Tag: English

  • College English classrooms should be slow (opinion)

    College English classrooms should be slow (opinion)

    In a minorly famous letter to the duchess of Sutherland, Henry James advises that The Ambassadors should be read “very easily and gently,” specifying that his correspondent should ideally “read five pages a day.” At this pace, the duchess would have taken almost exactly 13 weeks to finish the book if she read every day of the week. One imagines that the novel would be tucked into otherwise inaccessibly glamorous, luxurious days for the duchess, days filled with, among other comforts, corresponding with James about how to read his latest novel.

    Five pages a day is very slow reading, but most of us would love to approach our reading at a more leisurely pace, if not a pace determined so prescriptively. On the other side of the spectrum of reading experiences, one finds the average student in college English classes—both undergraduate and graduate. To use my experience as an example, I was at the nadir of my reading life as an undergraduate English major; as someone who naturally reads quite slowly, I spent many nights of my undergraduate career standing at my dresser so I wouldn’t fall asleep while reading. (I couldn’t afford, and doubt I had ever heard of, a standing desk at that point in my life, and my dresser was the tallest piece of furniture in my room.)

    While doing this, I often took notes blindly in a notebook with my right hand while I held whatever book I was reading in my left. I would reread my notes the next morning to help me remember what I had read the night before. I loved the books I was reading, and I wanted to succeed in the classes I took, but I was also, by trying to read upward of 500 pages a week, making myself miserable.

    I don’t blame the professors who assigned the reading—all of them were gifted pedagogues, and not all of them assigned too much reading. They, too, inhabited a culture in which they were expected to work quickly and fulfill numerous demanding institutional roles (years later, I still remember one of my undergraduate professors saying she worked around 70 hours a week).

    Now that I’m on the other side of the academic experience, however, I’ve come to realize that each of us is responsible for resisting a culture that is, by all accounts, making students anxious, depressed and—dare I say it—unproductive at unprecedented rates. Students in undergraduate classes are primed to work quickly. Almost every part of their life—their experience on social media, their online shopping, their use of ChatGPT to complete assignments and their selection of a route on Apple Maps—is designed to help them reach tangible and intangible destinations as quickly as possible. Most students, meanwhile, are terrible at working slowly.

    As academicians, we’re constricted, of course, by all the reasonable and unreasonable demands placed on us by work, family and the other important parts of life, and when we read—especially when we read for professional, critical purposes—we read and work as quickly as possible, that “possible” being an ever-nebulous boundary toward which we strain and suffer while still trying to produce quality work. As professors, if we read books like The Ambassadors, we’re likely to read them in bursts and chunks—butcherly words that sound as unappealing as the process of reading a dense, beautiful novel in such a manner actually is.

    While we cannot, in the immediate future, totally alter the institutional structures of postsecondary liberal arts education, there are still things that English professors can do to resist the pressure for speed. Chief among them is to design a classroom that encourages our students to go slow.

    In their 2016 book, The Slow Professor, Maggie Berg and Barbara K. Seeber challenged the culture of speed in academia by advising faculty to work more slowly, a laudable goal, but one that critics pointed out was a luxury that untenured faculty simply couldn’t enjoy. The problem, of course, is that the people who design a job decide how much work ought to be accomplished in a given time frame, and untenured faculty have little control over the amount of work they are expected to produce to attain job security. However, what almost all professors, regardless of contract status, do have control over is how much work we require within a given time frame from the students we teach. In other words, we should design classes that treat our students in a way that we’d like our institutions to treat us.

    As English professors, our job is not to encourage quick thinking but to foster thorough, imaginative and critical thinking. To do this, we must design our courses to foster and prompt slow work that breaks students out of the habits of expediency they have developed throughout their time in school. Designing classes that foster intentional slowness takes effort, but it also means that we can craft the kinds of spaces that make literature enjoyable and show students the value and beauty of literary texts when they are encountered in an environment suitable for literary consumption.

    A slow classroom can take several forms. In the slow classes I’ve taught, it means requiring students to purchase paper copies of the texts we read and to keep a real, physical journal in which they respond to prompts weekly outside of class. I also do something in these classes that I wish someone had done for me when I was a student: I make it clear that they should spend a certain amount of time on work for my class outside the classroom but that they should also give themselves a cutoff time, especially when it comes to reading for class. I tell them that I take around two or three minutes to read a page of a novel well, sometimes more if the prose is dense, and that they should plan for each page of reading to take three to four minutes. I also tell them that if they make time to read and don’t finish, they shouldn’t panic; they should move on with their day and enjoy the nonacademic parts of their life.

