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Tag: AI

Supporting Staff and Students in Moving from AI Scepticism to AI Exploration

How could I miss the latest HelF staff development session, as an avowed AI sceptic? Today Alice May and Shivani Wilson-Rochford from Birmingham City University talked about their approach to responding to the emergence of generative AI. As can be seen on the ‘roadmap’ above, this has included an AI working group, collaboration with staff and students on producing guidelines on use, sharing those via staff and student workshops, and collating resources on a SharePoint site. All things which mirror our approach at Sunderland.

Something they are doing which I liked was providing template text which academic staff can copy and paste into their assignment briefs on what kind of AI students are permitted to use, at four different levels from fully unrestricted, to fully prohibited. They are also working on an assessment redesign project which takes the risks of GAI into account, based on work from the University of Sydney which analysed all of the different types of assessment they have and put them into two lanes based on how secure they are to GAI plagiarism. It’s Table 2 on the page I’ve linked to, it’s a very good table. I like it a lot.

Briefly mentioned was the fact that Birmingham are one of the few institutions in the UK who have enabled Turnitin’s AI detection tool, and I would have liked to have learned more about this. From a student survey on GAI, the second screenshot above, concerns about the accuracy of AI detection was one of the big things they raised.

Alice and Shivani left us with plans for going forwards, which is to build a six-pillar framework on the different aspects of GAI’s impact on HE (third screenshot). Pillar 5 is ‘Ethical AI and Academic Integrity’. This one stood out as, once again, the ethical issues of the environmental impact and copyright were raised. Briefly. And then we moved on. It consistently bothers me, and I don’t have any brilliant answers, but I will reiterate the very basic one of simply choosing not to use these services unless they are solving a genuine problem.

AI Disclaimer: There is no ethical use of generative artificial intelligence. The environmental cost is devastating and the technology is built on plagiarised content and stolen art, for the purpose of deskilling, disempowering and replacing the work of real people.
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Studiosity Partner Forum 2025

Today saw me visiting London once again for Studiosity’s fourth annual UK Partner Forum. In the keynote service update from CEO, Mike Larson, it was all AI, all the time. Their pivot to AI powered feedback continues at a rapid pace, and the messaging has changed from personalised feedback provided by actual human beings a few years ago, to, this isn’t fast enough for students who often work in a ‘just in time’ frame, therefore they need feedback in minutes, not hours. They seem to be doing alright from it, as a substantial number of partners have now switched to Studiosity+, and they are working on a new tool for academics to help with course content creation. Previously announced human-powered services, like Study Assist, are still in development, but didn’t warrant a mention in the slides, someone had to ask the question of what was happening with them.

Rebecca Mace, an independent researcher, presented on their work reviewing early real-world usage of Studiosity+, which our pilot on Study Online Canvas has contributed to (I have writing about this forthcoming). Next, Andy Jaffrey from Ulster University presented about their experience in winning the Times Higher University of the Year Award. This was largely tangential, but there was some discussion about values and their emphasis on human-to-human contact, which is why, like Sunderland, they are staying with the Studiosity Classic service.

After lunch we had Sharon Perera and Nathaniel Pickering from the University of Greenwich presenting on their ‘Write With Confidence’ initiative, inspired by our Write it Right. That’s going very well for them, with enough data now to show improved continuation and progression rates, and a 20% uptake across the university. All very similar to our findings. One difference is that they have gone for the AI powered service.

Finally, Nick Hillman from the Higher Education Policy Institute (HEPI) gave the afternoon keynote on the state of UK Higher Education. I feel like Studiosity always has someone offering this kind of perspective at these events, and I always find them fascinating. Some highlights I noted included that 90% of students report using generative AI, but believe that if used for direct cheating they would be caught by institutional policies and technology. Shown in the third photo, above, HEPI surveyed students on institutions going bust and found that 31% were quite or very worried about this possibility. Finally, and related to this, Nick offered a prediction that there would be mergers of HEIs in the next few years to prevent worst case scenarios, but that, like the crisis in FE a few years ago, the sector would leave it too late and wait for a precipitating event to happen instead of getting ahead of the situation. I don’t think there was anything in his analysis that I would disagree with.

