Tag: writing

‘I can tell when it’s been written by AI’

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Warning: the first two paragraphs might feel a bit like wading through treacle but I think what follows is useful and is probably necessary context to the activity linked at the end!

LLMs generate text using sophisticated prediction/ probability models, and whilst I am no expert (so if you want proper, technical accounts please do go to an actual expert!) I think it useful to hone in on three concepts that help explain how their outputs feel and read: temperature, perplexity and burstiness. Temperature sets how adventurous the word-by-word choices are: low values produce steady, highly predictable prose; high values (this is on a 0-1 scale) invite surprise and variation (supposedly more ‘creativity’ and certainly more hallucination). Perplexity measures how hard it is to predict the next word overall, and burstiness captures how unevenly those surprises cluster, like the mix of long and short sentences in some human writing, and maybe even a smattering of stretched metaphor and whimsy. Most early (I say early making it sound like mediaeval times but we’re talking 2-3 years ago!) AI writing felt ‘flat’ or ‘bland’ and therefore more detectable to human readers because default temperatures were conservative and burstiness was low.

I imagine most ChatGPT (other tools are available) users do not think much about such things given these are not visible choices in the main user interface. Funnily enough, I do recall these were options in the tools that were publicly available and pre-dated GPT 3.5 (the BIG release in November ’22). Like a lot of things skilled use can impact (so a user might specify a style or tone in the prompt). Also, with money comes better options so, for example,  Pro account custom GPTs can have precise built in customisations. I also note that few seem to use the personalisation options that override some of the things that many folk find irritating in LLM outputs (Mine states for example that it should use British English as default, never use em dashes and use ‘no mark up’ as default). I should also note that some tools still allow for temperature manipulation in the main user interface (Google Gemini AI Studio for example) or when using the API (ChatGPT). Google AI Studio also has a ‘top P’ setting allowing users to specify the extent to which word choices are predictable or not.  These things can drive you to distraction so it’s probably no wonder that most right-thinking, time poor people have no time for experimental tweaking of this nature. But as models have evolved, developers have embedded dynamic temperature controls and other tuning methods that automatically vary these qualities. The result is that the claim ‘I can tell when it’s AI’ may be true of inexpert, unmodified outputs from free tools but so much harder from more sophisticated use and paid for tools. Interestingly, the same appears true for AI detectors. The early detectors’ reliance on low-temperature signatures now need revisiting too for those not already convinced of their vincibility.  

Evolutionary and embedded changes therefore have a humanising effect on LLM outputs. Modern systems can weave in natural fluctuations of rhythm and unexpected word choices, erasing much of the familiar ChatGPT blandness. Skilled (some would say ‘cynical’) users, whether through careful prompting or bypassing text through paraphrasers and ‘humanisers’,  can amplify this further. Early popular detectors such as GPTZero (at my work we are clear colleagues should NEVER be uploading student work to such platforms btw) leaned heavily on perplexity and burstiness patterns to spot machine-generated work, but this is increasingly a losing battle. Detector developers are responding with more complex model-based classifiers and watermarking ideas, yet the arms race remains uneven: every generation of LLMs makes it easier to sidestep statistical fingerprints and harder to prove authorship with certainty.

For fun I ran this article through GPT Zero….Phew!

It is also worth reflecting on what kinds of writing we value. My own style, for instance, happily mixes a smorgasbord of metaphors in a dizzying (or maybe its nauseating) cocktail of overlong sentences, excessive comma use and dated cultural references (ooh, and sprinkles in frequent parentheses too). Others might genuinely prefer the neat, low-temperature clarity an AI can produce. And some humans write with such regularity that a detector might wrongly flag them as synthetic. I understand that these traits may often reflect the writing of neurodivergent or multi-lingual students.

To explore this phenomenon and your own thinking further, please try this short activity. I used my own text as a starting point and generated (in Perplexity) five AI variants of varying temperatures. The activity was built in Claude. The idea is it reveals your own preferred ‘perplexity and burstiness combo’ and might prompt a fresh look at your writing preferences and the blurred boundaries between human and machine style. The temperature degree is revealed when you make your selection. Please try it out and let know how I might improve it (or whether I should chuck it out the window i.e. DefenestrAIt it)

Obviously, as my job is to encourage thinking and reflection about what this means for those teaching, those studying and broadly the institution they work or study in, I’ll finish with a few questions to stimulate reflection or discussion:

In teaching: Do you think you can detect AI writing? How might you respond when you suspect AI use but cannot prove it with certainty? What happens to the teacher-student relationship when detection becomes guesswork rather than evidence?

