Tag: time

  • Think Like a Linguist: It’s time for a national conversation about the value of languages 

    Think Like a Linguist: It’s time for a national conversation about the value of languages 

    Author:
    Dr Charlotte Ryland

    Published:

    This guest blog was kindly authored by Dr Charlotte Ryland, Director of the Translation Exchange. 

    ‘Languages are not just a skillset, they’re a mindset.’ 

    I still remember where I was when a teacher friend made this comment, a few years ago, because it highlighted something I’d been worrying at for a long time. I felt that languages education for young learners undervalued the process of language learning itself, by underrating what it means to be a linguist. That value needed to be completely reframed: to move far beyond the notion that language learning gives you a set of useful communicative skills – the ‘utility argument’ – towards a more holistic and ambitious vision of the linguist’s mindset.  

    Fast forward to this summer, and a HEPI report by Megan Bowler highlighted a programme that I co-founded as doing just that: ‘[Think Like a Linguist offers] 12-13 year olds clear demonstrations of the value of a linguistic “mindset” and its real-world applications’.  

    That notion of the ‘real-world application’ is essential to how we think and talk about language learning and needs unpicking. I founded a languages outreach and advocacy centre (based at The Queen’s College, Oxford) because I was frustrated by existing languages outreach mechanisms run by universities. This frustration came in part from what I perceived as an over-emphasis on precisely those ‘real-world applications’: the outreach programmes I encountered tended to rely heavily on imagined futures – Keep learning your vocab and practising your grammar, then you’ll see! A life of travel, international business careers, slightly higher salaries awaits you! Yet this approach did not seem to be working for the year groups whose minds needed to be changed.  

    The cliff-edge for languages – in England and Wales – is now GCSE options, with over 50% of pupils opting out at the age of 13/14, i.e. at their first opportunity to do so. Languages presents university outreach with a special case, then: with a need to engage much younger learners than has traditionally been the case. Ideally, we start at upper primary and focus on lower secondary school learners, before pupils begin to think seriously about their GCSE options. My approach to working with this demographic has been to take a ‘show, not tell’ approach – to involve learners from age 8 in rich, creative, cultural activities that enable them to experience first-hand the pleasure and purpose of being a linguist.  

    That focus on showing is key to how we should treat the real-world applications, too. It is not enough to give pupils a learning experience based solely on communicative skills, while trying to tell them that this education will secure them a good job in our competitive, AI-soaked 21st-century economy. They don’t buy it, and the uptake statistics for formal language learning bear this out. Instead, we need to show those learners how relevant and in-demand the ‘linguistic mindset’ they develop will be, by integrating into the learning experience the broadest conception of what it means to be a linguist.  

    Higher Education institutions can do this. And they’ll do so much more effectively if they work together. They have access to a huge community of language graduates, who have between them generations of experience in the widest range of professions. With this community, the broadest conception of the linguistic mindset becomes tangible. In my experience, it falls into your lap the minute you ask one of these graduates about the impact of their languages education on their career path and life experience. 

    A standard response runs like this: they move quickly through the frontline benefits around communication in other languages – taking them as a given – and light instead on what Bowler refers to as ‘the irreplaceable advantages of the “linguistic mindset”’. For a lawyer, it includes the capacity to cope with frustration, to tolerate and work through uncertainty; for a consultant, it is being able to build trusted relationships and read between the lines. A civil servant might reference their ability to synthesise and analyse a large amount of information, seeking out potential biases and multiple perspectives. The list goes on and is underlined by the striking words of a 13-year-old participant in Think Like a Linguist: ‘I learnt that there is more to languages than speaking and listening. It’s also about thinking in your own way.’  

    If we have access to a form of education that stands to raise a generation of individuals able to think for themselves, and to do so on the global stage, then what are we waiting for? 

    The readiness of languages graduates to share these insights is one of the sector’s greatest assets. We need a national conversation about the value of languages for individuals and for society, fuelled by these stories and taking full account of the challenges currently being set us by AI. Duolingo have set us on an excellent path, with evidence in their user statistics and polling that the UK is a country of languages enthusiasts. As Duolingo’s UK Director Michael Lynas notes in his introduction to Bowler’s report, we need not be dogged by the negativity that often frames conversations about languages: instead, we must build on the tangible positives.  

    For this national conversation to make an impact, collaboration will be key. Shared learning from effective university outreach programmes to date can provide a basis for this conversation. And The Languages Gateway, a new cross-sector initiative dedicated to collating resources and supporting strategic collaboration, can host it. Further backing for this national conversation from higher education institutions and central government will support the Gateway in its work to raise the national profile of languages to where it belongs: delivering ‘irreplaceable’ value to 21st-century global Britain. 

      

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  • For World Space Week it’s time to look up

    For World Space Week it’s time to look up

    This week marks World Space Week, an international celebration of humankind’s last frontier launched by the United Nations in 1999. In more than 80 countries, people are celebrating through thousands of events.

    One of the goals of space week is to let people know how many of the products we depend on down on earth came out of space exploration programs: Life support systems for miners, memory foam mattresses, scratch-resistant lenses, nutritional supplements, cordless tools and freeze-dried food.

