Tag: Means

  • The Karateka vs the Sumo Wrestler: what REF 2029 means for research leadership in UK universities

    The Karateka vs the Sumo Wrestler: what REF 2029 means for research leadership in UK universities

    This blog was kindly authored by Dr Antonios Kelarakis, Reader in Polymers and Nanomaterials, University of Lancashire

    UK universities increasingly reward size, visibility and institutional influence. Yet many of the discoveries that underpin scientific progress come from researchers whose work is slow, specialist and largely invisible – the academic karateka, whose precision contrasts sharply with the highly visible, institution-shaping sumo wrestler. With reforms to the Research Excellence Framework (REF) for 2029 confirmed in December 2025, there is now an opportunity to rebalance what we value in research leadership and to better align institutional incentives with how knowledge is actually produced.

    In today’s academic world, two very different research styles are stepping onto the mat.

    The karateka is defined by focus and precision. They dedicate themselves to mastering a single research field, refining a theory, improving a method or laying the foundations for a new diagnostic or experimental technique. Every publication is carefully considered, every contribution is incremental but cumulative. Their ambition is depth rather than scale, and they aim to reach previously inaccessible insights. These researchers often form the invisible engine of scientific progress. Their work may attract little attention beyond specialist communities, yet its influence is long-lasting and foundational.

    The sumo wrestler, by contrast, plays a broader game. Their strength lies in size, coordination and visibility. They lead large research groups, oversee multiple interdisciplinary projects and accumulate titles, affiliations and advisory roles. Their calendars are filled with conferences, policy briefings and media engagement. They shape research agendas as much as individual ideas and act as the public face of modern academia. While the karateka advances knowledge through precision, the sumo wrestler moves institutions through mass and momentum.

    A shifting balance of power

    For much of scientific history, the karateka was the primary driver of discovery. The laws of physics, advances in chemistry and the development of new materials and analytical techniques have typically emerged from decades of focused work by scholars deeply embedded in a single domain.

    In recent years, however, the balance in UK academia has tilted. Universities increasingly reward visibility, scale, collaboration and institutional contribution – metrics that naturally favour the sumo wrestler. Funding requirements emphasise partnerships, pathways to impact and the management of large consortia. Universities respond rationally by supporting researchers who can deliver coordination, profile and strategic alignment.

    The karateka, meanwhile, often struggles to justify slow, methodical work in systems dominated by short-term indicators. Their contributions are essential, but they are not always easily captured by institutional performance metrics or institutional narratives.

    Why REF matters now

    The REF has always been a powerful signal of what universities should value. Decisions taken as part of the REF 2029 reforms strengthen the emphasis on research culture, long-term contribution and the environments that sustain excellence, alongside continued recognition of impact.

    Under the revised framework, assessment is weighted across three elements: Contribution to Knowledge and Understanding (55%), Engagement and Impact (25%) and Strategy, People and Research Environment (20%), assessed at both disciplinary and institutional levels. This represents a clear shift from REF 2021, where the role of environment was more limited.

    This change matters. By strengthening the role of research environment and contribution, REF 2029 creates an opening for universities to recognise how excellence is actually sustained; through deep expertise, stable methods, supportive cultures and long-term institutional investment. Research outputs remain central, but they no longer crowd out other forms of contribution to the same extent.

    Karateka-style scholarship has often struggled to fit neatly into REF narratives. Breakthroughs take time, develop incrementally and may not translate into demonstrable impact within a single cycle. Yet many celebrated impact case studies ultimately rest on foundational research generated by specialist researchers whose work is less visible and harder to narrate.

    From critique to policy

    The reforms give universities greater scope and responsibility to act differently. REF 2029 does not dictate outcomes, but it reshapes the conditions under which institutions define excellence.

    In practical terms, universities can now use the framework to reaffirm the value of:

    • deep, specialist expertise, even when audiences are narrow
    • long-term, foundational inquiry that underpins later impact
    • precision scholarship that strengthens methods and disciplines
    • small, focused teams that are often more intellectually productive than large consortia

    REF 2029 offers a chance to rebalance the contest without lowering the bar for excellence. Protecting space for karateka-style research is not a retreat from impact; it is a precondition for it. When depth is preserved, leadership has something genuinely worth amplifying: impact that endures rather than merely dazzles.

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  • What the Employment Rights Act 2025 means for higher education

    What the Employment Rights Act 2025 means for higher education

    After months of parliamentary back-and-forth, the Bill finally made it onto the statute books just before Christmas. For universities, the implications are wide-ranging, and the clock is ticking on compliance.

    The Act is the centrepiece of the government’s “Plan to Make Work Pay”, promising a shake-up of employment rights, union access, and labour market enforcement. For the sector, where workforce structures and contractual arrangements are particularly complex, these reforms need to be considered carefully. In this article, we have focused on a rundown of five things universities need to know now.

    Unfair dismissal: the bar just got lower and compensation higher. From 2027, staff will only need six months’ service (down from two years) to claim unfair dismissal and the maximum cap on compensation is going. That means universities could face much bigger payouts if things go wrong. Universities should review probation policies, equip managers to proactively manage performance during probation and avoid extended probation periods, where possible, to reduce the legal risk.

    Zero-hours and casual contracts: new rules, new risk. Think visiting lecturers, exam invigilators, and a lot of student-facing roles. The Act introduces rights to request guaranteed hours, proper notice of shifts, and compensation for cancellations. If you rely heavily on a casual workforce, generally or in certain areas, now’s the time to audit those contracts and review use, although these measures won’t be brought into effect until 2027.

    Trade union access: expect more structured dialogue. With effect from 18 February 2026, the Act lowers the threshold for a valid industrial action ballot and shortens the notice period unions must give before taking action (14 to 10 days). It also extends the mandate for action from 6 to 12 months. This means it will be easier and quicker for unions to secure a mandate for strikes or other industrial action. Universities should expect a more agile approach from unions and be ready to respond to potential disruption with robust contingency planning and clear communication. It may be prudent to review recognition agreements, including the dispute resolution procedures, to seek to mitigate any negative impact.