For assignment design: Could you shift towards process-focused assessment or tasks requiring personal experience, local knowledge or novel data? What kinds of writing assignments become more meaningful when AI can handle the routine ones? Has that actually changed in your discipline or not?

For your students: How can understanding these technical concepts help students use AI tools more thoughtfully rather than simply trying to avoid detection? What might students learn about their own writing voice through activities that reveal their personal perplexity and burstiness patterns? What is it about AI outputs that students who use them value and what is it that so many teachers disdain?

For your institution: Should institutions invest in detection tools given this technological arms race, or focus resources elsewhere? How might academic integrity policies need updating as reliable detection becomes less feasible?

For equity: Are students with access to sophisticated prompting techniques or ‘humanising’ tools gaining unfair advantages? How do we ensure that AI developments don’t widen existing educational inequalities? Who might we be inadvertently discriminating against with blanket bans or no use policies?

For the bigger picture: What kinds of human writing and thinking do we most want to cultivate in an age when machines can produce increasingly convincing text? How do we help students develop authentic voice and critical thinking skills that remain distinctly valuable?

When you know the answer to the last question, let me know.

Essays & AI: collective reflections on the manifesto one year on

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Its roughly a year since we (Claire Gordon and I plus a collective of academics from King’s & LSE) published the Manifesto for the Essay in the Age of AI. Despite improvements in the tech AND often pretty compelling evidence and arguments for the reduction of take home, long form writing in summative assessments, I STILL maintain the essay has a role as I did this time last year. On one of the pages of the AI in Education short course authored by colleagues at King’s from the Institute of Psychiatry, Psychology & Neuroscience (Brenda Williams) and Faculty of Dentistry, Oral & Craniofacial Sciences (Pinsuda Srisontisuk and Isabel Miletich) they detail patterns of student AI usage. They end with a suggestion that participants take a structured approach to analysing the Manifesto and the outcome is around 150 responses (to date) offerring a broad range of thoughts and ideas from educators working across disciplines and educational levels across the world. This was the forum prompt:

Is the essay dead?

The manifesto above argues that this is not the case, but many believe that long form writing is no longer a reliable way to assess students. What do you think?

Although contributors come from diverse contexts, some shared patterns and tensions really stand out which I share below. I finish with a wee bit of my own flag waving (seems to be a popular pastime recently).

Sentiment balance

The overwhelming sentiment is broad agreement and reformist.

  • Most participants explicitly reject the idea that “the essay is dead”. They value essays for nurturing critical thinking, argumentation, independence and the ability to sustain a coherent structure.
  • A minority voice expresses stronger doubts, usually linked to practical issues (e.g. heavy marking loads, students’ shrinking reading stamina, or the ease of AI-generated text) and call for greater diversification of assessment.
  • There is also a strand of cautious pragmatism: many see the need for significant redesign of both teaching and assessment to remain relevant and credible.

In short, the mood is hopeful and constructive rather than nostalgic or doom ‘n’ gloom. The essay is not to be discarded but has to be re-imagined.

Here are a couple of sample responses:

Not quite dead, no. I think of essays as a ‘thinking tool’ – it’s a difficult cognitive task, but a worthwhile one. I think, as mentioned in the study, an evolution towards ‘process orientated’ assessment could be the saviour of the essay. Perhaps a movement away from the product (an essay itself) being the sole provider of a summative grade is what’s needed. Thinking of coursework, planning, supervisor meetings and a reflective journal on how their understanding developed over the process of researching, synthesising, planning, writing and redrafting could be included. (JF)

In their current form, many take-home essay assessments no long reliably measure a students’ learning, nor mirror the skills students need for the workplace (as has arguably always been the case for many subjects). I wonder if students may increasingly struggle to see the value of writing essays too. However, I do value the thought processes that go into crafting long form writing. I think if essays are thoughtfully redesigned and include an element of choice for the learner, perhaps with the need to draw on some in-house case study or locally significant issue, then essays are not necessarily dead.(AM)

The neat dodge to this question is to suggest the essay will be like the ship of Theseus. It will remain but every component in it will be made of different materials 🙂 (EP)

Key themes emerging from the comments

1. Process over product
A strikingly common thread is the shift from valuing the final script to valuing the journey of thought and writing. Contributors repeatedly advocate staged submissions, reflective journals, prompts disclosure, oral defences or supervised drafting. This aligns directly with the manifesto’s calls to redefine essay purposes and embed critical reflection (points 3 and 4).