    Learning about outer space and space exploration excites young people and attracts them to science, technology, engineering and math fields.

    But for News Decoder, it is the international cooperation we see in space exploration programs that excites us. When we look to the moon, our galaxy and beyond, we see the possibility for peace and cooperation here on Earth.

    To celebrate World Space Week, check out some of the stories we’ve published about outer space and the people exploring it.

     

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  • 3 College Student Retention Strategies to Prioritize at This Time of Year

    3 College Student Retention Strategies to Prioritize at This Time of Year

    Retention is not what you do. It is the outcome of what you do.

    It’s that time of year when retention committees, student success professionals, and leadership teams across the country calculate the retention rate for the fall 2024 cohort and compare it with their previous years’ outcomes. Some campuses have undoubtedly stayed the same, others decreased, and some increased, but the overall conversation is usually about how “it” can be done better for the fall 2025 class. 

    Let’s talk about “it” for a minute. Many of you have heard the message that two of our founders, Lee Noel and Randi Levitz, and the student success professionals who have followed in their footsteps, have shared for several decades: Retention is not what you do. “It” is the outcome of what you do. “It” is the result of quality faculty, staff, programs and services. As you consider improvements to your efforts which will impact the fall 2025 entering class and beyond, keep in mind the following three student retention strategies and practices. 

    1. Assess college student retention outcomes completely

    The first strategy RNL recommends is a comprehensive outcomes assessment. All colleges and universities compute a retention rate at this time of year because it has to be submitted via the IPEDS system as part of the federal requirements. But many schools go above and beyond what is required and compute other retention rates to inform planning purposes. For example, at what rates did you retain special populations or students enrolled in programs designed to improve student success? In order to best understand what contributed to the overall retention rate, other outcomes have to be assessed as well. For instance, how many students persisted but didn’t progress (successfully completed their courses)? Before you finalize the college student retention strategies for your fall 2025 students, be sure you know how your 2024 students persisted and progressed so that strategies can be developed for the year ahead. 

    2. Know what worked and what didn’t

    The second strategy we recommend is to consider what worked well during the previous year and what didn’t. Many of us have been in situations where we continue to do the same thing and expect different results, which has been called insanity! (Fun fact, this quote is often attributed to Einstein, but according to Google, was not actually said by him!) A common example would be the academic advising model.  RNL has many years of data which show that academic advising is one of the most important college student retention strategies. But just doing what you have always done may not still be working with today’s college students. Advising is an area which needs constant attention for appropriate improvements. Here are a few questions for you to consider: Does your academic advising model, its standards of practice, and outcomes assessment reveal that your students are academically progressing by taking the courses needed for completion? Can you identify for each of your advisees an expected graduation date (which is one of the expected outcomes of advising)? Establishing rich relationships between advisors and advisees, providing a quality academic advising experience, can ultimately manage and improve the institution’s graduation rate. 

    3. Don’t limit your scope of activity

    Once you have assessed the 2024 class outcomes and the quality of your programs and services, RNL encourages you to think differently about how you will develop college student retention strategies that will impact the 2025 class. Each college has an attrition curve, or a distribution of students with their likelihood of being retained. The attrition curve, like any normal distribution, will show which students are least and most likely to retain and will reveal the majority of students under the curve. See the example below:

    The Retention Attrition Curve showing that campuses should focus retention efforts on students who can be influenced to re-enroll. The Retention Attrition Curve showing that campuses should focus retention efforts on students who can be influenced to re-enroll.

    As you consider your current activities, you may find that many of your programs are designed for the students at the tail end of the curve (section A above) or to further support the students who are already likely to persist (section B). Institutions set goals to increase retention rates but then limit the scope of students they are impacting. To have the best return on retention strategies, consider how you can target support to the largest group of students in the middle (section C) who are open to influence on whether they stay or leave, based on what you do or don’t do for them, especially during their first term and their first year at your school. 

    Onward for the year ahead

    RNL congratulates those of you who have achieved your retention goals for the 2024 cohort. You certainly must have done some things right and must have had student retention strategies that were effective. For those of you who are looking for new directions in planning, consider the three practices outlined above. 

    And if you aren’t currently one of the hundreds of institutions already working with RNL, you may want to implement one or more of the RNL student success tools to support your efforts: the RNL motivational survey instruments to identify those students who are most dropout prone and most receptive to assistance, the RNL student retention data analytics to identify the unique factors that contribute to persistence at your institution, and the RNL satisfaction-priorities surveys that inform decision making and resource allocation across your campus population. RNL can provide support in all of these areas along with on-going consulting services to further direct and guide retention practices that can make a difference in your enrollment numbers and the success of both your students and your institution.  Contact me to learn more in any of these areas. 

    Note: Thanks to my former colleague Tim Culver for the original development of this content.

    Ask for a complimentary consultation with our student success experts

    What is your best approach to increasing student retention and completion? Our experts can help you identify roadblocks to student persistence and maximize student progression. Reach out to set up a time to talk.

    Request now

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  • Weekend Reading: Is it time to stop using the term ‘non-traditional student’? 