    Sexual harassment: from October 2026, the Act will require universities to take “all” reasonable steps, not just “reasonable steps”, to prevent sexual harassment of staff, with regulations to follow on what this means in practice. At the same time, employers will become liable for harassment of staff by third parties (such as students, visitors, or contractors) across all protected characteristics, unless they can show they took all reasonable steps to prevent it.

    Disclosures of sexual harassment will be explicitly protected under whistleblowing law, and most confidentiality clauses (NDAs) that seek to prevent staff from raising or disclosing allegations of discrimination or harassment will be void. For universities, these changes raise the bar for prevention, policy, and training and align closely with the Office for Students’ E6 condition of registration, which already requires robust systems to prevent and respond to harassment and sexual misconduct affecting students.

    “Fire and rehire”: also from October 2026, dismissing and re-engaging staff to force through changes to pay, hours, leave, or benefits will be automatically unfair unless the university can prove it’s facing severe financial trouble. If you’re planning a restructure or harmonising terms from October onwards, you’ll also need to follow the revised statutory Code of Practice and have your business case watertight.

    If I were you

    Universities are already navigating a maze of employment models, from permanent academics, fixed-term researchers to casual student workers. These reforms demand a proactive approach to ensure legal compliance but also to maintain staff morale and institutional reputation.

    If you are a university leader, now is a good time to make it part of your new year’s resolution to audit your casual contracts – zero-hours, fixed-term, and casual roles all need additional scrutiny to ensure they meet new legal minimums. It would also be a good time to review probation and dismissal policies and manager compliance, as the shorter qualifying period and uncapped compensation change the risk calculus.

    Most institutions are in communication with their local unions, but now would be a good time to talk to your unions specifically about the changes, as early engagement can help manage expectations and smooth the path to compliance.

    While many in England may have recently reviewed institutional harassment policies as part of recent regulatory changes from the Office for Students, it is important to review sexual harassment policies and ensure managers know what is changing, how they can ensure compliance and to keep an eye out for new regulations.

    As much of the sector faces significant financial challenges, additional restructuring plans may be in play for the upcoming academic year. If this is the case, it is essential you review your plans in light of additional legislation around contract changes, particularly around “fire and rehire”. This is already somewhat of a legal minefield, but the constraints on employers will be far more stringent from October onwards.

    And, if nothing else, you and your colleagues must keep good records. Documentation is your best defence if challenged.

    Ultimately, the Employment Rights Act 2025 isn’t just another HR update and universities must not treat it as one. Instead, it marks a cultural shift towards greater job security and worker voice. For universities, the challenge is to balance compliance with the need for flexibility to meet the complex needs of an institution in an evolving sector. Get ahead of the curve, and you can turn these changes into an opportunity to strengthen staff engagement and institutional resilience.

    Key dates for your diary

    18 February 2026

    • Simplifying industrial action notices and ballot papers
    • Increasing mandate period and reducing required notice period for industrial acton
    • Protections against dismissal and detriment for taking industrial action

    6 April 2026

    • Whistleblowing protection for sexual harassment disclosures
    • Collective redundancy protective award increase from 90 days gross pay to 180 days
    • (Expected) Repeal of the 50% threshold for industrial action ballots to revert to simple majority voting

    1 October 2026

    • “All reasonable steps” to prevent sexual harassment and prevent third party harassment
    • Trade union statutory access rights

    1 January 2027

    • Six month qualifying period for unfair dismissal and removal of compensation cap

    During 2027 (exact date to be determined)

    • Zero-hours and casual contract protections (guaranteed hours, notice, compensation)

    Some provisions are subject to further regulations or transitional arrangements. Check the latest government guidance for updates.

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  • What the DOJ Opinion Means for FAFSA Data Sharing and MSIs

    What the DOJ Opinion Means for FAFSA Data Sharing and MSIs

    In a dramatic reversal of long-standing federal support for minority students, the Department of Justice has declared that key programs serving historically Black and Hispanic-serving institutions are unconstitutional. The ruling targets race-conscious scholarship access and federal aid data sharing, effectively dismantling decades of policy designed to close educational gaps. For many MSIs and their students, the shift represents a Trump-era rollback of racial equity in higher education, leaving institutions scrambling to protect access and funding in a suddenly hostile legal landscape.

    The U.S. Department of Justice’s Office of Legal Counsel has delivered what may be one of the most consequential legal opinions affecting federal education policy in decades: a sweeping conclusion that a suite of federal programs tied to minority‑serving institutions (MSIs) and race‑specific scholarships are unconstitutional under current equal‑protection jurisprudence. 

    At the center of this interpretation is a fundamental shift in how federal racial criteria are viewed post-Students for Fair Admissions v. Harvard/UNC. In that landmark affirmative‑action decision, the Supreme Court significantly tightened the permissible bounds of race‑conscious decision making. The DOJ memo applies that framework beyond admissions, asserting that programs awarding federal funds based on racial or ethnic enrollment thresholds — including MSI grant programs — “effectively employ a racial quota.” 

    One particularly striking aspect of the opinion is its treatment of access to Free Application for Federal Student Aid (FAFSA) data by the United Negro College Fund and the Hispanic Scholarship Fund — organizations that award scholarships targeted to students of specific racial or ethnic backgrounds. The opinion deems it unconstitutional for these groups to receive FAFSA applicant data because the statute enabling such sharing confers access only to entities that grant race‑specific awards. 

    Supporters of aiding historically marginalized students and institutions view this as an unprecedented restriction that could severely constrain outreach and support for those populations. Critics charge the move fits a broader administrative pattern of dismantling federal race‑conscious programs and argue that it disregards the statutory authority Congress explicitly provided — including the discretionary authority vested in the Education Secretary to administer FAFSA data sharing.

