Call for Proposals: Special issue on Postplagiarism and Generativism: Human-AI Hybrid Approaches to Ethical Teaching, Learning, and Assessment

March 17, 2026

Special Issue Call for Papers

Postplagiarism and Generativism: Human-AI Hybrid Approaches to Ethical Teaching, Learning, and Assessment

For publication in the Journal of University Teaching and Learning Practice

Guest editors

Background

Every new technology brings with it societal and moral panic (Orben, 2020). When the Internet first became popular, concerns about plagiarism increased. Even though there is scant empirical evidence that the Internet was actually responsible for increases in rates of plagiarism, the perception that new technology resulted in more academic cheating persisted (Panning Davies & Howard, 2016).

Some plagiarism scholars have been emphatic that the majority of student plagiarism cases are not an intent to deceive, but rather a lack of academic literacy and poor academic practice, and have even advocated for disposing of plagiarism in academic misconduct policies in favour of increased student support (Howard, 1992; Jamieson & Howard, 2021). The idea that plagiarism could be decoupled from academic misconduct seems somewhat unlikely, but by the 2020s it was obvious to some that generative artificial intelligence (GenAI) would have an impact on writing, and by extension, on plagiarism (Mindzak & Eaton, 2021).

In response to these technological shifts, various frameworks have emerged to conceptualize academic integrity in the GenAI era. The postplagiarism framework, first introduced by Eaton (2021, 2023) and since discussed by scholars worldwide (Bali, 2023; Bagenal, 2024; Kenny, 2024), offers one approach. Other perspectives, such as Generativism (Pratschke, 2023), AI Literacy frameworks (Ng et al., 2021; Pretorius & Cahusac de Caux, 2024), and UNESCO’s Guidance for Generative AI in Education (2023), provide complementary or alternative viewpoints on similar phenomena.

Postplagiarism is based on six tenets (Eaton, 2023): (1) human-AI hybrid writing will become the norm; (2) creativity can be enhanced by AI; (3) AI can help to overcome language barriers; (4) we can outsource control of our writing to AI, but we do not outsource responsibility for what is written; (5) attribution remains important; and (6) historical definitions of plagiarism may require rethinking.

Empirical testing of these and related frameworks has shown differing levels of acceptance and application across educational contexts (Kumar, 2025).

Equity, Diversity, Inclusion, and Accessibility in a Postplagiarism Age

As higher education institutions aim to promote social justice through equity, diversity, and inclusion (EDI), GenAI holds the potential to either break down or reinforce barriers related to linguistic, cultural, socioeconomic, and ability differences requires critical examination.

Assessment practices should be designed proactively to enable all students to demonstrate their learning without being unfairly disadvantaged by their personal characteristics or circumstances (Tai et al., 2022). Similarly, McDermott (2024) highlights the importance of considering accessibility, equity, and inclusion in assessment and academic integrity.

GenAI offers opportunities to enhance equity by providing personalized support, overcoming language barriers, and assisting learners with diverse needs. However, without careful implementation, it may exacerbate existing inequities through unequal access to technology, algorithmic biases, or assessment designs that privilege certain ways of knowing and communicating.

In this special edition, we propose to examine the broader question: “How are pedagogies, learning, and teaching approaches evolving in response to GenAI, and what frameworks best support ethical academic practice in a postplagiarism landscape?”

We invite researchers and practitioners to submit their original research papers exploring the transformation of teaching, learning, and assessment in a GenAI age. We welcome both theoretical and empirical contributions, including positions that may present contrasting viewpoints. Potential topics of interest include, but are not limited to:

  • New developments in postplagiarism, generativism, and other emerging frameworks for understanding academic integrity in the GenAI era
  • Empirical studies testing these frameworks in different contexts and disciplines
  • The use of these frameworks to design or reform academic misconduct policies and procedures
  • The relationship between GenAI, academic literacies, and related competencies (e.g., digital literacy, information literacy)
  • Pedagogical approaches that embrace GenAI while maintaining academic integrity
  • Case studies of successful integration of GenAI into teaching, learning, and assessment
  • Critical perspectives on the limitations or challenges of current approaches to GenAI in education
  • Position papers presenting new or alternative frameworks for understanding GenAI in teaching and learning

We particularly encourage submissions that engage in dialogue with existing frameworks, offering either supportive evidence or critical alternatives. Our goal is to foster a robust debate about the future of teaching and learning in a GenAI (and even a post-GenAI) world.

We welcome submissions from both established researchers and early-career scholars from diverse academic and cultural backgrounds. All submissions will be peer-reviewed by an international panel of experts. Accepted papers will be published in a special issue of the Journal of University Teaching and Learning Practice.