2. Productive integration of AI
Few respondents argue for banning AI (obviously the responses are skewed towards those willing to undertake an AI in Education short course in the first place!). Instead, many echo the manifesto’s seventh and eighth points on integration and equity. Suggestions include:

  • require students to document prompts and edits,
  • use AI to generate counter-arguments or critique drafts,
  • support second-language writers or neurodivergent students with AI grammar or audio aids,
  • design tasks tied to personal data, lab results or workplace contexts that AI cannot easily fabricate.

A persistent caution is that without clear guidance, AI may encourage superficial engagement or plagiarism. Transparent ground rules and explicit teaching of critical AI literacy are seen as essential.

3. Expanding forms and contexts
Many contributors support the manifesto’s second point on diverse forms of written work. They propose hybrid assessments such as essays combined with oral presentations, podcasts, infographics or portfolios. Others emphasise discipline-specific needs: scientific reporting, medical case notes, or creative writing, each with distinct conventions and AI implications.

4. Equity, access and institutional support
There is strong agreement that AI’s benefits and risks are unevenly distributed. Participants highlight the need for:

  • institutional investment in staff development and student training,
  • clarity on acceptable AI use across programmes,
  • assessment designs that do not disadvantage those with limited technological access.

5. Rethinking academic integrity
Several comments resonate with the manifesto’s call to revisit definitions of cheating and originality. Rather than policing AI, some suggest designing assessments that render unauthorised use unhelpful or irrelevant, while foregrounding honesty and reflection.

What this means for the manifesto

The forum feedback affirms the manifesto’s central claim that the essay remains a vital, adaptable form, but it also pushes its agenda in useful directions.

  • Greater emphasis on process-based assessment. While the manifesto highlights process and reflection, practitioners want even stronger endorsement of multi-stage, scaffolded approaches and/ or dialogic or presentational components as the cornerstone of future essay design.
  • Operational guidance for AI use. Educators call for more than principles: they need models of prompt documentation, supervised writing practices and examples of AI-resistant or AI-enhanced tasks.
  • Disciplinary specificity. The manifesto could further acknowledge the wide variance in how essays function, from lab reports to creative pieces and provide pathways for each. Of course we, like everyone are subject to a major impediment…
  • Workload and resourcing. Several voices stress that meaningful change requires institutional support and realistic marking expectations; without these, even the best principles risk remaining aspirational. This for me is likely the biggest impediment, not least because of the ongoing, multi layered crises HE is confronted with just now.

Overall, the conversation demonstrates an appetite for renewal rather than retreat to sole reliance on in-person exams though this remains still a common call. I stand with the consensus view that the essay (and other long form writing) is not in terminal decline but in the midst of a necessary transformation. What we need to see is this: Educators alert to the affordances and limitations of AI, conversations happenning between students and those that support them in discipline and with academic skills and students writing assessments that are AI-literate. As we find our way to the other side of this transititional space we are in, deluged by inappropriate use and assessments too slow in changing, eventually the writing will (again) be genuinely engaging, students will see value in finding their own voices and we’ll move closer to consensus on some new ways of producing as legitimate. When I read posts on social media advocating wholesale shift to exams (irrespective of other competing damages this may connote and in apparent ignorance of the many ways cheating happens in invigilated in person exams) or ‘writing is pointless’ pieces I am struck by the usually implicit but sometimes overt assumption that writing is ONLY valuable as evidence of learning. Too rarely are formative/ developmental aspects rolled into the arguments alongside a failure to connect to persuasive (in this and wider for learning arguments) rationales for reconsidering the impact on grades on how students approach wiritng. And, finally, even if 80% of students did want the easiest route to a polished essay, I’m not abandoning the 20% that appreciate the skills development, the desirable difficulties and will to DO and BE as well as show what they KNOW. Too many of the current narratives advocate not only thowing the baby out with the bathwater but then refuse to feed the baby because, you know, the bathwater was dirty. Unpick THAT strangled metaphor if you can.

Plus ça change; plus c’est a scroll of death

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Hang on it was summer a minute a go
I looked at my blog just now and saw my last post was in July. How did the summer go so fast? There’s a wind howling outside, I am wearing a jumper and both actual long dark wintry nights and the long dark metaphorical ones of our political climate seem to loom. To warm myself up a little I have been looking through some tools that offer AI integrations into learning management systems (LMS aka VLEs)* rather than doing ‘actual’ work. That exploration reminded me of the first ever article I had published back in 2004. The piece has long since disappeared from wherever I save the printed version and is no longer online (not everything digital lasts forever, thank goodness) but I dug the text out of an old online storage account and reading it through has made me realise how much things have changed broadly while, in other ways, it is still the same show rumbling along in the background, like Coronation Street (but no-one really remembers when it went from black and white to colour).

