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A useful list of Generative AI platforms that are available with a free plan.

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Generative AI - Free to access platforms

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KnowHow Student tutorial on the use of Generative AI

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KnowHow Student tutorial on the use of Generative AI

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KnowHow Online tutorial on Best Practice of Generative Artificial Intelligence for students

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Maximise use and avoid pitfalls of GAI in your studies

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slide: GAI technologies: Maximise use and avoid pitfalls in your studies

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This YouTube playlist includes all the sessions from the week. You'll also find individual session links under the relevant section.

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A beginner's guide to Generative AI at the University of Liverpool

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A wide range of GenAI tools to support the research process, collated by Dr Na Li (XJTLU) and Dr Tunde Varga-Atkins (University of Liverpool).

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Creating accessible and inclusive learning resources with GenAI

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Creating accessible and inclusive learning resources with GenAI

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Presenters: Gary Ellis, Rob Lindsay

This video covers the creation of accessible content tailored for diverse user needs, the identification and amendment of non-inclusive language, and the production of multimodal learning materials. With a strong emphasis on user privacy, this session is for educators and students interested in the intersection of technology and inclusive education. Presented as part of the University of Liverpool's Global Accessibility Awareness Day programme.

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Generative AI in education: Creating accessible and inclusive learning resources

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Generative AI in research tools (Padlet)

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Generative AI in research tools (Padlet)

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An overview of the AI tools available to support the research process

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Custom GPTs: A pathway to personalised learning

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Custom GPTs: A pathway to personalised learning

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Presenter: Rob Lindsay

A short presentation on the use of CustomGPTs for personalised learning.

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A pathway to personalised learning: Engaging with custom GPTs: Rob Lindsay

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University of Liverpool Generative AI - Open staff forum

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University of Liverpool Generative AI - Open staff forum

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An open online community for staff for all things Generative AI at the University of Liverpool.

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A dedicated on-demand course: Generative Artificial Intelligence (GAI) for Teaching, Learning & Assessment.

Learn about GAI tools, assessment redesign methods, prompt literacy, and much more.  Read about this course and how to enrol in this blog post.

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Centre for Innovation in Education website

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Centre for Innovation in Education website

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This page will be regularly updated with links to new resources, policies and guidance on effectively using Generative AI in the context of teaching, learning and assessment, and also will contain information on upcoming events that the University is hosting dedicated to exploring this technology.

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Generative AI has the potential to be transformative in the context of pedagogic practice that takes place across Higher Education. Liverpool are exploring both the opportunities afforded by such technologies and mitigating the potential dangers that established teaching, learning and assessment practices might face as the technology becomes more and more embedded in wider society.

This page will be regularly updated with links to new resources, policies and guidance on effectively using Generative AI in the context of teaching, learning and assessment, and also will contain information on upcoming events that the University is hosting dedicated to exploring this technology. CIE has worked with colleagues from all across the University to produce this content:

CIE have also developed a Generative AI North West (GAINW) Network for educational institutions in the North West to share good practice and develop new uses for GAI in education. If you are interested in joining the GAINW network please contact cie@liverpool.ac.uk.

Many of our guides, resources and events are open to everybody to view and attend, and we are always open to conversations about our approach.

Back to: Centre for Innovation in Education

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Generative Artificial Intelligence in Teaching, Learning and Assessment

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Generative AI has the potential to be transformative in the context of pedagogic practice that takes place across Higher Education. Liverpool are exploring both the opportunities afforded by such technologies and mitigating the potential dangers that established teaching, learning and assessment practices might face as the technology becomes more and more embedded in wider society.

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Presenters: Dr Na Li, Dr Tunde Varga-Atkins (XJTLU)

Recording: Session recording (link)

Slides: Linked (navigate with left/right keys)

Miro board: AI Tools for Research

Have you thought about using Generative AI tools for research tasks? Come and find out about some tools that could help you along the way from administration, literature reviews, data collection, data analysis and reporting, dissemination. This will be an introductory session, demonstrating some potential tools that may be useful in your or your students’ research work.

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Interact with your audience using real-time voting. No installations or downloads required - and it’s free!

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GenAI Fest: All resources, recordings and presentations

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This Padlet collates all of the sessions from GenAI Fest 2024.

