Category: AI

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Introducing AI Policy to Students

Today we have a guest post from Dr. Devon Cantwell-Chavez, a postdoctoral scholar at the University of Copenhagen and current Chair of the Education and Learning Section of the International Studies Association. Devon shared her take on how to talk with students about AI use and policy on LinkedIN, and generously agreed to repost here on ALPS. You can find her at https://www.linkedin.com/in/devoncantwell/ and @devoncantwell.bsky.social.

Here’s what introducing my AI policy in the first day of class looked like today:

For context, I don’t ban AI in my classrooms because (1) my institution does not allow for this (2) any ban is unenforceable and (3) I’m uninterested in the surveillance necessary to implement a ban. I do tell students I strongly discourage AI and unpack why this is.

Before the class, they were assigned three readings:

– Tressie McMillan Cottom’s op-ed in the NYT on the midness of AI
– the new MIT report on AI and pedagogy
– Kate Crawford’s introduction chapter to Atlas of AI

We start off with basic definition of generative AI that emphasizes the large data corpus, probability outputs, and perceived confidence of those outputs. Then, we look at how governments are applying AI in public sector work around security issues (this is a security studies course). Many of my students will go on to the public sector (or are from the public sector) so I want them to start by thinking about the implications of these tools being in the public sector. These examples include discussing how the UK home office has used these algorithmic mechanisms to impute data for files and to make recommendations for decisions; how the US has used ML based translation software which has led to the rejection of refugee asylum claims due to inconsistencies generated through inaccurate translation; the impact on the public service labor market; and the vagueness surrounding most government guidance on the use of LLMs in work places. Find the slides here.

Then, we talk about AI use in this course. The university requires AI disclosures for all exams and assignments. Those that used AI in this last time I taught the course scored on average about a grade lower (we have weird scoring) than those who did not use AI. We unpacked some of the reasons why this might be.

What did students share and take away from this?
– they are noticing how LLM use atrophies their thinking and can even make them second guess their understanding of an issue or content they are working through
– they notice that the writing suggestions made by AI often make their points and analysis more convulted
– despite observing these things, they worry about “building AI skills” and have heard anecdotes about employers not hiring folks because they disclosed that they do not use AI
– there is a direct relationship between student confidence and LLM use- when they are less confident, they use AI more
– the pressure on students time is a driver for increased AI use
– students said they have not received any instruction on ethics related to AI
– students found the MIT report VERY compelling

We will be revisiting this topic a lot throughout the course due to how AI has become intertwined with contemporary security issues. I’m not sure I will necessarily change student’s AI behaviors but I am hoping through a sustained intervention with this topic throughout the course that students will be more critically aware of AI in future practitioner roles.

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Reflecting on recent UCL CPP events, Part 3: ‘Disability, Technology, and Inclusive Education’ 

This post is the third in a series reflecting on events hosted by the UCL Centre for the Pedagogy of Politics (CPP) last year. 

The first and second posts discussed, in some detail, ideas raised in our spring panel on ‘Relational Pedagogies Inside and Outside the Classroom‘.  

This post offers some more tentative reflections on our autumn panel on ‘Disability, Technology, and Inclusive Education’. For reasons that will become clear, I shall be oscillating between the usual blog format and the lesser-spotted bleg (this one, not this one…). 

My main aim in organising this panel was to bring together educators who have thought deeply about how technology can make higher education more inclusive for disabled and neurodivergent students, and who share a concern that widespread advances made during the early stages of the Covid-19 pandemic have been lost in the rush to ‘return to normal’. 

Initially, my hope was to hear mainly from people who teach politics (understood broadly) and have published their thoughts and reflections in disciplinary SoTL. But I was unable to find much, if anything, in the usual outlets (e.g., those covered in Jeremy’s SoTL round ups) that included a focus on inclusivity gains during the early part of the pandemic and subsequent losses.  

This was a surprise because, more generally, inclusivity is a strong theme in our discipline’s SoTL, as is co-production, and most of the disabled students we teach have a clear view on this: according to Disabled Students UK, 85% of disabled students report that they would benefit from the continuation of online teaching and learning options introduced during the early stages of the pandemic.  