    Weekend Reading: Is it time to stop using the term ‘non-traditional student’? 

    Author:
    HEPI Guest Post

    Published:

    This HEPI blog was kindly authored by Dr Steve Briggs, Director of Learning, Teaching and Libraries, University of Bedfordshire 

    In the context of UK higher education, the terms ‘traditional’ and ‘non-traditional’ are widely used when describing students – as apparent in recent blog posts published by HEPI. In this blog, I consider why the continued use of such terminology may become increasingly problematic and what might be a viable alternative.   

    Who are ‘traditional’ students?  

    The Cambridge dictionary defines ‘traditional’ as: 

    Following or belonging to the customs of ways of behaving that have continued in a group of people of society for a long time without changing. 

    As such, one can infer that the criterion for traditional students is that they will share established characteristics that have been fixed for a significant period.  
     

    The stereotypical traditional student 

    In the 1970s and 1980s, university students were generally young adults who left home and moved to a new city or town to study. They would routinely live with other students on or near to campus. Many would be able to undertake studies without needing to work and would have significant time available to spend on campus and engage in clubs, societies, sports teams and other social activities. In 2025, many commentators will cite this profile as being synonymous with a traditional student.  

    The rise of the non-traditional student   

    In the context of the UK, the term ‘non-traditional student’ has been widely used to differentiate learners who do not adhere to the aforementioned traditional student convention. Examples of characteristics seen to make a student non-traditional include: 

    • Commuting to university, rather than living on campus 
    • Being over the age of 21  
    • Having parental and/or caring responsibilities 
    • Hailing from a lower socio-economic background 
    • Being the first-in-family to study at university 
    • Having had experience of the care system 

    Such individuals are often time-poor but commitment-rich and in turn have very limited availability to spend on campus outside of scheduled sessions. The use of the non-traditional label has been used increasingly since the advent of widening participation in the 1990s. 

    Perceptions of traditional are not fixed  

    The concept of a traditional student is time-bound. For example, pre-1900, there was a small number of ancient universities in the UK and relatively very low numbers of students. Increased numbers of universities opening during the 1900s meant that more individuals were able to study at university, many of whom would be labelled as non-traditional relative to those pre-1900. However, the same group has since then been re-defined as traditional relative to those who studied in the 1990s.  

    Over the last twenty-five years non-traditional characteristics have become increasingly common amongst the student population. For example, in 2025, HESA reported that over half of students were from IMD quintiles 1 and 2, and the vast majority of students are now over the age of 20. Following previous trends, there will come a point, potentially in the not-too-distant future, whereby the current generation of non-traditional students will become viewed as traditional. The cyclical process will then likely start again with a new conceptualisation of what is non-traditional.  

    More nuanced classification options 

    Given the time-bound nature of both traditional and non-traditional characteristics I suggest that higher education commentators should consider the use of more exact terminology when discussing student cohorts. I suggest two options: 

    • By decade: Student groups could be framed in terms of decades, for example the demographic and characteristics of students of the 1990s, 2000s, 2010s and 2020s, etc. Such an approach could work well if there was stability over a decade however, the impact of social or global events (such as a recession, government policy or pandemic) may mean within a decade those studying within higher education could change markedly. For example, the significant impact of governmental immigration policy changes on the recruitment of international students studying in the UK during the mid-2020s.  
    • Create generational names: Since 1950, there have been five main birth generations: Baby Boomers, Generation X, Millennials, Generation Z and Generation Alpha. Each generation has shared characteristics synonymous with being born during that period. Analogously, specific generations could be defined in terms of university students. Each generation would have a distinctive name and characteristics common amongst most members studying at university during that specific window of time. The use of student generational names would offer flexibility to account for periods of stability that lasted longer than ten years and could also accommodate sudden changes to the profile of student cohorts.  

    I personally favour the use of generational names given the greater flexibility. I see this as necessary given the turbulence and change experienced within the higher education sector over the last decade. For instance, I propose that the pandemic was a catalyst for the emergence of a new generation of students, a defining characteristic of which being greater experience in remote communicating and learning online.  

    Putting into practice 

    As a starter for ten, I suggest seven generations of English students over the last 150 years. A caricature for each is provided – these are intended to be illustrative of generational difference rather than exhaustive: 

