news (external)

Gobal Sustainable Development Goal (SDG) indicator 4.1.1a measures the proportion of kids in grades 2 and 3 "achieving at least a minimum proficiency level in (i) reading and (ii) mathematics, by sex." As reported here, data for this indicator has not been forthcoming and it faces deletion "because of a technical debate about measurement and a turf war between testing agencies." This UNESCO article "attempts to sketch the outline of a sustainable solution." It's an important indicator, because it measures where children "pass from the 'learning to read' to the 'reading to learn' stage". But it involves a series of tests, some of which only measure foundational skills (like phonological awareness) and not the overall objective (reading comprehension). This article recommends "a reporting scheme that relies on disaggregating or 'unpacking' the reporting of the minimum proficiency level by skill or subskill and to allow partial reporting if the assessment is not measuring the minimum proficiency level."

Consider the following research: I wonder what makes cars go forward. I get into 100 cars, press the accelerator in each car, and nothing happens. I conclude that pressing the accelerator does not make the car go. So what do you think? If you think this is pretty poor research, then consider the current study (65 page PDF), which looks at changing one variable - lower tuition fees - to see whether things move forward. They do not. "Relative to a synthetic match constructed from public universities in the Southeast, NC Promise did not affect first-year enrollment at the Promise institutions." There's some backpedaling in the discussion - "a need for comprehensive strategies that not only make college more affordable but also address other barriers" - but it feels to me that the five years of the program were really time wasted rather than an actual effort to effect change.

I saw this mentioned in the SoLiD discussion Matrix, and there are obvious links. This short post links to a longer document (66 page PDF) describing a distributed trust-based network. Now we've been down this path before, with things like Web of Trust (WoT). This is a bit different, with a basis in modern technologies like Distributed Identity (DID). And unlike Blockchain, it proposes a network of micro-ledgers, instead of a centralized ledger. I think, though, that schemes like this are putting the commercial cart before the relationship horse. We're still figuring how how to make distributed social networks work. We can't make the leap to a distributed contract network before we've even figured out how to talk to each other (without spam, harassment, disinformation, etc.).

I have to say that I'm not really feeling threatened by AI-authored content. But as Ben Dickson reports, Medium - which charges subscription fees for 'Membership' content - is struggling. Though its writers are prohibited from uploading AI-generated content, they have no real incentive not to, and Medium has no real way to detect it. According to Dickson, "business models that will work in the age of AI-generated content are those that directly connect content creators to consumers." Maybe. But we will have to get past the idea that they are 'content creators' and think of them as something else. For while we may 'create' content, that's hardly the half of it.

This is OECD's 'live' live repository of AI strategies & policies from more than 70 countries, territories and the EU. I didn't find the interface very appealing but you can download all the policies as a .csv document. I wanted to link to the source article from IBM where I found this (it came in an email newsletter) but it seems to have disappeared, though there's a copy here. What was really weird was that as I tried to find the original by searching for extracts (this is my go-to method for finding sources) I found them scattered through other IBM documents, suggesting that this article was formed by combining these other articles by some means.

Campus Technology reports on the founding of the Digital Education Council (DEC) "to address ed tech issues worldwide, including the impact of AI on education and work" by SuperCharger Ventures and a dozen or so business and management schools. DEC came out in March with one of the more puzzling manifestos I've seen, and there are a few more vague articles on the website (here's news: university leaders are concerned about negative impacts from AI). No RSS, naturally, but there's plenty of Google and Facebook tracking on the website.

This is a good article and I appreciate Neil Mosley's desire to engage with the argument in the article 'Online learning has all but destroyed the university experience' (from the Telegraph, and paywalled). The key point appears near its end: "more online learning in on-campus courses may lead to, or risk, students becoming isolated in their accommodation, thus preventing interaction and socialisation with peers and educators." Mosley walks a reasonable path in response, but then there's a turn two thirds of the way through, where he asks, "Is online learning doing enough to support healthy study habits?" We could answer the question either way, but the question isn't relevant. That's not the sort of "interaction and socialisation" that proponents of a traditional university education at the Telegraph are looking for.

