Stephen Downes

What strikes me about Tim Klapdor's six dimensions of learning is how much overlap there is with my own critical literacies (note that I am not suggesting anything wrong here; I appreciate the similarity, nothing more). The middle four especially. I like the idea of a 'perceptual' dimension of learning; I want to think about that more. And I'm not sure I'd make 'creating' a separate dimension; to me, read-write are just two sides of the same coin. Overall, the broader system Klapdor is constructing is a useful frame (paraphrased): the dimensions and domains provide the structural framework; the learning types translate that framework into a learner-centred perspective; and then the learning patterns then provide building block.

Good discussion of micro-credentials, and in particular, how we trust that a micro-credential is worth anything in the first place. After all, anyone can issue a micro-credential (I actually built it into some of my MOOCs years ago). But why trust them? Wendy Palmer looks to food lables as an analogy. "I keep coming back to the food certification example. We have different standards and certification arrangements for different purposes, whether that's organic production, food safety or country of origin. Each tells us something different about the product. We don't expect one certification to cover everything, but we do need to understand what each certification means, who is responsible for it and what standards have been met."

Lance Eaton describes a ChatGPT skill he's working on to create audiobooks out of plan text versions of those books (being clear that he's doing so only for audiobooks that don't exist and never will. I like this concept; I've also tried ElevenLab Reader (and even paid for it once) but wasn't impressed. And there's tons of stuff I'd like to listen to while driving, cycling or in the evening. Eaton also reviews ElevenLab's "full cast" production of Frankenstein (you can listen for free but you have to sign up - hang on to your wallet). I have a deep love for Old Time Radio and can see how well this could play - but there's a long way to go before matching the innovation and creativity of Philip Marlowe or Johnny Dollar.

I've referenced articles in Rest of World numerous times and so find itunfortunate toreport that it "faces a January shutdown after six years as founder Sophie Schmidt searches for a new home amid declining web traffic." It was started with $60 million of seed money, which was probably what made it unsustainable, though its own decisions probably didn't help: "Rest of World attempted to strengthen its readership by prioritising Western audiences, increasing its focus on markets such as China and introducing a free registration requirement for regular readers." Most articles I've looked at on this attribute the decline to Facebook's changing piorities. "News publishers contend with declining referrals from search engines and social platforms, alongside the emergence of AI tools that answer questions without directing users to news websites." Related (via Alan Levine): Global Voices "is an international, multilingual community of writers, translators, and human rights activists." They're also facing a funding shortfall.

This article is ultimately a pitch for a new service, but it's developed in an interesting way. The question is how "to find ways of making decisions more rapidly without sacrificing the notion that in a shared governance system, decision-making responsibilities have to be broadly inclusive." The traditional formal structures, like a Senate, are too rigid, don't meet often enough, and are subject to internal politics. Alex Usher recommends, in the end, that "what institutions need to tackle 'big' issues is a focused, time-limited body that mixes breadth of perspective with expertise and is sent on its journey with some in-depth, balanced research." My first (and best) thought was that Usher has reinvented the Royal Commission process for universities!

Matthew Miller writes about some experimentation with vector embeddings at the Library of Congress. "Vector embeddings, in the simplest terms, are numbers that represent text. They are used in many machine learning and AI tools and provide a way to reduce natural language to numbers, which enables us to interact with language using algorithms." What they did was to transform a user's query into a "phantom record" in order "to find where in the embedding model and our existing records it would be located." Visualizing the catalogue, the system "also has a 'Communities' toggle that provides a view of the catalog in line with the embedding model's internal organization." Here are all the embeddings files.