    • Ancient Generation (pre-1900): A student would study at one of the ancient universities in the UK. Students were mainly from the upper social class, and a fraction of the population attended university. Those attending university would be financially supported by personal networks.  
    • Redbrick Generation (circa 1900-1945): Most students studied at an ancient or redbrick university. Students continued to be mainly from the upper social class, and in turn a small percentage of the population attended university. 
    • Post-World War Two Generation (circa 1946-1989): As the number of universities progressively expanded, students had greater geographic access to higher education. Students could access maintenance grants to cover the cost of living whilst studying. This allowed students to readily engage in activities alongside their studies.  
    • Widening Participation Generation (circa 1990 – 1997): The number of universities significantly increased following the integration of polytechnics. Concentrated efforts were made to expand access to higher education and the percentage of students from previously underrepresented groups increased. In addition to maintenance grants, students were able to access low-cost student loans.  
    • Tuition Fee Generation (circa 1998 – 2014): The widening participation imperative remained but students now paid a tuition fee to study. Choice of where to study remained limited by student number caps. Maintenance grants were abolished and replaced with student loans. As fees progressively increased more students found they needed to undertake work whilst studying.  
    • Free Market Generation (circa 2015 – 2019): Widening participation remained a priority. The student number cap is removed, and many universities actively expand the availability of places. Students have unprecedented choice in terms of where to study at university. Tuition fees and living costs remain a challenge for many students and numbers working whilst studying remains very high.  
    • Pandemic Generation (circa 2020 – current): The pandemic results in a sudden and seismic shift to online education across schools, colleges and universities. This results in students have new experiences and expectations related to online and blended learning. Cost of living increases following the pandemic resulted in more student facing financial hardships in turn resulting in many spending less time on campus. Demand for mental health and well-being support increases.  

    Analogous to birth generations, I would see that other interpretations of higher education student generation names could emerge through research outputs, thought pieces or social events as opposed to being determined by a single group or professional body. Influential think tanks like HEPI could play a key role in providing platforms for such discussion. 

    I foresee there potentially being variations in proposed student generational definitions (as is the case with birth generations) but if all are clearly defined, these would all be invaluable for higher education commentators when discussing longitudinal changes in cohorts over time.

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  • Green skills, graduate competencies, and championing subject diversity – it’s time to join up some agendas 

    Green skills, graduate competencies, and championing subject diversity – it’s time to join up some agendas 

    Author:
    Rebecca Collins and Santiago Poeira Ribeiro

    Published:

    This HEPI blog was kindly authored by Rebecca Collins, Director, Sustainability and Environment Research and Knowledge Exchange Institute, University of Chester and Santiago Poeira Ribeiro, student in Natural Sciences (Physics), University of Chester. 

    UK universities are currently grappling with a perfect storm of disruptors: financial challenges, ambivalence from national policymakers, and, increasingly, from prospective students as they question what a university education really offers them. At the same time, the employment landscape is weathering its own storms, including those driven by accelerating technological change (particularly AI), concerns about skills deficits, geopolitical turbulence, and equivocation about whether or not this net zero business is here to stay.  UK Government response to these challenges has most recently taken the form of Skills England’s analysis of the skills requirement across ten priority sectors and the promise of a new industrial strategy from 2026-27 that connects these requirements to reforms of the higher education system.  

    It is in this context that a strangely paradoxical scenario is playing out.  On the one hand are claims that the UK does not have the necessary skills for a ‘green transition’ to net zero – what are increasingly being described as ‘green skills’.  (Notwithstanding the current national political ambivalence about net zero, most sectors of the UK economy have long since recognised the necessary direction of travel and know they need an appropriately knowledgeable and skilled workforce to accelerate action.) On the other is a higher education sector beset by the contraction or closure of subject areas perceived by some political and industrial leaders as insufficiently relevant to our collective economic future, ‘green’ or otherwise. However, for many years now, UK higher education has cultivated students’ green skills through its commitment to education for sustainable development (EfSD), widely recognised as essential knowledge for graduates entering the workforce. Indeed, climate literacy training is now often embedded in university curricula, as well as becoming increasingly normalised as a core, if not mandatory, training requirement across a range of industry sectors. Whilst what EfSD looks like at different universities varies, the majority of institutions demonstrate some degree of engagement with this agenda across all subject areas, with some making it a flagship institutional policy.   

    UK higher education thus seems to be quite good already at cultivating green skills for graduates, and across a wide range of subject areas. How, then, does this map onto the very varied definitions of green skills that have emerged from different sectors? The proliferation of reports concerned with this topic has not (yet) resulted in a clear, unified definition. Rather, this tends to be determined by who is doing the defining. Considering the different definitions and concepts prioritised by different institutions, we propose that these intersecting concerns can ultimately be distilled into three main types of green skill: 

    1. Technical skills: particularly those needed to accelerate decarbonisation; concentration of this need in industries such as manufacturing, transportation, utilities and infrastructure.  
    1. Green-enabling skills: otherwise known as soft or transferable skills, including systems thinking, communication, collaboration, critical thinking, adaptability. 
    1. Values-based skills: such as environmental awareness, climate justice, democratic engagement, cultural sensitivity. 

    Whilst definition 1 skews towards STEM subjects (as well as forms of technical expertise developed through other forms of learning, such as apprenticeships or vocational training), definitions 2 and 3 are within the purview of many other subjects commonly studied at undergraduate level, particularly within the arts, humanities and social sciences.   

    It is a timely moment to be reflecting on the relationship between how skills deficit narratives are framed by some corners of industry and government, and how universities position their offer in response. It feels like every academic in UK higher education has a story about recent, current or imminent institution-wide curriculum transformation. Whilst the rationales presented for these varies, one of the stronger narratives concerns ensuring students develop competencies that are fit for the future, respond directly to regional, national or global skills needs, and give students the vocabulary to articulate how the former meets the latter. As such, curriculum transformation presents an opportunity to think about how universities frame their offer, not just to prospective students but equally to the sectors those students might move into as skilled graduates.   