Types of publications accepted into this Special Issue

The types of publications that are eligible for acceptance into this Special Issue include:

  • Research papers
  • Review articles (e.g., systematic review or meta-analysis)
  • Case studies and evidence-based good practice examples

Developing a high-quality proposal

We recommend the creation of a single document in Word (.doc or .docx) format that contains the following:

  • Proposed article title
  • Proposed authors names, affiliations, and ORCid
  • A clear evidence-based rationale for the line of inquiry proposed
  • Research question(s)
  • Proposed method (for both theoretical and empirical manuscripts)
  • Practice-based implications of the proposed research

The word limit for the proposal is 250 words (not including references) and is designed to give the Editorial Team a sense of the rigour of the manuscript proposed and the possible implications of such research. The Editorial Team may return with an invitation to combine similar manuscripts. Acceptance of proposals does not guarantee acceptance of final manuscripts.

Timeline

  • Proposals due – April 30, 2026
  • Proposal acceptance notifications: May 14, 2026
  • Full articles due: August 31, 2026

Submit your abstract via this online form: https://forms.gle/6sKjc2jkKGWCtGgw7

For further information contact Professor Sarah Elaine Eaton, University of Calgary.

References

Bali, M. (2023, March 3). Are We Approaching a Postplagiarism Era? https://blog.mahabali.me/educational-technology-2/are-we-approaching-a-postplagiarism-era/

Bagenal, J. (2024). Generative artificial intelligence and scientific publishing: Urgent questions, difficult answers. The Lancet, 403(10432), 1118–1120. https://doi.org/10.1016/S0140-6736(24)00416-1

Eaton, S. E. (2021). Plagiarism in Higher Education: Tackling Tough Topics in Academic Integrity. Bloomsbury.

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

Orben, A. (2020). The Sisyphean cycle of technology panics. Perspectives on Psychological Science, 15(5), 1143–1157. https://doi.org/10.1177/1745691620919372

Howard, R. M. (1992). A plagiarism pentimento. Journal of Teaching Writing, 11(2), 233–245.

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Posted by Sarah Elaine Eaton, Ph.D.

ChatGPT is in classrooms. What now?

February 2, 2026

“What should we be assessing exactly?” This was a question one of our research participants asked when we interviewed them as part of our project on artificial intelligence and academic integrity, sponsored by a University of Calgary Teaching Grant.

In an article published in The Conversation, we provide highlights of the results from our interviews with 28 educators across Canada, as well as our analysis of 15 years of research that looked at how AI affects education. (Spoiler alert: AI is a double-edged sword for educators and there are no easy answers.)

Alt text: Screenshot of The Conversation website showing a blurred smartphone screen with the ChatGPT app icon. Overlaid headline reads, “ChatGPT is in classrooms. How should educators now assess student learning?”
Screenshot from The Conversation.

We emphasize that, “in a post-plagiarism context, we consider that humans and AI co-writing and co-creating does not automatically equate to plagiarism.” Check out the full article in The Conversation.

You can check out the scholarly paper that we published in Assessment and Evaluation in Higher Education that goes into more detail about the methods and findings of our interviews.

I’d like to give a shoutout to all the project team members who worked with us on various aspects of this research: Robert (Bob) Brennan (Schulich School of Engineering, University of Calgary), Jason Weins (Faculty of Arts, University of Calgary), Brenda McDermott (Student Accessibility Services, University of Calgary), Rahul Kumar (Faculty of Education, Brock University), Beatriz Moya (Instituto de Éticas Aplicadas, Pontificia Universidad Católica de Chile) and the student research assistants who helped along the way (who have now all successfully graduated and moved on to the next phase of their careers): Jonathan Lesage, Helen Pethrick, and Mawuli Tay.

Related posts:

What Should We Be Assessing in a World with AI? Insights from Higher Education Educators – https://drsaraheaton.com/2025/11/25/what-should-we-be-assessing-in-a-world-with-ai-insights-from-higher-education-educators/

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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.

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Embedding Social Justice, Equity, Inclusion, Diversity, and Accessibility in Academic Integrity

August 25, 2025

As a new academic year begins here in the northern hemisphere, I’m worried. I am worried that equity-deserving students, including racialized and linguistic-minority students, disabled and neurodivergent students, and others from equity-deserving groups will fall through the cracks again this year.

Conversations about academic integrity often centre around detection and discipline. 

How many students will be accused of — and investigated for — academic cheating this year when what they actually needed was learning support? Or language support? Or just a clearer understanding of what academic integrity is and how to uphold it?