You can download a PDF including all of the resources within this Padlet by clicking the link above.

For any questions, please contact CIE@liverpool.ac.uk

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Presenters: Giovanni Sala, Gary Ellis and Rob Lindsay

Recording: Session recording (link)

Slides: Attached

Resources:

Curriculum aligner GPT (link)

Learning outcome developer GPT (link)

In this session, we will explore the capabilities of custom GPTs and their uses. Custom GPT and Retrieval Augmented Generative (RAG) models, including those from OpenAI and other platforms, are very flexible and can be tailored to handle a wide range of academic and administrative tasks.

We will explain how these models work, their benefits, and show practical examples of their use. Attendees will learn how to customise and implement their own GPT-based AI solutions to improve efficiency and effectiveness in various areas. This session aims to show the transformative potential of custom GPT models in both academic and administrative settings.

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Supporting Student Achievement: Using GenAI to Enhance Understanding of Assessment Briefs

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Supporting Student Achievement: Using GenAI to Enhance Understanding of Assessment Briefs

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Presenter: Katie Hudson

Recording: Session recording (link)

Slides: Attached

Resources: ChatGPT conversation example download

Explore how ChatGPT can assist students in understanding their assessment briefs in this talk which draws from a series of assessment support sessions provided by the English Language Centre in the MSc Nursing program during semester 2, 2022/23. These sessions supported a cohort of international students in grasping complex academic requirements.

Positive student feedback from this experimental teaching demonstrates how crafting clear prompts for ChatGPT to identify and explain key instruction words in assessment briefs can help students understand critical terminology and apply it in their essay writing process.

Join us to understand practical strategies and engage in discussions on integrating AI in academic support.

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Supporting Student Achievement - Using GenAI to Enhance Understanding of Assessment Briefs

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GenAI Tools for Literature Reviews: Could Students Write a Literature Review in a Weekend?

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GenAI Tools for Literature Reviews: Could Students Write a Literature Review in a Weekend?

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Presenter: Dean Harris

Recording: Session recording (link)

Slides: Attached

Blood pressure (watch the recording for insight):

10:30 - 146/91

11:30 - 149/97

17:00 - 121/92 (a drop!)

Final year dissertations are a prevalent feature amongst our programmes at the University and are a key component of programmes with the School of Applied Health Professionals and Nursing. GenAI can be used to turbocharge students' literature reviews, improving efficiency. While there is a lot of promise and hype around this topic, my experience suggests that the utility of these tools lies somewhere in between. Piloting of these tools is in the very early stages.

This session will introduce several tools to help students with literature reviews. Participants will have the opportunity to try out the tools with a research question of their choice, and we can reflect on their utility at the end. Hopefully, we’ll get closer to answering the question: Could this transform the way students conduct literature reviews?

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AI Tools for Literature Reviews - Could Students Write a Literature Review in a Weekend

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Presenter: Sam Saunders

Recording: Session recording (link)

Slides: Attached

Resources:

AI Assessment Designer GPT (link)

Assessment redesign Padlet (link)

This session will consider the impact of Generative AI on the design, implementation, and completion of formative and summative assessments in higher education, and will examine what steps can be taken to best harness the potential, and protect against the dangers, of the technology in an assessment context.

Participants will be invited to consider assessments on their module and evaluate them against a set of criteria, and discuss ideas for the incorporation of (or the removal of) the use of Generative AI in that assessment space - and what benefits it might ultimately bring students.

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Redesigning Assessments in the Era of Generative AI

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Is it possible to make GenAI academic policy fit for purpose?

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Is it possible to make GenAI academic policy fit for purpose?

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Presenter: Claire Ellison

Recording: Session recording (link)

Slides: Attached

Resources:

GenAI Policy Padlet (link)

Lance Eaton AI policy initiative

Over the past 18-months academics and professional services colleagues have been grappling with implementing academic integrity policy in the age of generative artificial intelligence. The age of GenAI has thrown up new challenges and magnified a myriad of existing problems with assessment practices. This has led to problems enacting a policy aiming to maintain academic standards.

Join us in this session for a guided discussion through the University of Liverpool’s policy on GenAI use. Colleagues from the Centre for Innovation in Education will share their findings from surveying staff and students on their opinions of the policy and provide a collaborative space where you can share your experiences of using the policy with colleagues, or just listen and learn from other’s experiences.