Slides from the day and other supporting documentation are available on Studiosity’s website, so you don’t have to squint at the scance few photos I took.

AI Disclaimer: There is no ethical use of generative artificial intelligence. The environmental cost is devastating and the technology is built on plagiarised content and stolen art, for the purpose of deskilling, disempowering and replacing the work of real people.
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Generative AI: A Problematic Illustration

Screenshot of a slide from the presentation, showing some delicious pancakes
Mmm… pancakes…

To give the workshop its full title, Generative AI: A Problematic Illustration of the Intersections of Racialized Gender, Race, and Ethnicity. Facilitated by Nayiri Keshishi from the University of Surrey and Dustin Hosseini from the University of Glasgow, and based on Dustin’s blog post. Hands down, the best session on generative AI I’ve attended over the past two years. It was so good I’m going to rework the timetable of our PG Cert to include a version of this for the cohort I’m currently teaching.

Why was it so good? Because it took some of the ethical issues over the use of generative AI and turned them into an interactive session where we, as participants, could interrogate the problems for ourselves. This was done via the medium of a seemingly innocuous prompt which was put into an image generating AI system: ‘Create an image of a sweet, old X grandmother making pancakes’, where X was a given nationality, e.g. Russian or American. We were then asked to analyse the generated results using a framework which asked us to consider atmosphere, decor and clothing, and expressions and ethnicity.

Discussions about what we can do about this included cascading the learning and knowledge more widely, which is why all of the slides and resources to deliver the session have been published under a Creative Commons licenses on ALDinHE’s website. Another suggestion was to document the issues we encounter when using these technologies and share them on relevant forums and social spaces, and finally, what I think is the best and most useful thing we can do as educators, is to embed AI literacy in the curriculum.

The only note I had coming out of the session was that there was a statement, an assumption, that all of these new AI companies are making huge amounts of money. There is certainly a lot of money moving around in the space, but it’s all speculative investment on presumed future returns. In actuality, OpenAI lost $5 billion last year, and they’re on track to lose another $10 billion this year.

AI Disclaimer: There is no ethical use of generative artificial intelligence. The environmental cost is devastating and the technology is built on plagiarised content and stolen art, for the purpose of deskilling, disempowering and replacing the work of real people.
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Copyright and Artificial Intelligence Consultation

Funny meme showing DeepSeek as a cat, stealing OpenAI's fish, which is stolen data
A gratuitously stolen meme from Reddit. Oh, the irony! The hypocrisy!

The UK government are currently running an open consultation on copyright and artificial intelligence, and have outlined their preferred solution to “include a mechanism for right holders to reserve their rights, enabling them to license and be paid for the use of their work in AI training” and to introduce “an exception [into copyright law] to support use at scale of a wide range of material by AI developers where rights have not been reserved.”

The main issue I have with this proposal is that it does nothing to respond to the wholesale copyright theft which the tech industry has already conducted. Additionally, it firmly places the emphasis on individual creators for protecting their copyright, when the bleak reality is that it is already the case that individuals have no practical means of redress against multinational mega corporations like Meta, OpenAI and DeepSeek*, who openly admit to copyright theft to train their large language models. I would much prefer that the government spent its efforts towards enforcing existing laws in order to protect the livelihoods of artists, authors and creators, rather than appeasing the tech industry.

But that’s just my opinion. If you have your own thoughts on the matter, you can read the full proposal on the gov.uk website and complete the consultation online. Like every government consultation I’ve ever engaged with, it’s dense, complicated, and time consuming. Almost like it was designed to be off-putting and to lead to a foregone conclusion. I was guided in my submission by the work of the Author’s Licensing and Collecting Society.

As well as seeking individual responses, organisations are also invited to respond to the consultation as collective bodies. ALT are doing so behalf of the learning technology community, and are asking for feedback to them by the 18th of February, with the consultation closing a week later on the 25th.

