Narrative as a Fundamental Way of Making Meaning
Keith Hamon,
Learning Complexity,
2026/03/04
I have spent my entire life resisting the idea of the narrative and storytelling (which is a hard place to be in for a writer). For Keith Hamon, though, the narrative is the core. He cites Pria Anand's The Confabulations of Oliver Sacks, where a 'confabulation' is "a neurological repair where the brain fills memory gaps with stories that the teller believes to be true." Well there's no doubt there are these gaps that are filled, but are they filled with stories? Hamon thinks so. "Narrative is the biological software that converts raw, chaotic data into a liveable reality. It's an instinctive search for order that slips beneath consciousness to insure that we always have a coherent sense of ourselves and our worlds." It strikes me as wrong, though, that the only sort of coherent sense we can have is a text-based linear structure. At the very least, it's a fabric - "it's all a rich tapestry," as Andrea likes to say. And for me, at least, it's thickly woven, multi-modal, and generally non-linguistic. I can, if I really try, represent it with a narrative, but it doesn't come naturally at all. I think we do people a disservice if we tell them all they can imagine is stories.
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Two Paths, One Purpose: How Fair Dealing and Open Education Work Together
Amanda Grey, Karen Meijer,
Kwantlen Polytechnic University, Teaching & Learning Commons,
2026/03/04
The term 'open education' has a variety of meanings, most being based on the idea of creating access to learning opportunities and resources. The term 'fair dealing' is a legal term providing reader rights to use copyright material under certain conditions, analogous to 'fair use' in the U.S. This article finds a lot on common between them and argues "they're rooted in the same values: fairness, accessibility, and a commitment to the public good." I mostly agree with the authors' vision: "Imagine an educational landscape where learners have rich, meaningful choices: open textbooks they can customize and adapt, fair dealing excerpts for highly specialized knowledge, collaborative assignments that contribute to shared knowledge, and community-created resources that reflect the world students live in." Also available: the Open Education Workbook (content is in the menu that runs across the top of the page in hard-to-see dark grey).
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Are service typologies the key to scaling agentic AI systems across public services?
Kay Dale,
GOV.UK AI Studio,
2026/03/04
There's more to this than meets, the eye, but I've added Updates from GOV.UK AI Studio to my RSS reader and will likely track further developments. Here's the gist: Kay Dale writes, "We've identified 8 different types of government service to help us see where agentic AI can add most value." These topologies, as they're called, underlie the existing list of 75 digital services they've identified across government. Of course this sort of analysis could be undertaken for any sort of service, including learning services. I think this sort of this is going to matter, and will watch how it plays out. If you're wondering, the eight types (illustrated) are: informational hub, task list, portal, application, register, license, appointment, and payment. Via Doug Belshaw, Tom Loosemore.
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UX Roundup: Year of the Horse
Jakob Nielsen,
UX Tigers,
2026/03/04
I think it's worth spending the time it takes to have a nice leisurely read through this article from Jakob Nielsen, one of the world's most notable experts on usability and user experience design, as he reflects on how AI has upended the last 40 years of his work. "AI will likely completely invalidate the manual UX design process I spent four decades evangelizing, from 1983 to 2023," he writes. "My error was in assuming that what had worked for forty years would continue to define the standard. A reasonable assumption, perhaps, but one I have now been proven wrong in holding." Stunning. And yet, still beautifully designed and written.
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Backpropagation Explained: How Modern AI Models Actually Get Smart
Darren Broemmer,
Medium,
2026/03/04
This is a good article describing the principle of 'back-propagation' in some detail. This is one of the major algorithms used to train neural networks (we've mentioned it here a lot over the years). The simple explanation is that back-propagation is the process of correcting outputs in response to feedback. But the trickier part is now this happens when we're looking at a neural network with multiple layers (so-called 'deep' learning). Darren Broemmer could go into more detail and describe the mathematics of it, but he doesn't, and the article doesn't really suffer for it. He does look at some alternatives to correct back-propagation around the edges, and considers some misconceptions, including the larges question, which is whether the human brain itself uses back-propagation (answer: probably not, though it needs to solve similar challenges).
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Where Technology Meets Learning: Inside Cornell’s Future of Learning Lab
Ashley Kim,
The Cornell Daily Sun,
2026/03/04
I completely disagree with this: "'Learning is not about feeling good,' Kizilcec said, who is the founder of the Future of Learning Lab at Cornell. 'The emotion of learning is frustration. That's the emotion that's most predictive of learning.'" In my view, if students are getting frustrated, then you're doing it wrong. Frustration is what people feel when things fail and they're getting no clue as to why. It's the opposite of that desire to make 'one more attempt' feeling you get from good software or well-structured problems (analagous to Sid Meier's 'one more turn' approach to gaming). Frustrated is what you feel when you think there's no possibility of success; challenged is what you feel; if you think you could do it if you solved 'one more problem'.
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