Category: Teaching & Learning

  • Regulation builds walls between different levels of education, but universities can build bridges

    Regulation builds walls between different levels of education, but universities can build bridges

    Education in England remains segmented by regulation.

    Schools operate within Ofsted’s education inspection framework and the statutory regimes of the DfE. FE colleges navigate the new suite of Ofsted frameworks alongside funding and skills accountability structures. Universities face OfS oversight, TEF metrics, and the expectations of the professional standards framework (PSF).

    Even within universities, initial teacher training (ITT) can sit slightly apart. It is tightly regulated, operationally complex, and often detached from wider higher education teaching development.

    This fragmentation undermines the very professional identity that all sectors claim to cultivate. Educators, whether in early years, FE, HE or the workplace, share core capabilities: pedagogical reasoning, reflective practice, evidence-informed decision-making and relational skill. Yet current inspection and quality structures often privilege compliance over coherence. The new regulatory climate – with Ofsted’s expanded reach and the Office for Students’ growing emphasis on outcomes – risks hardening rather than healing these divides.

    Connected teacher formation

    The development of educators should be understood as a connected professional landscape spanning all phases of education. Early-years practitioners cultivate curiosity and foundational learning; FE teachers integrate academic knowledge with technical and vocational practice; HE staff foster critical inquiry and disciplinary expertise; workplace trainers translate theory into competence and innovation.

    These contexts differ, yet the core professional capabilities – reflective practice, relational pedagogy, and evidence-informed judgement – are deeply aligned. It is this alignment that offers the potential for genuine coherence across the system.

    Yet policy and regulation often pull in the opposite direction. Current agendas, including the post-16 white paper and recent ITT reforms, prioritise measurable outcomes and workforce supply. While these imperatives matter, they risk reducing professional formation to a compliance exercise they privilege evidence collection over reflection and credentials over capability. Entrenching directive, overly prescribed curricula that constrain professional judgement rather than deepen it.

    The challenge for higher education is not to reject accountability, but to reclaim its meaning: to own, shape, and model what intelligent, developmental regulation could look like in practice for our educational professionals.

    Connecting silos

    Higher education institutions are uniquely positioned to reconcile accountability with professional growth across sectors. They already engage in ITT partnerships with schools, support FE teacher education through validated programmes, and offer HE teaching qualifications, from PGCerts to Advance HE fellowships.

    Yet in practice these streams often operate in splendid isolation, reinforcing sector barriers, constraining professional mobility, and limiting opportunities for genuine cross-sector learning.

    Recognising teacher formation as relational and interconnected allows universities to model genuine professional coherence. QTS, QTLS and HE-specific qualifications should not be seen as separate territories – but as mutually informing frameworks that share a commitment to learning, reflection and the public good. At their best, reflective and research-informed practices become the collaborative engine that drives dialogue and professional mobility to connect schools, FE and HE teaching, fostering shared inquiry, and generating innovation that travels across boundaries rather than staying within them.

    The central challenge is one of narrative and ownership. Policy discourse too often frames teacher education as a workforce pipeline and a mechanism for filling vacancies, meeting recruitment targets whilst delivering standardised outputs. While workforce priorities matter, they must not be allowed to define the profession. The new Ofsted frameworks for ITT and FE, and the emerging regulatory language in HE, offer a moment of reckoning: will these instruments shape teachers, or will teachers and universities shape them?

    Universities have the intellectual capital, research capacity, and civic role to do the latter. They can reposition teacher education as the means by which professional agency is restored. They can demonstrate that robust accountability can coexist with autonomy, and that inspection need not stifle innovation.

    As I’ve set out, ITT, education and training, and HE teaching frameworks share a foundational logic: reflective practice, evidence-informed professionalism, and a commitment to learner outcomes. Treating these frameworks as interdependent rather than siloed gives HEIs the permission to shape, not just satisfy, regulation.

    Bridging the gaps

    The spaces between sectors – the school-to-FE transition, FE-to-HE pathways, and workplace interfaces – are where professional formation is most fragile. Policy and inspection regimes often treat these spaces as administrative handovers, yet they are precisely where higher education can add value.

    Universities can convene cross-sector networks, support shared professional learning, and promote collaborative research that spans education from the early years to lifelong learning. In doing so, teacher education becomes both the hub and the bridge: a central space where insight, evidence and practice converge, and a connective route through which ideas, people and purpose move freely.

    When universities play this role with intent, they enable knowledge, skill and reflective practice to travel with educators, strengthening the coherence of teaching as a truly lifelong, connected profession.

    Looking forward

    Teaching is the connective tissue of education, yet current regulatory and inspection frameworks continue to partition the profession into sector-specific silos, limiting transitions and weakening shared professional identity. The post-16 white paper, ITT reforms, and evolving HE teaching frameworks present more than compliance obligations – they offer a pivotal moment to restructure teacher education towards collaborative, cross-sector and shared professional agency.

    HEIs are uniquely positioned to seize this opportunity. By bringing schools, FE, and HE into constructive dialogue, aligning teaching pathways, and engaging inspection regimes strategically, universities can model a profession that is both coherent and adaptive. In doing so, they can collectively lead the sector in addressing complex challenges, ensuring teacher education supports not just quality, but innovation, inquiry, and resilience across the system.

    The pressing question is this: if teaching is the thread that binds the system, will higher education step forward to unite the sectors, shape regulation, and demonstrate what it truly means to teach without borders?

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  • AI is challenging us to relocate our sense of educational purpose in the outward-future rather than the inward-past

    AI is challenging us to relocate our sense of educational purpose in the outward-future rather than the inward-past

    As the debates and discussions around use of AI continue to develop, I reflect that, perhaps too often, the questions we ask as educators about the impacts of AI can be too small.

    There seems to me to be a current over-preoccupation with inward-facing considerations of the impact of AI on our own practices and processes: How we can manage the risks of academic misconduct, how we make our assessments a bit more authentic, how we quality assure students’ development of “AI skills”. I don’t deny that these are important and timely questions, but I think they miss the bigger (knottier) purpose-led picture.

    As AI continues to infuse our work in a variety of means and ways we seem sometimes too focused on management and adaptation of processes, rather than working strategically and purposefully to define broader outcomes which face off into the professional and graduate futures of our students and the world they will occupy and shape over the next 50 years.

    Until we start asking the bigger questions about the more fundamental challenges to educational purposes that AI brings in its wake, we will not be in a position to understand the shifts in educator capabilities and competencies and indeed professional identities that such a paradigm shift will necessarily require.

    Recently, with Prof. Nick Jennings, I argued that we can see two “swim lanes” emerging in AI: one focused on process optimisation and efficiency; one on invention and co-creation. Both are useful, but they require very different things from educators.

    AI literacy for optimisation

    AI tools offer compelling possibilities to support students with personalised learning support, rapid retrieval of relevant information and coaching prompts for personal and career development. I don’t see these tools replacing human academic and student services professionals; instead they offer a degree of personalised insight and augmentation to human-centric services.

    Similarly, AI tools can assist with many of the functions of teaching and learning “delivery”, offering ideas for small-group activities, generating reading lists or other learning resources, offering prompts to structure discussion, rapidly processing student feedback, and so on. Again, this is an efficient, step change augmentation to the spectrum of digital tools that can support effective learning and teaching. Educators will adopt these if they find them to be useful, and according to their disciplinary culture, and their personal orientation towards technology in general.

    Just as we have adapted to email or MS Excel (other software is available) as baseline administrative tools used in organisations and businesses, over time I see that academic workflows will no doubt evolve in response to collective learning and accepted wider practices about the usefulness and effectiveness of various AI tools when applied to different elements of academic practice. Some tools might genuinely make academics’ lives easier; others may promise much and deliver very little.

    From an institutional perspective it makes sense to curate a flow of discussion about the adoption of AI tools for learning, teaching and student support. Doing so allows for the dissemination of useful practice, contributes to collective understanding about AI’s capabilities and limitations and, optimally, ensures that where AI tools are adopted they are applied ethically and in ways that do not compromise academic quality.

    AI literacy for reimagining education futures

    With the potential benefits of AI for optimisation duly noted, I don’t think that is the conversation that is going to be the most material for education leaders in the next few years. For me, AI does not represent a specific set of digital capabilities that must be mastered so much as it points to a future that is fundamentally uncertain, and subject to tectonic disruption.

    That loss of predictability speaks to a very different set of purposes and outcomes for education – less the acquisition of a body of knowledge than the development of high end human competencies exercised and mediated through a developed technological literacy, all underpinned by a disciplinary knowledge base.