What I wrote back then
In that 2004 article I described the excitement of experimenting with synchronous and asynchronous digital discussion tools in WebCT (for those not ancient like me, Web Course Tools – WebCT- was an early VLE developed by the University of British Columbia which was eventually subsumed into Blackboard). I was teaching GCSE English and was programme leader for an ‘Access to Primary Teaching’ course and many of my students were part time so only on campus for 6 hours per week across two evenings. I’d earlier taught myself HTML so I could build a website for my history students- it had lots of text! It had hyperlinks! It had a scolling marquee! Images would have been nice but I knew my limits. When I saw WebCT, I was fired up by the possibilities of discussion forums and live chat. When I set it up and trialled it I saw peer support, increased engagement with tough topics, participation from ‘quiet’ students amongst other benefits. I was so persuaded by the added value potential I even ran workshops with colleagues to share that excitement.

See this great into to WebCT from someone in CS dept at British Columbia from 1998:

That is still me of course. My job has changed and so has the context, but the impulse to share enthusiasm for digital tools that foster dialogue and interaction remains why I do what I do. It was nice to read that and I felt a fleeting affection for that much younger teacher, blissfully unaware of the challenges ahead! Even so and forming a rattling cognitive dissonace that is still there, I was frustrated by the clunky design and awkward user interface that made persuading colleagues to use it really challenging. Log in issues took up a lot of time and balancing ‘learning’ use with what I then called ‘horseplay’ (what was I, 75?!) took a while to calibrate. Nevertheless, I thought these worth working through but, even with some evidence of uptake across the college I was at was apparent, there was a wider scepticism and reluctance. Why wouldn’t they? ‘it’s too complex’; ‘I am too busy’; ‘the way I do it now works just fine, thank you’. Pretty much every digital innovation has been accompanied by similar responses; even the good ones! I speculated about whether we needed a blank sheet of paper to rethink what an LMS could be, but concluded that institutions were more likely to tinker and add features than to start again.

2004? Feels like yesterday; feels like centuries ago
It was only 2003–4 (he says, painfully aware that I have colleagues who were born then), yet experimenting with an LMS felt novel and that comes over really clearly in my article. If you’d asked me this morning when I started using an LMS I might have said 1998 or 99. 2003 feels so recent in the contexct of my whole teaching career. What the heck was I doing before all that? Thinking back I realise that in my first full time job there was only one computer in our office and John S. got to use that as he was a trained typist (so he said). And older than me. In the article I was carefully explaining what chat and forums were and how they were different from one another, so the need for that dates the phenomeon too I suppose. Later, after moving to a Moodle institution, I became e-learning lead and engaged with JISC working groups- a JISC colleague who oversaw the VLE working group jokingly called me Mr Anti-Moodle because I was vocal in my critiques. It wasn’t quite acccurate- I was critical for sure but then, as now, I liked the concept but disliked the way it worked. Persuading people to adopt an LMS was hard as I said, and, while I have seen some brilliant use of Moodle and the like, my impression is that the majority (argue with me on this though) of LMS course are functional repositiories with interactive and creative applications the exception rather than the norm. The scroll of death was a thing in 2005 and it is as much of a thing now. It also made me think of current ‘Marmitey’ positions folk are taking re: AI. Basically, AI (big and ill defined as it usually is) has to come with nuance and understanding so binary, entrenched, one size fits all positons are unhelpful and, in my view, hard to rationalise and sustain.

The familiar LMS problem
Back to the LMS, from WebCT to Moodle and other common current systems, the underlying functionality has barely shifted (I mean from the perspective of your average teacher/lecturer or student). Many still say Moodle feels very 1990s (probably they mean early 2000s but I suspect they, like me, find it hard to reconcile the idea of any year starting with a 2000 could be a long time ago). Ultimately I think none of these systems offered a genuinely encouraging combination of interface and user experience and that is an issues that persists to this day. The legacy of those early design decisions lingers, and we are still working around them. People have been predicting the death of the VLE for years (including me) but it has not happened. When I first saw Microsoft Teams just before Covid, I thought here’s the nail in the coffin. I was wrong again. Maybe being wrong about the end of the LMS is another running theme.