It seems to me that there are three possible explanations for my inability to find much disciplinary SoTL reflecting this perspective:  

Continue reading “Reflecting on recent UCL CPP events, Part 3: ‘Disability, Technology, and Inclusive Education’ “
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Meta-Cogitating Motivation, Part 1

As the readers of this blog know, but many of our students don’t, learning requires effort. People who want to learn how to play the guitar, bake croissants, or speak Tibetan are willing to expend considerable effort to learn these skills. Those who don’t aren’t.

Teaching in the age of AI?

At this stage of my career, I expect students to have the minimal level of motivation needed to learn something about the subject of the course I’m teaching. If they prefer outsourcing all cognitive effort to AI because they have no curiosity about, say, how the election of populist authoritarians has led to higher energy prices, they should go somewhere else. My enthusiasm in the classroom won’t by itself magically convert them to my religion.

For my autumn term courses, I will be introducing some exercises that should make the connection between motivation, effort, and learning more apparent to students. One such exercise is a graded* self-evaluation with the following questions:

  1. On a 1-5 scale, with 1 being lowest and 5 being highest, how much of a priority is this course compared to my other courses, work, personal life, etc.?
  2. Given my answer to Question 1, how much effort did I exert last week to learn in this course?
  3. What have I learned in this course?
  4. What specific actions did I take last week to learn more effectively in this course?
  5. How does my answer to Question 4 reflect advice from the “How to Maximize Learning” page in the course’s “Start Here” Canvas module?
  6. How have I connected my experience in this course to one of my interests?

I’ve scheduled this self-evaluation to occur four times across the term. I’m hoping that it will help students realize that learning is like taking one’s mind to the gym. They can either lift the mental weights themselves, or they can waste their time watching other people — or machines — do it. I’m happy to coach them on how to do the former. The latter isn’t my problem.

*Automatic full marks for completing the survey’s questions, courtesy of the LMS/VLE.

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Iran 2026 Simulation

Immersion in the simulations and games space for the last 15 years has taught me the challenges of creating and running simulations. I’ve written about these before, in ALPS and elsewhere, and time in particular is a barrier to using simulations in the classroom. Time to find or create a simulation, and time to run it in a packed curriculum. Faculty may want to try a simulation, but can’t find one for the topic, skill, or learning goal that they want, or it doesn’t fit the time they have available in their class. The ALPS team has taught workshops on simulation design and we acknowledge the challenges of putting together a bespoke simulation.

Well, AI just solved part of this problem for us. Yesterday, as part of a demo for my ‘Crash Course in AI’, I asked Claude Cowork to create a one-hour simulation on the Iran War for a large, lecture style class that met particular learning goals. In just a few minutes, it gave me a 32 page document that included all the materials I would need to put that simulation into action–everything from learning objectives, set up notes, facilitation timelines, debriefing questions and points to make, gameplay mechanics, and role sheets.

I’m turning this document over to you, ALPS readers. It’s unedited–I have not fact checked it or made any changes, but as a draft, it may be helpful to some of you teaching right now. Looking through it also shows you how powerful a tool AI can be as a teacher partner. Instead of my spending hours putting this material together, I had it write a draft while I was in the middle of a presentation, and now its ripe for editing, adaptation, and changes that reflect my (or in this case, your) judgement. Feel free to use this simulation in your classes–all I ask is that you report back here in the comments or on social media on what changes you made and how it went.

And if you are interested in the prompt I used to get this result, here it is. I had Chat GPT create the prompt for me, too. In the document you will first see a template you can use yourselves, followed by the example of what I used to create etc simulation document.

It’s a new world, my friends. Not sure if its exciting or scary or both, but its bringing radical change to this corner of the teaching and learning field.

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Six Faculty Archetypes for Navigating AI in Your Teaching

I’ve been developing a lot of workshops, trainings, and short courses on AI lately, all targeted at helping faculty learn the basics of AI and its applications in the college classroom. I wanted to share one part of those efforts that I think will have broad application and help educators who are thinking through their own approach to AI.

