OLDaily

Welcome to Online Learning Daily, your best source for news and commentary about learning technology, new media, and related topics.

Oblivion University
Jim Groom, 2023/12/12

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People around the fediverse are hailing the madness of Jim, Groom as this inspired launch on 'AI 106' dropped today. Related: from bavatuesday the AI Song blog post and the song itself (MP3).

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The State of the Open Web: 3 Takeaways Heading into 2024
Richard MacManus, The New Stack, 2023/12/12

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Richard MacManus identifies three major trends heading into 2024, though he spends the most time on the first: the fediverse as a social media renaissance. Decentralized applications like Mastodon and Peertube and others are gaining ground, but it's more of a slow burn than a meteoric rise. No problem. The second trend is a bit like the first, but for developers: the rise of web components over React. Finally, third, MacManus asserts that "two previous hype train trends were unceremoniously shunted off the tracks this year: Web3 and metaverse." There's no question AI hype drowned them out. But you'd be mistaken, I'd say, if you think they're going away. Maybe we'll use different names (like JSON Web Tokens, for example) but we need things like encryption and persistence, which is what these concepts represent. These, indeed, are the glue that will make decentralization work.

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What is the purpose of educational technology?
Martin Weller, The Ed Techie, 2023/12/12

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"What do you think educational technology is for?" asks Martin Weller. "When we adopt it, what is the purpose we are intending it to fulfil?" He's quite correct to say "the answer will vary depending on technology or context" but for my own part, the answer is almost always the second of the seven options he presents: to make learning more accessible. But he, if you disagree with me, there's a poll where you can register your opinion.

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The teacher education content framework we really need
Clare Brooks, Joanna McIntyre, Trevor Mutton, BERA, 2023/12/12

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"Teacher education is too important to be left to policymakers influenced by a few select individuals," write the authors. "It requires the consensus of multiple voices and actors: teachers, mentors, school leaders, teacher educators and researchers." Accordingly they offer a framwork of five elements that ought to inform teacher education (quoted/paraphrased):

• new teachers should be inducted into a conversation about the purpose of education;
• a sound understanding of how professionals learn and what professional practice looks like;
• intellectual basis for teacher education as complex, intellectual work;
• a signature pedagogy that prepares teachers 'to think, perform and act with integrity'; and
• content frameworks that support the development of teachers' understanding.

Clearly, the focus here is on 'teachers as professionals' - but I'm not sure the problem is that teachers don't see themselves as professional enough. Image: Utah.

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Food for Thought: What Are We Feeding LLMs, and How Will this Impact Humanity?
Stuart Leitch, The Scholarly Kitchen, 2023/12/12

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"Academia has developed an amazing tree of knowledge which is arguably the most important data for Large Language Models to be trained on," writes Stuart Leitch. "Where does the scholarly communication community fit in?" It's a good question, and one we need to be careful about as we answer. We know that the quality of the data given to an AI impacts the quality of the results. I saw a LinkedIn post a day ago (now unfinable because it's LinkedIn) complaining about the representation of "Irish professors" as uniformly older white men. Do a search on Google for that subject, though, and you'll get pretty much the same result. And it could be that the majority of Irish professors actually are older white men (I can't say one way or another). AI tends to reflect back the patterns it sees in the data.

AI will get better the more it becomes 'multi-modal'. We'll be hearing this term a lot. But there are two separate meanings. One sense of the term means that AI will be able to use things like images, videos, websites, and even real life, as input data. But the other sense of multi-modal AI is the sense connoted in this article: of governing the statistical inferences an AI makes with solid factural data as produced by, say, the scholarly communication community. I agree with Stuart Leitch: "rather than trying to get premium scholarly information out of LLM training sets, we should fight to get it in there, on terms that are economically sustainable." But that does not mean, as suggested here (and previously) combining it with symbolic model-driven AI (see the illustration). It can learn from symbolic models, but it should not be controlled by them.

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We publish six to eight or so short posts every weekday linking to the best, most interesting and most important pieces of content in the field. Read more about what we cover. We also list papers and articles by Stephen Downes and his presentations from around the world.

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