    Most importantly, I assign less reading. Of course, I’d love to live in a world where my students have thoroughly read the English literary canon (whatever that means), but more than anything, I want them to have read something and to have read it well. To this end, I try to assign between 20 and 30 pages of reading per class meeting, which amounts to around 10 to 15 pages per day, not too far from James’s edict. Rather than just assigning this reading and hoping for the best, I explain to my students about why I assign this number of pages, talk to them about creating and choosing a time and space to read in their daily lives, and describe the process of reading in my class as one they should understand as a reprieve from the time-pressured demands of other courses.

    In class, I designate much of our time together as technology-free in order to make space for the rich and meaningful conversations that occur most fruitfully when we aren’t distracted by notifications from our phones and laptops. Students engage in small group and classwide discussions, and I challenge them with daily questions that push them out of their comfort zones. I task them with coming up with steel man arguments in support of cultural and fictional villains, I ask them to articulate what makes a good life by finding evidence for and theories of good lives in their reading, and I frequently make them dwell with a given scene until we’ve extracted every last bit of sense (and often a bit of senselessness) from it.

    We tackle around one question a day, if we’re lucky. But the answers and questions we walk away with are finer and fuller than the formulaic answers that students give when they’re in a hurry. In return for designing my class in a way that allows students to work slowly, I expect around the same amount of essayistic output in terms of page numbers, but I design essays to be completed slowly, too, by scaffolding the work and requiring creative responses to prompts to encourage the slow, critical thinking and writing that English professors long to read and rarely encounter. I’ve received work that was thoughtful and occasionally even beautiful, work that couldn’t have been written by AI.

    In many ways, my experience of earnestly trying to read around 500 pages of fiction a week as an undergraduate might seem anachronistic. Professors across disciplines have noted the apparent inability of students to engage with any extended reading, whether this means they’re not reading at all or that they just ask ChatGPT to do the “reading” for them. The irony of worrying—as many academics seem to be doing these days—that students will use artificial intelligence to read or write for them is that many undergraduate classes require students to work like machines, to read and write at a breakneck pace, a demand that prompts the ridiculous phenomenon of classes on speed reading, which many universities advertise and which are also available online (the one I’ve linked here is accompanied by the terrifying motto “Reading at the Speed of Thought™”).

    In a discipline for which the core method is close reading, the idea of students reading a novel as quickly as possible ought to make English professors shudder, and while it’s not necessary to dedicate an entire semester to a single novel, we ought to see course design as part of the solution to students rushing through their work. In an age that privileges fast work, near-constant availability and answers on demand, the slow English classroom is a reprieve, a space where deep, creative and inspired thought is given the time it needs to blossom.

    While our students will likely never occupy the rarefied spaces that the duchess of Sutherland enjoyed when James wrote to her in 1903, with our guidance and course design, they can experience the joy, power and, yes, the luxury of reading and writing slowly. We just have to give them the time.

    Luke Vines is a sixth-year Ph.D. candidate in the Department of English at Vanderbilt University. He recently began serving as the assistant director for academic support at Berry College.

    Source link

  • Embracing a growth mindset when reviewing student data

    Embracing a growth mindset when reviewing student data

    Key points:

    In the words of Carol Dweck, “Becoming is better than being.” As novice sixth grade math and English teachers, we’ve learned to approach our mid-year benchmark assessments not as final judgments but as tools for reflection and growth. Many of our students entered the school year below grade level, and while achieving grade-level mastery is challenging, a growth mindset allows us to see their potential, celebrate progress, and plan for further successes amongst our students. This perspective transforms data analysis into an empowering process; data is a tool for improvement amongst our students rather than a measure of failure.

    A growth mindset is the belief that abilities grow through effort and persistence. This mindset shapes how we view data. Instead of focusing on what students can’t do, we emphasize what they can achieve. For us, this means turning gaps into opportunities for growth and modeling optimism and resilience for our students. When reviewing data, we don’t dwell on weaknesses. We set small and achievable goals to help students move forward to build confidence and momentum.

    Celebrating progress is vital. Even small wins (i.e., moving from a kindergarten grade-level to a 1st– or 2nd-grade level, significant growth in one domain, etc.) are causes for recognition. Highlighting these successes motivates students and shows them that effort leads to results.

    Involving students in the process is also advantageous. At student-led conferences, our students presented their data via slideshows that they created after they reviewed their growth, identified their strengths, and generated next steps with their teachers. This allowed them to feel and have tremendous ownership over their learning. In addition, interdisciplinary collaboration at our weekly professional learning communities (PLCs) has strengthened this process. To support our students who struggle in English and math, we work together to address overlapping challenges (i.e., teaching math vocabulary, chunking word-problems, etc.) to ensure students build skills in connected and meaningful ways.

