What’s new in the Subject Benchmark Statements? GenAI, ethics and the student experience

In this episode, QAA brings together four Subject Benchmark Advisory Group Chairs to explore how the latest Benchmark Statements address Generative AI, ethics, inequality and professional practice across Art & Design, Social Policy, Sociology and Social Work. Hear practical insights on critical and responsible AI use, safeguarding independent thinking, and embedding sustainability, accessibility and real‑world skills to ensure graduates are prepared for an evolving academic and professional landscape.

Transcript

Welcome And Guest Introductions

Dr Andy Smith 0:00

Welcome everyone. Welcome to a uh podcast to coincide with the publication of the latest suite of QAA subject benchmark statements. My name is Andy Smith. I'm the Quality and Standards Manager at the Quality Assurance Agency for Higher Education. I'm delighted to say that I'm joined today by chairs of some of the subject benchmark statements that we are going to be publishing on the 16th of April. So I'm going to ask them all to introduce themselves. So whoever would you like to go first?

Professor Hua Dong 0:32

Thank you, Andy. I'm Hua Dong, Chair of the Art and Design Advisory Group. I'm professor and the RCA. I have 20 years of experience teaching design and undergraduate and postgraduate levels, and I'm an active design researcher, fellow and vice chair of the Design Researcher Society.

Dr Andy Smith 0:54

Thank you, Kwa. Andrea.

Andrea Collins 0:57

Hi, thank you. I'm Andrea Collins. I had the privilege of chairing the Social Work Advisory Group, and I'm head of social work at Manchester Met University. I'm a qualified registered social worker with many, many years experience, including coming up to nearly 20 years experience in HEIs delivering social work training programs.

Dr Andy Smith 1:23

Thank you, Andrea. Liz.

Liz Cain 1:26

So my name is Liz Cain. I uh have been the chair of the Sociology Advisory Group, and I am the head of sociology and criminology at Manchester Metropolitan University. I am a reader in applied social sciences, and my area of expertise is in employability, strengthening students' outcomes, and work-integrated learning.

Dr Andy Smith 1:54

Thank you, Liz. And finally, Lee.

Dr Lee Gregory 1:56

Hi, yeah, I'm Lee Gregory at from the University of Nottingham, and I was the chair of the advisor group for the social policy uh subject um benchmark. So my background is again, I've done a number of different education leadership roles across a couple of different institutions, and have been involved in a number of um training initiatives around authentic assessment. Thanks, Lee.

What Subject Benchmarks Actually Do

Why Generative AI Changes Everything

Art And Design On Bias And Visibility

Dr Andy Smith 2:20

Um so before we get into a discussion around some of the uh work that's been done in the subject benchmark statements, I'll just talk a little bit about subject benchmark statements for those of you who may be new to them. So the QAA have been publishing subject benchmark statements for over 25 years now. Uh, they were originally part of what was called the old academic infrastructure, some of you may remember that. And their status and use by different higher education providers has changed over those last 25 years. They're mainly used to support course design, to support teaching, learning, and assessment processes within subject disciplines. And but what's really important about them is their ability to allow a subject community to come together and agree on what is really important in the subject, both in terms of student outcomes and also uh differential approaches to teaching, learning, and assessment. What has changed though over the last five years, since 2022, is that QEA have introduced five what we call cross-cutting themes into the subject benchmark statements designed to uh support subject communities to interrogate what those how those subjects approach each of those themes. And those themes cover uh equity and inclusivity, accessibility and the uh needs of disabled students, sustainability, entrepreneurship, and generative artificial intelligence. So I think in terms of the podcast, uh, we'd like to start just by looking in more detail at the cross-cutting theme of generative artificial intelligence that does seem to be a really important area for higher education at the moment. I'd like to start by just quoting from the uh subject benchmark statement for art and design, actually. Art and design education encourages students to critically examine how GII systems shape cultural visibility, who is rendered visible, whose knowledge is legitimized, and which ways of knowing are devalued or erased. Art and design courses explore how these systems participate in shaping knowledge hierarchies, developing creative practices that can resist, subvert, or reimagine these dynamics. So, Hua, I'll come to you first, obviously. Um, how does that particular statement in the SBS reflect what's happening in art and design in its approach to generative artificial intelligence?