It doesn’t have to be this way.

Academic integrity is also about creating a learning environment grounded in fairness and opportunity for every student. Social justice, equity, inclusion, diversity, and accessibility shape how students experience integrity in real ways:

  • Equity reminds us that students enter the classroom with different levels of preparation and support.
  • Inclusion ensures every student can participate in learning and assessment.
  • Accessibility removes barriers that make it harder for some students to meet expectations.
Infographic entitled 'Embedding Social Justice, Equity, Inclusion, Diversity, and Accessibility in Academic Integrity.' It features four bullet points: Equity acknowledges varied student preparation and support; Inclusion promotes participation in learning and assessment; Accessibility removes barriers to meeting expectations; and a Social Justice lens reveals patterns in integrity breaches. An illustration of a balanced scale appears below the text. The poster is credited to Sarah Elaine Eaton, PhD, August 2025.

A social justice lens helps us see patterns in who is reported or penalized for breaches of integrity and why.

  • Here are some actions educators can take in the first month of classes to support student success:
  • Review course materials to ensure instructions and policies about integrity are written in plain, accessible language.
  • Dedicate class time to talking with students about what integrity looks like in your course and why it matters.
  • Share examples of proper citation and collaboration that are relevant to your discipline.
  • Make time for questions about assessments so students understand what is expected and where to find help.
  • Connect students early to campus supports such as writing centres, student services, and accessibility services.

This is just a start.

My point is this: Do not assume that students should just know what academic integrity means. Take the time to explain your expectations and policies. In order for students to follow the rules, they need to know what the rules are.

Academic integrity is not only about avoiding plagiarism or cheating. It is also about fostering trust and fairness so that all students have a fair chance to learn and succeed. The choices we make in the first few weeks of the term set the tone for the entire year.

What steps are you taking at the start of this new school year to build a more inclusive and equitable approach to academic integrity?

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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.

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Embracing AI as a Teaching Tool: Practical Approaches for the Post-plagiarism Classroom

March 23, 2025

Artificial intelligence (AI) has moved from a futuristic concept to an everyday reality. Rather than viewing AI tools like ChatGPT as threats to academic integrity, forward-thinking educators are discovering their potential as powerful teaching instruments. Here’s how you can meaningfully incorporate AI into your classroom while promoting critical thinking and ethical technology use.

Making AI Visible in the Learning Process

One of the most effective approaches to teaching with AI is to bring it into the open. When we demystify these tools, students develop a more nuanced understanding of the tools’ capabilities and limitations.

Start by dedicating class time to explore AI tools together. You might begin with a demonstration of how ChatGPT or similar tools respond to different types of prompts. Ask students to compare the quality of responses when the tool is asked to:

  • Summarize factual information
  • Analyze a complex concept
  • Solve a problem in your discipline
A teaching tip infographic titled "Postplagiarism Teaching Tip by Sarah Elaine Eaton: Make AI Visible in the Learning Process." The infographic features a central image of a thinking face emoji, with three connected bubbles highlighting different aspects of AI integration in learning: Summarize Factual Information (blue): Encourages understanding of basic facts and data handling, represented by an icon of a document with a magnifying glass. Analyze Complex Concepts (green): Develops critical thinking and deep analysis skills, represented by an icon of a puzzle piece. Solve Discipline-Specific Problems (orange): Enhances problem-solving skills in specific subjects, represented by an icon of tools (wrench and screwdriver). In the bottom right corner, there’s a Creative Commons license (CC BY-NC) icon.

Have students identify where the AI excels and where it falls short. Hands-on experience that is supervised by an educator helps students understand that while AI can be impressive and  capable, it has clear boundaries and weaknesses.

From AI Drafts to Critical Analysis

AI tools can quickly generate content that serves as a starting point for deeper learning. Here is a step-by-step approach for using AI-generated drafts as teaching material:

  1. Assignment Preparation: Choose a topic relevant to your course and generate a draft response using an AI tool such as ChatGPT.
  2. Collaborative Analysis: Share the AI-generated draft with students and facilitate a discussion about its strengths and weaknesses. Prompt students with questions such as:
    • What perspectives are missing from this response?
    • How could the structure be improved?
    • What claims require additional evidence?
    • How might we make this content more engaging or relevant?

The idea is to bring students into conversations about AI, to build their critical thinking and also have them puzzle through the strengths and weaknesses of current AI tools.

