05/25/2026

Summer Series Pre-webinar Blog 1: Teaching ethical use of AI as part of academic integrity training

by Loretta Goff and Beatriz Antonieta Moya Figueroa

1) How have the ways you work in teaching academic integrity in relation to student use of generative artificial intelligence (GenAI) changed, or not changed, over the past few years?

Loretta: There are some aspects that stand the test of time and have not changed much, including framing responsible use of GenAI through the fundamental values of academic integrity and centering human capabilities like critical thinking that are needed to work well with these tools. That being said, as GenAI has evolved over the last few years along with our understanding of its uses and impacts in education, so too has my practice. For example, I’ve put additional focus on developing students’ confidence in their own abilities, ensuring they are taking the lead with GenAI tools, and not afraid to question or challenge them, rather than being led by them.

Beatriz: What has not changed is my educational approach to academic integrity: giving students clear expectations of how to carry out their learning and assessment tasks, and being available through the process to address their questions as the work unfolds. What has changed in my conceptualization of plagiarism. Drawing on Eaton’s (2023) plagiarism tenets, I have redesigned assessments to allow ethical generative GenAI integration where it makes sense, for example, tasks that invite students to critically analyze GenAI outputs. I believe that technology’s impact on our interactions still has much to tell us about what does and does not constitute a breach, and I am continuing to read in order to deepen my understanding.

2) How have you seen the discourse about teaching academic integrity and GenAI evolve, or not, over the past few years?

Loretta: GenAI has certainly increased the discourse about teaching academic integrity, and in many ways GenAI has come to dominate this discourse over the last few years. In my own context, I’ve seen increased demand for academic integrity training, with some degree of AI literacy woven in within this, or paired with it. Again, I think there are fundamental principles, values and academic skills that will stand the test of time as part of both academic integrity and GenAI training, but certainly elements of training specific to GenAI require continuous development as these tools and our uses of them evolve.

Beatriz: The initial moral panic about GenAI has gradually given way to an exploration of how these tools can support student learning with integrity. I see growing attention to embodying the value of responsibility through transparency and accountability practices, for example, encouraging students to show how they have integrated chatbots when use is permitted. Detection has not disappeared from the conversation, but the spotlight it once held has shifted toward redesigning assessments in ways that account for how GenAI could be used to circumvent learning.

3) What kind of intervention or approach to student use or misuse of GenAI have you used that worked well? Have you tried anything that did not work well?

Loretta: Hands on activities where students review GenAI tools or their outputs together (i.e., regarding privacy/security, output quality, usability, etc.) or use them for a set task (i.e., interrogating or challenging) to achieve a certain goal have been useful, particularly as they include evaluation, reflection, and discussion as part of the process. The discussion allows the group to learn together and from one another, while also enabling whoever is leading the activity to guide towards responsible use by raising points to consider or by demonstrating different approaches that illustrate this.

Beatriz: I designed an assessment where students could collaborate with GenAI to analyze ethical dilemmas in school contexts. GenAI use was authorized, and the task was not proctored, but students knew from the onset they were responsible for reviewing the outputs. The rubric rewarded the weaving of in-class content with insights drawn from personal experience, which are elements that I believe GenAI cannot fully express. The strongest answers reached a level of nuance and depth that GenAI prose could not produce. The cases were also situated in the Chilean context, and I think that chatbots still cannot capture local specificities the way humans can.

4) What has most challenged or frustrated you?

Loretta: The impacts of GenAI on education have led to many challenges and frustrations that I’m sure most of us are feeling to varying degrees, so it can be hard to pick which one is most challenging/frustrating! Assessment and how we can best assure learning is certainly a huge challenge now, but a couple of other things that have frustrated me are the hype around GenAI that has seen it pushed into so many areas without careful consideration and evaluation of its uses and impacts (both harmful and beneficial), and the increased breakdown in trust associated with these tools. This has unfortunately resulted, in some cases, in a growing divide between educators and students. It is important that we keep dialogue open and come together to share experiences and perspectives, reinforcing trust.

Beatriz: What I find most challenging is that teaching, learning, and assessment as they existed before the emergence of chatbots are no longer fully applicable. I sometimes hesitate to assign essays that explore concepts or annotated bibliographies, because these are now in GenAI territory. I do not assume my students are looking for ways to cheat, as most are not, but there are tasks I would once have set without second thought that now I avoid, and I cannot proctor everything I would like to. The frustration is that these hard choices have become unavoidable, in a way that was simply not part of my own experience as a learner.

5) What has given you hope?

Loretta: Seeing the ways that some students are really critically engaging with these tools and using them in ways that do extend their learning, or rejecting them where it doesn’t make sense to use them. I’ve run a couple of surveys and focus groups with students over the last few years on topics of GenAI, academic integrity, and assessment, and the many insightful and nuanced open responses within these always give me hope, offering a change from the narratives of cheating that often dominate this topic. Cheating is occurring, of course, but it's important not to lose sight of all the learning that is as well and all the students that are developing responsible, principled approaches to using (or not using) GenAI.

Beatriz: What gives me hope is that GenAI continues to show its limitations despite rapid advances, and that there is still space for creativity, with work carried out without GenAI that is still celebrated and valued. It is not that I reject this technology. What I fear is the homogenization of human thinking. So every time I hear a student offer a new insight that could only emerge from a shared learning process, I quietly celebrate it. There is beauty in creating and recognizing ideas of value that are not the product of a statistical prediction.

Dr Loretta Goff is the Academic Integrity Education Officer at University College Cork, where she provides training, short courses, and resources for both students and staff. She also sits on the Steering Committee of Ireland's National Academic Integrity Network.

Dr Beatriz Antonieta Moya Figueroa is Assistant Professor of the Institute of Applied Ethics at the Pontificia Universidad Católica de Chile and academic integrity researcher

The authors' views are their own.

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EDITOR'S NOTE:

This is the first of our blogs to accompany the ICAI Summer Series of webinars. Loretta and Beatriz will be delivering the first webinar on May 28 at 12pm EST. We look forward to seeing you there!

Here is some recommended pre-reading for the webinar.

Required reading: 

National Forum for the Enhancement of Teaching and Learning in Higher Education (2026) Ten Considerations for Generative AI Adoption in Irish Higher Education (HEA). Artificial Intelligence in Irish Higher Education

UC Davis University Writing Program(2026) Peer and AI review and reflection (PAIRR). UCDavis

Mill, A. (2026). Agentic AI, AI writing, and a 4Cs resolution. April 8  Unofficial Office Hour podcast.

Dineen, K., & Goff, L. (2024). Two sides of the same coin: a taxonomy of academic integrity and impropriety using intellectual virtues and vices. Assessment & Evaluation in Higher Education, 49(7), 935–947. https://doi.org/10.1080/02602938.2024.2340641

Recommended further reading:

Morari, Grimes, & Hawe (2026). Academic integrity and generative artificial intelligence–Views and perceptions of students in an Irish university. Journal of Academic Ethics, 24(17). https://doi.org/10.1007/s10805-025-09689-x

Notre Dame Observer (2025). Editorial: AI proof the core curriculum. October 2025. The Notre Dame Observer student newspaper.