OLDaily

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

It’s a question of order
Paul Kirschner, 3-Star Learning Experiences, 2024/04/17

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This short article references a 2022 paper that studies how the order of questions in a test impacts how well the test-takers do. "A perfectly logical test-taker should do equally well no matter the order of questions," writes the author, "but research shows that humans are influenced by the order." In particular, "students answered more... questions (correctly) when they began with easy questions compared to when they started with difficult ones." The relevant question to ask here is this: if the result depends so much on the order of the questions, what is it exactly that the test is measuring?

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A Phenomenal Theory of Grasping and Understanding
David Bourget, PhilPapers, 2024/04/17

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I often ask what it is we're doing when we're teaching and learning, that is, what counts as success? This paper offers some insight into the sort of question I have in mind. To 'learn' something is more than just to come to know that something is true. That's just memorization. No, as David Bourget would argue here, it's to grasp what is being taught. "It is one thing to believe something, and it is another to grasp it. For example, everyone knows that life is short, but most of us arguably do not fully grasp this fact." But what is it to 'grasp'? He argues, "we grasp to the extent that our thoughts are grounded in experience, whether occurrent or non-occurrent... , what we experience matters to how we reason because that is how we are wired: consciousness isn't a late addition to our minds; it is the
most central, causally potent form of mental activity." I think this argument works, overall. Image: Ding.

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A comprehensive exploration of artificial intelligence competence frameworks for educators: A critical review
Tamar Mikeladze, Paulien C. Meijer, Roald P. Verhoeff, European Journal of Education, 2024/04/17

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This paper (21 page PDF) is a review of papers proposing AI competence frameworks for teachers (CFT) and organizes them into five categories: integrating AI competencies in existing CFT; modelling new AI knowledge domains; process-driven; AI systems-driven; and competence level-driven. True to their field, the authors stress the need to theorize. "The empirical and design-based nature of AIED requires a solid theoretical foundation. The adoption of theoretical frameworks serves as a unifying force, fostering shared concepts and terminology among researchers and designers." But it's not clear there is (or is going to be) agreement on just what to theorize. This depends on what we want teachers to do, and as the authors note, "it is important to understand what kind of problems AI teachers' competencies will solve and what kind of solutions AI teachers' competencies convey."

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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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