    As one expert aide pointed out in private correspondence, the statutory provision that enabled FAFSA access was framed with Secretary discretion in mind — meaning it was lawful as written. But with DOJ now labeling such practices as impermissibly discriminatory, liability has been reallocated onto the administrative apparatus itself. That shift, in effect, insulates senior officials — including the Secretary — from culpability once the practice ends, leaving career bureaucrats to unwind systems built over years.

    The Policy and Legal Stakes

    For nearly four decades, the federal government has maintained a suite of targeted programs intended to close longstanding educational opportunity gaps. These include grants for MSIs, race‑specific scholarships, and data‑sharing mechanisms like FAFSA access that enable outreach to underrepresented students seeking financial aid.

    Beginning in July 2025, the Department of Education began scaling back discretionary grants to MSIs after the U.S. Solicitor General declined to defend race‑based criteria in court, particularly the Hispanic‑Serving Institutions definition requiring at least 25% Hispanic enrollment. By September, the Department officially announced the planned termination of most MSI discretionary grant funds for FY2025 — a decision informed by the constitutional concerns later articulated in the DOJ opinion. 

    Until now, many observers assumed that statutory authority and congressional backing provided a stable legal foundation for such programs. But the OLC’s memo challenges that assumption, concluding that race‑based eligibility criteria — whether for institutional support or student scholarships — are no longer defensible under current constitutional interpretation. 

    The implications extend far beyond MSI grants. If organizations that provide targeted scholarships based on race or ethnicity can no longer receive key federal administrative data, the practical capacity of those groups to serve students could be significantly hampered.

    Political and Institutional Reactions

    The DOJ opinion has drawn sharply polarized responses. Administration officials frame the memo as an affirmation of equal protection and a necessary correction to federal programs that, in their view, relied on impermissible racial criteria. Congressional allies of the Administration characterize the changes as ending “racial discrimination” in federal education policy.

    Conversely, Democratic legislators and MSI leaders condemn the opinion as ideologically driven and harmful to institutions that serve historically underserved populations. Critics say the analysis ignores longstanding bipartisan congressional support for such programs and portends deep cuts in educational opportunity. 

    Institutional leaders at a range of MSIs have expressed alarm, underlining that funding and support mechanisms now in jeopardy are “vital” to student success and campus mission. Many campuses are scrambling to assess fiscal exposure and consider contingency planning.

    Looking Ahead

    With federal policy in flux and several legal questions unresolved, higher education professionals face an uncertain environment. Institutions historically supported by race‑conscious federal programs may need to rethink recruitment, financial aid outreach, and partnerships with scholarship providers. Meanwhile, advocates and lawmakers may pursue legislative fixes or constitutional litigation to reshuffle the legal landscape once more.

    Whatever the outcome, the DOJ opinion marks a pivotal moment in federal student aid policy — one likely to reshape how race, equity, and opportunity are legally navigated in the years to come.

    HEI Reader Context: What This Means for MSIs

    • Historically Black Colleges and Universities (HBCUs): Loss of FAFSA data access and potential cuts to discretionary MSI grants could disrupt scholarship outreach, enrollment initiatives, and pipeline programs designed to recruit and retain underrepresented students. HBCUs may need to develop alternative channels for financial aid outreach, including direct partnerships with donors and private scholarship organizations.

    • Hispanic-Serving Institutions (HSIs): Many HSIs rely on federal discretionary grants to supplement state funding and support programs for first-generation and low-income students. The DOJ opinion may force HSIs to reallocate institutional resources to cover programs previously funded through race-conscious federal grants.

    • Scholarship Organizations: Groups like the United Negro College Fund (UNCF) and the Hispanic Scholarship Fund (HSF) may no longer receive FAFSA data, limiting their ability to identify eligible students efficiently. Expect increased reliance on outreach campaigns, social media, and partnerships with local school districts.

    • Institutional Planning: MSIs should assess short-term financial exposure, prioritize scholarship communications, and explore private funding alternatives. Legal and policy monitoring will be critical as legislative or judicial responses evolve.

    Sources

    1. Inside Higher Ed. “DOJ Report Declares MSIs Unconstitutional.” December 22, 2025. Link

    2. Higher Ed Dive. “DOJ Says MSI Grant Funding Unconstitutional.” December 22, 2025. Link

    3. ED.gov. “US Department of Education Ends Funding for Racially Discriminatory Discretionary Grant Programs, Minority-Serving Institutions.” July 2025. Link

    4. EducationCounsel. “E-Update: September 22, 2025.” Link

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  • Making sense of specialisation: what the Post-16 White Paper means for university identity

    Making sense of specialisation: what the Post-16 White Paper means for university identity

    Over the weekend we published blogs on the art of reimagining universities and on why the TEF could collapse under the weight of DfE and the OfS’ expectations.

    Today’s blog was kindly authored by Nick Barthram, Strategy Partner at Firehaus and Merry Scott Jones, Transformation Partner at Firehaus and Associate Lecturer at Birkbeck, University of London.

    It is the tenth  blog in HEPI’s series responding to the post-16 education and skills white paper. You can find the other blogs in the series here, here, here, here, here, here, here, here and here.

    The government’s Post-16 Education and Skills White Paper sets a new tone for tertiary education in England. It is not just another skill or funding reform. It is a statement of intent about how universities, colleges, and employers should work together to build the country’s economic capability.

    The paper sets out a broad reform agenda built around stronger employer collaboration, higher-quality technical education, and a more flexible lifelong learning system. Initiatives such as Local Skills Improvement Plans and the Lifelong Learning Entitlement illustrate how the system is being reshaped to enable post-16 institutions to play distinct, complementary roles within a shared ecosystem of skills and innovation. All of this will unfold against a backdrop of constrained funding, uneven regional capacity, and growing regulatory pressure, making clarity of role more important than the White Paper itself acknowledges.

