#EDEN Porto AC 2026 - Colin Lowry

Colin Lawry, who comes from Ireland and he is senior manager for teaching and learning enhancement and digital innovation at Ireland's Higher Education Authority. And it's the institution which focuses and develops a development body for higher education and research in Ireland and they they recently have developed a GenAI policy framework that she he's going to share with us. Thank you. >> thank you very much for that kind introduction and it's a real honor to be here and thank you to Eden for the invitation as well. And just to say thank you to all of you for all your presentations. I've learned a great deal from all of you over the last couple of days that I'll take back to Ireland into my work for sure. Um so I was going to start with a perception that we have but Anne stole my thunder. I was going to start with a similar perception in terms of um when we first set out on our work around generative AI uh readiness for our system in Ireland around that perception and the student perception, the perception that students um were looking for access to tools and further shortcuts and all the rest and instead what we found is that they were looking for clarity, uh looking for fairness and all of that. So that came through strongly in terms of some of the work that I'm going to share here with you. So look, just for some context, the Higher Education Authority in Ireland is the statutory funding, planning and regulatory body for higher education and research. So we uh kind of sit as a middle where between the publicly funded institutions and between our ministry or our department as we call it for higher uh further and higher education. And our sister agency for instance might include quality uh the quality assurance agency QQI. Um so we have about 279,000 students in public higher education in Ireland across 18 publicly funded uh institutions who are under statute in receipt of core public funding. So, we're quite a small system, and that does give us a unique advantage in terms of a certain degree of agility, and particularly when it comes to to this type of work. Um so, my unit is called the National Forum for the Enhancement of Teaching and Learning in Higher Education. Uh originally, we sat outside of the Higher Education Authority, and then they had the sense to establish us on a permanent sustainable basis as a key function of the Higher Education Authority since 2022. Um so, our mandate is enhancement, leading teaching and learning in partnership, and partnership is the keyword, with students, staff, and institutional uh leaders. So, not by directive. So, the National Forum um unit, it's it's very much so around the the the those those components of of of convening and and collaboration. Um so, we don't instruct institutions um on how to teach or assess. Of course, uh academic freedom and institutional autonomy is a big part of our system. So, if we do start with funding, um I suppose money shapes a lot of the behavior. Uh follow the money, as they say. So, SATL is our mechanism for funding teaching and learning enhancements. That's the Strategic Alignment of Teaching and Learning Enhancement Fund. And we're lucky enough in Ireland that we've been able to invest 28.8 million uh since 2022 to provide some multi-annual stability, uh where institutions can experiment and scale what works, and share it as well. In terms of work and developments in this space, we have a number of thematic priorities, digital transformation, academic integrity, and education for sustainable development. So, as you can imagine, AI cross-sections across all of those. Um and one of the things with enhancement funding or innovation funding like this, of course, this development of pilots and so on and so forth. And the graveyard of innovation quite often is of course well-funded pilots that died with their funding. So, a key mechanism in terms of our system developments that we have in place for for for this work is we attach a condition to our funding. And that condition is that outputs must be openly licensed and shared so that others can learn from them and build upon them. And one of the things that we did to support this work was to develop a central platform within the Higher Education Authority called the National Resource Hub. And that National Resource Hub, just to point out the person responsible for that is Ronan Bree of Eden fame here in the audience as well, who led out on that piece of work. So, through the requirements we require that those outputs are uploaded to the National Resource Hub where appropriate and that they can be shared so anybody can come in since they're licensed under open licensing. Um One other area that we've been supporting readiness across the sector is through centrally supporting short courses developed by the sector for the sector. And again, these are these are centrally hosted through a Moodle platform that we host. And we have a range of offerings from 25 hour short courses right down to maybe two or three hour offerings. And we find that using the the commons again for this work, the open licensing, that institutions can actually not just come in and and participate centrally on the platform. They can take away the course where embedded into their own virtual learning environment, adapted, remix it to their own context. And that's been quite successful. One of the short courses or suite of short courses that we funded, we've seen 950,000 enrollments globally through that. Um but funding and courses, of course, are the easy part. Uh policy is where most systems are supposed freeze or where they can sometimes maybe even overreach. Um so, we seconded a person from the sector to lead out this piece of work uh over a series of 18 months develop policy on generative AI, a policy framework that institutions could use. And the reason we went with somebody from the sector not a consultant is that uh that somebody would have to live with the results or live with the repercussions of what they develop. And that person, again, is uh Professor James O'Sullivan here in the audience that was a part of the panel here yesterday. Um so, just as supposed to give a shape to how that policy developments work took place, uh it was over uh 18 months and it would have first started with just some sectoral engagements, reaching out to individuals and groups to understand the shape of the landscape as it were in 2023 through to um 2024 and uh to do a desk review of our national AI strategy more broadly, uh the EU AI Act, uh as well as the UNESCO competency frameworks and map out where institutions currently are as well speak to them where they're at. And uh and that kind of a thing. So, we didn't want to duplicate what already existed. We wanted to bring it together. Um [snorts] and and and that structure of engagements with stakeholder groups was widened as well through advisory groups and and those types of similar structures as well. So, the first output of that, and this was within maybe the first 6 months of that work, was to put together something somewhat of a shared language, 10 considerations. Um so, I just shared some of those considerations that came through strongly from that initial sectoral engagements. So, right from academic integrity, allowable AI, sustainability, um I and what this really did is at the stage where institutions were in the development of policy and the development of guidelines, it provided a share a shared um a shared language. And what we even found after publishing this initial light-touch piece really just to kind of get something out there in terms of of of of of of where we were at, um is that institutions within two, three, four weeks started publishing uh their piece. So, what