    We also address the social-emotional side of learning. Many students come to us with fixed mindsets by believing they’re just “bad at math” or “not good readers.” We counter this by celebrating effort, by normalizing struggle, and by creating a safe and supportive environment where mistakes are part of learning. Progress is often slow, but it’s real. Students may not reach grade-level standards in one year, but gains in confidence, skills, and mindset set the stage for future success, as evidenced by our students’ mid-year benchmark results. We emphasize the concept of having a “growth mindset,” because in the words of Denzel Washington, “The road to success is always under construction.” By embracing growth and seeing potential in every student, improvement, resilience, and hope will allow for a brighter future.

    Latest posts by eSchool Media Contributors (see all)

    Source link

  • Revolutionizing storytelling with AI: Empowering ELLs

    Revolutionizing storytelling with AI: Empowering ELLs

    Key points:

    Imagine this: You assign your students a writing prompt, and while some eagerly begin crafting their stories, others stare at the blank page, muttering, “I have nothing to write,” or “I can’t think of a story.” For English Language Learners (ELLs), this scenario is even more daunting due to limited vocabulary or fear of making mistakes. In fact, studies show that a lack of confidence and linguistic resources often prevents ELLs from fully engaging in creative writing, despite their rich cultural and personal experiences.

    As educators, we constantly seek ways to help students overcome these barriers. Enter artificial intelligence (AI)–a powerful tool that transforms storytelling into an accessible and engaging experience for every student. By integrating AI into storytelling, we can empower students to generate ideas, build confidence, and create compelling narratives, all while developing their language skills.

    Getting started: Using AI to spark creativity

    A simple and engaging way to introduce AI in storytelling is by using a writing prompt and generating an example story opening with ChatGPT. For instance, you might ask: “Write the opening to a mysterious story about an abandoned lighthouse.”

    ChatGPT could respond: “The wind howled through the cracks of the abandoned lighthouse, carrying whispers of secrets long forgotten. The light, extinguished for decades, seemed to flicker faintly as if trying to tell a story no one had yet heard.”

    Students can take this opening and continue the story in their own words, expanding the scene, introducing new characters, or creating a plot twist. This method not only sparks creativity but also provides ELLs with a scaffold, building their confidence to dive into storytelling.

    To bring their stories to life, students can use AI image generators like DALL-E or tools like Canva to create visuals matching their narratives. For example, they could create an eerie image of the abandoned lighthouse with flickering light and stormy skies. This connection between words and visuals reinforces comprehension and engages students in the storytelling process.

    The final step is sharing stories and visuals with the class. Presenting their work allows students to practice speaking, gain confidence, and showcase their creativity.

    How AI enhances storytelling

    AI tools offer unique opportunities to support ELLs in their storytelling journey. When
    students struggle to come up with ideas, tools like ChatGPT can provide engaging prompts and vivid descriptions to spark creativity. For example, a student might request a description of a magical forest and receive a response like: “A forest bathed in golden sunlight, where trees tower like ancient guardians and the air shimmers with tiny, glowing orbs.” Such detailed imagery can inspire students to dive into their stories with greater confidence.

    In addition to idea generation, AI tools help expand students’ vocabulary. ELLs can use AI to explore synonyms or alternative ways to describe scenes, enriching their language repertoire.

    For instance, if a student wants to avoid repeating the word “beautiful,” the AI might suggest options like “stunning,” “captivating,” or “breathtaking,” enabling more nuanced and expressive writing.

    Visual storytelling is another area where AI shines. Tools like DALL-E or Adobe Express allow students to create images that align with their narratives, making their stories come to life. For example, a student writing about a mysterious glowing orb could generate a corresponding image, blending creative thinking with visual artistry.

    Once students have drafted their stories, AI-based writing assistants like Grammarly can help refine their grammar, spelling, and sentence structure. This process encourages independence and self-correction, teaching students to identify and address their mistakes while improving the overall clarity and polish of their work.

    Interactive platforms like Twine take storytelling to a new level by enabling students to create “choose your own adventure” narratives. For example, students might create a mystery where readers decide whether to follow a shadowy figure or stay hidden, leading to different outcomes. This fosters critical thinking and collaboration as students craft branching storylines and engage in problem-solving to connect various plot points.

    Classroom example: AI in action

    In a Grade 8 ESL classroom, students were given the prompt: “Write about a strange object you find buried in your backyard.” After brainstorming ideas with ChatGPT, one student created a story about a glowing orb that transported them to another dimension. They used DALL-E to generate an image of the orb, and Twine to develop a branching narrative where the reader decides whether to touch the orb or call for help. The result was an immersive storytelling experience that combined creativity with critical thinking.