    While the paper avoids overt market language, the phrase comparative advantage does a lot of work. It invites universities to reflect on what they are best at and how that compares with others, without requiring them to openly compete. The intention is clear: to encourage institutions to define, and then demonstrate, their unique value. This is not new thinking. Advance HE, supported by a sector steering group including representation from AHUA, CUC, Guild HE and UUK, published a discussion paper last year on Measuring What Matters, exploring institutional performance and the importance of evidencing and communicating value creation.

    For some, that will mean sharper choices about subjects, audiences, partnerships, and purpose. For others, it will be about aligning their contribution to regional priorities. Not every university serves its region in the same way. The most prestigious universities will act as lighthouses, shaping national and international ecosystems through research and innovation. Others will play a more local role, deepening their community impact and supporting regional industry.

    The common thread is focus. Universities can no longer rely on breadth as a badge of strength. The challenge now is to identify what makes their contribution distinct and coherent, and to express that with clarity.

    From strategy to articulation

    Responding to the White Paper will be a demanding process. It will call for rigorous analysis, evidence-gathering, and an honest evaluation of institutional strengths and weaknesses. It will also require a sophisticated understanding of stakeholders’ and audiences’ needs. And of course, diplomacy will be required to manage the trade-offs that follow. Every decision will carry consequences for identity, culture, and relationships.

    In time, many universities will produce credible strategies: detailed statements of focus, lists of priorities, and maps of partnerships. But the real risk is stopping there. Institutional strategy alone will not create coherence.

    Universities often complete strategic work and then move straight to execution, adding imagery or campaigns before uniting everything around a purpose that aligns what you offer and who it’s for. The step that often gets missed is articulation – translating strategic intent into something people can understand, believe in, and act on.

    The White Paper calls for coherence across regions and the sector. Universities need to mirror that with coherence within their own walls. When purpose, culture, and communication line up behind a shared sense of direction, policy responses become practice, not just strategy. And this, fundamentally, is what the Government is seeking.

    The groundwork for meeting these changes is only just beginning, with many hard yards still to come. While covering that ground, there are lessons from outside the sector worth remembering.

    1. Specialisation  is relative
      A university’s strengths mean little in isolation. What matters is how those strengths stand out within the broader system of institutions, partners, and employers. Understanding where your work overlaps with others and where it uniquely contributes is essential. Knowing what not to do is often as important as knowing where to lead.
    1. Demand is defined by more than the UK Government
      The White Paper rightly highlights the importance of the national industrial strategy in shaping what is ‘in demand’. But universities should also consider the needs and motivations of their wider audiences: students, partners, and communities. Clarity about who your work matters to is as important as clarity about what that work is.
    1. Purpose must be expressed, not just defined
      Defining purpose is a strategic exercise; expressing it is an act of leadership. Purpose that remains on paper does not change behaviour, attract talent, or inspire partners. It must be made visible and tangible across everything the institution says and does, from how staff describe their work to how the university presents itself to the world.
    1. Perception matters as much as reality
      Universities are naturally driven by research and evidence. Yet specialisation is as much about being perceived as specialised as it is about being so in practice. The most successful institutions will work not only to build genuine expertise but also to occupy space in their audiences’ hearts and minds. Shifting perception requires consistency in both story and substance.
    1. Alignment is critical to success
      The institutions that succeed will be those that align intent, culture, and message. When leadership, staff, and students share a single understanding of what the university stands for, decision-making becomes simpler, collaboration easier, and communication more powerful. Alignment is not achieved through a campaign but through ongoing dialogue and consistent behaviour.

    A catalyst for clarity

    The Post-16 White Paper is ultimately a call for focus. For universities, that means not only deciding where they fit but demonstrating that fit clearly and consistently to students, partners, and staff.

    Those who stop at strategy will adapt. Those who move beyond it — articulating their role with confidence, coherence, and conviction — will help define what a purposeful, modern university looks like in the decade ahead.

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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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  • What the NAEP Proficient Score Really Means for Learning – The 74

    What the NAEP Proficient Score Really Means for Learning – The 74


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    In September, The 74 published Robert Pondiscio’s opinion piece discussing how people without strong reading skills lack what it takes “to effectively weigh competing claims” and “can’t reconcile conflicts, judge evidence or detect bias.” He adds, “They may read the words, but they can’t test the arguments.”

    To make his case, Pondiscio relies on the skill level needed to achieve a proficient score or better on National Assessment of Educational Progress, a level that only 30% of tested students reached on 2024’s Grade 8 reading exam. Only 16% of Black students and 19% of Hispanics were proficient or more.

    Yet naysayers argue that the NAEP standard is simply set too high and that NAEP’s sobering messages are inaccurate. There is no crisis, according to these naysayers.

    So, who is right?

    Well, research on testing performance of eighth graders from Kentucky indicates that it’s Pondiscio, not the naysayers, who has the right message about the NAEP proficiency score. And, Kentucky’s data show this holds true not just for NAEP reading, but for NAEP math, as well.

    Kentucky offered a unique study opportunity. Starting in 2006, the Bluegrass State began testing all students in several grades with exams developed by the ACT, Inc. These tests include the ACT college entrance exam, which was administered to all 11th grade public school students, and the EXPLORE test, which was given to all of Kentucky’s public school eighth graders.

    Both the ACT and EXPLORE featured something unusual: “Readiness Benchmark” scores which ACT, Inc. developed by comparing its test scores to actual college freshman grades years later. Students reaching the benchmark scores for reading or math had at least a 75% chance to later earn a “C” or better in related college freshman courses.

    So, how did the comparisons between Kentucky’s benchmark score performance and the NAEP work out?

     Analysis found close agreement between the NAEP proficiency rates and the share of the same cohorts of students reaching EXPLORE’s readiness benchmarks. ​

    For example, in Grade 8 reading, EXPLORE benchmark performance and NAEP proficiency rates for the same cohorts of students never varied by more than four percentage points for testing in 2008-09, 2010-11, 2012-13 or 2014-15.