we found is that no single institution wanted to go first, but once one went, they all went. And that is really where we've seen the power of our role in what we can do in terms of convening, in terms of supporting. Um so, I won't dwell on this because it has been superseded by generative AI, um uh frame policy framework, uh and just to say as part of the cycle throughout the 18 months, what we did as well as we set up a central national level case studies database. So, we actually asked educators, those supporting teaching and learning, those in senior management, "Please just send us your case studies of uh what how you're dealing with generative AI in your context and share them out nationally as well." So, we developed this database that's a public database uh of various case studies, and we're still continuing to collect those as well. And that supports us in understanding the work across the sector, and it helps the sector, I suppose, look at other touchpoints across other institutions. So, that's been really quite useful as well. Now, for the consultation part of the development of a policy framework in and of itself, what we've done is we convened a series of focus groups. Um so, we convened 76 stakeholders across a range of roles, so not just academics, uh, academic developers, technologists, librarians, uh, as well as representatives from our national AI advisory council, our quality agency, uh, so I mean our infrastructure providers, industry, uh, student representative groups, and so on and so forth. And uh, those groups explored across kind of 10 kind of key themes that were emerging through the early work. Um, to share some of the voices that came through in that, we published this openly and honestly in terms of what we heard through our sectoral perspectives report last September. And this was really quite particularly useful to the sector at that stage. So that contains, uh, a lot of what we heard as well as the implications for policy. And that's what we were able to take forward to develop the framework. So just to give voice to some of the stuff that came through in that, I'm not sure if what I'm doing is encouraged, ignored, or discouraged. No one's talking about it. So that was the clarity gap. And that's coming from both students and staff. That there was no conversations, there was no openness about how you're using There was a shyness around it. And look, that's that's the thing as well. I mean, there's a lot of critical voices, there's a lot of uncritical and hyped-up voices, and there was a shyness around actually discussing, uh, the use of AI. And and that came through. Uh, some of the other voice that came through, they're submitting perfect-looking assignments, but when you talk to them, the thinking just isn't there. So that spoke a little bit to the skills degradation, uh, a piece that came through, uh, in this piece of work. And uh, another voice, we don't want students who can prompt well, we want students who can think about what the prompt is doing. Um, so the anxiety, uh, that this will complicate people's ability to think critically, creatively, and so on. So, we synthesized Um we synthesized um the the perspectives report and the recommendations for policy development from that. And and some of the emerging themes are just there on the screen, but the strongest one was a a need for national coordination, system coordination, a re-examination of educational purpose and authorship, inclusion designed not assumed, and an assessment reform that moves from detection towards that kind of authentic process-based approaches. And for me, working in teaching and learning for the past 10 years or so, that was very validating because I mean that's work that we were doing pre uh generative AI. So, it's now something we can leverage to even try and bring that forward uh as well. Um so, that that phrase away from detection as well became a kind of a defining position. And uh it's it's it it got a little bit of pushback, and it's not something we've quite figured out, but it's the whole idea of governing um the the purpose, and and don't make it about the about the tools themselves. And and and that will be transferable then across contexts and build a stronger system more broadly. Um so, I'll fast forward to the framework itself. So, in December last year, we brought all of this work together, and we arrived at the generative AI policy framework uh for higher education teaching and learning. So, it consists of two documents, the policy framework uh containing five principles, which I'll touch on in a moment, as well as the um the prin- the principles for ethical adoption, which is a kind of a more detailed document. Now, what we also did is we developed a series of annexes alongside this doing the operational work, the evidence. When we were doing this piece of work, James was said this has to be useful. It can't just be a policy uh piece that sits on a shelf. It has to be useful. So, we created these series of of annexes to go along with it um that explore the likes of the EU AI Act compliance, AI literacy training, uh it explores the evidence for the framework, uh assessment practices, as well as a vendor and procurement governance, and then role-by-role responsibilities, as well as the support institutional structures. And if we separate the layers, it becomes a bit easier to revise as well. So, it's a living framework, and we want the ability to be able to revise it. And by individualizing some of the components, it makes that easier for for a version control. So, the five principles uh briefly, academic integrity and accountability, equity and inclusion, critical engagement and human oversight, privacy and data governance, and sustainable pedagogy. So, five things that don't necessarily change with the next new model to come out from Claude or Open AI or whoever. Um so, that that that that, you know, um that that we're not revising um at a high level, um and and we're coming at it from a values perspective, which is particularly important. Then beneath each principle, and I just highlighted one particular principle area just as an example today, um it breaks it down uh in our second document, um for example here on critical engagement and AI literacy into kind of eight components in this case from embedding literacy as a core competency through to governance and evaluation of that. And then each principle comes with a set of recommendations that institutions can consider in the development of their own policies. So, as an example again from the critical engagement, treat AI literacy as a core graduate attribute, scaffolded across program, and resource educators to teach credibly. And this is the answer to the the detection question, assess it authentically, portfolios, case uh based collaborative projects, and so on and so forth. So, just to finish up, as I said, our role is coming from an enhancement focus. So, how do we govern it? We We don't set out any new audit apparatus, no new returns from institutions. We monitor through our existing dialogue processes. So, we have a number of mechanisms for engagement with our institutions, and that's how we learn. We understand how they're adopting the the principles, how they're adopting the recommendations, and based off what we hear back, we'll revise the framework. We'll revise the framework based on that feedback. And we'll look at other mechanisms if we think that there's a gap in the system or there's true or conditions for funding and so on and so forth. So, look, that's just a quick tour. I'm conscious of the time of kind of how we developed worked towards some level of readiness in AI through a systems-level approach in Ireland. Thank you very much. >> [applause]