    By incorporating AI tools, students not only created more engaging stories but also developed their language skills in a meaningful and enjoyable way.

    Making storytelling accessible and engaging

    Using AI in storytelling doesn’t just overcome barriers; it transforms the experience for students. Visual elements and interactivity keep learners engaged, while tools for grammar and vocabulary improvement build confidence. For ELLs, AI provides scaffolding and encouragement to take creative risks and express themselves authentically.

    Guiding responsible AI use

    While AI opens doors to creativity, teaching students to use these tools responsibly is
    essential.

    Students need to understand the concept of AI “hallucinations,” where AI generates
    inaccurate or entirely fabricated information. For instance, an AI might describe a historical event inaccurately or create a fictional fact that seems plausible. Educators should teach students to verify AI-generated information with reliable sources.

    Equally important is teaching students how to craft clear and specific prompts. For example, instead of asking, “What happens in a story?” they might ask, “Can you suggest a story idea about a character who solves a mystery in a small town?”

    Modeling this process helps students see how precise wording yields better results.
    Encouraging critical thinking is also crucial. Teachers can create opportunities for students to analyze AI-generated content by asking: “Does this make sense? Is it accurate? Can I verify it elsewhere?” Such discussions help students see AI as a helpful tool, but not an infallible one.

    Students should also learn that AI is a partner in creativity, not a replacement for their
    original thinking. They must guide the AI, evaluate its outputs, and make creative decisions to ensure their work remains authentically theirs. Additionally, students should be encouraged to credit AI-generated content appropriately to foster ethical use.

    Conclusion

    Storytelling is a cornerstone of language learning, offering ELLs opportunities to build
    vocabulary, practice grammar, and express their ideas. With AI, the storytelling process becomes more accessible, engaging, and impactful. From generating prompts to creating visuals and refining drafts, AI supports students in overcoming challenges and discovering the joy of storytelling.

    By integrating AI tools responsibly, educators empower every student to find their voice and share their unique stories with confidence. In the intersection of creativity and technology, AI has the potential to revolutionize the way we teach and learn storytelling

    Latest posts by eSchool Media Contributors (see all)

    Source link

  • Colombia, first nationals deported under the Donald Trump administration arrived (TeleSur English)

    Colombia, first nationals deported under the Donald Trump administration arrived (TeleSur English)

    The first flights carrying migrants deported from the United States to Colombia. The Colombian government confirmed on Tuesday that two planes
    carrying migrants had landed. Some were reportedly shackled. A total of 201 migrants: 110 sent from
    California and 90 from Texas were on board. Among the deportees were two pregnant women and more than 20 children. The cost to US taxpayers is estimated to be $100,000 to $700,000 per flight. The long-term costs and consequences of this program with Latin America, like many others over the last century, have not been estimated. 

    Source link

  • Rethinking the Financial Challenge of English Universities

    Rethinking the Financial Challenge of English Universities

    By Adam Habib, Vice-Chancellor at SOAS University of London, and Lord Dr. Michael Hastings of Scarisbrick CBE, Chair of the Board of Trustees at SOAS.

    The business model of English higher education is broken. We are not sure that this simple fact is sufficiently understood by all stakeholders in higher education. Do not mistake us: we all recognise the serious financial crises that most English universities are confronting. But this is not the same as understanding its causal features and what to do about it. The latest financial report from the Office for Students (OfS), released in mid-November, suggests 72% of English universities will be in deficit by the end of the academic year if they continue as is. It does not suggest much about how to address it. In fact, it does not even ask why the other 28% of universities are not in deficit. Is this because of their historical endowments or their specific student profile, or are they doing something the others are not?

    But the OfS is not the only stakeholder reluctant to ask the hard questions: how we got here and what to do about it. This malady afflicts almost all other stakeholders. Let’s begin with the basics. Almost three decades ago, the British government committed to massifying education and ensuring that at least 50% of their school-leaving population had the privilege of going to university. The challenge was how to pay for it. They introduced fees, first as a small proportion of the actual cost in 2006, and then to cover the entire cost in 2012 (at least for Business degrees, Humanities and the Social Sciences). The popular backlash this generated, especially since almost all universities rushed to implement the maximum permitted fee, led the politicians to subsequently avoid increasing fees in line with inflation. The net effect was that within a few years, the actual cost of university education outstripped the fees.

    The solution followed by most universities was to increase international fees and their intakes of foreign students. To attract more of these students, universities borrowed heavily, built shiny new facilities, expanded their pastoral services and grew their student numbers. This was assisted in part by the removal of student number caps on home students. Costs increased, and to cover these, more income was required, which led to even higher international fees and more foreign students.