    The same, close agreement was found in the comparison of NAEP grade 8 math proficiency rates to the EXPLORE math benchmark percentages. 

    EXPLORE to NAEP results were also examined separately for white, Black and learning-disabled students. Regardless of the student group, the EXPLORE’s readiness benchmark percentages and NAEP’s proficient or above statistics agreed closely.

    Doing an analysis with Kentucky’s ACT college entrance results test was a bit more challenging because NAEP doesn’t provide state test data for high school grades. However, it is possible to compare each student cohort’s Grade 8 NAEP performance to that cohort’s ACT benchmark score results posted four years later when they graduated from high school. Data for graduating classes in 2017, 2019 and 2021 uniformly show close agreement for overall average scores, as well as for separate student group scores.

    It’s worth noting that all NAEP scores have statistical sampling errors. After those plus and minus errors are considered, the agreements between the NAEP and the EXPLORE and ACT test results look even better.

    The bottom line is: Close agreement between NAEP proficiency rates and ACT benchmark score results for Kentucky suggests that NAEP proficiency levels are highly relevant indicators of critical educational performance. ​Those claiming NAEP’s proficiency standard is set too high are incorrect.

    That leaves us with the realization that overall performance of public school students in Kentucky and nationwide is very concerning. Many students do not have the reading and math skills needed to navigate modern life. Instead of simply rejecting the troubling results of the latest round of NAEP, education leaders need to double down on building key skills among all students.


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  • A change in approach means research may never be the same again

    A change in approach means research may never be the same again

    At first glance Liz Kendall may look like an odd choice for Secretary of State for Science, Innovation and Technology. She has never worked in science, she has rarely mentioned science directly in any intervention in her entire parliamentary career, and this is not a role with the kind of profile which will allow easy entry in any future leadership race.

    Although covering a related brief has never been a disqualifying quality for any predecessors, her move from the Department for Work and Pensions following her failed welfare reforms felt more like a hasty exit than a tactical manoeuvre.

    Her direct predecessor, Peter Kyle, often seemed more preoccupied with turning the UK into an “AI superpower” than he did the more tedious business of how the research ecosystem is governed and how it can be manipulated to fulfil the government’s ambitions. In truth, the business of research reform is not about more grand visions, frameworks, or strategies, but the rather grubbier work of deciding where to spend a finite amount of funding on an infinite amount of programmes.

    Practice and promise

    Kendall’s interest in research has so far been on the business of making the country better. As seen in her speeches during her time on the backbenches, research is about practical things like regional economies, skills, and curing diseases. For Kendall, “what matters is what works.” And in her speech at the Innovation for Growth Summit a management theory of research reform about balancing the speculative with the practical emerged.

    The premise of her speech was that the growth of the UK economy is reliant on making the most of the UK’s R&D strengths. To get the most out of the UK’s R&D strengths Kendall believes the government can neither be too directive and must allow curiosity-driven research to prosper. It should also not be too permissive, funding must be directed toward government priorities particularly when it comes to translation and application.

    It is a middle ground approach to research management for a third-way politician. In line with the three bucket model (outlined here by current Strathclyde professor of practice, research and innovation policy, and former DSIT and Research England person Ben Johnson) Kendall has clarified the government’s research funding allocations. There will be £14bn for curiosity driven R&D, £8bn toward the government’s priorities, and £7bn for scale up support. £7bn has also been announced in skills and infrastructure to secure the success of each bucket of activity.

    The label problem

    The labelling of existing funds in new ways is in itself not a strategy for economic growth. Clearly, doing the same thing, with the same people, in the same ways, would lead to exactly the same outcomes with a different name. A bit like when international research became about making the UK a “science superpower” or when every ambitious research programme was a “moonshot” or relabelling every economic benefit produced through research as “levelling up”.

    The boldest ambition of Kendall’s speech is perhaps the most understated. Kendall is committed to “doing fewer things better.” In a speech delivered at the same event by UKRI’s Chief Executive, Ian Chapman, this simple sentiment may have massive consequences.

    Chapman’s view is that the UK lacks any of the natural resources advantages of its major international competitors. Instead, the UK maintains its competitiveness through the smart use of its knowledge assets even if he believes these are “undervalued and underappreciated.”

    Chapman’s UKRI will be more interventionist. He will maintain curiosity driven research but warns that UKRI will not support the activities where it has no “right to win significant market-share in that sector,” and in backing spin-outs UKRI will be “much more selective.” The future being etched out here is one where there is much greater direction by government and UKRI toward funding that aligns with the industrial strategy and its mission for economic growth while maintaining a broad research base through curiosity driven research. Clearly, funding fewer programmes more generously means that some areas of research will receive less government funding.

    The government’s approach to research is coalescing around its approach to governing more broadly. Like the industrial strategy the government is not picking winners as such but creating the conditions through which some desirable policy outcomes like economic growth have a better chance of emerging. It’s a mix of directing funding toward areas where the UK may secure an advantage like the doubling of R&D investment in critical technologies, addressing market failures through measures like the £4.5m for Women in Innovation Awards, and regulating to shape the market with the emphasis of economic growth and sustainability in UKRI’s new framework document.

    Football’s coming home

    In her speech Kendall likened the selective funding approaches to the selective sports funding of the Olympics. Alighting on a different sporting metaphor Chapman recalled the time a non-specific European team he supports (almost definitely Liverpool) came back from 3-0 down to win the European Cup as a reminder that through collective support researchers can achieve great things.

    Perhaps, UK research has been more like the England men’s football team than it has the current Premier League champions. The right pieces in the wrong places with little sense of how the talent of individuals contribute to the success of the whole. In committing to funding fewer programmes better the government wants all its stars on the pitch in top condition. The challenge is that those who go from some funding to none are likely to feel their contributions to the team’s success have been overlooked

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  • What America’s Declining Happiness Means — and How Higher Education Fits In

    What America’s Declining Happiness Means — and How Higher Education Fits In

    A recent report has sounded an alarm: happiness in the United States is falling more sharply than in almost every other developed nation. According to coverage by CBS News, Americans increasingly report loneliness, deep political division, and diminished life satisfaction. While this trend is worrying in itself, a closer look shows that it’s not just a problem of individual melancholy — it reflects a broader weakening of social structures, civic trust, and community cohesion. Historically, these phenomena have been central to the nation’s sense of coherence; now, they may be eroding.