This is an important (if self-serving) article that looks at how the development of foundation models in artificial intelligence will (once again) change the way we look at data. It's the latest transformation in a series that began with documents, then relational databases, graphs, vector databases, and now, foundation models. Now it's true that "the latest advancements in knowledge representation really do usher in a steep increase in technical sophistication and complexity." But the greatest skill will be demonstrated by those not lost in the complexity but those able to make these concepts accessible - at least at some level - to the people who need to work with the data. As for me - well, the learning never stops. This article doesn't make things easier, but it lays out the territory. If you're with me, have a go at it, follow the links, but be OK with not understanding it all (he's not trying to make it easy).

I have a subscription to Duolingo and it gives me feedback and tries to get me to continue my long-languishing Spanish lessons (I have no planned visits to any Spanish speaking areas and this might explain my lack of motivation). It has a cutesy little character unimaginatively called 'Duo' to try to make it like a friend. I can see that it could be like a friend, if it were better designed. Anyhow, this article interviews all of seven people (so few it actually names them all) and interviews 32. Compare this to "data from over 500 million Duolingo learners around the globe." I don't want to criticize these researchers in particular, as they are just doing what is expected of them in academia. But I ask of all academia, especially in the field of education: what are you doing? How is this helping? Why not just write some speculative fiction: wouldn't that at least be more interesting? Journal editors: are you being responsible when you request and select this sort of study for publication? I wish I could force the entire discipline to stop and reflect on its methods for a bit.

Nobody needs to convince me of the importance of mental health, and therefore, of the importance of mental health education in general. But this post really missed the point. Here's the main point: "Now, more than ever, a large-scale, preventive mental health approach is needed to promote student mental health and well-being." So "A mandatory mental health training would teach students easy-to-implement strategies to manage stress and solidify "mental health literacy" to improve knowledge of mental health." So many problems with this. First, throwing mandatory training to solve a problem almost never solves the problem. Second, mental health is something that all of society needs, not just students. And third, universities aren't exactly the institutions I would trust to offer mental health education. Let's put this properly where it belongs: as a health issue, to be addressed by public health care, for everyone (not just those privileged enough to pay tuition), managed by doctors, with support where needed and requested from other institutions.

If you look at the source of, say, Ben Werdmuller's blog, you'll see a script of the form 'type="application/ld+json"'. This is a Javascript Object Notation (JSON) representation of the entire blog post. The idea is to make it possible to link the post into a wider linked data network (LDN). You won't find a plugin for this just by searching WordPress (I tried; what you see is mostly SEO). But Doug Belshaw links into a video and download of just such a plugin so you can try it on your own WordPress blog. On the surface, it will look like nothing happened. But if you view your blog source, you'll see the linked data. You don't need to do anything fancy like upload it into GPT-4, but if you did, GPT-4 would find it useful. (P.S. There are various other schemes for doing the same thing - schema, open graph (og), twitter, etc).

This is a pretty good post and will help readers hone their intuitions about what a large language model (LLM) like chatGPT actually does. But I want to focus on one tiny little statement: "ChatGPT doesn't really 'know' anything. It has no self-awareness or consciousness." Whoa, whoa, whoa, wait a minute now. Since when does 'knowledge' consist of 'self-awareness' or even 'consciousness'? When we look at current and historical accounts of knowledge (such as the widely discussed definition of knowledge as 'justified true belief') the critical elements seem to be (a) an assertion that some proposition is true or false (ie., a belief), that is is true (eg. according to Tarski's theorem), and that there are grounds for our assertion (based on evidence, confirmation, or any number of other proposals). If you want to say consciousness or self-awareness are necessary, that's fine, but you also need to tell us what consciousness or self-awareness bring to the table. Via Alan Levine.

Alex Usher has a couple of interesting posts about student aid in Canada. Never one to shy away from a straw man, Usher devotes the first post to attacking unnamed critics arguing "student debt is skyrocketing". It's pretty hard to find anyone saying this, and where we see the assertion being made, as here by the CFS, it's about total debt, which continues to rise unabated. Usher avoids this discussion entirely. But more interesting is the present post, in which he projects significant student debt increases. The reasoning - and in this case, it's sound - is that allowable limits on student debt are being raised 42% this year. "The weekly limit just jumped from $350/week to $500/week." I think we both agree that increases in debt like this are unsustainable. But our solutions are, I think, quite different. (P.S. the story of fees in the U.S., illustrated, is completely different, and where most of the 'skyrocketing' talk is actually coming from. It is also unsustainable, only even more so). Image: Annie Surla / Nvidia Blog.

