misconduct.
At the University of Calgary we take a proactive approach to academic integrity, including in the language we use and in keeping the focus on teaching, learning and fairness to students. In our conversations with students and others, it can be helpful to use the language of integrity that focuses on education and support” (Eaton, 2022, p. 13).
See the table below, which is also an expert from our handbook (with a few minor updates):
The language of academic integrity
Preferred language
Language to avoid
Explanation
Hold responsible
Guilt Guilty
The words “guilt” and “guilty” do not appear anywhere in our polices or procedures. We do not find students guilty of academic misconduct, but instead we hold them responsible for their behaviours.
Sanctions Consequence Outcome
Punish Punishment
When disciplinary actions are taken in response to academic misconduct, we do not use the terms “punish” or “punishment” in our institutional documents. We opt instead for “sanctions”, “discipline,” “consequences” or “outcome” which can include educational responses depending on the misconduct.
Hearing
Trial
The University of Calgary does not conduct trials related to academic misconduct. In other countries, various forms of academic misconduct can be considered an offense under the criminal code and students may be required to attend a criminal trial. That is not the case at the University of Calgary or anywhere in Canada. In the case of an appeal, a hearing might occur. In rare cases, an appeal case might escalate to an externally reviewed case in court, but these proceedings are not administered by the university itself.
When I talk about taking a postplagiarism approach to academic integrity I am talking about disrupting historically adversarial and antagonistic approaches to misconduct that pit students against their teachers. It is time to move past crime-and-punishment approaches to student misconduct where students are the villains and teachers are the heroes. When we talk about postplagiarism we talk about social justice and student success as being intertwined, and we focus on students as stewards of the future, who will be best equipped for an increasingly complex world when they understand the importance of ethical decision-making, both in theory and in practice.
Postplagiarism does not mean anything goes, and nor does it mean that we turn a blind eye to misconduct. Postplagiarism is about finding socially just ways to address misconduct include relationally, restoration, and the preservation of dignity and human rights. When we decriminalize language related to student misconduct, we are taking a step towards dignity and student success.
Our University of Calgary’s academic integrity Handbook for Academic Staff and Teaching Assistants is an open access handbook with a Creative Commons license. This means you can share and adapt the material, providing the original work is properly attributed.
If this is helpful to you, please share this with others.
Eaton, S. E. (2023). Postplagiarism: Transdisciplinary ethics and integrity in the age of artificial intelligence and neurotechnology. International Journal for Educational Integrity, 19(1), 1–10. https://doi.org/10.1007/s40979-023-00144-1
Eaton, S. E. (2025). Global Trends in Education: Artificial Intelligence, Postplagiarism, and Future-focused Learning for 2025 and Beyond – 2024–2025 Werklund Distinguished Research Lecture. International Journal for Educational Integrity, 21(1), 12. https://doi.org/10.1007/s40979-025-00187-6
Orr, J. E., & Hall, J. (2018). Student-led case adjudication: Promoting student learning through peer-to-peer engagement. 25th Annual International Center for Academic Integrity (ICAI) Conference, Richmond, VA.
Orr, J. E., & Orr, K. (2023). Restoring honor and integrity through integrating restorative practices in academic integrity with student leaders. Journal of Academic Ethics, 21, 55–70. https://doi.org/10.1007/s10805-021-09437-x
Orr, J. E., & Orren, S. (2018, March 4). The Development & Implementation of a Campus Academic Integrity Education Program. 25th Annual International Center for Academic Integrity (ICAI) Conference, Richmond, VA.
Sarah Elaine Eaton, PhD, is a Professor and Research Chair in the Werklund School of Education at the University of Calgary, Canada. Opinions are my own and do not represent those of my employer.
Chapter 10 explores the theoretical, policy, and practical aspects of navigating pedagogical ethics in learning environments augmented by generative artificial intelligence (GenAI). The chapter considers the role of higher education and the need to reconceptualize academic cheating in a post-plagiarism era. It discusses the role of learner agency, accountability, and responsibility within the context of learning and academic integrity. The chapter offers informed guidance for educators to incorporate GenAI in meaningful ways into teaching, learning, and assessment.
Our chapter is open access and free to read online and to download. We are really excited to continue the conversations happening about postplagiairsm and how we can can navigate teaching, learning, and assessment ethically in the age of generative AI.
Sarah Elaine Eaton, PhD, is a Professor and Research Chair in the Werklund School of Education at the University of Calgary, Canada. Opinions are my own and do not represent those of my employer.
In a recent talk I did at the University of Toronto Mississauga, I was chatting with a couple of folks afterwards and they asked if one specific slide was available as an infographic. It wasn’t and I promised to follow up. (This blog post is for you Amanda and Victoria!)