    Historical Roots and the Social Capital Framework

    To understand the scale of what’s happening, it helps to go back. Over two decades ago, Robert D. Putnam’s seminal Bowling Alone documented a dramatic decline in American “social capital” — the network of associations, civic participation, and interpersonal trust that undergirds a functioning democracy. Putnam traced declines in everything from civic organizations to informal social gatherings, arguing that this fraying of social infrastructure had profound consequences. 

    Social capital theory provides a useful lens here: trust between citizens, engagement in local institutions, and time spent in shared civic life are not just feel‑good extras, but foundations for collective resilience.

    Later empirical work has revisited these concerns. Weiss, Paxton, Velasco, and Ressler (2018) developed a newer measure of social capital and found evidence that the decline persists. Inequality also appears to play a role: as income gaps widen, interpersonal trust tends to decrease. In research published in Finance & Development, economists found that rising inequality explained a substantial portion of the decline in social trust in the United States.

    More recently, political scientists have documented how perceived political polarization erodes social trust. In a nationally representative panel study, Amber Hye‑Yon Lee showed that when people believe their country is deeply divided, their trust in fellow citizens drops — even beyond partisan loyalties. Pew Research Center data further illustrate this generational shift: younger cohorts, raised in a more polarized and atomized society, report lower social trust than earlier generations. 

    At the same time, the digital revolution hasn’t necessarily filled the gap. Sabatini and Sarracino (2014) found that while people are more active on social media, this does not compensate for lost in-person connection — and may even undermine trust. During the COVID-19 pandemic, researchers observed increased remote communication, but also stronger political echo chambers: in a study of 41,000 Americans’ social networks, political homophily (interacting mostly with those who share one’s partisan identity) increased. 

    Well-Being, Health, and Mortality

    The decline in social trust and cohesion is not just a sociological problem — it is deeply linked to health. A growing body of epidemiological research ties subjective well‑being to longevity and mortality. For instance, a widely cited study by Lawrence, Rogers, and Wadsworth found that lower happiness is associated with higher all‑cause mortality risk in U.S. adults. In another longitudinal study, researchers followed more than 30,000 adults over 14 years and found that individuals with low life satisfaction lived, on average, 8–10 years less than those with high satisfaction — even after controlling for sociodemographic and behavioral variables. 

    These findings suggest that declining happiness is not just a matter of mental distress or cultural malaise — it translates into concrete health inequities and life expectancy gaps.

    Recent Trends and the Global Context

    Over the past decade, the United States has slid in global happiness rankings, according to the World Happiness Report. Some analyses suggest that the U.S. now falls behind peer nations on measures of life evaluation, meaning that Americans are increasingly less satisfied with their lives in a broad, reflective sense. 

    Meanwhile, epidemiological studies of happy life expectancy — the number of years people spend in a state of subjective well‑being — show that although well-being improved from 1970–2000, gains were uneven by race and gender. The recent reversal or stagnation in happiness is thus especially alarming in light of these prior gains.

    The Role of Higher Education: Past, Present, and Potential Futures

    Given this historical and empirical context, higher education institutions have a complex and potentially pivotal role in responding to declining well-being.

    On one hand, universities could help rebuild social capital. Institutions of higher learning have unique capacity to foster cross-partisan civic engagement, to embed community-building in pedagogy, and to support students’ social and emotional development. By investing in mental health infrastructure, peer networks, and service-based learning, colleges could act as local laboratories for restoring trust and social cohesion.

    Higher education also has a research function: universities can produce evidence about what strengthens well-being, what interventions mitigate loneliness or political fragmentation, and how different models of community engagement impact long-term health outcomes. Through partnerships with public policy institutions, universities can help translate these findings into programs that bolster social infrastructure outside campus walls.

    However, higher education also runs risks. If institutions remain fragmented, politically polarized, or focused on prestige rather than public mission, they may contribute to social fragmentation rather than healing it. Elite universities, in particular, may be perceived as disconnected from broader communities, undermining trust rather than reinforcing it. In such a scenario, higher education may reproduce the very inequalities and isolation that are driving declining well‑being.

    Moreover, without deliberate strategies, campus networks may reinforce echo chambers: social connections among students may mirror broader partisan divides, especially in environments where political homogeneity is common.

    Health Equity Implications

    The decline in American happiness intersects directly with issues of health equity. Lower well-being and eroded trust disproportionately affect marginalized communities — those with fewer economic resources, less social support, and weaker civic infrastructure. When universities take an active role in promoting well-being and rebuilding social capital, they not only support individual students but may contribute to reducing structural health disparities.

    Conversely, if higher education plays a passive role, or if access to supportive, socially rich campus environments is limited to privileged groups, the decline in happiness may deepen existing inequities. The gap in life expectancy tied to subjective well-being suggests that we cannot ignore the social determinants of happiness: economic inequality, community fragmentation, political polarization, and institutional trust all matter.

    A Call to Action

    To address this crisis, higher education leaders, policymakers, and public health practitioners should consider the following:

    1. Reinforce community-building: Colleges should invest in programs that promote cross-group interaction, civic participation, and social trust.

    2. Prioritize mental health: Expand counseling, peer support, and proactive well-being initiatives, especially for students who might otherwise fall through the cracks.

    3. Align research with public value: Fund and promote research on social cohesion, well-being interventions, and the relationship between trust and health, and ensure that findings inform public policy.

    4. Foster institutional humility and outreach: Universities should engage with local communities, not as isolated centers of prestige, but as partners in building social infrastructure and resilience.