    Every new technology, from writing to print to the internet to large language models has prompted a reconsideration of the relationship between educational purposes and disciplinary knowledge. Over time, instead of a student “coming to the discipline” as an apprentice and an assumed future practitioner, disciplinary knowledge is increasingly deployed in the service of a broader range of student outcomes – the discipline “comes to the student.” This is also increasingly reflected in portfolio careers in which core knowledge is rehashed, redeployed, recontextualised and directed towards the challenges of the world and of the workplace, none of which are solved by a single discipline. The difference between previous shifts and the paradigm shift being ushered in by AI is the speed, volatility and unpredictability of what it will do. We are in uncharted waters and, if we are honest, we are not really sure where we are headed or how best to help shape those future outcomes and destinations.

    Despite these shifts, or perhaps in part because of them, the idea of the professor still defaults to the guardian and steward of disciplinary knowledge. Recognising that the strength of UK HE in particular comes from a tradition of being organised around somewhat compartmentalised deep disciplinary knowledge, this conceptualisation has remained remarkably consistent even as higher education has become more widely available and serving purposes beyond the passing on of knowledge.

    In this sense AI can never (and should never) “replace” academics as stewards of disciplinary knowledge, but it should prompt a deep examination of what that reconfiguration of the relationship between knowledge and education purpose looks like for the different disciplines – and the moments when students need to cross disciplinary boundaries in service of their potential futures, rather than the futures we imagined when in their shoes.

    The questions and discussion I am interested in curating asks academics about the potential shape of their discipline and its associated professions in 50 years: What does it mean to think, and “do” your discipline with and alongside AI? What does AI do to the professional practices and identities of the professions allied to your disciplines? The answers to such questions are more readily imagined through contemporary cutting edge research agendas than by established approaches to engaging students with existing bodies of knowledge.

    It is only in light of our imagination of the possible futures that await our students that we can start asking what kind of educational environments and approaches we need to build to create the conditions for the development of the skills sets, attitudes and competencies they will need.

    My hunch is that we will collectively need to “unwire” ourselves from “standard” PG Cert and PG Dip teaching development tracks and be prepared to look outside the classics of higher education pedagogy and literature, including to primary education, and innovative workplace CPD to find the approaches that work best. While we might retain a foundational basket of knowledge and skills required for entry to the academic profession, I think these will resonate more strongly with a broader set of high end human competencies than with the traditional skills associated with teaching development.

    It is likely we’ll need to take a more experimental, co-creative approach to the higher education pedagogy, which engages in the outward facing futurology of graduate paths across the next 50 years as a fundamental starting point for considering our own purpose-led practices. In this we might then retain concepts and theories that serve those purposes while discarding those that have outlived their usefulness.

    Sam Grogan will be among the speakers at Kortext LIVE education leaders event on 11 February in London, as part of a panel discussing the Wonkhe/Kortext project Educating the AI Generation. Find out more and book your free spot here.

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  • We want to make that heart beat more strongly

    We want to make that heart beat more strongly

    When people look at the apparently frenetic itineraries for our SUs study tours, we’re often met with confusion about why we would even attempt to visit so many cities in so few days.

    This year we managed to fit in fifteen university cities in five days across Germany, Switzerland, France, Luxembourg, the Netherlands and both halves of Belgium – avoiding low bridges and Belgian traffic, and re-routing around the worst of Storm Goretti on a chartered bus whose toilet had frozen up.

    In total we probably spent about 24 hours on the road with our driver Rene, which on first sight looks like an agenda full of dead time which could have been better spent immersing more deeply with our numerous hosts.

    Sometimes the journeys are a good opportunity for a nap, or to sneak a look at emails, or to catch up on the gossip or just to stare out of the window at pretty houses in Spreitenbach.

    But that time on the bus can also be a great time to look at and reflect on what we don’t see, the things we’re not told, the things that don’t make it onto the slide deck or into the tours and talks that we’re treated to by our largely student hosts.

    Some of us started the week in Munich, which provided the excuse to while away at least one journey looking at the Technical University of Munich (TUM)’s Agenda 2030 strategy and teaching model.

    On most programmes students choose from a bunch of “Plug-In Modules” – short courses designed to give students from one discipline a window into another – and one of the most popular ones is called “Politics for Rocket Scientists”, an introduction to political science for people who aren’t political scientists.

    It’s a three contact hours a week, 6 ECTS (12 UK CATS) “lecture” module, an hour of which is chalk and talk by research-active political scientists, while students from later semesters in politics run “exercise” sessions.

    Assessment takes the form of a ninety-minute closed-book exam – mainly a multiple choice quiz with a couple of open-ended questions – and it’s graded on the German system of 1.0, 1.3, 1.7, 2.0, 2.3, 2.7, 3.0, 3.3, 3.7, or 4.0. And you can retake that exam unlimited times until you pass.

    Every year that it runs, a joke which we reckon is funnier in German is used to open the first module:

    Welcome to Politics for Rocket Scientists. We also run Rocket Science for Politicians, but that one is less popular.

    TUM has won awards for its teaching, where the academic model reflects its guiding principle of human-centered engineering – aimed at providing students with sufficient “integrative valency and educational capacity” to benefit the natural, engineering, life and economic sciences as well as society more generally.

    The structure – which sees bachelor’s students only studying for about half of their credits in their “major” – also sees students separately acquire credit in “soft” skills, academic induction, out-duction to the labour market and electives in related subjects.

    Students who are earning while learning on the peer teaching team are trained in the latest pedagogical techniques and take part in the university’s annual teaching innovation competition, all of which is both great for their development and for improving outcomes.

    The structure ensures that some of the research active academics can continue their work without having to sustain entire degree programmes or departments framed around their own specialism. And the university’s student-staff ratio? 40.7.

    Students need some context

    There were plenty more like that. At our first official stop – Universität St. Gallen in Switzerland – every student, regardless of their main subject, has to complete 24 ECTS of “Contextual Studies” chosen from areas like Creativity, Technologies, Cultures and Responsibility. Neither the SU President nor his huge team of elected student officers and “teamies” were paid – but had the time to undertake their roles because the learning from them counts in the structure.

    At the University of Twente in the Netherlands, the final third of the bachelor’s programme is genuinely elective – minors, free choices, preparation for different master’s routes. Students also get real control over how they learn – which projects to pursue, which workshops to attend, and when to study. Much of the scaffolding is labelled “Student-Driven Learning”, and almost always involves problem-oriented group project work that students enjoy rather than resent.

    In France in 2017 the government launched Nouveaux Cursus à l’Université – New University Curricula – with funding distributed through competitive bids to fund undergraduate curriculum transformation. The core concept is “progressive specialisation”, where students specialise gradually rather than choosing narrow tracks at eighteen, with built-in gateways between different qualification routes, and flexible routes that can combine higher technical and academic tracks.

    At KU Leuven in Belgium, the final four weeks of each semester are reserved for “lab courses” where students integrate knowledge across subjects and connect it to society. At the University of Maastricht, students don’t spend hours in lectures – they meet twice a week in tutorial groups of ten to fifteen, working through cases where assessment might be participation, presentations, essays, or exams, but where the emphasis is on whether students can use what they’ve learned.

    Bits of all of this exist in the UK, of course, and there’s plenty to be proud of when we compare some of the facilities, support systems and services that we have built in the name of “student experience” back home. But while all of these systems are under financial pressure (everyone in Europe, it seems, wants a better education population but taxpayers are reluctant to fund it), what we didn’t find was a hurtle towards “do it all” 15 ECTS (30 CATS) modules to fit a forthcoming funding system and a rapid erosion of student choice.

    More often, we found ways of delivering efficiency that were about giving students educational and social responsibility.

    Maybe their Bologna-addled minds have been warped into collaborative conformity while the UK forges ahead alone by bolstering its reputation for excellence by overloading academics. But it was hard not to feel the impacts of isolation as visit after visit casually mentioned pan-European university alliances, compulsory mobility semesters, degrees that can be built from credit from multiple universities in multiple countries and systems that sustain student leaders whose English was often better than ours.

    At various points, we were asked what they might learn from us. What not to do was the theme of our answers.

    Money honey

    Sometimes on the trips, there’s things to steal. The pot of honey we were all given on arrival in Mulhouse was created by a project aimed at causing academic and vocational students from multiple universities to interact with craft and small industry experts in the region, with a beehive in the garden of the regionally-run halls. Maybe there’s a way to get something similar going back home.

    The international student spaces we saw in Wageningen and Leuven combined space for associations, facilities for cooking and seating for studying – as a set of (comparatively) skeleton set of staff to facilitate student-run study sessions, cultural nights and interaction both between international students and with those from the home countries. We’d face questions about risk assessments and students’ willingness to get involved – but there’s a pilot in there somewhere.