While we are all likely subject to institutional policies that affect the role of AI in our classroom, that context does not have to govern our individual perspectives on AI and what role it should play. I’ve talked with faculty who sit on all sides of the AI-spectrum—everything from full-scale denial of the role of AI to those who have thrown themselves into agents and vibe coding. For those that are still figuring out the role they want AI to play in their teaching, though, I have created six archetypes which may help.

Alt text: A 3×2 grid of illustrated panels, each depicting a different faculty archetype. Top row, left to right: a man in a suit labeled “Detective” holds a magnifying glass up to a piece of paper against a blue background with computer screens. A man in a purple shirt labeled “Architect” sits at a drafting table with blueprints and a pencil, with a warm yellow background. A woman in a blue jacket labeled “Pragmatist” sits at a desk with books and a laptop, with students visible behind her against a blue background. Bottom row, left to right: a woman labeled “Coach” sit across from two students at a table in conversation, in a classroom with motivational posters on the wall. A woman labeled “Resister” sits at a desk with a laptop and an open book, one hand raised in a stopping gesture, with a whiteboard behind her showing a diagram of human qualities that AI cannot replace. A man in an orange sweater labeled “Embracer” holds a laptop with a robot icon, surrounded by glowing digital icons against a teal background. Note: image created in Chat GPT and edited by Claude; alt text provided by Claude.

I’m going to walk through each approach and some of the strategies that you can employ if this is the role you see for yourself. Note that of course these are ideal types. You might switch from one role to another based on context, student, or assignment, or see parts of yourself in multiple roles. I share these not to force anyone into a box, but to illuminate the different roles I’m seeing faculty play so that those still figuring this out know what some of their options are.

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Best Coffee in Town: Update 1

 
 Creative Commons CC0 1.0 Universal

Taking a break from preparing for our next blizzard . . .

A quick progress report on my Best Coffee in Town research project, which I designed to counter AI and combat grade inflation: students, or at least some of them, submitted the first of a series of scaffolded StoryMap assignments. While this assignment constitutes only 2.5 percent of the final course grade, it forms an integral part of the project as a whole. In other words, it lets students know where they stand and where they are headed.

Of the class’s 17 students, 10 chose to complete the assignment, with an average score of 9.5 out of 25 points. In letter grade terms, everyone in the class earned an F.

Will this change as the semester progresses? I don’t know.

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Call for Papers/Panels/Fun Stuff: UACES, Prague, September 2026


This September UACES (University Association for Contemporary European Studies) will be in Prague for its Annual Conference and I’m looking for people to join me for some sessions on Learning and Teaching.

In particular, I’d welcome anyone interested in the following:
– A roundtable discussion about how to handle AI in the classroom. You can bring analysis, critique or solutions as we try to help colleagues make sense of this important shift in our practice;
– A workshop to help anyone looking for advice on developing their teaching practice. The format would be an informal space for discussions, with you bringing your ideas and experiences (whatever the level) to help others

If you’re up for either (both?) of these, then drop me a message (simon.usherwoodATopen.ac.uk). Close of the call is 1 February, so ideally don’t leave it to the last minute

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AI-Induced Course Improvements

I’ll be teaching a course on globalization again in the spring term. As usual, I’ve built the course around a StoryMap ethnography project, but I’m incorporating field research in response to how I’m seeing students (mis)use AI. The field research component comes from Amanda’s Best Breakfast in Town, which I used once before in 2019. This time each team of students will need to identify a Best Coffee in Town by evaluating the effects of coffee production in some other country and how and why the coffee is consumed locally. At minimum students might learn a little about the off-campus community. Best case scenario is that they talk with the people who produce the coffee and learn something about them.