    5. Measure what matters: Beyond graduation rates and research output, institutions should track well-being metrics — social trust, belonging, mental health — as central indicators of their impact.

    It Doesn’t Have to Be This Bad 

    The decline in happiness across the United States is not a passing phase or a matter of individual pathology. Rather, it reflects deep shifts in social trust, political cohesion, and community infrastructure. Historically, scholars like Putnam sounded the alarm on social capital’s erosion. Today, health researchers warn that falling well‑being shortens lives and exacerbates inequalities.

    Higher education, if reoriented toward building connections, purpose, and trust, could play a vital role in reversing this trajectory. But if universities remain inward-looking or inequality-driven, they risk accelerating the very forces that undermine societal well-being. The stakes are high — not only for individual students, but for the future health and cohesion of the nation.

    Scholarly Sources:

    • Lee, Amber H. Y. “Social Trust in Polarized Times: How Perceptions of Political Polarization Affect Americans’ Trust in Each Other.” Political Behavior, 2022. PMC

    • Weiss, Inbar, Pamela Paxton, Kristopher Velasco, and Robert W. Ressler. “Revisiting Declines in Social Capital: Evidence from a New Measure.” Social Indicators Research, 2018. PMC

    • Lawrence, Elizabeth M., Richard G. Rogers, and Tim Wadsworth. “Happiness and Longevity in the United States.” Social Science & Medicine, 2015. PMC

    • Study on life satisfaction and mortality (14-year follow-up): PMC

    • Research on income inequality and trust: “In Equality, We Trust” (IMF / Finance & Development) IMF

    • Study of happy life expectancy, 1970–2000: PMC

    • Putnam, Robert D. Bowling Alone: The Collapse and Revival of American Community. (on social capital history) Wikipedia+1

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  • WEEKEND READING: Building the transatlantic cyber bridge: what ‘Careers-First’ really means for the future workforce

    WEEKEND READING: Building the transatlantic cyber bridge: what ‘Careers-First’ really means for the future workforce

    This blog was kindly authored by Professor Paul Marshall, Vice-President (Global Campus) and Pro-Vice-Chancellor (Careers & Enterprise), University of East London.

    As the UK Government prepares its long-awaited White Paper on the future of higher education, it is timely to reflect on the purpose and impact of our universities. At their best, they are not simply sites of knowledge creation – they are instruments of national capability. Few challenges illustrate that more vividly than cybersecurity.

    When I joined a panel at the CyberBay Cybersecurity Conference in Tampa earlier this month, Dr Richard Munassi, Managing Director of Tampa Bay Wave, opened with a warning that set the tone for the discussion:

    We are in a cyber war – a war waged by well-financed, state-backed criminal organisations so sophisticated that they have their own HR divisions.

    He was right. Earlier this year, Jaguar Land Rover was forced to suspend production after a ransomware attack that rippled across its global supply chain. The UK Government’s intervention – with a support package approaching £1.5 billion – made clear that cybersecurity is not an IT issue; it is economic infrastructure.

    As the sector awaits the Government’s vision for the future, one truth already stands out: higher education must not only prepare individuals for work –  it must prepare the nation for risk.

    At the University of East London (UEL), that challenge sits at the heart of our institutional strategy, Vision 2028, which seeks to transform lives through education, innovation, and enterprise. The strategy’s organising principle – Careers-First – redefines employability as capability.

    Rather than positioning careers as an outcome of study, it embeds professional practice, enterprise, and resilience into every degree and partnership. The test for every programme is simple: does it equip our students to adapt, contribute, and lead in industries defined by constant change?

    Nowhere is this approach more tangible than in cybersecurity. Our BSc Cyber Security & Networks, MSc Information Security & Digital Forensics, and Cyber Security Technical Professional Degree Apprenticeship all combine rigorous academic study with live, industry-based application. 

    Students work directly with BT, IBM, Fujitsu, and Ford, tackling real-time challenges in threat analysis, data forensics, and network defence. By the time they graduate, they are not simply work-ready — they are work-proven, having contributed to the resilience of the very sectors they will soon join.

    The results speak for themselves:

    • With Siemens UK, students tested firmware vulnerabilities in industrial systems, informing Siemens’ internal training programmes.
    • With Barclays Eagle Labs, they created a fraud-analysis dashboard now in pilot testing.
    • With NHS Digital, they developed a ransomware-simulation tool to train hospital teams in incident response.

    Each collaboration demonstrates a single idea: learning is most powerful when it changes the world beyond the classroom.

    UEL’s Institute for Connected Communities (ICC), led by Professor Julia Davidson OBE, anchors this model in research excellence and policy leadership. The ICC brings together computing, criminology, psychology, and social science to examine the human, technical, and organisational dimensions of online safety.

    Its research informs the UK Council for Internet Safety, Ofcom, UNICEF, and multiple international governments. Through projects such as Global Kids Online, ICC research directly shapes teaching, ensuring that our graduates understand not only how to secure systems, but why digital trust matters to society.

    As policymakers consider the future role of universities in the forthcoming White Paper, the ICC already provides a working example of how academic research translates into practical and regulatory impact.

    The White Paper will also need to consider how global collaboration strengthens national capability. UEL’s Global Campus model demonstrates how this can work in practice — connecting students and employers across India, Greece, Egypt, and the United States to create shared pathways for study, innovation, and employment.

    Our developing partnership with Tampa Bay Wave, framed within the UK–Florida Memorandum of Understanding (2023), offers one illustration. We are building both virtual and physical experiences that will enable UEL students to engage with Florida’s growing cybersecurity and fintech ecosystem through mentoring, live projects, and placements, while providing a London base for US start-ups entering the UK market.

    A genuine transatlantic bridge is being constructed –  designed for movement in both directions, connecting students, researchers, and entrepreneurs to co-create secure-by-design technologies and governance frameworks. It is the Careers-First model, scaled globally.