    Further, whilst driven by a range of factors, curriculum transformation presents the opportunity to articulate the role of all subjects studied in higher education, and all types of higher education providers, to contribute to the skills needed for an economy resilient to the socio-political shocks that will inevitably be invoked by environmental crises. There is a role for university leaders to be much bolder in articulating the value of all subjects – STEM and the arts, humanities, social sciences, and everything in between – and the green skills they cultivate. Now is the moment to consider how the promise of higher education might speak to or work with other agendas concerned with ensuring environmentally and socially sustainable and inclusive economies, regionally, nationally and globally. University leaders have a central role to play in advocating for a national higher education system where diversity – of student, skill and subject area – is not just celebrated as a buzzword but is demonstrated to be an essential part of a thriving, resilient and sustainable society.  

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  • Pause for REFlection: Time to review the role of generative AI in REF2029

    Pause for REFlection: Time to review the role of generative AI in REF2029

    Author:
    Nick Hillman

    Published:

    • This blog has been kindly written for HEPI by Richard Watermeyer (Professor of Higher Education and Co-Director of the Centre for Higher Education at the University of Bristol), Tom Crick (Professor of Digital Policy at Swansea University) and Lawrie Phipps (Professor of Digital Leadership at the University of Chester and Senior Research Lead at Jisc).
    • On Tuesday, HEPI and Cambridge University Press & Assessment will be hosting the UK launch of the OECD’s Education at a Glance. On Wednesday, we will be hosting a webinar on students’ cost of living with TechnologyOne – for more information on booking a free place, see here.

    For as long as there has been national research assessment exercises (REF, RAE or otherwise), there have been efforts to improve the way with which research is evaluated and Quality Related (QR) research funding consequently distributed. Where REF2014 stands out for its introduction of impact as a measure of what counts as research excellence, for REF2029, it has been all about research culture. Though where impact has become an integral dimension of the REF, the installation of research culture (into a far weightier environment or as has been proposed People, Culture and Environment (PCE) statement) as a criterion of excellence appears far less assured, especially when set against a three-month extension to REF2029 plans. 

    A temporary pause on proceedings has been announced by Sir Patrick Vallance, the UK Government’s Minister for Science, as a means to ensure that the REF provides ‘a credible assessment of quality’. The corollary of such is that the hitherto proposed formula (many parts of which remain formally undeclared – much to the frustration of universities’ REF personnel and indeed researchers) is not quite fit for purpose, and certainly not so if the REF is to ‘support the government’s economic and social missions’. Thus, it may transpire that research culture is ultimately downplayed or omitted from the REF. For some, this volte face, if it materialises, may be greeted with relief; a pragmatic step-back from the jaws of an accountability regime that has become excessively complex, costly and inefficient (if not even estranged from the core business of evaluating and then funding so-called ‘excellent’ research) and despite proclamations at the conclusion of its every instalment, that next time it will be less burdensome.   

    While the potential backtrack on research culture and potential abandonment of PCE statements will be focused on to explain the REF’s most recent hiatus, these may be only cameos to discussion of its wider credibility and utility; a discussion which appears to be reaching apotheosis, not least given the financial difficulties endemic to the UK sector, which the REF, with its substantial cost, is counted as further exacerbating. Moreover, as we are finding in our current research, the REF may have entered a period not limited to incremental reform and tinkering at the edges but wholesale revision; and this as a consequence of higher education’s seemingly unstoppable colonisation by artificial intelligence. 

    With recent funding from Research England, we have undertaken to consult with research leaders and specialist REF personnel embedded across 17 UK HEIs – including large, research-intensive institutions and those historically with a more modest REF footprint, to gain an understanding of existing views of and practices in the adoption of generative AI tools for REF purposes. While our study has thrown up multiple views as to the utility and efficacy of using generative AI tools for REF purposes, it has nonetheless revealed broad consensus that the REF will inevitably become more AI-infused and enabled, if not ultimately, if it is to survive, entirely automated. The use of generative AI for purposes of narrative generation, evidence reconnaissance, and scoring of core REF components (research outputs and impact case studies) have all been mooted as potential applications with significant cost and labour-saving affordances and applications which might also get closer to ongoing, real-time assessments of research quality, unrestricted to seven-year assessment cycles. Yet the use of generative AI has also been (often strongly) cautioned against for the myriad ways with which it is implicated and engendered with bias and inaccuracy (as a ‘black box’ tool) and can itself be gamed in multiple ways, for instance in ‘adversarial white text’. This is coupled with wider ongoing scientific and technical considerations regarding transparency, provenance and reproducibility. Some even interpret its use as antithetical to the terms of responsible research evaluation set out by collectives like CoARA and COPE.

    Notwithstanding, such various objections, we are witnessing these tools being used extensively (if in many settings tacitly and tentatively) by academics and professional services staff involved in REF preparations. We are also being presented with a view that the use of GenAI tools by REF panels in four years’ time is a fait accompli, especially given the speed by which the tools are being innovated. It may even be that GenAI tools could be purposed in ways that circumvent the challenges of human judgement, the current pause intimates, in the evaluation of research culture. Moreover, if the credibility and integrity of the REF ultimately rests in its capacity to demonstrate excellence via alignment with Government missions (particularly ‘R&D for growth’), then we are already seeing evidence of how AI technologies can achieve this.

