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Is The New York Times’ newsroom just a bunch of Ivy Leaguers? (Kinda, sorta.)
Joshua Benton, Nieman Lab, 2024/03/01


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"They're not a majority, based on a new look at education data, but they are wildly overrepresented." Of course they are. It's easy to see this trend across journalism, and indeed, across any discipline where position, power and money intersect. And despite what the Yale graduate in this Harvard-owned newsletter says, the answer is not simply "hire more non-Ivy  Leaguers". No, no. The answer is to understand what it is that creates so much opportunity for graduates from these universities. It's not better professors. It's not smarter students. It's not content knowledge. No, it's all about marketing, networking and self-promotion - and even more, it's about how these are done at the schools. Harvard, for example, actually has a journalism newsletter, in which this article is located. MIT Media Lab has students work in real-world environments on real-world problems. Stanford graduates create their enterprises while they're still students. Understand all this and you're closer to understanding what 'success' in higher education amounts to. (That's why I say, people evaluating learning technology by looking at test scores aren't even asking the right questions.)

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The Viability of Topic Modeling to Identify Participant Motivations for Enrolling in Online Professional Development
Heather Barker, Hollylynne Lee, Shaun Kellogg, Robin Anderson, Online Learning, 2024/03/01


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Here's the starting point: "Despite the advantages MOOCs offer, MOOCs have high dropout rates, and literature suggests this may be tied to participant motivation." The idea here (21 page PDF) is to use topic modeling to identify participant motivations for taking a MOOC, and in turn use this to predict whether they'll drop out. Three different methods were used, with varying results. The discussion mostly revolves around a comparison of the three approaches, and I'm sort of left wondering whether they ever answered the question they posed at the start, and ultimately "the goal of this study was to investigate how topic modeling can be used for analyzing qualitative data," to which the answer is, 'maybe'.

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Teacher in a Strange Land: “My Research is Better than Your Research” Wars
Nancy Flanagan, National Education Policy Center, 2024/03/01


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I am sympathetic with both sides in this debate and I am definitely sympathetic with someone who has done everything in a PhD but stalled because their committee thought their research proposal wasn't worth doing. Two two sides are, on the one hand, some teachers who conducted a limited trial in their school and got interesting results, and on the other hand researchers who are looking at broader questions with "equations and complex theoretical frameworks." And it doesn't matter to me whether or not the researchers are teachers or whether or not they get grants. To me, research boils down to: try something with the group you've got, see if it works, iterate, try again. It doesn't stop, there isn't a final answer, people looking from broad generalizations at the cognitive level are misunderstanding the subject, and people 'ranking' schools or instructional methods are just playing politics.

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The Leapfrog Hypothesis for AI Consciousness
Eric Schwitzgebel, The Splintered Mind, 2024/03/01


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Interesting hypothesis: " The first conscious AI systems will have rich and complex conscious intelligence, rather than simple conscious intelligence." Why? Well because although "AI systems are -- presumably! -- not yet meaningfully conscious, not yet sentient..." nonetheless "they do already far exceed all non-human animals in their capacity to explain the ironies of Hamlet and plan the formation of federally tax-exempt organizations... Let's see a frog try that!" What would it take? Well, that's trickier. Well, according to Eric Schwitzgebel, developers would need to "create rich and complex representations or intelligent behavioral capacities." Maybe - but I don't agree. I don't think consciousness depends on representation. Consciousness is experience, and when we experience things, we experience them directly, not representationally.

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AI Is Becoming an Integral Part of the Instructional Design Process
Philippa Hardman, Dr Phil's Newsletter, 2024/03/01


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It will probably take a while before this hits the academic journals, but if this research pans out, then (as they say) the horses have already left the AI barn. "A whopping 95.3% of the instructional designers interviewed said they use AI in their day to day work. Those who don't use AI cite access or permission issues as the primary reason that they haven't integrated AI into their process." Remember, though, 'using AI' isn't the same as 'using chatGPT'. Though in this case, it probably does: "When mapped to the ADDIE process, the breakdown of use cases goes as follows: Analysis: 5.5% of use cases; Design: 32.1%; Development: 53.2%; Implementation: 1.8%; Evaluation: 7.3%." That 50+% in development is probably all chatGPT. (There's an 8 page PDF available for download, if you pass through the spamwall, but don't bother, it's in huge text and contains less content than the article).

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Why Writing by Hand Is Better for Memory and Learning
Charlotte Hu, Scientific American, 2024/03/01


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I'm afraid people will draw the wrong lesson from this research. The wrong lesson, of course, is that people should take notes by hand. Sure, this will improve learning compared to the way they take notes by keyboard. But " people taking notes by computer were typing without thinking," according tot he researchers. "It's very tempting to type down everything that the lecturer is saying...  But when taking notes by hand... students have to actively pay attention to the incoming information and process it—prioritize it, consolidate it and try to relate it to things they've learned before." So - I suggest - the real lesson here is that people should learn to take better notes when typing, to work with the content as it's presented, and not merely try to replicate it.

Web: [Direct Link] [This Post]


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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