  • Revision Workshop: Have students work individually or in groups to revised an AI draft into a more nuanced, complete response. This process teaches students that the value lies not in generating initial content (which AI can do) but in refining, expanding, and critically evaluating information (which requires human judgment).
  • Reflection: Ask students to document what they learned through the revision process. What gaps did they identify in the AI’s understanding? How did their human perspective enhance the work? Building in meta-cognitive awareness is one of the skills that assessment experts such as Bearman and Luckin (2020) emphasize in their work.

This approach shifts the educational focus from content creation to content evaluation and refinement—skills that will remain valuable regardless of technological advancement.

Teaching Fact-Checking Through Deliberate Errors

AI systems often present information confidently, even when that information is incorrect or fabricated. This characteristic makes AI-generated content perfect for teaching fact-checking skills.

Try this classroom activity:

  1. Generate Content with Errors: Use an AI tool to create content in your subject area, either by requesting information you know contains errors or by asking about obscure topics where the AI might fabricate details.
  2. Fact-Finding Mission: Provide this content to students with the explicit instruction to identify potential errors and verify information. You might structure this as:
    • Individual verification of specific claims
    • Small group investigation with different sections assigned to each group
    • A whole-class collaborative fact-checking document
  3. Source Evaluation: Have students document not just whether information is correct, but how they determined its accuracy. This reinforces the importance of consulting authoritative sources and cross-referencing information.
  4. Meta-Discussion: Use this opportunity to discuss why AI systems make these kinds of errors. Topics might include:
  • How large language models are trained
  • The concept of ‘hallucination’ in AI
  • The difference between pattern recognition and understanding
  • Why AI might present incorrect information with high confidence

These activities teach students not just to be skeptical of AI outputs but to develop systematic approaches to information verification—an essential skill in our information-saturated world.

Case Studies in AI Ethics

Ethical considerations around AI use should be explicit rather than implicit in education. Develop case studies that prompt students to engage with real ethical dilemmas:

  1. Attribution Discussions: Present scenarios where students must decide how to properly attribute AI contributions to their work. For example, if an AI helps to brainstorm ideas or provides an outline that a student substantially revises, how could this be acknowledged?
  2. Equity Considerations: Explore cases highlighting AI’s accessibility implications. Who benefits from these tools? Who might be disadvantaged? How might different cultural perspectives be underrepresented in AI outputs?
  3. Professional Standards: Discuss how different fields are developing guidelines for AI use. Medical students might examine how AI diagnostic tools should be used alongside human expertise, while creative writing students could debate the role of AI in authorship.
  4. Decision-Making Frameworks: Help students develop personal guidelines for when and how to use AI tools. What types of tasks might benefit from AI assistance? Where is independent human work essential?

These discussions help students develop thoughtful approaches to technology use that will serve them well beyond the classroom.

Implementation Tips for Educators

As you incorporate these approaches into your teaching, consider these practical suggestions:

  • Start small with one AI-focused activity before expanding to broader integration
  • Be transparent with students about your own learning curve with these technologies
  • Update your syllabus to clearly outline expectations for appropriate AI use
  • Document successes and challenges to refine your approach over time
  • Share experiences with colleagues to build institutional knowledge

Moving Beyond the AI Panic

The concept of postplagiarism does not mean abandoning academic integrity—rather, it calls for reimagining how we teach integrity in a technologically integrated world. By bringing AI tools directly into our teaching practices, we help students develop the critical thinking, evaluation skills, and ethical awareness needed to use these technologies responsibly.

When we shift our focus from preventing AI use to teaching with and about AI, we prepare students not just for academic success, but for thoughtful engagement with technology throughout their lives and careers.

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 

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

Edwards, B. (2023, April 6). Why ChatGPT and Bing Chat are so good at making things up. Arts Technica. https://arstechnica.com/information-technology/2023/04/why-ai-chatbots-are-the-ultimate-bs-machines-and-how-people-hope-to-fix-them/ 

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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.

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Inclusive Academic Integrity: A Holistic Approach to Ethical Learning for Everyone

November 15, 2024

Earlier this semester, I accepted a new leadership role in the Werklund School of Education as the Academic Coordinator of the Master of Education (MEd) graduate topic in Inclusive Education. (We are accepting applications the 2025-2026 academic year, in case you’ve been thinking about doing an MEd. It is a fully online four-course topic.)

This got me thinking about academic integrity through an inclusive lens. My interest in the connection between social justice, equity, inclusion, and accessibility goes back a few years. In 2022, I partnered with a Werklund graduate student in educational psychology, Rachel Pagaling, and Dr. Brenda McDermott, Senior Manager, Student Accessibility Services to write up a brief open access report on Academic Integrity Considerations for Accessibility, Equity and Inclusion.