    The posters up in Strasbourg asking students if they thought all the hours they were having to work were “normal”, the student (and staff) arts centre in the middle of an ostensibly STEM-oriented university, the student-run city-centre study spaces projects we saw in different forms, the lighting and the furniture and the St Gallen symposium – they’re all worthy of a try, if we can find the time.

    Sometimes those long journeys between stops allow us to wallow not in possibility but its opposite – it’s the culture of the country, it’s a hundred years of history, it’s the funding system or the governance of student services away from the academic endeavour that produces the Truman show of magic in the powerpoints and presentations that must mask worse mental health problems and higher attrition than we enjoy in the UK.

    But sometimes the projects – like the one at the Eidgenössische Technische Hochschule (the Swiss Federal Institute of Technology in Zurich – were the antidote to such moments of pessimism.

    Easier and more enjoyable

    In the autumn of 2021, Sarah Hofer – a researcher who had previously documented how teaching methods rather than student ability explained vast gender gaps in physics performance – returned to ETH as a professor.

    She quickly got to know the student board at VMP – the maths and physics student association – which has been making studying easier and more enjoyable for its members for 80 years.

    Somewhere between an academic society and a set of course reps, it’s a bit of associative scaffolding that runs its own little welcome week, offers group social mentoring on arrival, provides old exams and organizes assessment preparation courses, and puts on poker and chess tournaments, fondue nights, parties and barbecues. And the VMP offers its members one free coffee a day at its lounge on campus.

    It also stages its own careers fair, holds formal representation on departmental governance structures including the Departement conference (the highest departmental body), teaching committees, and grading conferences where exam standards are set.

    It has working groups on sustainability and conduct, it has a project that focuses on equal opportunities through coffee lectures with professors, organises company excursions and social gatherings for computational science students, and supports international and master’s students with practical issues like housing and supervision.

    Events include weekly talks on theoretical physics, an undergraduate colloquium with student presentations and apéro (think wine, beer, soft drinks, nibbles, and light finger food), as well as social events like ski weekends, fondue nights, and poker tournaments. Its student magazine VAMP publishes twice a semester in print and digital formats. And so on.

    Unlike in the UK, where much of what it offers would be delivered for students by professionals in separate centrally-run departments inside student services or the SU, the assumption is that peer delivery backed up by the centre and associatively scaffolded at faculty level is good for the volunteers, good for belonging, good for innovation and good for students. Broadway musicals fail – school plays sell out.

    And for Sarah Hofer, it was the perfect partner for operationalising some of her research.

    No dumb questions

    The idea was simple – create “exercise class” groups aimed at students who self-assessed as having less prior knowledge and/or imposter syndrome, where students facilitating would spend more time on fundamentals and where a “there are no dumb questions” culture was explicit rather than aspirational.

    The pilot worked. Participants who might have been expected to underperform passed at higher rates than for the cohort overall, all via an intervention that was part-belonging, part-pedagogical and part-confidence building, changing the composition of the room so that nobody has to perform competence they don’t feel.

    Workshops train TAs to think about what stops people asking questions – the group composition means there’s less stopping them. The research had said teaching methods were the barrier, not student ability. The recognition that heterogeneous prior knowledge makes some students fall silent, and that silence compounds, had found an outlet in a student society.

    When Hofer left ETH for LMU Munich less than a year later, the initiative didn’t leave with her. VSETH kept running it. The SU now provides significant implementation infrastructure – recruiting student TAs, coordinating with departments, embedding it in their broader educational development work.

    A working group – AG Fokusgruppen – sits under VSETH and works through the faculty student associations. Klara Sasse, who became the key student lead, was simultaneously active in VMP (the maths and physics faculty association, established over 80 years ago). Her dual positioning mattered – she could advocate at university level while having credibility and networks within the specific departments where focus groups needed to be implemented.

    Departments have adopted it enthusiastically – Physics merged it with their existing Exercise Class Market infrastructure – but ownership remains with the SU. Klara has since become VSETH Vice President, VMP President, and Head of Communications at VSS (the national Swiss student union), and won second place in ETH’s individual Diversity Award 2024. The focus groups themselves won third place in the organisation category the same year.

    I could KOKO

    We heard so many stories like it during the week. They were rarely about responding to regulation, or delivering on KPIs, or lobbying the university to “provide” more for students. They were more often about students having the associative infrastructure – not so small as a course rep, not so large as a university-wide SU or student services department – to do things for each other.

    Sometimes, ECTS credits were on offer. Sometimes students were paid for their work. One system saw students financially supported to pause while serving others for a semester. But almost without fail, when we interrogated why those in front of us had got involved, the money or the time or the academic recognition were always second-order hygiene. The real answer was always that they wanted to be the person that had first helped them.

    At student social association KOKO in Maastricht, student chair Japke Zoon directs the board, oversees policy implementation, and maintains contact with Maastricht University, Zuyd University of Applied Sciences, the municipality, and other key partners. Sophie van Oosterhout oversees the bar committee, the club building, and safety during activities and parties.

    Both Japke and Sophie were viscerally impressive and eminently employable – but it wasn’t really the things in their job descriptions that mattered the most. In conversation, it was the student who needed support, the first year that was thinking about dropping out, the international student who felt lonely, and the neurodiverse students who found a way to socialise with those who weren’t. Sophie was responsible for changing a barrel, but she was really responsible for other students’ success.

    Cecile Kwekeu took the mic next – Secretary and Academic Co-Comissionier of SCOPE, the official study association of the university’s School of Business and Economics. She’s 20, originally from a small city in Germany, and got involved when she went to a Maastricht Business Days event:

    As Academic Commissioner, my mission is simple: make sure our events actually help you grow. Whether it’s soft skills like communication and networking or hard skills like analytical thinking, I want to create opportunities that matter – both now and down the road. This year, I’m heading up some exciting projects including the Symposium, Consulting Case Challenge, Business Case Challenges, Career Development Days, and our Brussels Trip.

    She also talks of building better systems, streamlining processes, and making sure her team can get the most out of student life. She and over 350 students like her across the university are helped by a bit of scaffolding that allows students to pause their studies to undertake an association board year or semester – and in turn, they support thousands of students to support others through projects, groups, committees and events.

    The cold never bothered me anyway

    None of it should be a surprise. Plenty of academic theory tells us that whole chunks of our lives have become increasingly hyper-organised, professionalised, and compliance-driven, adopting formal structures, metrics, and professionally-led processes that mirror “good organisation” norms but unintentionally erode amateur-led energy.

    Money, measurement, risk management, staffing growth, and symbolic compliance often displace informal, trust-based activity. There’s evidence from wider civic life that shows that declining volunteering, loss of social infrastructure and low institutional trust is part of a broader hollowing-out of associational life, and has deep impacts on mental health, trust in governments and attitudes to others.

    Increasingly, what we do in adult life is what students do – taking part in technically excellent but tightly controlled, professionally-run, highly transactional service provision – and in doing so there’s a crowding out of participation, a reduction in social solidarity and a widening of the intention–behaviour gap for those who might otherwise help others.

    Letting go is hard. The pressure on UK students’ time is real. The regulation demands safety, the funding follows the metrics, and everyone remembers that time when that thing went wrong before the grown-ups took control. But this is less about letting go, and more about creating the conditions for student success.

    Live and kick-in

    When Frans van Vught got elected as Rector Magnificus of the University of Twente back in 1997, he inherited a technical university with declining student numbers, fragmented departments, a huge hole in the budget and a culture that had attempted to fix things by doing more centrally:

    Campus life was bureaucratically controlled by a campus director. Not much was allowed, there were closing times, and students had to apply for permits for all kinds of things. I found that very unappealing. I felt that as a campus, or rather as a university community, we should be able to do better than that. Let the students organise things themselves.

    Many encouraged Van Vught to retain the systems and structures that had been built up, only to operate them more efficiently. Instead, he set about shifting the culture both academically and socially – designing structures and scaffolds that would sustain a collaborative community with benefits both for individuals too.

    And after his own study visit with some of his student associations to Queens in Belfast, he returned and set up the SU, giving it (against available advice) a raft of responsibilities previously assumed to be the university’s – all on the condition (agreed in a covenant) that they found student groups to run them.

    “Universities have to take care not to become a bundle of non-communicating hyperspecialisms”, he said on the day he retired – bearing the scars on his back from a radical restructure:

    [Students] are a very important part of the academic community and I think it’s important that they take their own responsibility… we have increased cohesion in student activism and increased the community feeling for the university as a whole.

    Today, the SU hosts a student-led outreach and talent development programme for secondary school pupils, a £0.5m student run “kick in” welcome programme designed to build belonging, study space facilities across the city and hundreds of other student committees that operate everything from student support to PC repairs to the world’s biggest case competition.