Professor Hua Dong 4:50

Thank you, Andy. Art and Design Advisory Group actually have a very active and extensive discussion on Gen AI. Um, it's more than generative AI, it's about the AI systems. The Gen AI systems draw from data sets that tend to amplify dominant perspectives and reproduce systematic biases. You know, many of our expertise are in inclusive design accessibility. So we debated on these, and we think those are often excluding underrepresented voices, geographies, and forms of knowledge. And other than design students need to be critically examining how this is going to shape the future culture visibility. In the learning context, uh, generative AI is approached as one-two among many that promote experimentation and support iterative inquiry within creative workflows. There is obviously a spectrum of interaction with Gen AI, and art and design education helps students to navigate this spectrum and establish their own position. Students are recognized as future generations to create creative practitioners, thinkers, and culture uh contributors who will shape the future of these technologies. So we are very excited to end this new cross-cutting theme into our SBS.

Dr Andy Smith 6:37

Thank you, Hua. Yeah, that's really important to know how it's going to be used in in the future. And I think one of the things that interests me, particularly for um Andrea, your particular approach in social work is around kind of emphasizing how AI can actually reinforce some of those kind of structural inequalities. And obviously, particularly social work and sociology and social policy are very subjects that are very kind of attuned to how we get students to think about critically uh addressing those kind of structural inequalities within the subject. So again, I wonder how you how the group approached that particular area of generative AI in the context of the subject discipline.

Social Work Ethics And Confidentiality Risks

Andrea Collins 7:18

Yeah, sure. I think for us in social work, it kind of went a little bit deeper, even, because we didn't just consider well, what might that look like in terms of social work education, but the benchmark statement itself also had to reflect the requirements of the profession. And we've got emerging use of generative AI in many different guises within the profession itself, which that itself raises ethical considerations. So we thought from a program perspective, we're not just looking at what that means in terms of curriculum design, how we're using it to engage and capture our students, how we're getting them to really scrutinize if, for example, they're using um you know software that's giving them responses, that's churning out um data, that that's giving them suggested kind of thought processes almost, how they can critically engage in that, but also what that might mean when they're using different levels of apps, software and technology out in practice and what that means. So for our students, we were thinking actually, they need to be looking at wider issues around ethical use, not just in terms of thinking about you know its environmental impact, but also things like confidentiality, to what extent the data that's put in there might then compromise the data breach of, for example, somebody with lived experience, what that might mean. Um, we also had to consider the emerging literature coming from uh research, including research commissioned by, for example, Research in Practice, Social Work England, as one of the four regulators that we worked with, research commissioned and undertaken by the Open University, that talked about the complexity of the ethical use of AI in the profession. And we then started to balance well, actually, we've got the complexity of how we might, you know, engender its use within the university and within the classroom, but actually what that might then look like in terms of practice placement within the organisations that they're going to be placed in. And again, thinking about you know the challenges of the boundaries that students sometimes have to navigate and straddle around what might be permissible use in practice and what we might not deem permissible use back in the university. So we were very mindful to just suggest guidance that each course provider developed its own, because it has to be in the context of the local setting, the practice considerations within the geographical area in which practice was being undertaken, and the extent to which different levels of generative AI are being used. So we had kind of multi-layers to that complexity, if that makes sense. You know, we just thought how do we balance this with how AI is actually being used out in practice? You know, think about consent, data storage, wider concerns. I think one of the big topical issues that we we as a group discussed at length was the potential for bias, influence, and cognitive dependency. How can we support students to be critical thinkers, to be able to defend and articulate their defensible decisions in practice? And how can they use generative AI within the classroom to augment that critical thinking as opposed to replace it? Because I think there was a little bit of caution around that, and I think that caution is still very much out there in the profession. And I think what we tried to capture as well is whatever we're using at the moment around Gen AI is going to look very different in 12 months, two years, three years. So we were mindful not to be too prescriptive in that regard.

Sociology Inequality And The Skills Gap

Dr Andy Smith 11:11

Yeah, thanks, Andrew. That's really helpful to reinforce basically how graduates are going to be using certain types of um digital technologies and tools in the workplace, the impact that's going to have upon how they work with clients and with different kinds of people, particularly in the area of social work. And I think also the fact that this, you know, AI doesn't happen in a contextual vacuum, you know, it's about that kind of lived experience of both the people who are using it for a particular purpose and then actually the subjects that they might be using to gain some kind of sense of data from them as well. So I think that's really important. I think, Liz, that comes back to again how sociology has approached um AI in those contexts. I think one of the things that interested me was I read this morning on the OneKey website was that students from lower socioeconomic backgrounds are more likely to experience AI as a production tool, and students from higher socio-economic backgrounds are more likely to experience it as a learning tool. So there's that real different sense of what it is that we use AI in terms of producing material, producing content, and then also how it's used then as a learning tool as well. I wonder if that's something that obviously the SBS Group for Sociology were concerned with, those kind of structural inequalities again.