* My compliments to DeepSeek on training their AI model on OpenAI’s AI model, then releasing it as open AI, which OpenAI is not, something which has irked them greatly, and for that alone they are worthy of praise.

AI Disclaimer: There is no ethical use of generative artificial intelligence. The environmental cost is devastating and the technology is built on plagiarised content and stolen art, for the purpose of deskilling, disempowering and replacing the work of real people.
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AI and Assessment Workshop

Perplexity AI User Interface
Screenshot of Perplexity search options

Today I attended one of our own AI and Assessment Workshops to see what advice and guidance we are giving to academics and what their feelings and needs are around this topic. This is a new run of sessions which we have just started, and has been organised by one of our academics working on the topic alongside a member of my team.

Despite having published staff and student guidance documents and a dedicated SharePoint space to collate resources and our response, I found from conversing with staff at this event that there is still a prevailing feeling of lacking steer and direction. People were telling me they don’t know what tools it’s safe to use, or what students should be told to avoid. We also had a lot of people from the Library Service today, which is perhaps also indicative of the need for firmer student guidance.

I was pleased to note that there is some good practice filtering through too, such as using a quiz based declaration of use which students have to complete before unlocking their assignment submission link. We talked about adding this to our Canvas module template for next academic year, that’s something one of the academics suggested to us. On the other hand, I found people were still talking in terms of ChatGPT ‘knowing’ things, which is troubling because of the implication that these systems are more than they actually are.

While much of the session took the form of a guided dialogue, my colleague was also providing a hand’s on demo of various systems, including Perplexity which people liked for providing links out to the sources it had used (sometimes, not always), the ability to restrict answers to data from specific sources, such as ‘academic’, but noted a very US bias in the results, a consequence of the training data which has gone into these models. I was quite impressed when I tried to ‘break’ the model with leading prompts and it didn’t indulge me.

A new tool to me was Visual Electric, an image generation site aimed at producing high quality photo-like images. I have thoughts on some of their marketing… But I’m going to try and be more positive when writing about this topic, as I find it very easy to go into a rant! So instead of doing that, I have added a short disclaimer to the bottom of this post, which I’m also going to add to future posts which I write about AI.

AI Disclaimer: There is no ethical use of generative artificial intelligence. The environmental cost is devastating and the technology is built on plagiarised content and stolen art, for the purpose of deskilling, disempowering and replacing the work of real people.
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Helping Students Develop Critical Thinking Skills When Using Generative AI (Part 2)

Part two of Kent’s Digitally Enhanced Education series looking at how generative AI is affecting critical thinking skills. This week we had stand out presentations from:

Professor Jess Gregory, of Southern Connecticut State University (nice to see reach of the network, well, reaching out), who presented on the problem of mastering difficult conversations for teachers in training. These students will often find themselves thrust into difficult situations upon graduation, having to deal with stubborn colleagues, angry parents, etc., and Jean has developed a method of preparing them by using generative AI systems with speech capabilities to simulate difficult conversations. This can, and has, been done by humans of course, but that is time consuming, could be expensive, and doesn’t offer the same kind of safe space for students to practice freely.

David Bedford, from Canterbury Christ Church University, presented on how the challenges of critical analysis are not new, and that anything produced as a result of generative AI needs to be evaluated in just the same way as we would the results of an internet search, or a Wikipedia article, or from books and journals. He presented us with the ‘BREAD’ model, first produced in 2016, for analysis (see first screenshot for detail). This asks us to consider Bias, Relevance, Evidence, Author, and Date.

Nicki Clarkson, University of Southampton, talked about co-producing resources about generative AI with students, and noted how they were very good at paring content down to the most relevant parts, and that the final videos were improved by having a student voiceover on them, rather than that of staff.

Dr Sideeq Mohammed, from the University of Kent, presented about his experience of running a session on identifying misleading information, using a combination of true and convincingly false articles and information, and said of the results that students always left far more sceptical and wanting to check the validity of information at the end of sessions. My second screenshot is from this presentation, showing three example articles. Peter Kyle is in fact a completely made-up government minister. Or is he?