    The wider academic infrastructure helps. Every department gives space to an an academic student association on the basis that students need a “home” to work together in. On their courses, students work in multiple teams over extended periods, encouraging early peer bonding, a sense of belonging, and shared responsibility, reducing anonymity and social isolation.

    There’s an emphasis on collaboration, role negotiation, and joint problem-solving that develops interpersonal skills like communication, empathy, and conflict management, while the coaching role of staff an integrated authentic assessment structure strengthens confidence, creativity, self-efficacy, and emotional resilience by providing an environment where students learn from mistakes and high-stakes pressure is reduced.

    On the tours, we often pick up the differences in dual systems between elite universities and their old ideals of education for education’s sake, and newer players in the applied sciences who focus on labour-market prep. On paper, Twente ought to have been the most individualistic, transactional, skills-for-the-CV provider on the trip. But it wasn’t.

    The Netherlands has a much higher percentage of students working while studying than the UK. Belgian and French students are just as likely to be struggling with the costs of living. Students in Luxembourg find it difficult to afford their placements, and Bavarian students are attempting to rent the most expensive student bedrooms in Germany. Even Swiss students struggle to maintain the sort of student experience that their parents said was possible.

    But while HE and student funding was never far from the top of the lists of problems on the slides, it was also repeatedly obvious that the spaces and structures deliberately designed to create collaboration, engender responsibility and operate autonomously were helping to ensure that students were both transformed by their education, and were helping to transform both their university and their municipality as a result.

    Society concerns social relationships and civic participation. Social networks provide support and contribute to quality of life. It is also important that everyone can participate in society, and trust other people, the government and other institutions.

    Statistics Netherlands (CBS) reports that in 2024, 49.5 per cent of the population aged 15+ did voluntary work for an organisation or association at least once in the previous year – and it’s much higher for graduates. In the end, both in the university and the country, isn’t HE partly about the community you’re trying to create?

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  • Transparency about AI should be a sector-wide principle

    Transparency about AI should be a sector-wide principle

    Josh Thorpe’s recent Wonkhe article – What should the higher education sector do about AI fatigue? – captured how many are feeling about artificial intelligence. The sector is tired of hype, uncertainty, and trying to keep up with a technology that seems to evolve faster than our capacity to respond. But AI fatigue, as that article suggests, is not failure. It’s a signal that we need to pause, reflect, and respond with human-centred coherence.

    One of the most accessible and powerful responses to AI uncertainty is transparency. By taking a consistent approach to declaring AI use in work or assessment, many educators are taking a first step by simply declaring: “no AI is used in…”

    The statement alone supports development of trust between educators and students, and it can create space for dialogue. It’s not about rushing into AI adoption, it’s about being honest and intentional, whatever the current practice. From there, we can begin to explore what small, discipline-relevant, and appropriate uses of AI might look like.

    The journey starts with transparency, not technology. We need to support staff in engaging with AI in ways that feel ethical, manageable, and empowering. We mustn’t begin with technical training or institutional mandates. We must begin with a simple request to communicate clearly about AI use (or non-use) in our teaching, learning and assessment practices.

    Sheffield Hallam University has implemented an AI Transparency Scale as a communication tool that helps educators consider how they disclose AI use to students, and supports how they can clarify expectations for students in assessment. It’s a conversation starter which prompts educators to reflect on whether AI tools are used in their practice, how this use is communicated with students, and how transparency supports academic integrity and student trust. The scale is helping move from uncertainty to clarity. Not by simplifying AI, but by humanising and clarifying how we engage with it.

    Moving to transparency

    For educators wondering where to start, confident transparency begins with making AI clear and understandable within its specific context. Transparency builds trust and sets clear expectations for staff and students. A simple statement, even a neutral one such as “AI tools were not used in the development of this module,” provides clarity and signals openness. You might adopt a tool like the AI Transparency Scale where prompts can scaffold your communication of AI use or create your own local language. Even short discussions in course or programme team meetings can surface valuable insights and lead to shared practices. The goal is not just to disclose, but to create a shared understanding and practice.

    Engaging students in the conversation about AI and inviting them to share how they are using AI tools helps educators understand emerging practices and co-create ethical boundaries. As Naima Rahman and Gunter Saunders noted in their Wonkhe article, students want AI integrated into their learning – but they want it to be fair, transparent, and ethical.

    Listening and responding transparently reinforces trust. Together, explore questions such as: “what does responsible AI use look like in our subject area?” Consider where automation or analysis might add value, and where human judgment remains essential.

    Transparency here means being explicit about why certain tasks should remain human-led and where AI might play a supportive role. Positioning students as co-leaders in these discussions builds a stronger, more transparent foundation for responsible AI use.

    From individual burden to institutional strategy

    Josh Thorpe’s article rightly calls out the lack of institutional coordination and fragmented AI discourse. The burden of response has fallen largely on individuals, with limited support from policy, leadership, or infrastructure.

    To move forward, we need coherent institutional leadership that frames AI not just as a technical challenge, but as a support, pedagogical, and ethical challenge. By sharing our experiences, resources, and approaches openly, we can develop shared principles that can guide diverse practices across the sector. Finally, we need alignment with the changing nature of authorship, assessment, and professional competence in an AI-enabled world. Simon Sneddon goes into the need to prepare students for the world of (artificial intelligence-enabled) work in another recent Wonkhe article.

    Transparency offers a bridge between policy and practice. It’s a principle that can be embedded in institutional guidance, supported through professional development, and aligned with sector-wide values.

    As the Office for Students, Jisc, and other bodies continue to shape the AI landscape and how we navigate it, institutions must find ways to empower their staff, not just inform them. That means creating space for reflection, dialogue, and ethical experimentation.

    Transparency alone will not solve the challenges of AI in education, but it is a good place to start. The sector can begin to move from fatigue to fluency, one transparent step at a time.

    AI transparency statement: In developing this article, I used Microsoft Copilot to support the writing process. I provided original textual inputs, guided the reference of relevant existing materials, added additional sources, and critically reviewed and refined generated outputs to produce the final piece. This corresponds to level 3 of the AI Transparency Scale, indicating active human oversight, original content, and editorial control.

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  • Could the Lifelong Learning Entitlement usher in a new era of skills-based curriculum?

    Could the Lifelong Learning Entitlement usher in a new era of skills-based curriculum?

    As it stands the Lifelong Learning Entitlement mostly represents a reorganisation of higher education funding and systems for quite a lot of short term operational pain and very little payoff.

    But for institutions prepared to play the long game, it could represent a real shift in how higher education is configured and how it integrates with the labour market.

    That doesn’t just mean taking existing courses that were designed for three years of intensive study and breaking them up into constituent parts – though in some cases the ability to do that could offer a lifeline for students needing to earn before they can learn. The larger prize on offer is courses that are actively designed for the contemporary labour market, in which the building blocks of the curriculum are skills and work-related competences, rather than academic knowledge.

    Let’s acknowledge from the outset the false dichotomy – knowledge requires skills to acquire and apply it, and skills require a structured context of knowledge to be meaningful and applicable. But the “skills-based curriculum” is gaining traction around the world for a reason: primarily to address a perceived demand among students and employers for learning that is practical and applied, and that prepares students to succeed in the contemporary labour market, which requires a complex mix of technical and interpersonal skills. It promises more than the embedding of in-demand skills into a traditional academic curriculum; skills-based curriculum centres work-based skills as the primary learning outcome.

    Opportunities and risks

    One corollary is that the learning itself becomes more hands-on, project-based, active, and collaborative, in order to foster those skills. Students are very clear from the outset what they are learning to do and what the workplace application will be. As some employers turn to skills-based hiring practices, graduates can readily match their experience to employers’ expectations and demonstrate, with evidence, their competences, reducing the need for a long tail of additional experience to supplement the degree certificate in the name of “employability.”.The focus on authentic learning environments and assessments also goes some way towards AI-proofing the curriculum: AI can be deployed authentically in workplace-relevant ways, not used as a shortcut to evidencing thought.

    This all sounds fantastic and straightforward, even hyper-efficient. The relevance to the LLE’s intention of a more flexible, stackable HE model lies both in the notional desirability of education oriented towards work and employment, and in the efficiency and transparency of the relationship between skills developed through education, and work.

    But there are risks, too, for both providers and students. In the absence of any kind of agreed national (or global) taxonomy of skills, that could allow for a body of practice to develop around the pedagogies and environments that demonstrably allow students to develop them, any provider may claim to offer something “skills-based” with little in the way of evidence or robust quality assurance. In an open market, students may be drawn in by the promise of work-readiness, only to discover that their learning adds up to very little. Skills England has in the last few weeks published a new UK standard skills classification that addresses the first problem; the second remains open for solutions.

