Stephen Downes

My first thought on reading the title was that the news does not have to fit a commercial for-profit model, and so entrepreneurs aren't always needed. I draw on a long-standing analogy with education, where this is much more clearly true. Ben Werdmuller makes the case through a descussion of news product design. "In most newsrooms, the Product lead needs to lead strategy, product, platform, technology, brand, design, and audience; they need to figure out how to build revenue into the offering; they need to be hyper-focused on the underlying needs of the people and communities they're addressing." This, though, is a broader role than we see in most digital operations. It needs "people with the right kind of prototype-driven, experimental mindset and a bias towards action." These, he says, are entrepreneurs, people who "aren't afraid to take big risks, have the cross-functional skills to execute, and can forge radically collaborative cultures that are centered on the needs of their communities." I see the point, but I'm stiull not buying it. This is a classically provider-consumer based model; that's why there's "big risks". When a community is building for itself, though, what we perceive as 'risk' looks completely different.

Phil Hill looks at Microsoft's Classroom offering, outlining what it does, what it doesn't do, and what may be Microsoft's strategy going forward. "For Big Tech," he writes, "an LMS can be a gateway drug: introduce students to an ecosystem of productivity and AI tools, and potentially keep them as users throughout their working lives. Could Microsoft Classroom push Google to become more aggressive with Classroom in higher ed?" Maybe. But Microsoft is going to have to be a lot easier to use for that to happen. I'm not talking about Word or other Office applications, which are excellent. Using Teams, though, or anything that starts with an institutional login can be a nightmare for people trying to work collaboratively.

On the one hand, online learning programs should be standardized to a certain degree to ensure they are usable and effective. On the other hand, academic faculty have long had a key role in course design and expect agency and autonomy when doing this work. There's a tension here, and that's what this article (14 page PDF) explores, defining bounded standardization "as a practical decision protocol for determining when a course-design element should be required, recommended as a default, or left to contextual faculty or programme choice." After all, "the strongest case for standardisation is not that every course should look or function the same. It is that predictable learner-facing architecture can reduce avoidable variation." There's a proposed test requiring institutions to justify consistency before creating requirements, and a set of four implementation conditions.

Normally I don't like to link to LinkedIn but I'll make an exception for Pierre Dillenbourg's post. Cognitive load theorists, he writes, "fought against demanding learning tasks, like giving learners a problem before showing them how to solve it." Now sometimes the very same people are warning against the use of AI because it makes learners passive. But, says Dillenbourg, "they're the ones who buried the idea that learners must be active... But no load, no learning."

Good article on the use of AI written from the perspective of someone who suffered a long-term (but fortunately temporary) disability. Having lost the use of their arm, they used AI to fill the physical gap. "The real question was not which tasks to keep or drop but which parts of the work were my own and which were the mechanisms I had used to perform it. Talking, ideating out loud, and thinking through my own voice remained mine." It wasn't always perfect; editing AI-writing can actually take longer than writing it yourself. And it means adapting. "The goal of using GenAI during recovery was not to overcome my physical limitation but to continue thriving as a scholar while working within it," writes Michael Cassens.

Definitely worth a read, this article (27 page PDF) introduces and then presents a chain letter of responses from women and gender fluid academics describing their experiences with AI. "These recurring tensions mirror the broader global context in which critical and feminist scholarship is under threat (Butler 2022). Insisting on collective and experiential knowledge production is also a political and ethical claim. Understanding GenAI in education requires attending to how people actually live with it, and to who is permitted to say so with authority."