Will AI change the LMS story?
So what about AI powered integrations? Will they revolutionise how the LMS works? Will they be part of the reason for a shift away from them? Unlikely in either sense is my best guess. Everything I see now is about embellishments and shortcuts that feed into the existing structure. My old dream of a blank-sheet LMS revolution has faded. Thirty years of teaching and more than twenty years using LMSs suggest that this is one component of digital education that will not fade away. The tools will keep evolving, but the slow, steady thrum of the LMS endures in the background. I realise that I have finally predicted non change so don’t bet on that as I have been wrong quite a bit in the past. What I do know is that digital discussions using tools to support dialogic pedagogies have persisted as have the issues related to them. Only 10-20% of my students use the forums! I hear that still. But what I realised in 2004 and maintain to this day is that 10-20% is a significat embellishment for some and alternative for others so I stick with what I said back then in that sense at least. Oh, and lurking is a legit and fine thing for yet others!

One of the most wonderful things about the AI in Education course (so close to 15,000 participants!) is the forums. They add layers of interest that cannot be planned or produced. I estimate only 10-15% of participants post but what a contribution they are making and its an enhancement that keeps me there and, I am convinced, adds real value to those not posting too.

*I’ll stick with LMS as this seems to be pretty ubiquitous these days though I am aware of the distinctions and when I wrote the piece about ‘WebCT’ the term VLE was very much go to.

Is AI like a cute puppy?

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Audio version of this post

TL:DR? No, it is not, so why would you embrace it?

I have mentioned this before but it keeps cropping up so I am going to labour the point again. The idea of ‘embracing’ AI in education (or anywhere) can be seen to grow as a narrative throughout 2023 and was already on a steep upward trajectory prior to that.

A line chart showing the frequency of the phrase “Embrace AI” in published texts from 2000 to 2022. The horizontal axis runs from 2000 to 2022; the vertical axis shows tiny percentage values from 0 % up to 0.00000024 %. From 2000 through about 2014, the blue line hugs the baseline at essentially 0 %, with a very slight rise between 2006 and 2012 and a dip around 2014. Beginning around 2015, the line climbs steeply, reaching approximately 0.00000022 % by 2022. A tooltip at the year 2000 notes a value of 0.00000000 %.
Google Ngram viewer for ‘Embrace AI’

But a significant contribution to this notion came in this HEPI blog of 5 January 2024. Professor Yike Guo urges UK universities to move beyond mere caution and become active adopters of artificial intelligence. Drawing on 34 years of AI, data-mining and machine-learning research at Imperial College London and his  role as Provost at HKUST, he warned that AI is not a peripheral tool but a fundamental shift in the educational paradigm. His focus on structural, systemic and pre-existing issues in how we construct education such as  the persistence of rote memorisation in curricula mirrors my own case for using AI as an opportunity to leverage research-informed changes long needed. Professor Guo advocates for compulsory AI literacy modules that teach students to interrogate and collaborate with digital co-pilots and insists that the true value of education will lie in cultivating ethical reasoning, emotional intelligence and creativity which, importantly, are qualities that machines cannot replicate. He says (and I quote this a lot):

“…UK universities face a choice: either embrace AI as an integral component of academic pursuit or risk obsolescence in a world where digital co-pilots could become as ubiquitous as textbooks.”

I tend to agree with much of Professor Guo’s stance: AI will reshape (and already is)  higher education pretty profoundly but I find his call to “embrace” AI really troubling. This phrase seems to be everywhere in relation to AI. I hear it every day and I don’t  think it is helpful at all.  I embrace my wife and daughter (and, somewhat awkwardly, my son and my mum: it’s a generational thing I think!), a kitten, and even my Spurs-supporting mates last week when we finally won a trophy after 17 years of pain (see picture below). 

A photograph taken inside a dimly lit bar showing a joyous celebration among football supporters. In the foreground, an older man wearing glasses and a flat cap laughs with his mouth wide open as a younger man embraces him from behind, both arms wrapped around his shoulders. The younger man, in a light trench coat, leans in close, smiling broadly. Behind them to the right, two other fans—one in a yellow Tottenham Hotspur shirt bearing the name “Kane” and the number 7—are similarly embracing. The background is softly focused, revealing a few more patrons and industrial-style décor with exposed beams and abstract wall art.
Me being embraced by my Spurs buddy ‘JM’ (Photo: Tom Sweetland)

But I do not embrace people or things I neither know nor trust. I do not embrace strangers. Even when I employed someone to complete a loft conversion, and we came to know them well over the course of the (interminable) job, we still didn’t end up hugging each other. Some people love their phones too much and might kiss and hug them but I think they’re daft. These are tools, nothing more. ‘Embracing AI’ narratives only feed anthropomorphism. It also feeds binary narratives: are you ‘fully embrace’ or ‘outright reject’? Actually, reality demands something far more nuanced.