    The market for such provision in the UK remains untested; the current premise of the LLE rests on the assumption that existing programmes can be disaggregated meaningfully into modules that simultaneously offer something of value as a short course of study, while also contributing towards a larger qualification. While this may be true in some cases, it certainly will not readily apply to all. Introducing skills as a core outcome, while it may work quite well for a module or short course, opens up the question of which aggregated sets of skills can be said to be meaningful in a journey towards a substantive qualification. This is a significant challenge for higher education as it is currently configured, going far beyond the merely functional and operational, touching on the core purposes and processes of higher education and the need to manage carefully the consequences of bringing “skills” to the forefront of higher education pedagogy.

    More prosaically, all this active, authentic learning doesn’t come cheap, and it requires a strong relationship with employers to deliver, raising questions about whether it is possible to develop a high-quality skills-based offer at scale. And that’s before you start questioning what the regulatory implications might be.

    These risks are only risks, not insuperable obstacles – UK HE providers, such as the London Interdisciplinary School, have adopted a “skills first” model of higher education without incident. While appetite within the sector to develop a more skills-focused offer is variable, there are institutions – such as Kingston University – that have developed an explicitly skills-focused element to complement existing programmes, and others that are interested in the potential for reconfiguring or extending their offer around skills, especially in light of the creation of Skills England and the prospect of a more systematic approach to meeting national skills needs.

    What needs to be true

    But for this model to become more widely embedded across higher education providers, and to realise the potential of the LLE to facilitate innovation in curriculum content as well as delivery, some things that are not currently true will need to become so. At the Festival of Higher Education, together with Ellucian colleagues, we hosted a private round table discussion exploring what a student journey through a more skills-based, “stackable” offer might need to look like.

    Not everything needs to be done collaboratively all the time, but there are moments in which there can be greater strategic advantage in collective innovation than in being the first mover, and significant higher education innovation could be one of them. Working collectively creates greater security both for institutions and students that the offer is well thought through and robustly quality assured, and that it will be legible to prospective students seeking to explore their choices, and have credibility in the labour market. Pooling risks in this way could help to reduce the stakes in making the decision to roll out a novel kind of provision, and potentially allow for some sharing of start-up costs.

    One area that is lacking is better market intelligence – the assumption that there is a sustainable demand for shorter and stackable higher education courses remains unproven, and some investment in exploring the nature of that demand would help institutions to tailor their offer more effectively rather than spinning up provision that is at high risk of failure either because it does not recruit or because it does not adequately meet the needs of the people who are attracted to it on principle.

    In the domain of core learning and teaching there is a need for exploration of the pedagogic frameworks and approaches that can support a high-quality and academically robust skills-based offer. Some degree of consistency in approach to building pathways through programmes designed around skills could offer an alternative to reliance on credit as the currency that notionally allows for portability between providers and in practice is very hard to implement. Retaining student choice and the possibility of personalisation is typically important to students and providers alike, so there is a flexibility imperative there that it would be hard to tackle as an individual provider.

    Accessing this type of higher education, in this way, opens up the question of reimagining the “student experience” and the underpinning systems that can enable institutions to manage it. Students will need clarity about access to work – through placement, internships or joint provision with employers – the relationship between work, learning and skills development, and ultimately who is responsible for their experience. Access to services will need to be tailored to the student, and both students and providers will need to accurately keep track of modules completed, and skills acquired, and when.

    Curriculum management systems will need to allow students to chart their way through a particular pathway and register for modules, while incorporating guardrails to avoid students choosing pathways that add up to, in the words of one attendee, a “smorgasbord of nonsense.” Support for students in mapping or curating their chosen pathways will need to be built in from their very first module, and they would need to be able to request and access a “transcript” that details their skills at the point of completion of any module.

    Skills-based curriculum needn’t be stackable and stackable higher education needn’t be skills-based, but there is clear potential for synergies between the two. Just as skills-based curriculum is unlikely to replace traditional knowledge-based curriculum wholesale, modular study is unlikely to replace the full-time experience. That doesn’t rule out the possibility of significant change though.

    Opinion is divided as to whether the LLE will enable higher education growth through innovation and access to new demand, function to create some ease and flex in a system that will enhance access to those who find engaging with the current system a struggle, or neither (or something else as-yet-unanticipated). But as higher education institutions consider the future, growth and access seem like the right targets to be aiming for. Skills-based curriculum, if developed strategically and thoughtfully, avoiding “innovation theatre,” could be helpful in both cases.

    This article is published in association with Ellucian. Take a glimpse at the technology supporting the future of lifelong learning here.

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  • Reclaiming the narrative of educational excellence despite the decline of educational gain

    Reclaiming the narrative of educational excellence despite the decline of educational gain

    There was a time when enhancement was the sector’s watchword.

    Under the Higher Education Funding Council for England (HEFCE), concepts like educational gain captured the idea that universities should focus not only on assuring quality, but on improving it. Teaching enhancement funds, learning and teaching strategies, and collaborative initiatives flourished. Today, that language has all but disappeared. The conversation has shifted from enhancement to assurance, from curiosity to compliance. Educational gain has quietly declined, not as an idea, but as a priority.

    Educational gain was never a perfect concept. Like its cousin learning gain, it struggled to be measured in ways that were meaningful across disciplines, institutions, and student journeys. Yet its value lay less in what it measured than in what it symbolised. It represented a shared belief that higher education is about transformation: the development of knowledge, capability, and identity through the act of learning. It reminded us that the student experience was not reducible to outcomes, but highly personal, developmental, and distinctive.

    Shifting sands

    The shift from HEFCE to the Office for Students (OfS) marked more than a change of regulator; it signalled a change in the state’s philosophy, from partnership to performance management. The emphasis moved from enhancement to accountability. Where HEFCE invested in collaborative improvement, OfS measures and monitors. Where enhancement assumed trust in the professional judgement of universities and their staff, regulation presumes the need for assurance through metrics. This has shaped the sector’s language: risk, compliance, outcomes, baselines – all necessary, perhaps, but narrowing.

    The latest OfS proposals on revising the Teaching Excellence Framework mark a shift in their treatment of “educational gain.” Rather than developing new measures or asking institutions to present their own evidence of gain, OfS now proposes removing this element entirely, on the grounds that it produced inconsistent and non-comparable evidence. This change is significant: it signals a tighter focus on standardised outcomes indicators. Yet by narrowing the frame in this way, we risk losing sight of the broader educational gains that matter most to students, gains that are diverse, contextual, and resistant to capture through a uniform set of metrics. It speaks to a familiar truth: “not everything that counts can be counted, and not everything that can be counted counts”.

    And this narrowing has consequences. When national frameworks reduce quality to a narrow set of indicators, they risk erasing the very distinctiveness that defines higher education. Within a framework of uniform metrics, where does the space remain for difference, for innovation, for the unique forms of learning that make higher education a rich and diverse ecosystem? If we are all accountable to the same measures, it becomes even more important that we define for ourselves what excellence in education looks like, within disciplines, within institutions, and within the communities we serve.

    Engine room

    This is where the idea of enhancement again becomes critical. Enhancement is the engine of educational innovation: it drives new methods, new thinking, and the continuous improvement of the student experience. Without enhancement, innovation risks becoming ornamental: flashes of good practice without sustained institutional learning. The loss of “educational gain” as a guiding idea has coincided with a hollowing out of that enhancement mindset. We have become good at reporting quality, but less confident in building it.

    Reclaiming the narrative of excellence is, therefore, not simply about recognition and reward; it is about re-establishing the connection between excellence and enhancement. Excellence is what we value, enhancement is how we realise it. The Universitas 21 project Redefining Teaching Excellence in Research-Intensive Universities speaks directly to this need. It asks: if we are to value teaching as we do research, how do we define excellence on our own terms? What does excellence look like in an environment where metrics are shared but missions are not?

    For research-intensive universities in particular, this question matters. These institutions are often defined by their research outputs and global rankings, yet they also possess distinctive educational strengths: disciplinary depth, scholarly teaching, and research-informed curricula. Redefining teaching excellence means articulating those strengths clearly, and ensuring they are recognised, rewarded, and shared. It also means returning to the principle of enhancement: a commitment to continual improvement, collegial learning, and innovation grounded in scholarship.

    Compass point

    The challenge, and opportunity, for the sector is to rebuild the infrastructure that once supported enhancement. HEFCE-era initiatives, from the Subject Centres to the Higher Education Academy, created national and disciplinary communities of practice. They gave legitimacy to innovation and space for experimentation. The dismantling of that infrastructure has left many educators working in isolation, without the shared structures that once turned good teaching into collective progress. Reclaiming enhancement will require new forms of collaboration, cross-institutional, international, and interdisciplinary, that enable staff to learn from one another and build capacity for educational change.