    The next phase of cybersecurity will occur where AI, data, and physical systems converge. Attacks will target intelligent infrastructure –  transport grids, hospitals and manufacturing. UEL is already embedding these challenges into its curriculum, guided by ICC research. Students design adversarial-AI tests, examine supply-chain vulnerabilities, and develop frameworks for organisational resilience.

    This approach recognises that technology evolves faster than any static syllabus. Students are therefore treated as co-creators, working alongside academics and employers to design the solutions industry will need next.

    As the UK Government prepares its White Paper, one principle should underpin the national conversation: universities are not peripheral to resilience –  they are central to it. They educate the workforce, generate the research, and sustain the partnerships that keep the nation secure.

    UEL’s Careers-First model, aligned to Vision 2028, embodies that principle. It fuses employability, enterprise, and global engagement into one coherent system of capability. Our collaboration with Tampa Bay Wave is a single, tangible expression of this –  connecting East London’s lecture theatres to innovation ecosystems across the Atlantic.

    In a global cyber war, the question is not whether universities should respond, but how fast they can. At UEL, that response is already underway –  this is what Careers-First looks like.

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  • Preparing students for the world of work means embracing an AI-positive culture

    Preparing students for the world of work means embracing an AI-positive culture

    When ChatGPT was released in November 2022, it sent shockwaves through higher education.

    In response, universities moved at pace during the first half of 2023 to develop policy and good practice guidance for staff and students on appropriate use of GenAI for education purposes; the Russell Group’s Principles on the use of generative AI tools in education are particularly noteworthy. Developments since, however, have been fairly sluggish by comparison.

    The sector is still very much at an exploratory phase of development: funding pilots, individual staff using AI tools for formative learning and assessment, baseline studies of practice, student and staff support, understanding of tools’ functionality and utilisation etc. The result is a patchwork of practice not coherent strategy.

    Yet AI literacy is one of the fastest growing skills demanded by industry leaders. In a survey of 500 business leaders from organisations in the US and UK, over two-thirds respondents considered it essential for day-to-day work. Within AI literacy, demand for foundation skills such as understanding AI-related concepts, being able to prompt outputs and identify use cases surpassed demand for advanced skills such as developing AI systems.

    Students understand this too. In HEPI’s Student generative AI survey 2025 67 per cent of student respondents felt that it was essential to understand and use AI to be successful in the workplace whereas only 36 per cent felt they had received AI skill-specific support from their institution.

    There is a resulting gap between universities’ current support provision and the needs of industry/ business which presents a significant risk.

    Co-creation for AI literacy

    AI literacy for students includes defining AI literacy, designing courses aligned with identified learning outcomes, and assessment of those outcomes.

    The higher education sector has a good understanding of AI literacy at a cross disciplinary level articulated through several AI literacy frameworks. For example, UNESCO’s AI Competency Framework for Students or the Open University in the UK’s own framework. However, most universities have yet to articulate nuanced discipline-specific definitions of AI literacy beyond specialist AI-related subjects.

    Assessment and AI continues to be a critical challenge. Introducing AI tools in the classroom to enhance student learning and formatively assess students is fairly commonplace, however, summative assessment of students’ effective use of AI is much less so. Such “authentic assessments” are essential if we are serious about adequately preparing our students for the future world of work. Much of the negative discourse around AI in pedagogy has been around academic integrity and concerns that students’ critical thinking is being stifled. But there is a different way to think about generative AI.

    Co-creation between staff and students is a well-established principle for modern higher education pedagogy; there are benefits for both students and educators such as deeper engagement, shared sense of ownership and enhanced learning outcomes. Co-creation in the age of AI now involves three co-creators: students, educators and AI.

    Effective adoption and implementation of AI offers a range of benefits specific to students, specific to educators and a range of mutual benefits. For example, AI in conjunction with educators, offers the potential for significantly enhancing the personalisation of students’ experience on an on-demand basis regardless of the time of day. AI can also greatly assist with assessment processes such as marking turnaround times and enhanced consistency of feedback to students. AI also allows staff greater data-driven insights for example into students at risk of non-progression, areas where students performed well or struggled in assessments allowing targeted follow up support.

    There is a wealth of opportunity for innovation and scholarship as the potential of co-creation and quality enhancement involving staff, students and AI is in its infancy and technology continues to evolve at pace.

    Nurturing an AI-positive culture

    At Queen Mary University of London, we are funding various AI in education pilots, offering staff development programmes, student-led activities and through our new Centre for Excellence in AI Education, we are embedding AI meaningfully across disciplines. Successfully embedding AI within university policy and practice across the breadth of operations of the institution (education, research and professional practice), requires an AI-positive culture.

    Adoption of AI that aligns with the University’s values and strategy is key. It should be an enabler rather than some kind of add-on. Visible executive leadership for AI is critical, supported by effective use of existing champions within schools and faculties, professional services and the student body to harness expertise, provide support and build capacity. In some disciplines, our students may even be our leading institutional AI experts.

    Successful engagement and partnership working with industry, business and alumni is key to ensure our graduates continue to have the necessary skills, knowledge and AI literacy to achieve success in the developing workplace.

    There is no escaping the fact that embedding AI within all aspects of a university’s operations requires significant investment in terms of technology but also its people. In our experience, providing practical support through CPD, case studies, multimedia storytelling etc whilst ensuring space for debate are essential for a vibrant, evolving community of practice.

    A key challenge is trying to maintain oversight and co-ordinate activities in large complex institutions in a field that is evolving rapidly. Providing the necessary scaffolding in terms of strategy and policy, regulatory compliance and appropriate infrastructure whilst ensuring there is sufficient flexibility to allow agility and encourage innovation is another key factor for an AI-positive culture to thrive.

    AI is reshaping society and building an AI-positive culture is central to the future of higher education. Through strategic clarity and cultural readiness, universities need to effectively harness AI to enhance student learning, support staff, improve productivity and prepare students for a changing world.

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