To these ends, I am constantly challenging the idea of embracing AI. So, instead, I argue for engagement. We can engage with affection, care, warmth and appreciation, but we can also engage with suspicion, trepidation, anxiety, distrust, even fear. Engagement accommodates critical scrutiny as readily as it does positive and productive collaboration.So, bottom line, let’s drop the idea of embracing AI but encourage critical engagement with AI (in all its diversity…what we conceptualise AI as is another thing that vexes me btw). Also: Come on you Spurs!

Rewilding higher education: weeds and wildflowers

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Connie Gillies and Martin Compton

It was a privilege to offer reflections at Professor Cathy Elliott’s inaugural lecture, Rewilding the University recently. Her lecture was more than a celebration of an academic career: it was also a call to action. A provocation. A gentle but insistent reminder that education (and nature and the world!) does not need to look the way it does now. A packed lecture hall listened intently to Cathy’s arguments, ideas and jokes: it was a tough act to follow. Cathy said she hardly ever lectures but a skillful lecture is a thing of joy and is utterly compelling and we were lucky to witness one.  Here we share some reflections on Cathy’s ideas and how they have helped shape aspects of our own. 

Cathy made clear that rewilding is not a metaphor of neglect or abandonment, but of restoration, connection and flourishing. It recognises that overly managed systems, whether ecological or educational, can become depleted, homogenous and fragile. In both cases, monoculture and rigidity are warning signs: what Cathy referred to as ‘command and control’.  The invitation we heard was to value and support diversity, likewise in both nature  and education, to value what is often dismissed, and to allow for the possibility of unpredictable, unmeasurable growth.

This vision has shaped how we think about education and how we’ve each worked together with Cathy. Our own relationships, as a fellow academic (with similarly unconventional paths to current roles) and as a student (who had been disillusioned by educational experiences to the point of encountering Cathy’s course), and now as authors, as collaborators, is a component of the network that Connie has described as mycelial: Like subterranean fungal connections but nourishing ideas, allowing knowledge to travel, and making future growth possible. Like mycelium in forest ecosystems, these relationships and ideas remain largely invisible to the untrained eye, but they are foundational. They remind us that learning does not happen in isolation, but in intricate, collaborative webs.

When students sign up for Cathy’s Politics of Nature class, they often don’t fully grasp the lasting impact it will have on them. A friend once told Connie, “A Cathy Elliott module will change your life,” and while the statement may seem grand, it’s not far from the truth. For many, this course didn’t just teach content; it reshaped our approach to thinking, learning, and even our careers. Cathy’s teaching blends critical rigor with intellectual play, making the class a rare space where students can be both creatively curious and academically rigorous. Most importantly, she empowers students to discover their unique intellectual passions, encouraging them to contribute perspectives no one else could, simply because they aren’t anyone else.

Education, when rewilded, becomes an ecosystem. A space where mutual dependence is generative. A space where difference is not simply tolerated but required. It is through this lens that we’ve come to understand projects like ungrading, student co-authorship, and the politics of belonging, not as reforms, but as regenerative acts. These are not surface-level interventions, but shifts in the soil.

One of the most notable aspects of Cathy’s work is her broad intellectual curiosity. She’s not confined to any one field of study — from politics and nature to democracy, development, gender, race, disability and sexuality, Cathy’s academic interests are as diverse as they are profound. In an academic world that often pushes students toward ever-narrower specialization, Cathy’s approach encourages students to break free from this limitation.

Cathy’s teaching has long enacted this ethos. She nurtures students not through control but through trust. Her pedagogy invites learners to bring their whole selves, to make connections across disciplinary and personal boundaries, and to treat knowledge as something to be inhabited, not merely acquired. She encourages risk, slowness, reflection, and relationality which are qualities too often sidelined in institutional discourses of impact, efficiency and performance.

The dandelion is another metaphor Cathy draws on frequently and one we were also drawn to in our appreciation. Often dismissed as a weed, the dandelion (The French is ‘pissenlit’ which really does say everything about its reputation)  is in fact a profoundly restorative plant. It detoxifies soil, strengthens roots and nourishes ecosystems. It grows where it is not wanted and flourishes nonetheless. To children, it is a source of wonder, blown seeds, floating wishes,transformation, softness at one time, vibrant yellow before. But to adults, it is a nuisance to be removed. Cathy’s work, like the dandelion, asks us to reconsider who gets to decide what counts as valuable, as beautiful, as worthy. We need to ask ourselves to what extent have we constructed educational systems that we want to be like perfect lawns- predictable, clean, neat and each blade of grass much like the others. Cathy says: ‘don’t cut the grass and plant wildflowers instead!’ This is a literal and metaphorical phrase we can get behind!

