Stella Lee facilitates the MYFest session held on 22 July 2024. AI literacy is more than learning how to code. It’s about critically examining and using AI ethically and effectively. In our session, we break down what it means to be AI literate and explore an AI Literacy Framework designed for educators. We cover seven key areas, discuss the essential skills for each, and share practical resources. Join in for an animated discussion and prepare to dig in for some fun activities.

A project from UMaine New Media

Part 3: Associative Networks and AIs ‘Mind’

Part 2: Optimization Terrains and Confusion Matrices

Scatter Plots of Data Patterns and Relationships

Accelerating the adoption of artificial intelligence across the tertiary education sector.

Artificial intelligence is already transforming education, the workplace, and society.   These principles have been created by Jisc in partnership with the Association of Colleges (AoC) Technology Reference Group. They are intended for colleges to adopt as a statement of intent, guiding strategic direction. They aim to help colleges navigate challenges and maximising the opportunities […]

On Tuesday 27th February, we had our third community meeting. We had a great group who joined us for an insightful discussion around how to provide learners with guidance around AI. The first half of our session was led by AI Technologist, James Hodgkinson, who began with a poll, asking whether their institutions had produced […]

We've had lots of interest in the best way to provide advice to students in colleges.  In this blog post we’ve created an example of learner advice.

AI is of course much more than just generative AI, and a full discussion around AI literacy would need to cover more traditional AI uses too, for example predictive models, adaptive learning, image recognition, recommendation engines and many other tools and techniques.  Generative AI is the hot topic now though, so the groups discussion focused […]

If you’ve been following this blog, you know I’ve written about critical AI literacy, and as I’ve keynoted, taught, and workshopped this, I’ve been developing my model furth…

This study explores how discussing metaphors for AI can help build awareness of the frames that shape our understanding of AI systems, particularly large language models (LLMs) like ChatGPT. Given the pressing need to teach “critical AI literacy”, discussion of metaphor provides an opportunity for inquiry and dialogue with space for nuance, playfulness, and critique. Using a collaborative autoethnographic methodology, we analyzed metaphors from a range of sources, and reflected on them individually according to seven questions, then met and discussed our interpretations. We then analyzed how our reflections contributed to the three kinds of literacies delineated in Selber’s multiliteracies framework: functional, critical and rhetorical. These allowed us to analyze questions of ethics, equity, and accessibility in relation to AI. We explored each metaphor along the dimension of whether or not it was promoting anthropomorphizing, and to what extent such metaphors imply that AI is sentient. Our findings highlight the role of metaphor reflection in fostering a nuanced understanding of AI, suggesting that our collaborative autoethnographic approach as well as the heuristic model of plotting AI metaphors on dimensions of anthropomorphism and multiliteracies, might be useful for educators and researchers in the pursuit of advancing critical AI literacy.