Liz Cain 12:29

Yeah, absolutely. Um we we talked quite at length about about the the inequalities that that um Gen AI can um serve to reproduce as well. And and something we were very mindful of is the digital skills gap that can um emerge through the use of of um Gen AI. I think one of the things that we we were mindful of as an advisory group is the way that sociology as a discipline can um support students to develop creative and critical skills and to scrutinize inequalities. And we felt that these were skills that will stand students in good stead when engaging with uh generative AI. So we were also, as Andrea said, we were mindful of um creating um guidance that will last because Gen AI is obviously such a very fast-moving um area at the moment. But what we wanted to do was to encourage students to engage with AI and to be aware of the way that um Gen AI can be used to support learning, with the the uh importance on what we can do to encourage some ethical reflection and a level of criticality within the use of um AI, including how it can be used to marginalize and heighten inequalities. I think what we we were talking about the way that uh Gen AI can be used to support employability, and that this is something that future employers are very likely to want to um the students and graduates to have a level of understanding and literacy around. So it's really important that we encourage engagement with uh Gen AI and to build that in where we can to um programs and courses, um, to embed where we can to with with the intention of reducing inequalities where possible.

Social Policy AI And Digital Welfare

Dr Andy Smith 14:42

Yeah, thank you, Liz. And I guess Lee, very similar for social policy, looking at those kind of structural inequalities that can arise, but also some of the issues around AI in terms of things like what's called cognitive offloading and that whole dichotomy between using it as a production tool and a learning tool, again, is something that I think probably the group had a lot of discussions about.

Dr Lee Gregory 15:03

Yeah, as you can imagine, with an advisory group, we have lots of people from different institutions, all of which have different institutional policies about how to address AI. So it was interesting to bring in, you know, that into the debates. And I think similar to what's already been said, our main concerns ended up being focused on ethical and critical treatment of AI and encouraging reflective use of AI as well. You know, we discussed in detail in line with other parts of the SBS that things around biases, as Hugh mentioned, um, are concerned with often quite Western-centric um outputs from AI. Lots of this is sort of like ignored by AI outputs, um, as well as like ethical and environmental implications of using AI. So there was you know that concern in terms of how we encourage um institutions when developing social policy courses in programs to think you know about that critical treatment of any use of AI. But I think we also were aware, as Liz was just saying at the end of um her section just then, that there's a link with AI to the employability theme as well. And I think for social policy, it's being aware of how that use of AI is part of a wider sort of digital welfare provision, digital social policy, governments, um, service providers will be integrating AI in lots of different ways into their governance structures, into their welfare delivery systems. So it's not just about thinking through how students use AI, whether that's as a tool for to produce work or as a learning opportunity, but also getting them to think critically about how that's part of a wider digital welfare state and how governments are using AI to deliver welfare outcomes. So I think that's also a key thing which featured in our debates. Yeah, thank you, Lee.

Dr Andy Smith 17:05

And I guess it comes back again to what you said earlier about how graduates in art and design, you know, they're going to be entering um a world or an employment area where those kinds of um AI-supported tools are going to be driving a lot of kind of design frameworks in the future. And it's about understanding how they can use those in a way which is supportive and ethical. But how do we protect both intellectual property of designers in an AI world and how we can be sure that the work that's being created is still generated by the individual uh human rather than by uh an AI tool or a large language model?

Professor Hua Dong 17:49

Around that, we actually decided not to be too descriptive because at the moment AI is moving so fast. So we think when the SBS is published, AI has already moved on. What we wanted is the principles of attitudes towards AI. We are using it as one of the tools. Uh, and we are not over-relying on that. And we have a critical uh way of thinking about it, how it's going to shape the future. So, how we collaborate with it, how we interact with it, being aware of its potential bias, being aware of the interaction, the trust, you know, all these data sets, and even being aware of the resource it consumes, because AI is going to cause a lot of energy consumption. Are we um thinking about it when using AI? So, what we propose is a balanced approach, not over-relying on AI, but we are embracing AI because it is a very useful tool for ident design.