    If educational gain as a metric was flawed, educational gain as an ambition is not. It reminds us that the purpose of higher education is not only to produce measurable outcomes but to foster human and intellectual development. It is about what students become, not just what they achieve. As generative AI reshapes how students learn and how knowledge itself is constructed, this broader conception of gain becomes more vital than ever. In this new context, enhancement is about helping students, and staff, to adapt, to grow, and to keep learning.

    So perhaps it is time to bring back “educational gain,” not as a measure, but as a mindset; a reminder that excellence in education cannot be mandated through policy or reduced to data. It must be defined and driven by universities themselves, through thoughtful design, collaborative enhancement, and continual renewal.

    Excellence is the destination, but enhancement is the journey. If we are serious about defining one, we must rediscover the other.

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  • High quality learning means developing and upskilling educators on the pedagogy of AI

    High quality learning means developing and upskilling educators on the pedagogy of AI

    There’s been endless discussion about what students do with generative AI tools, and what constitutes legitimate use of AI in assessment, but as the technology continues to improve there’s a whole conversation to be had about what educators do with AI tools.

    We’re using the term “educators” to encompass both the academics leading modules and programmes and the professionals who support, enable and contribute to learning and teaching and student support.

    Realising the potential of the technologies that an institution invests in to support student success requires educators to be willing and able to deploy it in ways that are appropriate for their context. It requires them to be active and creative users of that technology, not simply following a process or showing compliance with a policy.

    So it was a bit worrying when in the course of exploring what effective preparation for digital learning futures could look like for our Capability for change report last year, it was noticeable how concerned digital and education leaders were about the variable digital capabilities of their staff.

    Where technology meets pedagogy

    Inevitably, when it comes to AI, some HE staff are enthusiastic early adopters and innovators; others are more cautious or less confident – and some are highly critical and/or just want it to go away. Some of this is about personal orientation towards particular technologies – there is a lively and important critical debate about how society comes into a relationship with AI technology and the implications for, well, the future of humanity.

    Some of it is about the realities of the pressures that educators are under, and the lack of available time and headspace to engage with developmental activity. As one education leader put it:

    Sometimes staff, they know that they need to change what they’re doing, but they get caught in the academic cycle. So every year it’s back to teaching again, really, really large groups of students; they haven’t had the time to go and think about how to do things differently.

    But there’s also an institutional strategic challenge here about situating AI within the pedagogic environment – recognising that students will not only be using it habitually in their work and learning, but that they will expect to graduate with a level of competence in it in anticipation of using AI in the workplace. There’s an efficiency question about how using AI can reprofile educator working patterns and workflows. Even if the prospect of “freeing up” lots of time might feel a bit remote right now, educators are clearly going to be using AI in interesting ways to make some of their work a bit more efficient, to surface insight from large datasets that might not otherwise be accessible, or as a co-creator to help enhance their thinking and practice.

    In the context of learning and teaching, educators need to be ready to go beyond asking “how do the tools work and what can I do with them?” and be prepared to ask and answer a larger question: “what does it mean for academic quality and pedagogy when I do?”

    As Tom Chatfield has persuasively argued in his recent white paper on AI and the future of pedagogy, AI needs to have a clear educative purpose when it is deployed in learning and teaching, and should be about actively enhancing pedagogy. Reaching this halcyon state requires educators who are not only competent in the technical use of the tools that are available but prepared to work creatively to embed those tools to achieve particular learning objectives within the wider framework and structures of their academic discipline. Expertise of this nature is not cheaply won – it takes time and resource to think, experiment, test, and refine.

    Educators have the power – and responsibility – to work out how best to harness AI in learning and teaching in their disciplines, but education leaders need to create the right environment for innovation to flourish. As one leader put it:

    How do we create an environment where we’re allowing people to feel like they are the arbiters of their own day to day, that they’ve got more time, that they’re able to do the things that they want to do?…So that’s really an excitement for me. I think there’s real opportunity in digital to enable those things.

    Introducing “Educating the AI generation”

    For our new project “Educating the AI generation” we want to explore how institutions are developing educator AI literacy and practice – what frameworks, interventions, and provisions are helpful and effective, and where the barriers and challenges lie. What sort of environment helps educators to develop not just the capability, but also the motivation and opportunity to become skilled and critical users of AI in learning and teaching? And what does that teach us about how the role of educators might change as the higher education learning environment evolves?

    At the discussion session Rachel co-hosted alongside Kortext advisor Janice Kay at the Festival of Higher Education earlier this month there was a strong sense among attendees that educating the AI generation requires universities to take action on multiple fronts simultaneously if they are to keep up with the pace of change in AI technology.

    Achieving this kind of agility means making space for risk-taking, and moving away from compliance-focused language to a more collaborative and exploratory approach, including with students, who are equally finding their feet with AI. For leaders, that could mean offering both reassurance that this approach is welcomed, and fostering spaces in which it can be deployed.

    In a time of such fast-paced change, staying grounded in concepts of what it means to be a professional educator can help manage the potential sense of threat from AI in learning and teaching. Discussions focused on the “how” of effective use of AI, and the ways it can support student learning and educator practice, are always grounded in core knowledge of pedagogy and education.

    On AI in assessment, it was instructive to hear student participants share a desire to be able to demonstrate learning and skills above and beyond what is captured in traditional assessment, and find different, authentic ways to engage with knowledge. Assessment is always a bit of a flashpoint in pedagogy, especially in constructing students’ understanding of their learning, and there is an open question on how AI technology can support educators in assessment design and execution. More prosaically, the risks to traditional assessment from large language models indicate that staff may need to spend proportionally more of their time on managing assessment going forward.

    Participants drew upon the experiences of the Covid pivot to emergency remote teaching and taking the best lessons from trialling new ways of learning and teaching as a useful reminder that the sector can pivot quickly – and well – when required. Yet the feeling that AI is often something of a “talking point” rather than an “action point” led some to suggest that there may not yet be a sufficiently pressing sense of urgency to kickstart change in practice.

    What is clear about the present moment is that the sector will make the most progress on these questions when there is sharing of thinking and practice and co-development of approaches. Over the next six months we’ll be building up our insight and we’d love to hear your views on what works to support educator development of AI in pedagogy. We’re not expecting any silver bullets, but if you have an example of practice to share, please get in touch.

    This article is published in association with Kortext. Join Debbie, Rachel and a host of other speakers at Kortext LIVE on Wednesday 11 February in London, where we’ll be discussing some of our findings – find out more and book your place here.

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  • Student engagement does not work if institutions are stuck in survival mode

    Student engagement does not work if institutions are stuck in survival mode

    The current state of UK higher education in 2025 is marked by an existential crisis, rather than merely a series of difficult challenges.

    This crisis comes from the inherent tension of attempting to operate a 20th century institutional model within the complex realities of the 21st century. This strain is exacerbated by complex socio-economic difficulties facing students, coupled with the immense pressures experienced by staff.

    A city under siege

    Conceptualising UK HE as a “city”, it becomes evident that while valuable as centres of learning, community and potential, this “city” is currently under siege and there is a “dragon at the gates”. The “dragon” represents a multifaceted array of contemporary pressures. These include, but are not limited to, funding reductions, evolving regulatory demands and the escalating cost-of-living crisis. Empirical research indicates that the cost-of-living crisis profoundly impacts students’ capacity for engagement.

    Furthermore, this “dragon” is continuously evolving. With the rapid ascent of artificial intelligence (AI) and the distinct characteristics of Gen Z learners representing two of its newest and most salient “heads”. While AI offers opportunities for personalised learning, simultaneously, it presents substantial challenges to academic integrity and carries the risk of augmenting student isolation if not balanced with human connection. Concurrently, Gen Z learners have learned a state of “continuous partial attention” through constant exposure to multiple information streams. This poses a unique challenge to pedagogical design.

    Defence, survival and the limits of future-proofing

    In response to these multifaceted challenges, the prevalent institutional instinct is to defend the city. This typically involves retreating behind existing structures, consolidating operations, centralising processes, tightening policies and intensifying reliance on familiar metrics such as Key Performance Indicators (KPIs), National Student Survey (NSS) action plans, attendance rates and overall survey scores.

    However, survival mode often means the sacrifice of genuine student engagement. This refers not to the easily quantifiable forms of engagement, but the relational, human dimension, wherein students develop a sense of belonging, perceive their contributions as meaningful and feel integrated into a valuable community. Research consistently demonstrates that this sense of belonging is paramount for psychological engagement and overall student success. Consequently, an exclusive focus on defending established practices, reliant on systemically imposed metrics, risks reinforcing barriers that actually impede connection, wellbeing and the institutional resilience that is critically needed.