    While arguments have been previously made that the REF offers good value for (public) money, the immediate joint contexts of severe financial hardship for the sector; ambivalence as to the organisational credibility of the REF as currently proposed; and the attractiveness of AI solutions may produce a new calculation. This is a calculation, however, which the sector must own, and transparently and honestly. It should not be wholly outsourced, and especially not to one of a small number of dominant technology vendors. A period of review must attend not only to the constituent parts of the REF but how these are actioned and responded to. A guidebook for GenAI use in the REF is exigent and this must place consistent practice at its heart. The current and likely escalating impact of Generative AI on the REF cannot be overlooked if it is to be claimed as a credible assessment of quality. The question then remains: is three months enough? 

    Notes

    • The REF-AI study is due to report in January 2026. It is a research collaboration between the universities of Bristol and Swansea and Jisc.
    • With generous thanks to Professor Huw Morris (UCL IoE) for his input into earlier drafts of this article.

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  • Now Is the Time to Overhaul Federal Regulations

    Now Is the Time to Overhaul Federal Regulations

    Researchers spend more than 40 percent of their research time complying with regulations.

    Photo illustration by Justin Morrison/Inside Higher Ed | kyoshino/iStock/Getty Images

    The rise of generative artificial intelligence and the Trump administration’s deregulation push make now the right time to streamline and reduce federal scientific research regulations, argues a report the National Academies of Sciences, Engineering and Medicine published Wednesday.

    “At a time when the scientific enterprise is under a lot of pressure—we don’t want to pretend that’s not true—this is also a wonderful opportunity to streamline the workload not only of researchers, but of institutions and other individuals,” Alan Leshner, chair of the NASEM committee that produced the report, said at a public briefing. “We would be foolish not to take advantage of the policy climate that favors deregulation and unburdening our scientific enterprise from unnecessary, duplicative and uncoordinated rules and regulations.”

    The 125-page report, entitled “Simplifying Research Regulations and Policies: Optimizing American Science,” lays out a three-pronged framework to guide a cohesive national strategy toward implementing more economical regulations. Those prongs include harmonizing regulations and requirements across federal and state agencies and research institutions, ensuring that regulatory requirements match the risk related to the project, and using technology to make regulation-compliance processes more efficient.

    From there, the report offers a menu of 53 potential options across all aspects of research compliance, including research security, misconduct and grant management, designed for interagency adoption.

    It’s all part of an effort by the National Academies to seize this political moment and accomplish their long-standing goal of freeing scientists from the weight of often redundant, expensive and excessive regulations.

    Currently, researchers whose work is supported by grants from agencies such as the National Science Foundation, the National Institutes of Health and the Department of Defense spend more than 40 percent of their research time complying with each agency’s varying administrative and regulatory requirements, “wasting intellectual capacity and taxpayer dollars,” according to Federal Demonstration Partnership data cited in the report.

    “There’s no question that regulation is necessary to ensure that the science we produce is of the best quality, the highest integrity and is conducted with full accountability and transparency to the American public,” said Leshner, who has previously held leadership positions at the NIH and the NSF. “Having said that, the current regulatory environment has grown to a point that it’s actually hampering innovation.”

    Despite previous calls by the NASEM and other groups to reduce regulatory burdens on researchers, few of those plans have come to fruition. Instead, data from the Council on Government Relations (COGR) shows that 62 percent of the regulations and policies federal agencies adopted or changed since 1991 were issued from 2014 to 2024.

    For example, both the U.S. Department of Agriculture and the Office of Laboratory Animal Welfare regulate animal research, but in some cases, their requirements conflict.

    When a research project is subject to both agencies’ requirements, it can create “confusion, redundancy, and extra work,” the report says. “The natural result is for academic institutions to create additional requirements of their own to manage the complexity and risk of noncompliance stemming from regulatory complexity.”

    ‘An Urgency to This’

    Complying with inconsistent or redundant regulations also costs a lot for universities, which are now facing significant cuts to federal research funding. In 2022, COGR estimated that institutions receiving more than $100 million in federal research funds spent an estimated $1.4 million a year to comply with the NIH’s Data Sharing and Management Policy while smaller institutions spend just over $1 million a year.

    The burden of regulatory compliance can also further exacerbate research inequities.

    “Typically, the more underresourced institutions—regional state institutions, minority-serving institutions, HBCUs and tribal colleges—may not have as large of a research infrastructure or staff to handle some of the regulations that filter down from the federal level,” said Emanuel Waddell, committee member and chair of the nanoengineering department at North Carolina A&T State University. “When the infrastructure isn’t there to answer questions, that burden falls on the researchers themselves to seek out answers, and it takes away time from pursuing intellectual curiosity.”