Dr Andy Smith 19:00

Yeah, thank you. Is that the same as well for some of the other subjects as well, in terms of getting that balance right?

Liz Cain 19:05

Yeah, absolutely. Yeah, I'm um um I think for sociology, we we very much talked about the um the importance of a balance, of encouraging students to um engage where they want to, um, because we recognize that some students won't want to, but where they want to to engage with it, but also be mindful of the um impacts, you know, the the ethical uh implications, the sustainability implications. Yeah, I think I think we we talked quite a lot about the the inequalities that come that can be um uh present with the use of AI, whilst recognizing also that it's a really important tool for students to engage with, and there is an expectation around that around it going forward.

Dr Andy Smith 19:54

Yeah, I think Lee, as you said, you know, you've got so many different institutional policies around AI, some of whom follow similar models, such as a kind of two-tier system or traffic light system. But actually, what you needed to do, as you know, Hugh and is already mentioned, is create a kind of set of principles around that kind of effective and ethical use.

Dr Lee Gregory 20:16

Yeah, and I think that's what the social policy SPS intentionally seeks to do, and it sounds like it's the same with others in the chat as well, that we don't want to be too prescriptive, because as already been said, Gen AI is going to move much quicker than publication cycles and discipline development. So we need to set out primarily for us is that you know that critical reflection of output. So it's not so much a concern about whether it's being used or not. Again, students will vary, as uh Liz has just said, in whether they want to use AI or not. But I think it's about trying to ensure its use doesn't erode that independent critical thinking of students, their reasoning skills, even just their willingness to read materials and engage with it themselves. You know, this is where AI I think potentially has more risks for academic development, is that it can be a shortcut for many students in developing activity, developing work, which you know we don't we want to try and resist. But as I said, it's also something they need to be able to use, they need to be able to develop practice around and also critical practice. So be aware of its limitations, being aware of its um where its practical implications can be, but as Hua said, aware of the environmental costs for doing that as well. And I think this is where, again, you know, some of the discussion we had was, you know, broadly around, you know, in thinking about authentic assessment designs and how AI might relate to elements of that as well, you know, as a is an assessment tool where you can be then more critical of its output, perhaps.

Dr Andy Smith 21:56

That's the other thing I just want to just find finish on, Andrea, really, with the JN. AI debate is around it's not only going to affect the way students kind of consume or understand that relationship between knowledge and conceptual understanding, but also it's going to change the way course teams and providers approach how we assess students on meeting learning outcomes around conceptual knowledge and understanding as well.

Andrea Collins 22:24

Yeah, absolutely. And that's something that we debated at length as part of the advisory group. Think in particularly about the importance of the relational element of social work and the relationship base and the skills that students need to demonstrate, including, I mentioned earlier, the concept of you know defensible decision making. How do you defend your professional decision? You might use tools to help you reach that decision, but in a court of law, you're taking the stand. It's you that's got to be able to articulate that. So whilst you might have used something as a tool, you still then need to own the decision and you still need to be able to demonstrate that skill. And at the moment, Jen AI can't do that for you. I say at the moment because who knows what the future's gonna hold. Um, but yeah, so we've tried not to be too prescriptive, but also to balance that and to think about what the assessment strategies might then look like. Thinking, you know, about more authentic assessment, the use of viors, for example, um, you know, the use of problem-based learning, um, you know, problem-based type assessments. Um, yeah, so thinking about how we really capture the essence and the spirit of the relational element of the profession of social work.

Rewriting Benchmarks For Fast Moving Disciplines

Dr Andy Smith 23:42

Thank you, Andrea. Yeah, so that's a really helpful discussion on generative AI. I just wanted to slightly change our focus a little bit now in terms of looking at the subject benchmark statement as a whole. And I'll come to Hue first. In your sense, and in terms of the work with the advisory group, what did they feel were the most important changes or need to recognize uh differences in art and design education that's in this statement as opposed to what was produced uh 10, 12 years ago?

