OLDaily

Online learning in 2020: perfect vision in the Year of the Rat
Tony Bates, Online learning and distance education resources, 2020/01/01

Tony Bates offers three major prediction sets: first, that we may begin to see more online program managers (OPM) in Canada as the companies begin to lobby provincial governments; second, "we will certainly see a push from several right-leaning provincial governments in 2020 for better ‘metrics’ from universities and colleges, such as measures of ‘output’ (e.g. degree completion rates, graduate employment) as well as ‘input’ (finances, etc.)"; and third, while we may see more moves toward the use of learning analytics, the main issue here is measurement. And he points out, "it is just not good enough now for academics to sit back and say we can do this but AI can’t. Where’s the evidence?"

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Exploring Minds: Modes of Modelling and Simulation in Artificial Intelligence
Hajo Greif, Perspectives on Science, 2020/01/01

Ignoring the title and main purpose of the paper (29 page PDF) for a moment, I encourage people to look at the first section for a really useful discussion of the various types of models that have been proposed through the years. Models might "bear observable and pre-theoretic similarities to their target systems." Or maybe they "are structures that express interpretations of a formal theory." Or maybe they " are structures that bear a formally defined relation of isomorphism to their target system," as Bas van Fraassen suggested in 1980. Whatever your definition (semantic, syntactic, or other) "models are epistemically more central to science than theories."

All of this becomes really important if you think of minds as being (or containing) models of knowledge, the world, or whatever, whether they are representations, reflections or whatever. This in many ways is the core element of constructivism, as it recognizes the central role played by models, and focuses on ways to build them and manipulate them (as opposed to instructionist theories, which simply stack fact upon fact until you have a big pile of knowledge). Anyhow, what makes modern AI (and modern theories of learning) different (in my view) is that some of the models they propose are not representational; the models are connective structures that may produce a characteristic output (ie., recognition) but not an interpretation either of phenomena nor of formal theory. Image: Kotu & Deshpande.

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Negativity in Massive Online Open Courses: Impacts on Learning and Teaching and How Instructional Teams May Be Able to Address It
Denise Comer, Ryan Baker, Yuan Wang, InSight : A Journal of Scholarly Teaching, Paperity, 2020/01/01

There is "a considerable amount of negativity in MOOCs," write the authors, "emerging from learners on discussion forums and through peer assessment, from disciplinary colleagues and from public discourse around MOOCs." This article (22 page PDF) looks to analyze it and maybe quantify it a bit. There are two case studies, and these help identify types of negativity (eg., toward the instructor, toward the platform) and to offer ways to anticipate[ate and perhaps mitigate its effects.

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Apps that protect your digital rights
Blockstack, 2020/01/01

I'm still exploring Blockstack, which appears to have developed a fairly large ecosystem of applications and services (which it won't let you see until you create an identity). But the idea is that it provides access to applications that allow you to create data and store it wherever you want, all connected and protected by a blockchain. As the website says, "Blockstack ID provides user-controlled login and storage that enable you to take back control of your identity and data." There's a blogging app, Sigle, that takes you step by step through the process. It includes a way to define your own storage. Yes, it's open source.

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