This ethos extends into her work on gender, race and sexuality, which consistently challenges the structures that exclude some or  may diminish the presence or experience of others. In classrooms, in curricula, in institutional policy, she reminds us in her work that exclusion is never accidental, it is designed. But that also gives us pause for positive reflection: this means they can be redesigned. 

What we’ve come to understand through Cathy’s influence, and through our ongoing partnership, is that rewilding higher education is not a metaphorical indulgence, it is a pedagogical imperative. It calls us to rethink the terms of participation, the assumptions of merit, the rituals of assessment, and the conditions under which learning takes place. It also calls for attention to scale: recognising that large transformations begin with small shifts, relationships and new practices. 

It felt fitting, then, that the very day after Cathy’s lecture, a special issue of the Journal of Learning Development in Higher Education was published. Co-edited by one of us and containing a piece co-authored by the other, the issue is seeded with many of these same ideas. It features students and a Vice Chancellor; early career ac academics and emeritus professors, reimaginings of assessment, and reflections on academic community that echo and extend Cathy’s provocations. The special issue is a timely continuation of many of the conversations we have had with Cathy, who, unsurprisingly, also has a paper in the special issue and was part of the King’s/ UCL editorial collective. 

We both have very different careers and are at very different ends of them! But we share the sense that the rigid, often foreboding and frequently distrustful academy could be rewilded. It doesn’t have to be this way; more importantly, it could be otherwise.

Meme-ingful reflections on AI, teaching and assessment

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I did a session earlier today for the RAISE special interest group on AI. I thought I’d have a bit of fun with it 1. because I was originally invited by Dr. Tadhg Blommerde (and Dr. Amarpreet Kaur) who likes a heterodox approach (see his YouTube channel here) and 2. Because I was preparing on Friday evening and my daughter was looking over my shoulder and suggesting more and more memes. Anyway, I was just reading the chat back and note my former colleague Steve asked: “Is the rest of the sector really short of memes these days now that Martin has them all?” I felt guilty so decided to share them back.

My point: There’s a danger we assume students will invariably cheat if given the chance. This meme challenges educators to reconsider what they define as cheating and encourages transparent, explicit dialogue around academic integrity. What will we lose if we assume all students are all about pulling a fast one?

My daughter (aged 13) suggested this one. How teachers view ChatGPT output: homogenised, overly polished essays lacking individuality. My daughter used the ‘who will be the next contestant on ‘The Bachelor’ (some reality show I am told) image to illustrate how teachers confidently claim they can spot AI-generated assignments because “they all look the same.” My point: I think this highlights early scepticism about AI-produced writing but that we should as educators consider the extent to which these tools have evolved beyond initial assumptions and remind our students (and ourselves) that imperfections and quirks can define a style. Just ask anyone reading one of my metaphor-stretched, overly complex sentences. Perhaps, for too long we have over-valued grammatical accuracy and formulaic writing?

My point: It’s not just about AI detectors of course. It’s more that this is an arms race we can’t win. If we see big tech as our enemy then fighting back with more of their big tech makes no sense. If we see students as the enemy then we have a much bigger problem. Collective punishment and starting with an assumption of guilt are hugely problematic in schools/ unis much as they are in life and tyrannical societies in general. When it comes to revisiting academic integrity I am keen discuss what it is we are protecting. I am also very much drawn to Ellis and Murdoch’s ‘responsive regulation’ approach. I don’t think I’m quite on the same page regarding automated detection but I do agree regarding the application (and resourcing of) deserved sanction for the ‘criminal’ (willful cheats) along with efforts to widen self-regulation and move as many students as possible from carelessness (or chancer behaviours) to self-regulation is critical.

Pretty obvious I guess but my point is this: We also need to resist assumptions that all students prioritise grades over genuine learning and creativity. Yes, there are those who are wilfully trying to find the easiest path to the piece of paper that confirms a grade or a degree or whatever. Yes, there are those whose heads may be turned by the promise of a corner-cutting opportunity. But there are SO many more who want to learn, who are anxious because they know others who are being accused of using these tech inappropriately (because, for example, they use ‘big’ words… really, this has happened). ALSO, we need to challenge the structural features that define education in terms of employability and value. I know how to use chatgpt but I am writing this. Why am I bothering writing? Because I like it. Because – I hope- my writing, even when convoluted (much like this sentence) is more compelling. Because it’s more gratifying than the thing I’m supposed to be doing. Above all, for me, it’s because it actually helps me articulate my thoughts better. We must continue valuing intrinsic motivation and the joy students derive from learning and creating independently. But more than that: we need to face up to the systemic issues that drive more students towards corner cutting or willful cheating. By the way, I often use generated text in things I write. All the alt text in these images is AI generated (then approved / edited by me) for example.