    All higher education stakeholders were complicit in this. The Government initially supported this solution because it obviated the need for more government subsidies and enabled foreign currency earnings. Vice-chancellors and higher education executives deluded themselves in thinking that the international postgraduate masters students came to the UK universities because of their institutions’ research reputations, even though survey after survey demonstrated that these students were increasingly attracted by the prospect of employment prospects and the post-study visa. Unions, both academic and professional service ones, acquiesced given that these international fees enabled higher salaries and subsidised greater research time for academics. There was even broader public support as it contained the fees for domestic students.

    Until of course, a new breed of ethnically oriented right-wing politicians mobilised on the chauvinistic instinct of there being too many foreigners in Britain. This first manifested in Brexit, then China and subsequently all foreigner-bashing, and finally visa restrictions on dependents. The net effect was a dramatic fall in applications and enrolment of international students, with the ensuing financial crisis of universities in the UK. A positive spin-off of this state of affairs is that almost all stakeholders now recognise the flimsy fiscal foundation of universities. The negative feature is that it still has not generated an honest reflection and behaviour on the part of all stakeholders or a sufficiently deep deliberation on the business model of higher education in the UK and what to do about it.

    Take, for instance, the stance of government. The Secretary of State for Education announced in the House of Commons on 4 November 2024 the first university fee increase for undergraduate students in eight years. Yet the Chancellor had increased the Employer National insurance a few days before from 13.8 to 15 percent. The net effect is a further loss of £59 million for universities in the UK from the 2025/26 academic year.

    Neither is the debate in universities more imaginative on what to do about the financial crisis and the business model of higher education. University vice-chancellors and Universities UK have recognised the need to revert to greater public funding for higher education, although there is a broad recognition that this is an unlikely solution in the near future given the fiscal crisis of the state. They have suggested through individual vice-chancellor advocacies that universities would require the financial equivalence of £12,000 fees, but again, almost all recognise the political challenge of achieving this during a cost-of-living crisis. The reluctant fallback back? A retreat to international student fees by retracting or reforming the visa restrictions, thereby allowing for further increases in income from foreign students.

    But this is just not a feasible solution for the long term. Higher education in the UK has priced itself out for ordinary international students looking solely for a higher education qualification. The only rationales for postgraduate master’s students accessing UK universities, given their high-cost structure, are either post-study employment or the learning of a specific qualification not available in alternative higher education settings. The former is increasingly becoming politically unfeasible, and the latter is not a sufficiently large market to financially sustain British universities.

    This is in addition to the moral and commercial challenges of this business model. As we have suggested elsewhere, there should be serious objections to this model, which is effectively directed towards sucking out resources from countries far more impoverished than the UK, to essentially cross-subsidise domestic citizens. Moreover, it accelerates the brain drain, weakening institutional capacities and human capabilities in the majoritarian world at precisely the moment when such societies require an enhancement of capabilities to address the local manifestations of transnational challenges like climate change, pandemics, food insecurity and war.

    Where to go from here, then? First, there is an urgent need for an honest conversation led by government without any smoke and mirrors on the fiscal latitude available to it and the consequences thereof for the financing of higher education. Second, there is a need for a thorough reflection on what has fiscally worked, and what has not in the recent past on the management and executive stewardship of universities in the UK. Third, there is a need for an honest discussion in universities on the fiscal viability of excessively small classes and unduly low staff-student ratios, 40% research time for all teaching and research contracts, and the importance of institutional differentiation in mandates and how these should speak to the former two elements. Finally, we need to think through the limits of cross-subsidising from international student fees and what new opportunities are opening up globally for fulfilling our institutional mandates.

    One opportunity, that has not been sufficiently explored by British universities, is how to assist in the education and training of hundreds of millions of young people in the majoritarian world. This is an urgent necessity not only for the economic development of these societies but also for enabling societies across the world to manage the transnational challenges of our time, without which we may not survive as a human species. Obviously, this will not be possible on the existing cost structures or business models of higher education. But partnering with universities in the Global South, involving the joint development of curricula, co-teaching and co-assessment, could bring down cost structures of higher education. This could then feed into more reasonable fees being charged, thereby opening up new higher education markets for British universities. Cost structures could also be reconsidered in relation to scale. The more students there are within a program, limited to pedagogical requirements, the more cost per student is reduced, and the more competitive fees can become. New technologies involving online teaching and global classrooms, many of which were pioneered for our own students during the Covid-19 Pandemic, can make this equitable transnational teaching even more feasible.