Helen Beetham is someone with whom I routinely disagree, which makes her a valuable foil for my thinking on education and artificial intelligence. In the current case, I think we have a common starting point: the idea of a simple concept of 'intelligence', as measured by (say) 'intelligence tests', is unhelpful, and very likely to lead to problematic and discrinminatory assessments of people and their potential. This was true before artificial intelligence became so prominent, and continues to be so. What follows in Beetham's post is a long list of ways the biases and prejudices of the people currently building AI are bad, but it is a discussion (to my mind) that needs more recommendations and less in the way of "we don't like these people". Image: Wikipedia.

According to this paper, a systemic review of 38 studies, "Adaptive learning technologies are closely related to learners' self-regulatory processes in individual and collaborative learning." The authors elaborate, "we identified the seven main objectives (feedback and scaffolding, self-regulatory skills and strategies, learning trajectories, collaborative learning processes, adaptation and regulation, self-assessment, and help-seeking behaviour) that the adaptive technology research has been focusing on." As an aside, I've long wondered about the assumptions behind the term 'self-regulation', which implies a corrective function, as opposed to, say, 'engagement' or 'initiation', and such, which suggest greater empowerment. This idea of learning as doing something you don't want to do (and hence requiring willpower and self-regulation) doesn't really sit well with me.

This story may well gain a lot of traction. But one wonders why we should draw any lessons from an AI initiative launched in 2011 and abandoned five years later. That's the story this article tells us, though, and we're supposed to conclude on that basis that AI is pretty limited. But as Ethan Mollick writes, "The current best estimates of the rate of improvement in Large Language Models show capabilities doubling ever 5 to 14 months." You can't base your predictions on what AI can or cannot do on what it's doing today, let alone ten years ago. No small number of populist writers will try to appear to readers' fears and emotions about AI by assuring them that they're still special and privileged. But AI is, in it's own way, a Copernican revolution.

This is just a short post consisting mostly of the image. Still, the image is useful enough and powerful enough to rate a mention here. It's an odd mix of privilege and inclusivity (this is an observation more than a criticism - you would only have things in your chart like 'supporting first-gen students' or 'inclusive approaches for international students + english learners' if you were creating this graphic from a perspective of privilege, and specifically, working for an English-language university (probably, based on the terminology, in the U.S.).

Do you sometimes feel like you're just being played? A communications app called Beeper came out of beta today, meaning anyone can use it, no invitation needed. And it also launched an Android app! It was enough to make Alan Levine say "This is cool!" But before we could even send our first message, Beeper was acquired by Automattic. And the fun ended that quickly. The people I feel for are those who helped in the beta testing. The Beeper home page still says "Beeper is an entirely independent software product, with no relationship to, or endorsement by, Apple, Google, Facebook, or any other supported chat networks." I guess they should remove that. Now we'll have to watch as the application is slowly depreciated in order to pay the debt created by the acquisition. Now Automattic isn't the worst place they could land. But when (not if) the company goes public, everything changes. (Having said all that, I still signed up for an account. Part of the job. My username on Beeper: @downes).

In my email today: "The International Science Council's CODATA Working Group on Data Ethics has been developing policy briefings responding to the UNESCO Recommendation on Open Science." Three such briefings are available for review and comment: Data Ethics and Research Integrity (provide feedback here); Data Ethics and Privacy (and feedback); and Data Ethics and Structural Inequities in Science (feedback).

So I would definitely have approached the subject matter differently, but the core thrust of the paper is sound, in my view. The main argument is found at the mid point of the paper in the section on reclaiming, recentring, and rehabilitating voices attributed to Felicitas Macgilchrist, who cites the "the 'shambles' of learning theory". She writes, "the EdTech industry makes all-encompassing promises, yet imagines students as versions of Pavlov's dogs... The equivalent would be something like '[App Name]: Behaviourist drills, but kind of fun for a few minutes'."  Reviewer number two (the reviews are helpfully appended to the paper) sums it best: " By embracing emotions, personal narratives, and the concept of practicescapes, the article advocates for a more holistic, heart-centre approach to learning design."