Project outcomes thus now depend much more on engaging with the physical world than they used to, and I’ve changed my assessment metrics accordingly by down-weighting text-driven activities that students can offload to AI, such as the location and synthesis of published source material. Students will now need to do a better job with the harder elements of the project, which now comprise a far greater share of assignment grades — which should have the added benefit of helping me continue to combat grade inflation. To illustrate this, here is the rubric I’ll be using to score the final, complete versions of students’ StoryMaps:

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Disability, Technology, and Inclusive Education

CPP logo

This academic year, the UCL Centre for the Pedagogy of Politics (CPP) is hosting a series of online panel events. Our first event on 4 December was on the theme of ‘Disability, Technology, and Inclusive Education‘. In this guest post, one of the panellists at that event, Martin Compton (College Lead for AI and Innovation in Education, King’s College London), offers further reflections on how best to use technology to facilitate the inclusion of disabled and neurodivergent students, the extent to which changes required in the early part of the Covid-19 pandemic improved inclusion for disabled students, and whether those improvements have been maintained.

I was delighted to be invited to speak at the UCL Centre for the Pedagogy of Politics’ recent panel on Disability, Technology, and Inclusive Education. My current role at King’s College London (AI and innovation in education lead) can sometimes mask my wider faculty development and student engagement passions related to inclusive education but this was a perfect opportunity to connect these aspects of my work. The invite prompted me to reflect again on my own position, shaped by both professional and personal experience. I spoke alongside two people whose work I admire greatly. Dr Miranda Melcher’s coherent thinking, scholarship and advocacy of high impact interventions were passionately shared. And my former colleague, Ben Watson’s, leadership in digital accessibility at UCL has had cross-sector impacts. It was a great opportunity to be reminded of the clarity of their arguments, their commitment to practical change and their willingness to challenge the limits of established thinking. 

My own starting point in this space is relatively simple. Digital tools, and now generative AI, have already changed what is possible for many learners, especially those who have been historically marginalised. A significant complicating factor is that these same tools can widen divides at the same time. I understand the many good reasons to resist certain developments in educational technology. I understand the arguments that warn of harm and the potentials for exacerbating marginalisation. So to that end, I am neither a technological determinist nor a tech evangelist. I do, however, feel concerned by the strength of anti-technology narratives that often drown out successful inclusive applications and hard-won gains. Too often accessibility is an afterthought as opposed to embedded practice. In a 2023 paper, (co-authored with Ben and Dr Alex Standen, now at LSE), I argued  that there was a risk (already apparent in fact) that progress made during the Covid lockdown period, and recently expanded through responsible uses of AI, would be undone wherever opportunity to ‘return to normal’ presented itself. But, wilfully ignoring or winding back on approaches that can narrow engagement and attainment gaps should never be on the table. We need to hold on to what worked for those whose needs and voices are so often the least heard in policy discussions.

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Online panel event: Disability, Technology, and Inclusive Education (4 December, 4.00 – 5.00pm)

CPP logo

This year, the UCL Centre for the Pedagogy of Politics (CPP) is once again hosting a series of themed online panel events. 

We are delighted to share the details of our first event on ‘Disability, Technology, and Inclusive Education’, which is taking place on Thursday 4th December, 4.00-5.00pm (UK time).  

It will include contributions from the following panelists alongside time for audience Q&A: 

Martin Compton (College Lead for AI and Innovation in Education, King’s College London);

Miranda Melcher (Educational Technologist, Learning Enhancement and Development (LEaD) department, City, University of London)   

Ben Watson (Head of Digital Accessibility, UCL)  

The event will run as a Teams webinar. If you would like to attend, please register beforehand on the following event page, whereupon you will receive access details: Webinar: ‘Disability, Technology, and Inclusive Education’. 

 We hope for a wide-ranging discussion on issues such as how best to use technology to facilitate the inclusion of disabled students; the extent to which changes required in the early part of the Covid-19 pandemic improved inclusion for disabled students and, if so, whether those improvements have been maintained; the current state of the Scholarship of Teaching and Learning in this area. 

The event is primarily aimed at academics working in politics (or adjacent) departments who have an interest in pedagogical research and best practice in this area. 

We hope to see some of you there for a thought-provoking discussion!