    Some forms of transnational teaching are already underway in UK universities. But these often take the form of online learning, overseas campuses and franchise models of higher education, all of which are only directed at obviating the financial challenges of British universities. While we would be reluctant to take rigid positions against these models – they may indeed be relevant in certain contextual circumstances – we do hold that the equitable partnership model identified above holds the pedagogical benefit of enabling learning that is both globally grounded and locally relevant. It also does not pit the financial security of British universities against that of universities of the majoritarian world. Essentially, these equitable teaching partnerships can pioneer one element of a new business model that enhances collaboration and mutual benefit for universities in the UK and the majoritarian world.

    Such a model of higher education could also become part of the soft power arsenal of the UK. Increasingly, government has broached the idea of a global Britain. This would be a Britain recognised as a collaborative partner of other nations, enabling them to achieve their national objectives, while enabling itself to be economically competitive and socially responsive to both its own citizens and its international obligations. An equitable orientation to its higher education system would assist this strategic national agenda.

    We are by no means suggesting that equitable transnational learning should replace all other forms of teaching in UK higher education. This would be unrealistic and, frankly, would violate the responsibility of British universities to be nationally responsive. Instead, we recommend that in the pursuit of a financially sustainable higher education system, a diverse set of income strategies – subsidy, domestic fees, international fees, ODL, executive education and equitable transnational educational partnerships – is required. This final strategy not only opens up a new higher education student market at a different price point but also enables us to square our imperative to be financially sustainable with our commitment to be socially and globally responsive.

    The strategic challenge of managing higher education institutions in the contemporary era is the management of tensions between competing imperatives. It also requires thinking outside the box, innovating and finding new markets, and servicing these at new price points, while continuing to meet the social obligations implicit in the mandate of universities. This is what we believe is sometimes missing from the deliberations on making British universities financially sustainable. The debate can only be enriched and the recommendations made more robust if we are prepared to think beyond what we are comfortable with.

    Source link

  • Innovation and skills in the English devolution white paper

    Innovation and skills in the English devolution white paper

    Devolution is a central plank of the government’s growth agenda. Providing places with the tools and resources to address local problems in ways that make sense on the ground is a means to unleash potential – and to end what English devolution minister Jim McMahon is happy to call the “top-down micromanaging” approach of ringfencing funds and centralising decision making.

    The launch of the English devolution white paper is the first step on that journey. Strategic authorities, led (for preference) by elected mayors, will cover the entirety of England. Integrated settlements will provide powers covering transport, infrastructure, housing, public services – and, of particular interest to the higher education sector, skills and innovation.

    A big part of the work of the white paper is in consolidating and standardising what had become an unruly system. Sitting above unitary, county, and district councils, a layer of strategic authorities will take on the services that larger areas need to thrive:

    Our goal is simple. Universal coverage in England of Strategic Authorities – which should be a number of councils working together, covering areas that people recognise and work in. Many places already have Combined Authorities that serve this role.

    The forthcoming English Devolution Bill will enshrine this concept in law. We get a computer game-like hierarchy of how strategic authorities will level up (so to speak): foundation strategic authorities (which do not – yet – have a mayor), followed by mayoral strategic authorities, which can then “unlock” designation as established mayoral strategic authorities through fulfilling various criteria. This will grant integrated funding settlements and other treats such as the ability to pilot new kinds of devolution.

    Already eligible for this top designation are Greater Manchester, Liverpool City Region, the North East, South Yorkshire, West Midlands, and West Yorkshire. There’s an aspiration for something similar to apply to London as well, but some legislative fiddling will be needed due to the capital’s “unique circumstances.”

    Innovation

    If you’ve got your head around the different levels of hierarchy, there’s actually quite a lot in the white paper for research and innovation, dependent on an area’s level of devolution.

    In language echoing the industrial strategy green paper, we are told that a strong local network of public and private institutions focused on R&D, innovation, and the diffusion of ideas “is one of the factors which sets highly productive local economies apart.” A big part of this is closer join-up between UKRI and local government.

    Working our way up the devolution ladder, all strategic authorities (including foundation level) will be able to draw on UKRI data on the location of R&D investments, to better allow them to “understand publicly supported innovation activity in their region and how to best take advantage of it.”

    Those mayoral strategic authorities will additionally work with Innovate UK to produce joint plans, to shape long-term innovation strategies and investments in places. UKRI will also be extending its regional partnerships and “network of embedded points of contact” with mayoral strategic authorities.

    And then coming up to the pinnacle of devolution, those established mayoral strategic authorities – to remind you: Greater Manchester, Liverpool City Region, the North East, South Yorkshire, West Midlands, and West Yorkshire, and possibly London – will get actual devolved research funding, in the form of a future regional innovation funding programme allowing local leaders to develop “bespoke innovation support offers for their regions.”