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Is it possible to make GenAI academic policy fit for purpose

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Restraining the uncanny guest: AI Ethics and University Practice

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Restraining the uncanny guest: AI Ethics and University Practice

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Presenter: Dave Webster

Recording: Session recording (link)

Blog post: The Uncanny Guest (link)

If GAI is the 'uncanniest of guests' (with apologies to Nietzsche) in the University, who seems here to stay what can we do about any their misbehaviour? After decades of seeking to eliminate prejudices and bias, GAI threatens to reinscribe misogyny, racism, homophobia and other unethical discrimination back into the academy.

After centuries of citation tradition and careful attribution of sources, GAI seems intent on shuffling the work of human scholars and presenting it without any clarity as to whence it came. What do we do with this uninvited guest who behaves badly, won't leave and seems intent on asserting that it's their house now anyway?

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Nihilism stands at the door: whence comes this uncanniest of all guests?[1]

Is Generative AI an uncanny and uninvited guest at the table of Higher Education? For Nietzsche the uncanny guest at the door is nihilism. This guest has arrived to undermine our existing sense of purpose and throw the world into turmoil as we realise that the prior sources of value and meaning we have relied upon are useless, and indeed ultimately harmful. Our prior bulwarks against life often seeming futile, empty and meaningless, are unmasked for Nietzsche, as anti-life lies. He rejects (largely, and often in mixed and complex measure) Christianity as a source of meaning, and all the ultimate-value-offering bedfellows that accompany it[2]. This tumult washes away our preconceived understandings of purpose and meaning. Nietzsche has much to say about how nihilism (and often he equates this to either his, or maybe Zarathustra's, declamation of nihilism) will upend the world[3] and lead to cataclysmic catastrophes, and many see the outworking of this in the twentieth century. But the catastrophe is not forever, and ultimately there is hope that beyond nihilism there can be something better, some way of living a meaningful life, but not one based on metaphysical fictions, which is how Nietzsche largely characterised Christianity.

Bernard Reginster, in The Affirmation of Life: Nietzsche on Overcoming Nihilism[4] clarifies the term, but also Nietzsche's overall goal in relation to it: Nietzsche's philosophical project consists in determining whether there is a way to overcome nihilism. Nihilism is the conviction that life is meaningless, or not worth living. Reginster is, I would argue, accurate in identifying Nietzsche as ultimately an optimist about the hope for affirming life. Reginster, in the closing page of his book states:
In many ways, Nietzsche's own life, and in particular the manner in which he practiced philosophy, exemplifies the life-affirming ideal he advocates. As he conceives of it, philosophical greatness consists in challenging hallowed and deeply entrenched views (what he often calls "the ideal"), and in setting off to discover new worlds of ideas. And few philosophers have been more successful in doing both than he has. His books are either severe polemics against traditions that reach back thousands of years, in which case he had to be a philosophical "warrior," or they blaze trails to unexplored new worlds, for which he must have become a philosophical "discoverer."[5]
In seeing AI as the uncanny guest that will upend so much of Higher Education, I suggest that we should also be optimistic. Many concerns centre on academic integrity and being sure that work students produce is their own work, and that with the loss of that we will have no way to assess if students have actually learned what their qualification states they have learnt. Assessment in Higher Education is meant to assess what a student knows and can do. If assessments don't allow us to actually measure what we need to pass judgement on - whether a students has certain attributes and competencies - it is hard to imagine how a University might meaningfully function.

I believe many of our worries about Higher Education and Generative (and other forms of) Artificial Intelligence can be overcome. But as with Nietzsche's announcement of the arrival of Nihilism, the overcoming will be eventual, following an upheaval that sees us of necessity take a hammer to much existing HE practice. It really is dämmerung[6] for much of what many hold dear in the University world. Before I imagine where we might be going in HE, I want to say a little about why uncanniness is such a good fit for AI, as it was for nihilism.