    While the concept of “future-proofing” is often invoked, it is imperative to question the feasibility of achieving perfect preparedness against unknowable future contingencies.

    Attack strategies

    Given the limitations of a purely defensive stance, a different strategic orientation is warranted: a proactive “attack” on the challenges confronting HE. Genuine engagement should be reconceptualised not merely as a student characteristic, but as an institutional design choice. Institutions cannot expect students to arrive with pre-existing engagement; rather, they must actively design for it.

    This proactive engagement strategy aligns precisely with the University of Cumbria’s commitment to people, place, and partnerships. These themes are woven through the university’s new learning, teaching and assessment plan, providing a framework for institutional pedagogic transformation.

    Relationships as the bedrock of community

    The “citizens” of our HE “city” – students and staff – constitute its absolute bedrock. Strong relationships between these stakeholders are fundamental to fostering a resilient academic community. A critical institutional challenge lies in ensuring that existing systems, policies and workload models adequately support these vital connections. It is imperative to grant staff the requisite time, flexibility and recognition for their crucial relational work. This represents a shift in focus from a transactional interaction to a relationship-centric approach.

    Understanding the distinct experiences of diverse groups of students (e.g. apprentices, online learners and commuter students) is of critical importance for building meaningful and authentic engagement. Fundamentally, ensuring that students feel “seen, heard and valued” is a key determinant of psychological engagement and a prerequisite for all other forms of learning to take root.

    Designing for inclusive environments

    The concept of “place” encompasses the entire physical and digital environment of the HE institution. Belonging, rather than being an abstract sentiment, possesses a strong spatial and environmental dimension. For institutions like the University of Cumbria, intentional design of consistent environments that cultivate a sense of “This is my place” is paramount. An important tactic in this regard is to build belonging by design, particularly at critical transition points such as induction.

    This notion of “place” is particularly vital for commuter students, who often lack the built-in community afforded by residential halls. For this cohort, the physical campus serves as the primary site of their university experience. A critical assessment of their campus experience between scheduled classes is needed. Are institutional spaces designed to encourage students to remain, study and connect? When students choose to utilise them, these spaces facilitate spontaneous conversations, the formation of friendships, and the organic development of belonging.

    This kind of intentionality is required for digital learning environments. Are virtual learning environments (VLEs) merely content repositories, or are they designed as welcoming community hubs? The creation of inclusive, supportive environments – both physical and virtual – where students feel genuinely connected, is absolutely fundamental to effective engagement. Moreover, clear opportunities exist to strengthen recognition of how an individual’s sense of place can positively impact learning experiences primarily delivered online.

    Partnerships in fostering genuine student experiences

    The final pillar, “partnerships,” refers to the cultivation of alliances within the HE “city”. While “student voice” is frequently championed, research strongly indicates a necessity to move beyond mere collection of voice towards fostering genuine student influence and co-creation. The distinction is crucial: “student voice” may involve an end-of-module survey, whereas “student influence” entails inviting students to co-design assessment questions for subsequent iterations of that module.

    The University of Cumbria’s recent consistent module evaluation approach serves as an exemplary model. Achieving a 34.2% response rate in the first semester of 2024/25, which exceeds sector averages, and, critically, delivering 100% “closing the loop” reports to students, demonstrates a commitment to acknowledging and acting upon all feedback. This provides a concrete illustration of making student influence visible.

    From strategy to action

    This approach is a fundamental paradigm shift: from a reactive, defensive posture focused on metrics to a proactive engagement strategy. This “attack” on the challenges, framed by the University of Cumbria’s distinctive strategic approach, is predicated on three core actions: prioritising People by enabling relational work, designing a sense of Place to foster belonging, and building authentic Partnerships that transform student voice into visible influence. Translating this strategy into actionable practice does not necessitate additional burdens, but rather the integration of five practical tactics into existing workflows:

    1. Rethink what you measure and why: Transition from a “data-led” to a “data-informed” approach. This involves utilising data for meaningful reflection and making deliberate choices to enhance the student experience, rather than reacting defensively to metrics such as KPIs, NSS scores and attendance data.
    2. Build belonging at transitions: Recognising belonging as a critical component of psychological engagement and overall student success, this tactic underscores the importance of intentionally designing key junctures in the student journey, such as induction and progression points, to be inherently inclusive.
    3. Enable relational work: Acknowledging that strong student-staff relationships form the “bedrock” of a resilient academic community, and that staff often face conflicts between fostering these connections and workload pressures, this tactic advocates for formally enabling “relational work”.
    4. Turn voice into influence: Meaningful partnership necessitates moving beyond mere collection of student “voice” to cultivating their genuine “influence”. The critical determinant is not simply whether the institution is listening, but whether substantive changes are being implemented based on student feedback. This can be achieved through the establishment of “visible feedback loops” that demonstrate the impact of student input and leveraging technology to complement, rather than replace, human interaction.
    5. Partnership by design: This final tactic advocates for embedding co-creation with students as an intrinsic element from the initial stages. Rather than being an occasional or supplementary activity, authentic partnership should be structurally integrated, with students actively involved in key decision-making processes.

    The fundamental question facing HE in 2025 – “What is a university for?” – is increasingly met with the unsettling realisation that conventional answers no longer suffice. However, a cautiously optimistic outlook prevails. The answer to this pivotal question lies not in defending existing paradigms, but in actively and courageously constructing a new institutional reality.

    This article has been adapted from a keynote address delivered by Dr Helena Lim at the University of Cumbria Learning and Teaching Conference on 18 June 2025, and has been jointly authored with Dr Jonathan Eaton, Pro Vice Chancellor (Learning & Teaching) at the University of Cumbria.

    For further insights into the research underpinning these arguments, the “Future-proofing student engagement” report is available here.

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  • AI is unlocking insights from PTES to drive enhancement of the PGT experience faster than ever before

    AI is unlocking insights from PTES to drive enhancement of the PGT experience faster than ever before

    If, like me, you grew up watching Looney Tunes cartoons, you may remember Yosemite Sam’s popular phrase, “There’s gold in them thar hills.”

    In surveys, as in gold mining, the greatest riches are often hidden and difficult to extract. This principle is perhaps especially true when institutions are seeking to enhance the postgraduate taught (PGT) student experience.

    PGT students are far more than an extension of the undergraduate community; they represent a crucial, diverse and financially significant segment of the student body. Yet, despite their growing numbers and increasing strategic importance, PGT students, as Kelly Edmunds and Kate Strudwick have recently pointed out on Wonkhe, remain largely invisible in both published research and core institutional strategy.

    Advance HE’s Postgraduate Taught Experience Survey (PTES) is therefore one of the few critical insights we have about the PGT experience. But while the quantitative results offer a (usually fairly consistent) high-level view, the real intelligence required to drive meaningful enhancement inside higher education institutions is buried deep within the thousands of open-text comments collected. Faced with the sheer volume of data the choice is between eye-ball scanning and the inevitable introduction of human bias, or laborious and time-consuming manual coding. The challenge for the institutions participating in PTES this year isn’t the lack of data: it’s efficiently and reliably turning that dense, often contradictory, qualitative data into actionable, ethical, and equitable insights.

    AI to the rescue

    The application of machine learning AI technology to analysis of qualitative student survey data presents us with a generational opportunity to amplify the student voice. The critical question is not whether AI should be used, but how to ensure its use meets robust and ethical standards. For that you need the right process – and the right partner – to prioritise analytical substance, comprehensiveness, and sector-specific nuance.

    UK HE training is non-negotiable. AI models must be deeply trained on a vast corpus of UK HE student comments. Without this sector-specific training, analysis will fail to accurately interpret the nuances of student language, sector jargon, and UK-specific feedback patterns.

    Analysis must rely on a categorisation structure that has been developed and refined against multiple years of PTES data. This continuity ensures that the thematic framework reflects the nuances of the PGT experience.

    To drive targeted enhancement, the model must break down feedback into highly granular sub-themes – moving far beyond simplistic buckets – ensuring staff can pinpoint the exact issue, whether it falls under learning resources, assessment feedback, or thesis supervision.

    The analysis must be more than a static report. It must be delivered through integrated dashboard solutions that allow institutions to filter, drill down, and cross-reference the qualitative findings with demographic and discipline data. Only this level of flexibility enables staff to take equitable and targeted enhancement actions across their diverse PGT cohorts.

    When these principles are prioritised, the result is an analytical framework specifically designed to meet the rigour and complexity required by the sector.

    The partnership between Advance HE, evasys, and Student Voice AI, which analysed this year’s PTES data, demonstrates what is possible when these rigorous standards are prioritised. We have offered participating institutions a comprehensive service that analyses open comments alongside the detailed benchmarking reports that Advance HE already provides. This collaboration has successfully built an analytical framework that exemplifies how sector-trained AI can deliver high-confidence, actionable intelligence.