This leads me to the next one. I mean I do use AI every day for translation, transcription, information management, easing access to information, reformatting, providing alternative media, writing alt text… Many don’t I know. Many refuse; I know this too. But we are way into majority territory here I think. Students are recognising this real (or imagined) hypocrisy. The only really valid response to this I have heard goes something like: ‘I can use it because I am educated to x level. first year undergrads do not have the critical awareness or developed voice to make an informed choice’. I mean, I think that may be the case to an extent or in some cases but it reminds me a bit of the ‘pen licences’ my daughter’s primary school issued: you get one when you prove you can use a pencil first (little Timmy, bless him, is still on crayons). Have you seen the data on student routine use of generative AI? It elevates the tool to some sort of next level implement but is it even? I think I could make a better case for normalisation and acceptance of a future where human / AI hybrid writing is just how it is done (as per Dr Sarah Eaton’s work- note the firve other elements in the tenets.)

My point: The narratives around essential changes we need to implement ‘because of AI’ presents a false dichotomy between reverting to traditional exam halls or relying solely on AI detection tools. Neither option adequately addresses modern academic integrity challenges. Exams can be as problematic and inequitable as AI detection. It is not a binary choice. There are other things that can be done. I’ll leave this one hanging a bit as it overlaps with the next one.

My point: We need to critically re-evaluate how and why essays are used in assessment. We can maintain the essay but evolve its form to better reflect authentic, inclusive and meaningful assessments rather than relying on traditional, formulaic, high-stakes versions. Anyway I (with Dr Claire Gordon) have said it before, we already have a manifesto and Dr Alicia Syskja takes the argument to the next level here.

Really, though, you should have been there; we had a great time.

The Essay in the Age of AI: a test case for transformation

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We need to get beyond entrenched thinking. We need to see that we are at a threshold of change in many of the ways that we work, write, study, research etc. Large language models as a key development in AI (with ChatGPT as a symbolic shorthand for that) have led to some pretty extreme pronouncements. Many see it as an existential threat, heralding the ‘death of the essay’ for example. These narratives, though, are unhelpful as they oversimplify a complex issue and mask long-standing, evidence-informed calls for change in educational assessment practices (and wider pedagogic practices). The ‘death of the essay’ narratives do though give us an opportunity to interrogate the thinking and (mis)understandings that underpin these discourses and tensions. We have a chance to challenge tacit assumptions about the value and purpose of essays as one aspect of educational practice that has been considered an immutable part of the ways learning and the evaluation of that learning happens. We are at a point where it is not just people like me (teacher trainers; instructional designers; academic developers; enthusiastic tech fiddlers; contrarians; compassionate & critical pedagogues; disability advocates etc.) that are voicing concerns about conventional practices. My view is that we leverage the heck out of this opportunity and find ways to effect change that is meaningful, scalable, responsive and coherent.

So it was that in a conversation over coffee (in my favourite coffee shop in the Strand area)  on these things with Claire Gordon (Director of the Eden Centre at LSE) that we decided to use the essay as a stimulus for a synthesis of thinking and to evolve a Manifesto for the essay (and other long form writing) in the age of AI.  To explore these ideas further, we invited colleagues from King’s College London and the London School of Economics (as well as special guests from Richmond American University and the University of Sydney) to a workshop. We explored questions like:

  • What are the core issues and concerns surrounding essays in the age of AI?
  • What alternatives might we consider in our quest for validity, reliability and authenticity?
  • Why do some educators and students love the essay format, and why do others not?
  • What is the future of writing? What gains can we harness, especially in terms of equity and inclusion?
  • How might we conceptualise human/hybrid writing processes?

A morning of sharing research, discussion, debate and reflection enabled us to draft and subsequently hone and fine tune a collection of provocations which we have called a ‘Manifesto for the Essay in the age of AI’

I invite you to read our full manifesto and the accompanying blog post outlining our workshop discussions. As we navigate this period of significant change in higher education, it’s crucial that we engage in open, critical dialogue about the future of assessment.

What are your thoughts on the role of essays in the age of AI? Or, indeed, how assessment and teaching will change shape over the next few years? I welcome your comments and reflections below.