What made me think initially of the 'uncanny' was the phrase 'the uncanny valley', used to describe the disturbing aesthetic response we have as a portrayal of the human, or something like part of a person, nears the realistic, and yet something is 'off' about it. The more realistic the portrayal is, the more we feel affinity with it. Originally noted in 1970 by Masahiro Mori at the Tokyo Institute of Technology " Mori coined the term "uncanny valley" to describe his observation that as robots appear more humanlike, they become more appealing-but only up to a certain point. Upon reaching the uncanny valley, our affinity descends into a feeling of strangeness, a sense of unease, and a tendency to be scared or freaked out"[7] Mori's graph below shows how we feel more affinity with a representation the more human it seems - until it is too realistic to be very obviously not human, but has something that gives it away.

The particular thing that drew me to think of Mori's notion was not the much-remarked-upon oddness of AI-drawn hands, but the video trail for the soon-to-be-released Sora from Open AI, which I watched in a room full of colleagues from a range of universities. Everyone sat there being impressed until there are a couple of, I guess 'odd' is the right word, things with the walker's legs near the end - and nearly everyone in the room gasped or said 'eurgh'. This made me think of the uncanny valley, and of Nietzsche's phrase about a different kind of uncanniness. The disquieting is perhaps initially the uncanniness of Mori's valley, but ultimately more like Nietzsche's coming catastrophe and ' revaluation of all values'.

The more AI-written essays you generate and/or read the more you see, for now, a slight oddness to them, a detachment that can seem uncanny, even a little creepy. The AI-made (DALL·E 3) images in this post have the strangeness of AI-art that is recognisable, if hard to exactly capture definitionally. This may prove to be a transitional phase as AI gets 'better' at mimicking the human voice/eye in writing and art. This, combined with our skill and familiarity in the use of the systems,[8] may well push us to a point where this kind of uncanniness recedes. But as this happens is when the challenges for those of us in universities get really serious, possibly really fast.

The departure from the uncanny valley in aesthetic terms is when we see the interim risk-mitigation methods many of us in Higher Education have put in place around GAI start to falter and fail. If Generative AI starts to be less distinguishable from humanly penned work, even indistinguishable, and we are already seeing the limited efficacy of so-called GAI-detection software, where does this leave concerns about academic integrity? How will we be able to verify that a certain student is capable in some respect, knows and understands and can apply ideas, can argue, synthesise and evaluate sources, draw well-grounded conclusions, operate on a brain, design a safe bridge or any of the many things we hope graduates will be capable of? This is the challenge that we face and may seem to strike at the heart of Higher Education, but I believe this is also an opportunity to enact positive change. The uncanny guest may be uninvited be they are not leaving any time soon.

At this stage it might be argued that the best policy is to return to in-person, pen-and-paper examinations in large halls, with no technology. There may even be a place for some of this, but ultimately, we can't examine everything and there are good reasons we have seen many move away from exams. Indeed it seems like a retrograde step which fails to acknowledge the new AI-based world that students will graduate into. One key point is these type of exams don't actually test the skills we might want students in Higher Education to develop. Arguably, the memory-test element that sits at the heart of exams is the least useful skill in a world full of devices capable of fact-retrieval. But conversations about students ability to retain and retrieve facts are only part of the conversation. There is something about GAI that is qualitatively distinct from tools that retrieve information - the generative bit matters. So, while Higher Education has survived MOOCs, Wikipedia, Microsoft Encarta, and YouTube the challenge from Generative AI is of a different and more existential order. We can reasonably see this as a fundamental threat to the very nature of the engine of the industrial, culture and knowledge economies - the university.

At worst we might wonder what the point is, like those cast adrift into the kind of existential anxiety prompted by nihilism, but there really is another way to see the coming AI disruption of Higher Education. As tutors use GAI to help with their workload, and possibly to prepare sessions, and students use GAI to help them produce work, and feedback/grading is done by AI, might we get to a point where GAI sets work, does the work, and then marks the work. This starts to feel pretty futile and dystopian and there doesn't seem to be a lot of learning going on. But this is not the inevitable conclusion of where we currently are. As Jon Dron blogs: It doesn't have to be this way. We can choose to recognize the more important roles of our educational systems and redesign them accordingly, as many educational thinkers have been recommending for considerably more than a century.

We need to ask a serious question of ourselves in Higher Education. What do we really think it is that we have to offer students, society, commerce, politics, and the wider world? Are we still the repository of knowledge, or perhaps the arbiter and curator of competing knowledge collections and assertions? What do we think we have to give young people? Most of us in universities still think that being able to write and develop an argument, or design an experiment and draw conclusions, matters. Alongside knowing enough to know what to look up, or retrieve having the skills to weigh competing assertions, seems vital.

