OLDaily

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

Data Engineering in the Age of AI
Andy Kwan, O'Reilly Media, 2025/11/11

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Data engineers are in the unusual position of not only being threatened with replacement by AI, but also of being the people responsible for ensuring the reach and reliability of AI. So their role isn't disappearing just yet, according to this article. "The next generation of AI systems requires real-time context and responsive pipelines that support autonomous decisions across distributed systems, well beyond traditional data pipelines that can only support batch-trained models or power reports." Quite right. I would not be surprised to learn that there's a "React for AI input" in a pitch deck out there somewhere for a system that sends real-time updates to an AI context. Andy Kwan reflects, "While data engineers are responsible for keeping up with these innovations, that can be easier said than done, due to steep learning curves and the time required to truly upskill in something versus AI's perpetual wheel of change." 

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Building a standalone bookmarks web application
D'Arcy Norman, 2025/11/11

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I have't tried D'Arcy Norman's application, though it's on my list. What is really interesting, though, is not what he made (though it's quite useful) but how he made it. "The process of vibecoding (gag) this thing went pretty well. To be transparent, it was definitely not a one-shot vibecoding thing. It took 46 sessions spread over 3 weeks - 237 'turns' of going back-and-forth to get the application to this point. It's like working with a novice intern that can kinda-sorta do the thing, with enough guidance." That's similar to my own experience working with AI to write software, l except that in my case I worked alongside AI on the code itself, more like pair programming than working with an intern.

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A Guide to AI in Schools: Perspectives for the Perplexed
Julie M. Smith, Jesse Dukes, Josh Sheldon, Manee Ngozi Nnamani, Natasha Esteves, Justin Reich, MIT Teaching Systems Lab, Institute for Advancing Computing Education, 2025/11/11

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In the Chronicle last week (paywalled, but you can find it in the archive at A70mF) MIT's Justin Reich argued that we should 'stop pretending we know how to teach AI'. This perspective is reflected in this guide, but instead of then stopping at page two, it proceed through the 56 page PDF to pass along a lot of what can only be called 'folk knowledge' about AI, based on "over 90 interviews with teachers, school administrators, and students about the impact of AI on education." To me it felt like reading stuff like "we don't know whether monsters eat children, but here are some thoughts on that." The report includes discussions of AI ethics, its impact on students and teachers, how to create AI policies, how do decide whether to allow AI use, and similar commentary of the sort you would get reading discussion boards and social media. To be fair, there's a good set of resources listed near the end of the report, but it isn't clear these were used to inform it.

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This is Why Cycling is Dangerous in America
Not Just Bikes, YouTube, 2025/11/11

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This is a remarkable hour-and-a-half video from one of my go-to channels, Not Just Bikes. The video is a detailed take-down of 'vehicular cycling' as advocated by John Forester. According to Forester, cyclists should act like cars, and bike infrastructure, such as bike lanes, is more dangerous than cycling in traffic. I'm including it here because it's a textbook example of the use of reason and research in support of argumentation (and, to be honest, as a response to our provincial government's very misguided campaign against bike infrastructure).

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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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