OLDaily

Big Tech Always Fails at Doing Radio
Matt Deegan, Matt on Audio, 2022/03/15

I think the broad generalization in the title is very much overstated, but there are still numerous good bits in this article. Like this: "If I was building radio from the ground up I would not be concentrating on 'anybody with a phone, a voice, and a love for music'," writes Matt Deegan. "Radio is not about the producer. It's about the listener. Great radio is focused on them." For example, radio "is the polar opposite of an app-driven culture. Why? Because it's essential to go where listeners are. You go to their party, you don't demand they come to yours." Some things here, I think, that education could learn.

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The Parable of the Overconfident Student -- and Why Academic Philosophy Still Favors the Socially Privileged
Eric Schwitzgebel, The Splintered Mind, 2022/03/15

We all know the type - the young and usually male student who sits at the front of the class questioning everything the professor says and projecting his own views into every topic, discussion and example. I may even have been one of those students! My apologies to everyone around me. But according to this article this expression of privilege translates into a significant academic advantage. "He gets practice asserting his philosophical views in an argumentative context... he receives customized expert feedback on his philosophical views... he engages his emotions and enhances his memory (and) he wins the support and encouragement of his professor." These are all good things, though. So the question isn't how to shut down the privileged student, but rather, how to extend this privilege to everyone in the class? But, as the article notes, this approach does work everywhere. " If a first-year chemistry student has strong, ignorant opinions about the electronegativity of fluorine, it won't go so well." So this form of elevated engagement needs to be tempered with an ability to sense what's open for discussion and what isn't.

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Neuro-symbolic AI brings us closer to machines with common sense
Ben Dickson, TechTalks, 2022/03/15

OK, I feel all this is wrong-headed, but I feel an obligation to share it with you anyway. This post summarizes a talk by Joshua Tenenbaum, who is focused on the question, ""How do we go beyond the idea of intelligence as recognizing patterns in data and approximating functions and more toward the idea of all the things the human mind does when you're modeling the world, explaining and understanding the things you're seeing." I think there's a big (and wrong) presumption that this is what the brain does. But many (probably most) people disagree with me, and would agree that "Our minds are built not just to see patterns in pixels and soundwaves but to understand the world through models." That's why they'd probably be comfortable with the idea of neuro-symbolic AI, or as Tenenbaum calls it, "the game engine in our head." Anyhow. Enjoy the paper.

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College students often don’t know when they’re learning
Jill Barshay, Hechinger Report, 2022/03/15

the main point here is that "learning by trying something yourself is superior to passively listening to lectures, especially in science", but that students feel they learn more in the lecture. I've certainly experienced the former; When I'm actually trying to create something or solve a problem, I'm far more likely to learn by trying it myself (though I might need someone to help me out as I work through it). "Sports and music instruction make this really clear. Watching [Roger] Federer play tennis can get you really excited about tennis, but it's not going to make you a great tennis player." The latter we see reflected in any number of studies and reports showing students prefer a 'traditional' and 'in-class' presentation of content. Image: Harvard Gazette.

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Does Self-directed Learning Readiness Predict Undergraduate Students’ Instructional Preferences?
Brandon J. Justus, Shayna A. Rusticus, Brittney L. P. Stobbe, The Canadian Journal for the Scholarship of Teaching and Learning, 2022/03/15

This paper considers whether a student's self-directed learning readiness (SDLR) score, which "looks at the attitudes, abilities, and personality characteristics necessary for self-directed learning", is predictive of a student's classroom preference style (knowledge construction, teacher direction, cooperative learning, and passive learning). You might think so, and an earlier study suggested it would, but this study didn't really find a correlation. "These results seem to suggest that a students' level of SDL is generally not related to their preferences for  teaching  style."

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A Data-First Approach to Learning Real-World Statistical Modeling
Luke Bornn, Jacob Mortensen, Daria Ahrensmeier, Canadian Journal for the Scholarship of Teaching and Learning, 2022/03/15

This is an interesting approach featuring a "design for an upper-level undergraduate statistics course structured around data rather than methods. The course is designed around curated datasets to reflect real-world data science practice and engages students in experiential and peer learning using (a) data science competition platform." There's detailed discussion of the course, first launched at Harvard in 2014, the data competition tool, Kaggle, and of student responses to the process. But note: "the  course  requires  an  instructor  with  a  broad  base  of  knowledge in statistical models, as well as experience applying these methods to real data."

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