On this theme, Marc Watkins, in a piece called Our Obsession with Cheating is Ruining Our Relationship with Studentswrites: We're going to have to search for moments of learning. One way of starting this exploration is to heed John Warner's call to stop automating the writing process. Students write predictable, formulaic essays and teachers leave similarly predictable, formulaic responses. What was learned and what was gained in such a system? The reasons why we've adopted this structure are based on convenience and labor.

The current system, as Watkins partly notes, was never designed from scratch as the ideal way to promote learning and transmit skills, and knowledge. It is very much shaped by the economic circumstances and systems that Universities have grown in, and much of Higher Education practice is the result of imperfect accretions that have become fixed norms. Reforms have often been frustrated by funding systems, the conservativism of large groups of complex institutions, and perceptions of the value of 'tradition'. The system under threat from GAI has much to value within it, but it is also riddled with non-trivial problems and is far from perfect.

As such it doesn't seem to be merely rhetorical flamboyance on my part to compare the arrival of GAI in Universities to the shock that nihilism was about to deliver in Nietzsche's analysis. Those of us in Higher Education will have to face up to the fact that we are on the cusp of massive change, and that much of our current massified HE practice is not going to survive the next decade. We can bemoan this, and I am sure I'll do some of that on occasion, but we can also greet this future with optimism. In this turbulence there is the opportunity to reevaluate all the values of our undertaking. What kind of Higher Education emerges, alongside a world where all kinds of AI have become increasingly pervasive, is not yet determined. It is an open field of terrifying, exhilarating and surprising possibility. The only thing I would suggest that is determined is that the University of the future will look very different to the University of today.

[1] Nietzsche. T he Will to Power, trans. Walter Kaufmann and R. J. Hollingdale, ed., with commentary, Walter Kaufmann, Vintage, 1968.

[2] We might want to add Platonism, and much of its legacy to this - but Catherine Zickert argues for a more sophisticated reading here, while maintaining Nietzsche's nihilism and rejection of a metaphysical Platonism.

Zuckert, Catherine. "Nietzsche's Rereading of Plato." Political Theory, vol. 13, no. 2, 1985, pp. 213-38. JSTOR, http://www.jstor.org/stable/191529. Accessed 4 Mar. 2024.

[3] In the 1888 Preface to The Will to Power, he wrote:

What I relate is the history of the next two centuries. I describe what is coming, what can no longer come differently: the advent of nihilism. This history can be related even now; for necessity itself is at work here. This future speaks even now in a hundred signs, this destiny announces itself everywhere; for this music of the future all ears are cocked even now. For some time now, our whole European culture has been moving as toward a catastrophe, with a tortured tension that is growing from decade to decade: restlessly, violently, headlong, like a river that wants to reach the end, that no longer reflects, that is afraid to reflect.

Nietzsche, Friedrich. The Will to Power. Translated by Walter Kaufmann and R. J. Hollingdale. Edited, with commentary, by Walter Kaufmann. New York: Vintage Books, 1968.

[4] Reginster, Bernard. The Affirmation of Life: Nietzsche on Overcoming Nihilism, Harvard University Press, 2006. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/liverpool/detail.action?docID=3300356.

[6] To refer to Nietzsche's 1989 book Twilight of the Idols, or, How to Philosophize with a Hammer

[7] https://spectrum.ieee.org/what-is-the-uncanny-valley IEEE Spectrum article: What Is the Uncanny Valley? Creepy robots and the strange phenomenon of the uncanny valley: definition, history, examples, and how to avoid it. Rina Diane Caballar 06 Nov 2019

[8] The term "prompt engineering' to refer to the instructions given to an AI system is seen by some as a whole new job class, and the subject of study. Others are less sure. Alex Warren in a blog post wrote: Prompt engineering isn't rocket science. In fact, it's not even engineering. It's just good old-fashioned writing. Clear, concise copywriting, designed to convey meaning.

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The Uncanny Guest: Artificial Intelligence and the University

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Nihilism stands at the door: whence comes this uncanniest of all guests?[1] Is Generative AI an uncanny and uninvited guest at the table of Higher Education? For Nietzsche the uncanny guest at the door is nihilism. This guest has arrived to undermine our existing sense of purpose and throw the world into turmoil as we...

