OLDaily

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

Your data, your power: the Fediverse's big advantage over the walled gardens of Big Tech
Elena Rossini, 2024/07/15

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This is mostly an introductory post, but useful if you need to introduce and advocate for the idea of the Fediverse to some of your more sceptical colleagues who (for reasons unknown) can't seem to shake the toxic Twitter or Facebook habit. "What really excites me is the promise of the Fediverse and how it revolutionizes relationships between people. The future is decentralized relationships: every artist, creative person, social entrepreneur, educator - everyone really - should pay attention to this brand new era of the internet, made possible by the Fediverse." Quite right.

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Mapping the Landscape of AI-Powered Nonprofits
Kevin Barenblat, Brigitte Hoyer Gosselink, SSIR, 2024/07/15

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This article maps what it calls the AI-Powered Nonprofit (APN) sector. "We developed a working landscape to connect the dots, and in the end, four big categories of nonprofit AI use cases emerged: Structuring Data, Advising, Translating, and Platforms." It's all interesting reading but one wonders why public AI services need to be characterized as nonprofits. Why not as public services (which could even be government funded). Europe, for example, has something called eTranslation, which "is the European Commission's online machine translation tool." Translation as a public service - an idea whose time has come.

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Imitation Intelligence, my keynote for PyCon US 2024
Simon Willison, 2024/07/15

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I am always interested in affordances. That's why with Simon Willison, "Every time I evaluate a new technology throughout my entire career I've had one question that I've wanted to answer: what can I build with this that I couldn't have built before?" Discovering things like Vosk, an open source library that includes models that can run speech recognition on your desktop, for example. This is to my mind the right way to approach something like Large Language Models (LLM). Sure, there's a ton of things they can't do. The same is true of everything! But how do we measure what they can do? We need a common dimension - and Willison describes a new industry standard called 'vibes'. These are measured in the LMSYS Chatbot Arena. Willison also discussed 'openly licensed' models (or 'open weights'). He also discusses some neat tricks - like Retrieval Augmented Generation (RAG) that can be used to help LLMs using 'wrapper code' (and in this way, makes sense of dangers like 'prompt injection'). "The key rule here is to never mix untrusted text—text from emails or that you've scraped from the web—with access to tools and access to private information." Also: the ChatGPT Code Interpreter. This is a brilliant talk, with stunning discoveries almost every other slide.

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It's really this thing that gets me.
Chris Coyier, 2024/07/15

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We all agree that websites should be accessible, but what's the best way to accomplish this? Chris Coyier considers two options: either building accessibility into the browser, or building it into the website. Both options have a cost, he suggests. The better option is to build it into browsers, since the reach would be universal, but this means charging the browser users who need the feature, and they tend not to have a lot of money. So companies have chosen to focus on making websites accessible, a much more expensive and less universal option (and one that needs to be backed by legislation), because people who create websites tend to have more money. Browsers are expensive to develop and maintain - there has been a lot of discussion about Mozilla's acquisition of an advertising company (and the addition of the Privacy Preserving Attribution API in its latest release (see this thread)). And yet they are essential public infrastructure - the sort of thing a public service should provide, so we don't have to depend on corporate sponsorship to (say) get the news. Or pay extra if we want to browse the web while blind. Image: Intuit.

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Calibrating The Theory of Model Mediated Measurement: Metrological Extension, Dimensional Analysis, and High Pressure Physics
Jalloh, Mahmoud, PhilSci-Archive, 2024/07/15

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When researchers study something through the "lens" of some theory, what are they doing? They are investigating one property by studying another property that some theory (or more specifically, model) says is covariant with it. For example, we don't study pressure directly; we use an instrument, such as a barometer, which varies as pressure varies. That's fine for physical theories where we can easily trace a causal relationship between the two, but what about, say, mental phenomena? A person can feel 'under pressure', but we can see the signs - sweaty forehead, for example. How do we know what we are measuring even exists? Or as Mahmoud Jalloh puts the question, "what if my measurement process is measuring something other than the intended measurand?" How do we calibrate for error? Jalloh's discussion applies to high-pressure physics, and he argues that two theories can calibrate against each other if they are measuring across the same dimension (aka the principle of dimensional homogeneity). But what even are we measuring when we measure mental pressure? We have things like the perceived stress scale (PSS), but what values do the numbers represent? All food for thought. This is a dense technical paper that can be a difficult read, but the first half especially is valuable if you are deeply interested in the concept. Image: DALL-E 2.

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Australian teachers' conceptualisations of wellbeing at work: A prototype analysis
Duyen T. Vo, Kelly-Ann Allen, Andrea Reupert, Teaching and Teacher Education, 2024/07/15

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According to this article, "Researchers from Monash University have surveyed 1000 primary and secondary teachers across the country and their results reveal what health and wellbeing measures educators consider essential at work." The result (13 page PDF) is a nice little list of things like safety, respect, autonomy and trust. It's important, I think, not to misconstrue what is being said here. There is no discussion of compensation or pay whatsoever, so the results apply only "to foster thriving educational environments for all teachers," as the authors write, and not "solving the teacher shortage crisis through recruiting and retaining teachers," as the Education Review summary suggests. It's a conceptual exercise; wellbeing is explicitly contrasted with 'fear' in the instructions. P.S. I like the use of the CRediT authorship contribution statement at the end, which makes it clear that the paper had one author (Duyen T. Vo) and two supervisors (Kelly-Ann Allen, Andrea Reupert) all of whom appear in the byline.

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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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