    This draws somewhat on the spirit of the Regional Innovation Fund, though this was allocated to individual higher education institutions – what’s on offer here sounds like a pot of money controlled by mayors. Its format is also to be based on lessons learned from the Innovation Accelerator pilot, which was funding by levelling up money.

    Plus, established mayoralties will get an annual meeting with the science minister, more regular engagement with senior staff at UKRI, and the chance to be consulted on the development of relevant DSIT and UKRI strategies.

    All in all, it’s a decent start down the road of a more significantly devolved research landscape. Important to note, however, that the actual funding on offer to established mayors is contingent on next year’s spending review, and so we’re talking about 2026–27 onwards here. And we might also observe that the House of Commons science committee’s inquiry into regional R&D, announced last week, has clearly been set up with an eye to influencing how this all comes together.

    At least to begin with, there will also be a not insignificant gap between what’s on offer to the most established sites of devolution – some funds to spend as desired, a seat at the strategy table – and what those “foundation” strategic authorities receive, which will be little more than a bit of regional R&D data. There’s potential for imbalance between regions here. Foundation-level authorities are described as a “stepping stone” to later acquiring a mayor, but it could be a long and drawn-out process.

    Skills and more

    On skills, strategic authorities will retain ownership of the Adult Skills Fund (with ringfencing removed from bootcamp and free course pots to allow for flexibility), take on joint ownership of Local Skills Improvement Plans alongside employer representative bodies, and work with employers to take on responsibility for promoting 16-19 pathways. In future, strategic authorities will have a “substantial role” in careers and employment support design outside of the existing Jobcentre Plus network, as the Get Britain Working white paper gestured towards.

    You’ll have spotted that this does not immediately extend to higher education, except to the extent that universities and colleges already get involved with adult skills provision. However the centre of gravity is such that any provider with an avowed interest in the local area will end up developing close relationships with strategic authorities. It isn’t just on skills or innovation – many universities work with local government on issues that affect students (and staff!) such as housing, infrastructure, and transport, and will have a strong interest in working with strategic authorities with new and wider powers to act.

    Administrative geography corner

    If you are labouring under the impression that dividing England up into administrative chunks is a fairly straightforward task, may we introduce you to possibly the single finest document ever published by the Office for National Statistics: the Hierarchical Representation of UK Geographies.

    Pedants may also note that the existing geography of LSIPs, which was controversially allowed to evolve into being outside of the established local authority boundaries, does not map cleanly to current or proposed local authorities – something that a future iteration of plans may need to consider. Likewise, the scope of university core recruitment areas or civic aspirations may not map to either.

    What we’d have loved to have shown you is a map showing which of the new strategic authorities your campus might be in. Sadly the boundaries of the “current map of English devolution” included in the white paper do not cleanly map to England’s many contradictory systems of administrative geography. Some of the devolved areas depicted are almost LSIP regions, one (Surrey) is a non-metropolitan ceremonial county, and one – Devon, including Torbay but not under any circumstances Plymouth – is just plain mad.

    As soon as we get an answer and some boundaries from ONS, we’ll let you know. In the meantime, here’s the map from the white paper:

    Source link

  • Institutional constraints to higher education datafication: an English case study

    Institutional constraints to higher education datafication: an English case study

    by Rachel Brooks

    ‘Intractable’ datafication?

    Over recent years, both policymakers and university leaders have extolled the virtues of moving to a more metricised higher education sector: statistics about student satisfaction with their degree programme are held to improve the decision-making processes of prospective students, while data analytics are purported to help the shift to more personalised learning, for example. Moreover, academic studies have contended that datafication has become an ‘intractable’ part of higher education institutions (HEIs) across the world.

    Nevertheless, our research (conducted in ten English HEIs, funded by TASO) – of data use with respect to widening participation to undergraduate ‘sandwich’ courses (where students spend a year on a work placement, typically during the third year of a four-year degree programme) – indicates that, despite the strong claims about the advantages of making more and better use of data, in this particular area of activity at least, significant constraints operate, limiting the advantages that can accrue through datafication.