Finally, Anders Reagan, from the University of Oxford, compared generative AI tools to the Norse trickster god, Loki. As per my third screenshot, both are powerful, seemingly magic, persuasive and charismatic, and capable of transformation. Andres noted, correctly, that now that this technology is available, we must support it. If we don’t, students and academics are still going to be using it on their own initiative, the allure being too powerful, so it is better for us as learning technology experts to provide support and guidance. In so doing we can encourage criticality, warn of the dangers, and encourage more specialised research based generative AI tools such as Elicit and Consensus.

You can find recordings of all of the sessions on the @digitallyenhancededucation554 YouTube channel.

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Helping Students Develop Critical Thinking Skills When Using Generative AI (Part 1)

From the University of Kent’s Digitally Enhanced Education series, a two-parter on the theme of how generative AI is affecting student’s critical thinking skills, with the second part coming next week. We’ve been living with generative AI for a while now, and I am finding diminishing returns from the various webinars and training I have been attending. Nevertheless, there’s always new things to learn and nuggets of wisdom to be found in these events. The Kent webinar series has such a wide reach now that the general chat, as much as the presentations, is a fantastic resource. Phil has done a magnificent job with this initiative, and is a real credit in the TEL community.

Dr Mary Jacob, from Aberystwyth University, presented an overview of their new AI guidance for staff and students, highlighting for students that they shouldn’t rely on AI; for staff to understand what it can and can’t do, and the legal and ethical implications of the technology; and for everyone to be critical of the output – is it true? Complete? Unbiased?

Professor Earle Abrahamson, from the University of Hertfordshire, presented on the importance of using good and relevant prompts to build critical analysis skills. The first screenshot above is from Earle’s presentation, showing different perceptions on generative AI from students and staff. There were some good comments in the chat during Earle’s presentation, on how everything we’ve discussed today comes back from information literacy.

Dr Sian Lindsay, from the University of Reading, talked about the risks of AI on critical thinking, namely that students may be exposed to a narrower range of ideas due to the biases inherent in all existing generative AI systems and the limited ranges of data they have access to, and are trained upon. The second screenshot is from Sian’s presentation, highlighting some of the research in this area.

I can’t remember who shared this, if it came from one of the presentations or the chat, but someone shared a great article on Inside Higher Ed on the option to opt out of using generative AI at all. Yes! Very good, I enjoyed this very much. I don’t agree with all of it. But most of it! My own take in short: there is no ethical use of generative artificial intelligence, and we should only use it when it serves a genuine need or use.

As always, recordings of all presentations are available on the @digitallyenhancededucation554 YouTube channel.

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Institutional Experiences of Microsoft Copilot

Diagram of MS Copilot architecture
Diagram of Microsoft Copilot Architecture

November 2023, I wrote a rambling post about my thoughts on generative AI and where it was going to go for the ALT Blog. I made a prediction there that someone was going to buy a site license for ChatGPT, and lo! This HeLF discussion was about exactly that. Sort of. It’s Microsoft’s Copilot tool that the majority of people are going for, because we are all, or mostly, existing Microsoft customers and they are baking it into their Office 365 offering. Though there are a couple of institutions looking at ChatGPT as an alternative.

Costs and practically was a big issue under discussion. Microsoft are only giving us the very basic service for free, and if you want full Copilot Premium that it’s an additional cost of around £30 a month per individual. Pricey, but it gets worse. They have tiers upon tiers, and if you want to do more advanced things like having your own Copilot chatbot available in your VLE for example, then you’re into another level of premium which goes up to hundreds a month.

We also discussed concerns about privacy and data security. If Copilot is given access to your OneDrive and SharePoint files for example, then you need to make sure that everything has correct data labels, or else you run the risk of the chatbot surfacing confidential information to users.