    Jonathan Neves, Head of Research and Surveys, Advance HE calls our solution “customised, transparent and genuinely focused on improving the student experience, “ and adds, “We’re particularly impressed by how they present the data visually and look forward to seeing results from using these specialised tools in tandem.”

    Substance uber alles

    The commitment to analytical substance is paramount; without it, the risk to institutional resources and equity is severe. If institutions are to derive value, the analysis must be comprehensive. When the analysis lacks this depth institutional resources are wasted acting on partial or misleading evidence.

    Rigorous analysis requires minimising what we call data leakage: the systematic failure to capture or categorise substantive feedback. Consider the alternative: when large percentages of feedback are ignored or left uncategorised, institutions are effectively muting a significant portion of the student voice. Or when a third of the remaining data is lumped into meaningless buckets like “other,” staff are left without actionable insight, forced to manually review thousands of comments to find the true issues.

    This is the point where the qualitative data, intended to unlock enhancement, becomes unusable for quality assurance. The result is not just a flawed report, but the failure to deliver equitable enhancement for the cohorts whose voices were lost in the analytical noise.

    Reliable, comprehensive processing is just the first step. The ultimate goal of AI analysis should be to deliver intelligence in a format that seamlessly integrates into strategic workflows. While impressive interfaces are visually appealing, genuine substance comes from the capacity to produce accurate, sector-relevant outputs. Institutions must be wary of solutions that offer a polished facade but deliver compromised analysis. Generic generative AI platforms, for example, offer the illusion of thematic analysis but are not robust.

    But robust validation of any output is still required. This is the danger of smoke and mirrors – attractive dashboards that simply mask a high degree of data leakage, where large volumes of valuable feedback are ignored, miscategorised or rendered unusable by failing to assign sentiment.

    Dig deep, act fast

    When institutions choose rigour, the outcomes are fundamentally different, built on a foundation of confidence. Analysis ensures that virtually every substantive PGT comment is allocated to one or more UK-derived categories, providing a clear thematic structure for enhancement planning.

    Every comment with substance is assigned both positive and negative sentiment, providing staff with the full, nuanced picture needed to build strategies that leverage strengths while addressing weaknesses.

    This shift from raw data to actionable intelligence allows institutions to move quickly from insight to action. As Parama Chaudhury, Pro-Vice Provost (Education – Student Academic Experience) at UCL noted, the speed and quality of this approach “really helped us to get the qualitative results alongside the quantitative ones and encourage departmental colleagues to use the two in conjunction to start their work on quality enhancement.”

    The capacity to produce accurate, sector-relevant outputs, driven by rigorous processing, is what truly unlocks strategic value. Converting complex data tables into readable narrative summaries for each theme allows academic and professional services leaders alike to immediately grasp the findings and move to action. The ability to access categorised data via flexible dashboards and in exportable formats ensures the analysis is useful for every level of institutional planning, from the department to the executive team. And providing sector benchmark reports allows institutions to understand their performance relative to peers, turning internal data into external intelligence.

    The postgraduate taught experience is a critical pillar of UK higher education. The PTES data confirms the challenge, but the true opportunity lies in how institutions choose to interpret the wealth of student feedback they receive. The sheer volume of PGT feedback combined with the ethical imperative to deliver equitable enhancement for all students demands analytical rigour that is complete, nuanced, and sector-specific.

    This means shifting the focus from simply collecting data to intelligently translating the student voice into strategic priorities. When institutions insist on this level of analytical integrity, they move past the risk of smoke and mirrors and gain the confidence to act fast and decisively.

    It turns out Yosemite Sam was right all along: there’s gold in them thar hills. But finding it requires more than just a map; it requires the right analytical tools and rigour to finally extract that valuable resource and forge it into meaningful institutional change.

    This article is published in association with evasys. evasys and Student Voice AI are offering no-cost advanced analysis of NSS open comments delivering comprehensive categorisation and sentiment analysis, secure dashboard to view results and a sector benchmark report. Click here to find out more and request your free analysis.

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  • How to build smarter partnerships and become digitally mature

    How to build smarter partnerships and become digitally mature

    Across higher education, the conversation about digital transformation has shifted from connection to capability. Most universities are digitally connected, yet few are digitally mature

    The challenge for 2026 and beyond is not whether institutions use technology, but whether their systems and partnerships enable people and processes to work together to strengthen institutional capacity, learner outcomes, and agility.

    Boundless Learning’s 2025 Higher Education Technology and Strategy Survey underscored this transition: 95 per cent of leaders said education management partners are appealing, and one in three described them as extremely so. Yet preferences are changing: modular, fee-for-service models now outpace traditional revenue-sharing arrangements, signalling a desire for flexibility and control.

    Leaders also identified their top digital priorities: innovation enablement (53 per cent), streamlined faculty workflows (52 per cent), and integrated analytics (49 per cent). In other words, universities are no longer chasing the next platform; they want systems that think.

    Why systems thinking matters

    That idea is central to Suha Tamim’s workAnalyzing the Complexities of Online Education Systems: A Systems Thinking Perspective. Tamim frames online education as a dynamic ecosystem in which a change in one area, such as technology, pedagogy, or management, ripples through the whole. She argues that institutions need a “systems-level” view connecting the macro (strategy), meso (infrastructure and management), and micro (teaching and learning) layers.

    Seen this way, technology decisions become design choices that shape the culture and operations of the institution. Adopting a new platform is not just an IT project; it influences governance, academic workload, and the student experience. The goal is alignment across those levels so that each reinforces the other.

    Boundless Learning’s Learning Experience Suite (LXS) embodies this approach. Rather than adding another application into an already crowded environment, LXS helps institutions orchestrate existing systems; linking learning management, analytics, and support functions into a cohesive, secure, learner-centred framework. It is a practical application of systems thinking: connecting data flows, surfacing insights, and simplifying faculty and learner experiences within one integrated ecosystem.

    From outsourcing to empowering

    The shift toward integration also reflects how universities engage external partners. Jeffrey Sun, Heather Turner, and Robert Cermak, in the American Journal of Distance Education, describe four main reasons universities outsource online programme management:

    1. Responding quickly to competitive pressures
    2. Accessing upfront capital
    3. Filling capability gaps
    4. Learning and scaling in-house

    Their College Curation Strategy Framework shows that institutions partner with external providers not just to cut costs, but to build strategic capacity. Yet the traditional online programme management (OPM) model anchored in long-term revenue-share contracts has drawn criticism for limited transparency and loss of institutional control.

    Our own data suggest that this critique is reshaping practice. Universities are moving from outsourcing to empowerment: seeking education-management partners who enhance internal capability rather than replace it. This evolution from OPMs to Education Management Partners (EMPs) marks a decisive turn toward collaborative, capacity-building relationships.

    The Learning Experience Suite fits squarely within this new model. It is not an outsourced service but a connective layer that enables institutions to manage their digital ecosystems with greater visibility and confidence, while benefiting from enterprise-grade integration and security. It exemplifies partnership as a mechanism for capability development, a move from vendor management to shared strategic growth.

    From fragmentation to fluency

    Many institutions remain caught in what might be called digital fragmentation. According to our survey, nearly half of leaders cite data silos, disconnected platforms, and inconsistent learner experiences as obstacles to progress. These are not isolated technical issues; they are systemic barriers that affect pedagogy, governance, and institutional trust.

    Tamim’s framework describes such misalignment as a state of “disequilibrium.” Overcoming it requires coordinated action across levels, strategic clarity from leadership, adaptive management structures, and interoperable tools that make integration intuitive. The objective is to move from digital accumulation to digital fluency: an environment where technology amplifies, rather than fragments, institutional purpose.

    Learning Experience Suite was designed precisely to address this. By connecting data across systems, enabling real-time analytics, and ensuring accessibility through a mobile-first design, it allows institutions to build coherence and confidence in their digital operations.

    Building partnerships

    The next phase of higher education technology will be defined not by the tools universities choose but by the quality of their partnerships. As scholars like Sun have cautioned, outsourcing core academic functions without transparency can erode autonomy. Conversely, partnerships grounded in shared governance, open data, and aligned values can strengthen the academic mission.

    For Boundless Learning, this is the central opportunity of the coming decade: to reimagine partnership as co-evolution. Universities, platforms, and providers function best as interconnected actors within a wider learning system, each contributing expertise to advance learner success and institutional resilience.

    When viewed through a systems lens, the key question is no longer whether universities should outsource, but how they orchestrate. The challenge is to combine the right mix of internal capability, external expertise, and interoperable technology to achieve measurable impact.

    That, ultimately, is what digital maturity requires and what the Learning Experience Suite was designed to deliver.

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