    Little evidence of widespread data use

    Our interviewees were those responsible for sandwich course provision in their HEI. While most thought that data could offer useful insights into the effectiveness of their area of activity, there was little evidence of ‘intractable’ data use. This was for three main reasons. First, in some cases, interviewees explained that no relevant data were collected – in relation to access to sandwich courses and/or the outcomes of such courses. Second, in some HEIs, relevant data were collected but not analysed. Such evidence tends to support the contention that ‘data lakes’ are emerging, as HEIs collect more and more data that often remain untapped. Third, in other cases, appropriate data were collected and analysed, but in a very limited manner. For example, one interviewee explained how data were collected and analysed in relation to the participation of students from under-represented ethnic groups, but not with respect to any other widening participation categories. This limited form of datafication, in which only some social characteristics were datafied, was not, therefore, able to inform any action with respect to the participation of widening participation students generally. Indeed, across all ten HEIs, there was only one example of where data were used in a systematic fashion to help analyse who was accessing sandwich courses within the institution, and the extent to which they were representative of the wider student population.

    Constraints on data use

    Lack of institutional capacity

    In explaining this absence of data use, the most commonly identified constraint was the lack of institutional capacity to collect and/or analyse appropriate data. For example, one interviewee commented that they did not have a very good data system for placements – ‘we are still quite Excel- based’. Excel spreadsheets were viewed as limited as they could not be easily shared or updated, and data were relatively hard to manipulate. This, according to the interviewee, made collection of appropriate data laborious, and systematic analysis of the data difficult. Interviewees also pointed to the limited time staff had available to analyse data that the institution had collected.

    Prioritisation of ‘externally-facing’ data

    Several interviewees described how ‘externally-facing data’ – i.e. that required by regulatory bodies and/or that fed into national and international league tables – was commonly prioritised, leaving little time for information officers to devote to generating and/or analysing data for internal purposes. One interviewee, for example, was unclear about what data, if any, were collected about equity gaps but believed that they were generally only pulled together for high-level reports ‘such as for the TEF’.

    Institutional cultures

    A further barrier to using data to analyse access to and outcomes of sandwich courses was perceived to be the wider culture of the institution, including its attitude to risk. An interviewee explained that the data collected in their institution was limited to two main variables – subject of study and fee status (home or international) – because of ‘ongoing cautiousness at the university about how some of that data is used and how it’s shared with different teams’.

    In addition, many participants outlined the struggles they had faced in gaining access to relevant data, and in influencing decisions about what should be collected and what analyses should be run. Several spoke of having to ‘request’ particular analyses to be run (which could be turned down), leading to a fairly ad hoc and inefficient way of proceeding, and illustrating the relative lack of agency accorded to staff – typically occupying mid-level organisational roles – in accessing and manipulating data.

    Reflections

    Examining a discrete set of activities within the UK higher education sector – those relating to sandwich courses – provides a useful lens to examine quotidian practices with respect to the availability and use of data. Despite the strong emphasis on data by government bodies and HEI senior management teams, as well as the claims made about the ‘intractability’ of HEI data use in the academic literature, our research suggests that datafication is perhaps not as widespread as some have claimed. Indeed, it indicates that some areas of activity – even those linked to high profile political and institutional priorities (in this case, employability and widening participation) – have remained largely untouched by ‘intractable’ datafication, with relevant data either not being collected or, where it is collected, not being made available to staff working in pertinent areas.

    As a consequence, the extent to which students from widening participation backgrounds were accessing sandwich courses – and then succeeding on them – relative to their peers typically remained invisible. While the majority of our interviewees were able to speculate on the extent of any under-representation and/or poor experience, this was typically on the basis of anecdotal evidence and their own ‘sense’ of how inequalities were played out in this area. Although reflecting on professional experience is obviously important, many inequalities may not be visible to staff (for example, if a student chooses not to talk about their neurodiversity or first-in-family status), even if they have regular contact with those eligible to take a sandwich course. Moreover, given the status often accorded to quantitative data within the senior management teams of universities, the lack of any statistical reporting about inequalities by social characteristic, as they pertain to sandwich courses, makes it highly likely that such issues will struggle to gain the attention of senior leaders. The barriers to the effective use of metrics highlighted above may thus have a direct impact on HEIs’ capacity to recognise and address inequalities.  

    The research on which this blog is based was carried out with Jill Timms (University of Surrey) and is discussed in more detail in this article Institutional constraints to higher education datafication: an English case study | Higher Education

    Rachel Brooks is Professor of Higher Education at the University of Oxford and current President of the British Sociological Association. She has conducted a wide range of research on the sociology of higher education; her most recent book is Constructing the Higher Education Student: perspectives from across Europe, published (open access) with Policy Press.

    Author: SRHE News Blog

    An international learned society, concerned with supporting research and researchers into Higher Education

    Source link

  • Article for History UK on what’s next for English HE

    Article for History UK on what’s next for English HE

    Enter your email address to subscribe to this blog and receive notifications of new posts by email.






    Join 379 other subscribers

    Source link