A lot more work has been done in this area since we wrote that report. Professor Mary Davis has been a particular champion of this topic. Her 2022 open access article, Examining and improving inclusive practice in institutional academic integrity policies, procedures, teaching and support, is worth checking out. There is also an entire section of the Second Handbook of Academic Integrity (2024) dedicated to equity, diversity, inclusion, accessibility, and decolonization. 

We know that academic integrity is a cornerstone of both K-12 and higher education. We want to ensure that learning, assessment, and credentials uphold the highest ethical standards. However, as educators, we can — and should — consider how the principles of inclusive education can strengthen and complement our approach to academic integrity.

Inclusive education means ensuring that all students, regardless of their background, abilities, or learning needs, have equitable access to educational opportunities and can meaningfully participate. Thomas and May sum it up nicely when they say that being inclusive means “proactively making higher education accessible, relevant and engaging to all students” (p. 5).  Of course, the same thinking could be extended to K-12 education, too. Applying these inclusive principles to academic integrity means recognizing that diverse learners may express and demonstrate their knowledge in different ways. 

Inclusion is not only about students with physical disabilities, developmental disabilities, or neurodivergence, but rather it is about creating conditions where all students can thrive. Associate Professor Joanna Tai and colleagues have a great article on Assessment for Inclusion that helps us think about how to design equitable and rigorous.

In addition, Dr. Eliana Elkhoury has a great chapter on how to create, An Equitable Approach to Academic Integrity Through Alternative Assessment.

The point here is that by fostering an inclusive academic culture, we empower all students to bring their best selves to school and learn with integrity.

Beyond accessibility and cultural responsiveness, inclusive academic integrity also means actively addressing systemic barriers and implicit biases. If certain groups of students consistently struggle with academic integrity issues, it may reveal deeper inequities that need to be examined and addressed. In other words, we can look at the barriers to success, rather than the limitations of our students, as being the problem. As Juuso Nieminen and I have pointed out, even accommodations policies have an underlying assumption that students who need accommodations are out to cheat the system. 

If you’re interested in reading more about disability justice to inform your thinking, I highly recommend Doron Dorfman’s article on the fear of the disability con and Jay Dolman’s work on academic ableism.

The benefits of this holistic, inclusive approach to academic integrity are numerous. When students feel respected, supported, and able to succeed, they are more engaged and motivated. This, in turn, leads to better learning outcomes. Moreover, graduates who have internalized inclusive academic integrity will be better equipped to uphold ethical standards in their future careers and communities.

As educators, we have a responsibility to nurture academic integrity in ways that are inclusive, accessible, culturally responsive, and empowering for diverse learners. By applying the principles of inclusive education, we can transform academic integrity from a rigid set of rules into a collaborative, values-driven endeavor that brings out the best in our students and ourselves.

References

Davis, M. (2022). Examining and improving inclusive practice in institutional academic integrity policies, procedures, teaching and support. International Journal for Educational Integrity, 18(1), 14. https://doi.org/10.1007/s40979-022-00108-x 

Dolmage, J. T. (2017). Academic Ableism: Disability and Higher Education. University of Michigan Press. 

Dorfman, D. (2019). Fear of the disability con: Perceptions of fraud and special rights discourse. Law & society review, 53(4), 1051-1091. https://doi.org/10.1111/lasr.12437 

Elkhoury, E. (2024). An Equitable Approach to Academic Integrity Through Alternative Assessment. In S. E. Eaton (Ed.), Second Handbook of Academic Integrity (pp. 1261-1272). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54144-5_135 

Nieminen, J. H., & Eaton, S. E. (2023). Are assessment accommodations cheating? A critical policy analysis. Assessment & Evaluation in Higher Education, 1-16. https://doi.org/10.1080/02602938.2023.2259632 

Pagaling, R., Eaton, S. E., & McDermott, B. (2022, April 4). Academic Integrity: Considerations for Accessibility, Equity, and Inclusion. http://hdl.handle.net/1880/114519

Thomas, L., & May, H. (2010). Inclusive learning and teaching in Higher Education. Higher Education Academy. https://www.advance-he.ac.uk/knowledge-hub/inclusive-learning-and-teaching-higher-education

Tai, J., Ajjawi, R., Bearman, M., Boud, D., Dawson, P., & Jorre de St Jorre, T. (Eds.). (2022). Assessment for inclusion: rethinking contemporary strategies in assessment design. Routledge. https://doi.org/10.1080/07294360.2022.2057451 

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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.

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