    And with looming cuts to federal research budgets, including mass layoffs at the federal agencies that oversee research, members of the committee believe now is the time to reduce the cost of regulatory compliance if the United States wants to remain a competitive producer of scientific innovation.

    “There’s an urgency to this. We really have to get this done. Think about how constrained budgets are—we have $37 trillion debt in this country and it continues to grow,” said Kelvin Droegemeier, a member of the committee and a professor and special adviser to the chancellor for science and policy at the University of Illinois at Urbana-Champaign. “With relatively little cost, we can unlock a lot of money that is now being directed toward things which are not helpful and put that money toward doing research.”

    But making it happen will be up to the federal government.

    Matt Owens, president of COGR, urged federal policymakers in a statement Wednesday afternoon “to act this fall on the most actionable and timely of the options.”

    “If the administration and Congress are rightly interested in reducing regulatory burden and to promote scientific advancements, then they now have a clear roadmap for doing so efficiently and effectively,” he wrote. “What remains to be seen is whether federal policymakers will get behind the wheel, step on the gas, and accelerate through the finish line to fully deliver.”

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  • US proposes visa time limit rule to end “abuse” of system

    US proposes visa time limit rule to end “abuse” of system

    The proposed rule, announced by the Department of Homeland Security (DHS) on August 27, would upend the longstanding “duration of status” policy and enforce additional restrictions on students changing programs and institutions.  

    If finalised, the new rule would limit the length of time international students, professors and other visa holders can stay in the US, which DHS claims would curb “visa abuse” and increase the department’s “ability to vet and oversee these individuals”.  

    Trump initially put forward the proposal during his first administration, only for it to be withdrawn under Biden. In recent weeks, a rehashed version of the plans has been moving closer towards final approval.  

    Yesterday’s publication of the finalised proposal in the Federal Register was met with immediate denunciation by stakeholders who say it would place an undue administrative burden on students as well as representing a “dangerous government overreach”. Now the proposal is under a 30-day public comment period.  

    “These changes will only serve to force aspiring students and scholars into a sea of administrative delays at best, and at worst, into unlawful presence status – leaving them vulnerable to punitive actions through no fault of their own,” said NAFSA CEO Fanta Aw.  

    Under the rule, students could only remain in the US on a student visa for a maximum of four years and would have to apply for a DHS extension to stay longer.  

    The policy document reasons that 79% of students in the US are studying undergraduate or master’s degrees which are generally two or four-year programs, thus: “a four-year period of admission would not pose an undue burden to most nonimmigrant students”.  

    And yet, stakeholders have previously pointed out that the average time taken to complete an undergraduate degree – for both domestic and international students – exceeds four years, meaning that the majority of students would have to file for an extension to complete their studies.  

    Meanwhile, this reasoning does not consider postgraduate students on longer programs or the many students that go onto Optional Practical Training (OPT), who would have to apply for a visa extension as well as the work permit itself. 

    If finalised, master’s students would no longer be able to change their program of study, and first year students would be unable to transfer from the institution that issued their visa documents.   

    Alarmingly, the rule would hand power to the government to determine academic progress, with “a student’s repeated inability or unwillingness” to complete their degree, deemed an “unacceptable” reason for program extensions.  

    It would also limit English-language students to a visa period of less than 24 months, and the grace period for F-1 students, post-completion, would be reduced from 60 to 30 days.  

    Such far reaching provisions amount to “a dangerous overreach by government into academia,” said Aw, pointing out that international students and exchange visitors are already “the most closely monitored non-immigrants in the country.”  

    Government interference into the academic realm in this way introduces a wholly unnecessary and new level of uncertainty to international student experience

    Fanta Aw, NAFSA

    “For too long, past administrations have allowed foreign students and other visa holders to remain in the US virtually indefinitely, posing safety risks, costing untold amount of taxpayer dollars, and disadvantaging US citizens,” DHS said in a statement.  

    Framing the issue as one of national security, the department said it had identified 2,100 F-1 visa holders who arrived between 2000 and 2010 and have remained in status, becoming what DHS called “forever” students “taking advantage of US generosity”.  

    Putting this in perspective, commentators have highlighted that in 2023 alone there were 1.6 million F-1 visa holders in the US.  

    As well as imposing significant burdens on students and intruding on academic decision-making, the proposal would also place strain on federal agencies and increase the existing immigration backlog, warned Miriam Feldblum, CEO of the Presidents’ Alliance on Higher Education and Immigration.

    “International students deserve assurance that their admission period to the US will conform to the requirements of their academic programs,” said Feldblum, issuing a grave warning that the rule would further deter international students and “diminish” US competitiveness.  

    “At a time when the US is already facing declines in international student enrolment, we must do everything we can to keep the door open to these individuals, who are essential to our future prosperity,” she continued, alluding to recent falls in US visa issuance.  

    Since coming to office, a barrage of hostile policies from the Trump administration have erected unprecedented barriers for students hoping to study in the US, with a near-month long visa interview suspension earlier this summer still wreaking havoc on visa appointment availability around the world. 

    The latest government data revealed a 30% drop in student arrivals this July, with colleges bracing for a drastic drop in international student numbers for the upcoming year. If the decline continues, experts have warned of USD $7bn in damages to the US economy.  

