Stephen Downes

Alan Levine shares his experience with a "sleazy outfit" called WebinarTV that surreptitiously records what it calls public webinars and puts them up on its website. As Levine explains, "Just because you set up registration, it does not protect your webinar. You actually have to do extra work of approving registrations or verifying attendees, adding special links/passcodes to 'protect' your events from being taken by WebinarTV. You have to create barriers of access for event participation." How are they doing this? "Most people will assume that they are somehow registering bots to attend events and record, like notetaking ones. This is not what's happening, IMHO," says Levine. This would mean they're accessing the recordings somehow directly from Zoom. But Zoom says WebinarTV "accesses meetings using links that have been shared publicly, then records the sessions using browser extension or 'other tools.'" See also this report from CyberAlberta.

In a LinkedIn article, Dan Meyer proclaimed the 'death' of Khanmigo. Not death in the sense of going away, but in the sense thjat nobody is using it. "For a lot of students, it was a non-event," Khan told Matt Barnum last week in Chalkbeat, referring to Khanmigo's release three years ago. "They just didn't use it much" This article examines that proposition. Why does the software go unused? "The recurring blind spot (is) EdTech's promises of frictionless scale. EdTech repeatedly promises low-cost, scalable transformation - but often repackages old models without solving engagement or economics." The argument here is that in order to scale a technology company needs "sustained marketing investment, institutional credibility, student support infrastructure, and retention strategies that go well beyond content delivery." All true - but as Glenda Morgan notes, the real issue is that these companies repackage the old model over and over again. See also this discussion in Learning Engineering.

This article points to a report (58 page PDF) addressing a variety of issues facing "Wealthy selective private universities such as Yale" such as "cost, admissions, political homogeneity, self censorship, (and) grade inflation." According to the report, "universities exist to preserve, create, and share knowledge." It recommends a return to this foundational principle and suggest it forms the basis for all the recommendations in the report, but that relationship is hard to see. Indeed, from where I sit, there's noting in this foundational principle that recommends a path of being wealthy, selective or private, but that is essentially what Yale seeks to preserve. Don't get me wrong: the discussion is good, up to the point of the recommendations (which go off the rails and on their own tangent starting at recommendation 10 ('recenter the classroom')). Jeff Jarvis is unsparing in his criticism, saying it "prostrates itself before the cancel-culture trope," which it does, but the greater fault is that it never questions the fundamental elitism on which Yale is founded, and which lies at the heart of the mistrust it faces today.

The title of this post may as well be switched around: what does the public owe universities? That's the tenor of the article, even as author Ted Hewitt in the same breath says "the fundamental role of the university, within its broader societal and community context, is, in my view, seriously at risk, along with our own liberal democracy." He recommends three things: protection of academic freedom, university leaders to maintain an open dialogue with the public, and resourcing. Now sure, the example south of the border is nothing to be emulated. But the response of the university system can't be "support us or the bunny gets it." What the system needs to do, in my opinion, is what it utterly failed to do in the U.S. - enable full participation and success in higher education regardless of socio-economic status. Universities need to directly benefit the entire community. That, to me, looks very different from what we have today. It's certainly not being offered by Hewitt in this article.

I said the other day that another word for 'cognitive offloading' might be 'trust'. We don't manually check everything the AI does because we trust it to do (more or less) the right thing. So the title of this post caught my eye; Josh Brake summarizes and to a degree endorses Stephen M. R. Covey's book The Speed of Trust. "Covey decomposes trust into two main elements: character and competence... character, he argues, is composed of integrity and intent... competence can similarly be decomposed into two pieces, capability and results." These all together represent "a strong foundation of character" that ought to be instilled in students, suggests Brake. But is it a good account of trust? I don't think so, because truth is a much broader concept. We can trust things that are not human and do not possess virtue or intent: trust the math, trust the process, trust the ice, trust in the future. Trust isn't a property of the thing being trusted, it is a willingness on our side to grant certain expectations to it regarding the outcome.

This is an introduction to a paper, the full text of which is found here. Michael Feldstein has alo provided some AI structures that both help explain what the paper says and test the predictions offered in the paper. I didn't use the AI components, but I did read the intro post and the paper as a whole, which was well worth the effort. It defies summarization in a short post such as this, but here goes: transformer-based AI (such as ChatGPT) learn complex and apparently rule-based systems (such as language or chess) by preserving distinctions that have predictive import in a given context, and discarding the rest. Feldstein calls this the conservation of predictive meaning (CPM) theory. My assessment is that he is not wrong. I say it that way because I would word things a bit differently and draw slightly different conclusions. What he calls 'distinctions' I would call 'patterns'. What he calls "a general mechanism to reduce predictive surprise" I would call 'salience'. I would not say language learners are "like effective cryptographers", nor would I say they "decode what has been communicated." Overall, though, I think he is on the right track.