Artificial intelligence tools can generate human-like text and knowledge creation has become increasingly collaborative, questions arise about traditional academic practices. Although many conventions are being reimagined, citing, referencing, and attribution remain important. Attribution — acknowledging those who have shaped our thinking—transcends the mechanical act of citing sources according to prescribed formats. It represents an ethical commitment to intellectual honesty and respect (Eaton, 2023).
Attribution is a cornerstone of the postplagiarism framework. In the postplagiarism era, where the boundaries between human and AI-generated content blur and traditional definitions of authorship are challenged, the practice of acknowledging our intellectual influences becomes more vital, not less (Kumar, 2025). Attribution serves multiple purposes: it honors those who contributed to knowledge development, establishes credibility for the writer, and allows readers to explore foundational ideas more deeply.
Many educators and students mistakenly equate attribution with the technical minutiae of citation styles. I am talking here about the precise placement of commas, periods, and parentheses. While these conventions serve practical purposes in academic writing, they represent only the surface of what attribution entails (Gladue & Poitras Pratt, 2024). At its core, attribution demands that we answer questions such as: How do I know what I know? Who were my teachers? Whose ideas have influenced my thinking?
In this post (a re-blog from the postplagiarism site) I explore attribution as an enduring ethical principle within the postplagiarism framework. We’ll distinguish between citation as mechanical practice and attribution as intellectual honesty, examine how attribution practices might evolve with technology, and consider how we might teach attribution as a value rather than merely a skill (Eaton, 2024). Throughout, we’ll keep returning to a central idea: even as definitions of plagiarism transform, the need to recognize and pay respect to those from whom we have learned remains constant.
Attribution vs. Citation: Understanding the Differences
Understanding the distinction between attribution and referencing is crucial in our discussion of academic integrity in a postplagiarism era. The terms ‘referencing’ and ‘attribution’ are often used interchangeably, but they represent fundamentally different approaches to giving credit where it is due. In the table below, I present an overview of some of the differences.
Table 1
Attribution versus Referencing
Citing and Referencing
First, let’s talk about citing and referencing. Citing is often referred to in-text citation. In APA format, for example, we cite sources in the main body of the text as we write. Then, we produce a list of references, usually with the heading “References” at the end of the paper. (I have modelled this practice throughout). If we follow APA, the sources cited in the body of the text should exactly match the sources in the reference list at the end, and vice versa. So, citing and referencing go hand-in-hand. For the purposes of this post, I’ll use the term ‘referencing’ collectively to refer to both citing and referencing, given that the two are intertwined.
A foundational question about referencing is: How can I learn and demonstrate the technical norms of a prescribed style manual?
Let me give you an example of what I mean. I did my undergraduate and master’s degrees in literature. We used the Modern Language Association (MLA) style guide. When I moved over to Education to undertake my PhD, I had to learn a completely different style, the one prescribed by the American Psychological Association (APA), as that is the style used across much of the social sciences. I often describe having to shift from learning MLA style to APA style as intellectual trauma. I had spent years meticulously learning to be rule-compliant to MLA style. I knew the details of MLA style inside and out. Having to learn APA style meant unlearning everything I’d spent years learning about MLA style. My PhD supervisor marked up drafts of my work with a red pen, noting APA errors everywhere.
I bought the APA style guide (we were using the 5th edition back then) and set out to memorize every detail to ensure that I knew the rules. Citing and referencing are taught and evaluated using style guides, checklists, and technical rubrics to evaluate how well someone has followed the rules. Citing and referencing are essentially about rule compliance.
Attribution
Attribution goes beyond the technical aspects of rule compliance. When we give attribution, we dig deeper into questions about our intellectual lineage. We ask: How do I know what I know? Who did I learn from? Who influenced the those from whom I have learned?
Attribution requires meta-cognitive awareness and evaluative judgement. If you are unfamiliar with these concepts, I recommend the work of Bearman and Luckin (2020), Fischer et al. (2024), and Tai et al. (2018). Collectively, they explain evaluative judgement and meta-cognitive awareness better than I ever could.
(If you’re paying attention, you’ll see that I just combined citing with attribution there… I provided the sources as per the citing rules of APA, and I also talked about how I learned about deeper concepts from some terrific folks who have done deep work on the topic. See, you can combine citing and referencing with attribution. It’s not all or nothing.)
We teach attribution through a shared collective understanding, by establishing communal expectations and through (often informal) relational coaching.
In everyday conversations, we often reference where we learned ideas. We say, “As my grandmother always said…” or “I read in an article that…” These informal attribution practices demonstrate how instinctively we connect ideas to their sources. Citing and referencing formalizes socialized practices that have extended across various cultures for centuries.
When we give attribution, we show gratitude for the conversations, texts, and teachings that have formed our understanding. This perspective shifts attribution from a defensive practice (avoiding plagiarism accusations) to an affirmative one (acknowledging the intellectual debt we owe to others who have generously shared their knowledge with us).