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How to improve accessibility standards and support using GAI

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How to improve accessibility standards and support using GAI

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Presenters: Ben McGrae, Kat Purdy, Ste Summers

Recording: Session recording (link)

Slides: Attached

This session will explore how Generative AI can enhance digital accessibility. We will examine practical applications and successful examples of GAI in accessibility, provide tips for integrating GAI tools, and address potential challenges, including ethical and technological concerns. Finally, we will explore emerging trends and the future potential of GAI.

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Generative AI embedded in Canvas and accessibility support

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Presenters: Sam Saunders and Caroline Hands

Recording: Session recording (link)

Slides: Attached

Resources:

Environmental Impact of AI (Padlet link)

Long-Term Sustainability (Padlet link)

The ubiquitous nature of Generative AI, and its almost unchecked growth over the past 12 months, has opened up a swathe of new opportunities and approaches to solving complex human problems.

But the technology is not without its dangers. The datasets on which AI models are built reflect existing biases within them, and the outputs from AIs therefore reinforce these biases. AI technologies also consume a significant amount of energy and contribute to climate change. And ownership of data that goes into, and comes out of, AI models is contested. This session will therefore ask participants to consider the different ethical and sustainability dimensions to the advent of Generative AI.

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Identifying AI Risks in Learning Outcomes: Providing engaging, AI-proof teaching alternatives

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Identifying AI Risks in Learning Outcomes: Providing engaging, AI-proof teaching alternatives

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Presenter: Owen Patchell (Feedback Fruits)

Recording: Session recording (link)

Slides: Attached

Resources:

Lance Eaton AI policy initiative

Imperial College London Use Case

If you would like to direct any questions to Owen directly, please contact him via: owen@feedbackfruits.com

We will also be hosting Feedback Fruits for a platform demonstration at a Digital Education Network event in October. Contact CIE@Liverpool.ac.uk for more information.

In this guest slot, we host educational industry expert Owen Patchell (Feedback Fruits) discussing the common approaches seen towards AI and explaining how we can diversify assessment to be more AI proof, aligning them to learning outcomes that are relevant to the employability market where AI will ever present.

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Identifying AI Risks in Learning Outcomes: Providing engaging, AI-proof teaching alternatives University of Liverpool Presenatation

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Welcome to IT Services new AI powered chatbot service

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Welcome to IT Services new AI powered chatbot service

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Presenter: Duncan Brown

Recording: Session recording (link)

Slides: Attached

From idea to service: In 2023, IT Services created a proof of concept for a chat bot, powered by OpenAI and DialogFlow, which could be used by students to answer questions relevant to their University activities. Since then, IT Services has looked to create a new AI-powered chatbot service which can be used by any area of the University to provide a personalised chatbot for staff and students, able to provide answers quickly to the relevant subject matter.

This will be the first time IT Services demonstrates the new AI chatbot service.

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A beginner's guide to Generative AI at the University of Liverpool

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A beginner's guide to Generative AI at the University of Liverpool

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Presenters: Gary Ellis and Rob Lindsay

Recording: Session recording (link)

Slides: Attached above

Join us online for an introductory session on Generative AI designed for those new to the technology. This session will cover the basics of Generative AI, focusing on its application in educational settings.

Topics include:

An overview of Generative AI at the University

Practical examples of Generative AI tools for education.

Ethical considerations in using AI in the classroom.

Resources for integrating AI into teaching and learning.

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Discovering how UoL students are using GAI tools for academic writing purposes

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Discovering how UoL students are using GAI tools for academic writing purposes

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Presenters: Bryony Parsons and Heather Johnston

Recording: Session recording (link)

Slides: Attached

This presentation discusses the findings of a user experience study we conducted this semester which aimed to provide a clearer picture of UoL student confidence and competence in using Generative Artificial Intelligence tools when researching and planning academic writing assignments.

As well as discussing the common themes identified from the research and exploring our insights into how students are using these tools, we explored how this has informed ways in which we can incorporate teaching of using GAI tools in a productive and effective manner.

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Discovering how students use Generative Artificial Intelligence Tools for planning essay assignments