Professor Hua Dong 24:16

That's interesting because at the beginning we had two options. One is to revise and update the old version, and the other is to start from scratch. So the advisors discussed and we decided to we need to start from scratch because the last one was a long time ago, especially for art and design. Things have moved so fast. So almost everything we wrote is new. Uh, but we referenced the past SPS, and we also horizontally referenced the cross-cutting themes already published by other relevant disciplines like architecture music. So there's a lot of work by the Domain experts, 16 advisors, seven advisory meetings, more than 400 hours of writing, discussion, and revision. And we decided to have a very concise table to um to show the attributes and skills. Uh that took a lot of time, but the result is uh great because you can just have a table and you know threshold a reach and excellent. So I I think um in terms of what's new, uh fundamentally um, you know, what we discussed is what are the common attributes of so many different disciplines. And we are very pleased. It's not easy, but uh we achieved that. We were able to articulate what are the common skills and attributes. That would be extremely helpful for employers and for students and academic institutions when they use it as a reference.

Dr Andy Smith 26:03

So, yeah, thank you for that really uh interesting and very informative discussion around generative AI. I think it'd be interesting just to talk a little bit about how each of your individual subject benchmark statements has approached the significant changes that have happened in the discipline over the past 10 years since the last publication. So I think it'd be helpful just to just to really clarify what those what were the significant differences that the group needed to focus on or thinking about how you might future proof the statement in the context of the subject discipline. So, Andrea, I'm gonna come to you first.

Andrea Collins 26:43

Sure, thank you. Um in terms of changes, we tried to use some of what worked really well in the previous uh subject benchmark statement. We really did take the approach that we didn't want to reinvent the wheel. That said, we've got a plethora in the profession of different standards, um, including standards set by the four regulators that we worked with. And what we tried to do was to capture the overarching issues and central themes and the requirement from all of the regulators across the four nations. One of the things that we were really, really keen to do was to you know maintain the position that social work is both a practice-based profession and an academic discipline, and that central to that are the principles of social justice, human rights, and collective responsibility, as well as respect for diversity and working with the concept of inequalities and oppression. And what we really wanted to capture was that social work frequently requires practitioners to engage with individuals, communities, and systems to address challenges injustice and inequalities with a view to enhancing well-being. So we really wanted to build on the international definition of social work. Um, what's very different in this current SBS, certainly the inclusion of the standards themselves, which, as I've mentioned already, capture the generic nature of social work, but also the nature of social work across a range of different employment settings, not just in a particular area or field. And we really wanted to stress that courses should prepare graduates to work across multiple sectors, whether or not they choose to use the protected title of social worker, because we recognize that social work practice is undertaken in a range of diverse settings. And we wanted to really give due regard and consideration to the current contemporary issues and challenges in the profession itself, including the complexity and implications of a changing political landscape. What was very, very different for us this time was the inclusion of the cross-cutting themes. Very different in as much as they've all got their own sections. Arguably, the cross-cutting themes are integral to social work as a profession itself and ought to be integral to all courses. But we thought this was a real opportunity for courses to start to think about what they might do to build on this and include them. Thinking about the concepts of inclusivity, accessibility, sustainability, entrepreneurship, and what that means around graduate outcomes, including how we use, as we've mentioned earlier, gen AI and what that means in the profession, but also for social work courses and how we enable our graduates to be digitally competent and ready for the requirements of professional practice. So, what what it did was it enabled our group to reflect on emerging developments, opportunities and challenges for the profession and for educators.

Dr Andy Smith 29:59

Yeah, thanks, Andrew. It's really helpful. Obviously, you know, there in order to be a registered social worker, you do need to be qualified with a degree in the subject, and that was a very strong kind of focus of the um of the statement in terms of getting those kind of overall standards right, uh, in terms of what the expectations of graduates are. Like as you say, some graduates may go into being um a social worker and others, but there's also diversity of other opportunities as well. I think Liz, again, you know, with sociology, there was a really interesting approach to the cross-cutting themes and the kind of changes that happened, but you also introduced it, introduced a new cross-cutting theme as well that was unique to sociology as well. So you might want to talk about a little bit about that as well.