At Sunderland we have no plans for any premium generative AI tools at present, the costs are just prohibitive. And it’s not just at this level, the entire field of generative AI is hugely expensive and completely unsustainable. So I’ll end as I began, with prognostications: OpenAI is haemorrhaging money, they lost over half a billion dollars last year. They are living on investment capital, and unless the finance bods start seeing a serious return, they are going to pull the plug. Sooner rather than later I reckon. I don’t think OpenAI will go under exactly, but I do think they are going to get eaten by one of the big players, Microsoft most likely. A lot of headlines were made last year about Microsoft’s $10 billion investment, but people haven’t read the fine print – that $10 billion was in the form of server credits, so Microsoft is going to get that back one way or another. I’m going to give the AI bubble another six to eighteen months.

What will come after that? Generative AI isn’t going to go away of course, it’s a great technological achievement, but I think we will see a shift towards smaller models being run locally on our personal devices. It will be interesting to see how Apple Intelligence will pan out, they aren’t putting all of their eggs into the ChatGPT basket. And as for the tech and finance industries? They’ll just move onto the next bubble. Quantum computing anyone?

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AI-Augmented Marking

Chart showing correlation of human and KEATH.ai grading
Accuracy of KEATH.ai Grading vs. Human Markers

This was a HeLF webinar facilitated by Christopher Trace at the Surrey Institute of Education, to provide us with an introduction to KEATH.ai, a new generative AI powered feedback and marking service which Surrey have been piloting.

It looked very interesting. The service was described as a small language model, meaning that it is trained on very specific data which you – the academic end user – feeds into it. You provide some sample marked assignments, the rubric they were marked against, and the model can then grade new assignments with a high level of concurrence to human markers, as shown in the chart above of Surrey’s analysis of the pilot. Feedback and grading of a 3-5,000 word essay-style assignment takes less than a minute, and even with that being moderated by the academic for quality, which was highly recommended, it is easy to see how the system could save a great deal of time.

In our breakout rooms, questions arose around what the institution would do with this ‘extra time’, whether they would even be willing to pay the new upfront cost of such a service when the cost of marking and feedback work is already embedded into the contracts of academic and teaching staff, and how students would react to their work being AI graded? Someone in the chat shared this post by the University of Sydney discussing some of these questions.

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ALT NE User Group: June 2024

Northumbria Uni library ceiling with power 'blocks' from the ceiling, and a humours 8-bit Mario hitting one of them
I’m not the only one who sees this, right?

Northumbria’s turn to do hosting honours this time around. It’s been a while since I was on my old campus, and I was shocked to see that the Library refurb ran out of money to finish the ceiling. I did like the ceiling mounted power extensions that look like Mario coin blocks though. Solves the problem of tripping over or accessing floor panel extensions, but introduces new problems for the vertically challenged. Julie said she couldn’t reach them to pull them down, while I, on the other end of the spectrum, had to duck and weave to avoid bonking my head on them at times. I wouldn’t mind if they actually dispensed gold coins, but no such luck.

Anyway, that’s enough shade thrown at my previous employer, time to be serious. Generative AI once again dominated our morning discussions, with a presentation by Tadhg, an academic at Northumbria, who has revamped their Business module with content related to Generative AI, teaching students how to use it to help write research proposals. This was followed by Ralph in their learning technologies team who has been using D-ID and Elevenlabs to create animated videos to supplement written case studies for students in Nursing. Dawn from Northumbria’s Library service then gave us a talk on their experience of Adobe Creative Campus, and reported a much more positive experience than Teesside.

After lunch we had some open discussions on digital exams. Newcastle are using Inspera to facilitate a proportion of their exams, and have mixed feelings about it. I was pleased to note that they have strongly pushed back on using online proctoring on ethical grounds. Emma from Teesside led a discussion on WCAG changes which prompted us to discuss getting the balance right between supporting all students along the principles of UDL, while being practical and having to work within the technical and cultural limits of the systems we have to use and processes we have to follow. Student record systems only allowing one assignment per module, for example.

Finally, Craig from Northumbria gave us a demo of some interactive 360 degree content they have created, including surgical simulations, nursing scenarios, and examining crime scenes. They are producing this content such that the scenarios can be accessed via any web browser, at the expenses of immersion, but they are also exported into a format that can be used with their bank of Vive VR headsets for students to get the full experience.

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