Acknowledging Others’ Work in the Age of GenAI
Generative AI tools have disrupted our traditional understandings of authorship and attribution. These technologies create new questions about intellectual ownership and acknowledgment practices that our citing and referencing systems weren’t designed to address. GenAI models produce outputs based on massive training datasets containing human-created works. When a student uses ChatGPT to draft an essay, the resulting text represents a complex blend of sources that even the AI developers cannot fully trace. This opacity challenges our ability to attribute ideas to their original creators (Kumar, 2025).
The collaborative nature of AI-assisted writing further blurs authorship boundaries. Who deserves credit when a human prompts, edits, and refines AI-generated text? The distinction between tool and co-creator is difficult to establish. This is another tenet in the postplagiarism framework.
In work led by my colleague, Dr. Soroush Sabbagan, we found graduate students wanted agency in how they integrate AI tools while maintaining academic integrity (Sabbaghan and Eaton (2025). The graduate students who participated in our study, “Participants also emphasized the importance of combining their own expertise and judgment with the AI’s suggestions to create truly original research.” (Sabbaghan & Eaton, 2025, p. 18).
The postplagiarism framework offers helpful guidance by distinguishing between control and responsibility. Although students may share control with AI tools, they retain full responsibility for the integrity of their work, including proper attribution of all sources, both human and machine. Ultimately, the goal isn’t to prevent AI use but to cultivate ethical practices for learning, working, and living.
As Corbin et al (2025) have noted, AI presents wicked problems when it comes to assessment. I would extend their idea further by saying that AI presents wicked problems for plagiarism in general. There are no absolute definitions of plagiarism, but if we think about citing, referencing, and giving attribution as ways of preventing or mitigating plagiarism, then AI has certainly complicated everything. These are problems that we do not have all the answers to, but disentangling the difference between rule-based referencing and attribution as a social practice of paying our respects to those from whom we have learned, might be one step forward as we enter into a postplagiarism age.
The ideas I’ve shared here are not intended to be exhaustive, but rather to help folks make sense of some key differences between referencing and giving attribution and to recognize that citing and referencing are deeply connected to rule compliance and technical rules, whereas giving attribution can at times be imprecise, but may in fact be more deeply-rooted in a desire to give respect where it is due.
As I have tried to model above, it does not have to be all or nothing. Referencing can exist in the absence of any desire to respect others for the work they have created and attribution can be given orally or in any variety of ways that may not comply with a technical style guide. When we are working with students, it can be helpful to unpack the differences and talk about why both are need in academic environments.
There is more to say on this topic, but I’ll wrap up here for now. Thanks again to Amanda and Victoria, who nudged me to write down and share ideas that I have been talking about for a few years now.
References
Bearman, M., & Luckin, R. (2020). Preparing university assessment for a world with AI: Tasks for human intelligence. In M. Bearman, P. Dawson, R. Ajjawi, J. Tai, & D. Boud (Eds.), Re-imagining University Assessment in a Digital World (pp. 49–63). Springer International Publishing. https://doi.org/10.1007/978-3-030-41956-1_5
Corbin, T., Bearman, M., Boud, D., & Dawson, P. (2025). The wicked problem of AI and assessment. Assessment & Evaluation in Higher Education, 1–17. https://doi.org/10.1080/02602938.2025.2553340
Eaton, S. E. (2023). Postplagiarism: Transdisciplinary ethics and integrity in the age of artificial intelligence and neurotechnology. International Journal for Educational Integrity, 19(1), 1–10. https://doi.org/10.1007/s40979-023-00144-1
Eaton, S. E. (2024). Decolonizing academic integrity: Knowledge caretaking as ethical practice. Assessment & Evaluation in Higher Education, 49(7), 962-977. https://doi.org/10.1080/02602938.2024.2312918
Fischer, J., Bearman, M., Boud, D., & Tai, J. (2024). How does assessment drive learning? A focus on students’ development of evaluative judgement. Assessment & Evaluation in Higher Education, 49(2), 233–245. https://doi.org/10.1080/02602938.2023.2206986
Kumar, R. (2025). Understanding PSE students’ reactions to the postplagiarism concept: a quantitative analysis. International Journal for Educational Integrity, 21(1), 9. https://doi.org/10.1007/s40979-025-00182-x
Sabbaghan, S., & Eaton, S. E. (2025). Navigating the ethical frontier: Graduate students’ experiences with generative AI-mediated scholarship. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00454-6
Tai, J., Ajjawi, R., Boud, D., Dawson, P., & Panadero, E. (2018). Developing evaluative judgement: enabling students to make decisions about the quality of work. Higher Education, 76(3), 467–481. https://doi.org/10.1007/s10734-017-0220-3
Note: This is a re-blog. See the original post here:
Posted by Sarah Elaine Eaton, Ph.D. 
Learning, Teaching and Leadership 
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