Liz Cain 30:44

Yeah, thank you, Andy. Yeah. Um, again, as others have said, we had a really good starting point with the previous benchmark statement. Um, and and we we wanted to um to learn from that as a as a source of good practice where where we could. And as others have said, the the framework that was provided by QAA really gave us the opportunity to reflect on the way that we structure the the sociology programmes. As you say, one of the things that we decided to do as an advisory group is to include the theme of internationalisation. Um so whilst we have the specific inclusion of the cross-cutting themes, we felt that internationalisation was an important theme for us to include for sociology. Really to encourage an internationalised sociology curriculum, um, supporting students to understand a range of global perspectives. Um, we also felt that this responds to a need for shared cross-cultural learning and the mutual benefit of this approach as well. I think one of the things that perhaps is is different from the the previous statement is the the use of the cross-cutting themes, I think for us, really helped us to reflect not just on the way that on the offer of sociology programmes and the way that we structure them, but also the way that students will access and engage with the subject. Um, and this is built into the statement, I think, through so, for example, through accessibility, through the the discussion of EDI, of of um sustainability. There's more here as the opportunities for students to um think about the way that they engage with the subject.

Dr Andy Smith 32:32

Yeah, thank you, Liz. That's extremely helpful to emphasize that importance of internationalization as a separate cross-cutting theme and what that means for sociology um departments, not only in the UK but in other jurisdictions as well. Lee, again, social policy again had a very particular approach to the development of the subject benchmark statement, and particularly any changes that might may have been noted since the last review as well.

Dr Lee Gregory 32:58

Yeah, I think when we started, myself and the deputy chairs had a discussion about whether we were going to be doing just an update of the previous benchmark or more of a revision. And initially we thought it would just be an update, but as we got into it, more and more started to be revised. And I think, as others have said, the cross-cutting themes were one of the triggers for that and a very useful trigger for some of that thinking. But our starter point ended up actually reflecting more on how we'd define the discipline because previous benchmark statements hadn't really crept into that territory, and I think if we hadn't been on a strict timetable to get the SPS done, we'd probably still be debating what we mean by social policy today because it's something which would never be um fully agreed on. But we also integrated into this the you know awareness of polychrisis and the fact that welfare provision is responding to multiple challenges at once. It's not just one challenge at a time. So I think primarily then we've, you know, we've it's that front section of the SPS which has seen the most revision. Um we've introduced that definition, we've linked it to this idea of polycrisis, we've brought in those cross-cutting themes, and where appropriate, we've integrated those themes later into this the statement as well, but we've kind of left implicit that those themes are cross-crutted and they should feature in all sort of curricular design initiatives. Apart from the AI discussion we've already had, I'd say the other sort of key thing we've introduced this time around was the new master's level uh sort of criteria and benchmarks. Um, those hadn't existed previously, but kind of reflecting the nature of the discipline, a lot more provision of social policy is at postgrad taught level now. So we felt it was really important to develop those standards for um increase the numbers of PGT students, and I guess as well, sort of reflecting on a lot of the discussions we've had, trying to integrate more global social policy perspectives. Typically, the discipline's history has been, you know, the UK welfare state, which doesn't really reflect a lot of the global and comparative work that happens in the discipline now. So we've tweaked some of that within the statement and also try to really emphasize that climate change, sustainability, eco-social policy factor as well. And I guess the other aspect, which I feel was probably in previous statements that we've been able to bring more to the foreground, relates to the use of authentic assessment and real-world professional skills, which a lot of our graduates will need when they enter into that sort of policy analysis and policy-making world.

Thanks And Where To Download

Dr Andy Smith 35:41

Yeah, thanks, Lee. Really helpful to emphasize um those changes to not only the standards but also um the emphasis of the new statement around uh defining the content of it as well. I just want to bring the podcast to an end now. I just want to say a huge thank you to Hua, to Andrea, to Liz, and to Lee for their contributions today. Um, I think it probably is helpful to say that the work couldn't have been done without um the contributions of your advisory groups who really wrote, developed, drafted the statement. And again, QA is a huge thank you to everyone who's involved in the advisory groups and giving us consultation feedback in order to develop what we hope are four statements that really reflect both what the uh subject areas and disciplines are dealing with on a pedagogic basis in terms of um those contexts around learning and teaching and assessment, but also hopefully defining those graduate standards for students that are up to date and reflective of real-world practice and the employment opportunities that students from the disciplines will go into. So I'm sure you'll all agree with me. A big thank you to everybody involved in the advisory groups as well, uh, and of course, you know, the deputy chairs that supported you all so very ably as well. So thank you for that. Um and please do access the subject benchmark statements on the QA uh website. They're available now to download. Um, please do go and have a look at them, and um I hope that they will support you in the work you need to do uh in the future in terms of developing your curriculum, your teaching and learning processes, and supporting really good student outcomes, which is why we're all here. So, thank you again to my guests, uh, and hopefully we'll see you again very soon.