    According to Aw, the proposed rule would “certainly” deter international students further, “without any evidence that the changes would solve any of the real problems that exist in our outdated immigration system”. 

    Appealing to Trump’s recent remarks pushing for a more-than doubling of the Chinese student population in the US, Aw urged the government to engage with the sector to ensure the US remained the “premier destination” for global talent while keeping the country “safe and prosperous”. 

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  • In training educators to use AI, we must not outsource the foundational work of teaching

    In training educators to use AI, we must not outsource the foundational work of teaching

    This story was originally published by Chalkbeat. Sign up for their newsletters at ckbe.at/newsletters.

    I was conferencing with a group of students when I heard the excitement building across my third grade classroom. A boy at the back table had been working on his catapult project for over an hour through our science lesson, into recess, and now during personalized learning time. I watched him adjust the wooden arm for what felt like the 20th time, measure another launch distance, and scribble numbers on his increasingly messy data sheet.

    “The longer arm launches farther!” he announced to no one in particular, his voice carrying the matter-of-fact tone of someone who had just uncovered a truth about the universe. I felt that familiar teacher thrill, not because I had successfully delivered a physics lesson, but because I hadn’t taught him anything at all.

    Last year, all of my students chose a topic they wanted to explore and pursued a personal learning project about it. This particular student had discovered the relationship between lever arm length and projectile distance entirely through his own experiments, which involved mathematics, physics, history, and data visualization.

    Other students drifted over to try his longer-armed design, and soon, a cluster of 8-year-olds were debating trajectory angles and comparing medieval siege engines to ancient Chinese catapults.

    They were doing exactly what I dream of as an educator: learning because they wanted to know, not because they had to perform.

    Then, just recently, I read about the American Federation of Teachers’ new $23 million partnership with Microsoft, OpenAI, and Anthropic to train educators how to use AI “wisely, safely and ethically.” The training sessions would teach them how to generate lesson plans and “microwave” routine communications with artificial intelligence.

    My heart sank.

    As an elementary teacher who also conducts independent research on the intersection of AI and education, and writes the ‘Algorithmic Mind’ column about it for Psychology Today, I live in the uncomfortable space between what technology promises and what children actually need. Yes, I use AI, but only for administrative work like drafting parent newsletters, organizing student data, and filling out required curriculum planning documents. It saves me hours on repetitive tasks that have nothing to do with teaching.

    I’m all for showing educators how to use AI to cut down on rote work. But I fear the AFT’s $23 million initiative isn’t about administrative efficiency. According to their press release, they’re training teachers to use AI for “instructional planning” and as a “thought partner” for teaching decisions. One featured teacher describes using AI tools to help her communicate “in the right voice” when she’s burned out. Another says AI can assist with “late-night lesson planning.”

    That sounds more like outsourcing the foundational work of teaching.

    Watching my student discover physics principles through intrinsic curiosity reminded me why this matters so much. When we start relying on AI to plan our lessons and find our teaching voice, we’re replacing human judgment with algorithmic thinking at the very moment students need us most. We’re prioritizing the product of teaching over the process of learning.

    Most teachers I talk to share similar concerns about AI. They focus on cheating and plagiarism. They worry about students outsourcing their thinking and how to assess learning when they can’t tell if students actually understand anything. The uncomfortable truth is that students have always found ways to avoid genuine thinking when we value products over process. I used SparkNotes. Others used Google. Now, students use ChatGPT.

    The problem is not technology; it’s that we continue prioritizing finished products over messy learning processes. And as long as education rewards predetermined answers over curiosity, students will find shortcuts.

    That’s why teachers need professional development that moves in the opposite direction. They need PD that helps them facilitate genuine inquiry and human connection; foster classrooms where confusion is valued as a precursor to understanding; and develop in students an intrinsic motivation.

    When I think about that boy measuring launch distances with handmade tools, I realize he was demonstrating the distinctly human capacity to ask questions that only he wanted to address. He didn’t need me to structure his investigation or discovery. He needed the freedom to explore, materials to experiment with, and time to pursue his curiosity wherever it led.

    The learning happened not because I efficiently delivered content, but because I stepped back and trusted his natural drive to understand.

    Children don’t need teachers who can generate lesson plans faster or give AI-generated feedback, but educators who can inspire questions, model intellectual courage, and create communities where wonder thrives and real-world problems are solved.

    The future belongs to those who can combine computational tools with human wisdom, ethics, and creativity. But this requires us to maintain the cognitive independence to guide AI systems rather than becoming dependent on them.

    Every time I watch my students make unexpected connections, I’m reminded that the most important learning happens in the spaces between subjects, in the questions that emerge from genuine curiosity, in the collaborative thinking that builds knowledge through relationships. We can’t microwave that. And we shouldn’t try.

    Chalkbeat is a nonprofit news site covering educational change in public schools.

    For more news on AI in education, visit eSN’s Digital Learning hub.

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  • Building a Course from Scratch: When Time is Not on Your Side – Faculty Focus

    Building a Course from Scratch: When Time is Not on Your Side – Faculty Focus

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