OLDaily

AI/ML in EdTech: The Miracle, The Grind, and the Wall
Michael Feldstein, eLiterate, 2022/10/05

This is a nice set of metaphors to illustrate the deployment of artificial intelligence (AI) in education. The 'miracle' is, of course, the "mind-blowing demos with these tools." We'e been having a lot of that recently. The 'grind' is the work it takes behind the scenes to produce these miracles. I cover this in my ethics course, outlining the decisions we make. It's not just writing software and collecting data. Finally, the 'wall' is, according to Feldstein, "the limit of what your tech can do for you." There are different ways of reading this. One way is to see it as the limit of what current tech can accomplish, and those are the examples Feldstein offers. Another way is the limit of what any tech can accomplish, which is what Feldstein seems to suggest he's talking about. Another way is to define the limit as whatever we can't imagine tech can do, which is what I think Feldstein is actually describing.

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Education at a Glance 2022
OECD, 2022/10/05

This report (42 page PDF) gathers educational statistics for OECD nations and reports on educational attainment, access, spending, and organization (including teacher salaries). It's particularly relevant this year as we recover from the pandemic, and it notes "the pandemic forced countries to adopt solutions for digital teaching and learning to compensate for periods when in-person lessons were limited or not possible at all. Although many of these solutions were implemented as emergency measures, they have proved valuable beyond periods of remote learning." I'm sure people will pore over the data, but my main takeaway is that most of the national averages (ending, salaries, etc) obfuscate between public and private spending, and this would go a long way toward explaining some of the large inequities observed in some countries. And, as always, it wold be preferable to have a global survey, not just an arbitrary selection of wealthier nations.

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Entangled Pedagogy
Peter Skillen, The Construction Zone, 2022/10/05

This is a really short article but it makes a really important point. "'Pedagogy Before Technology' is a well-intentioned, yet naive, perspective. This 'pedagogy first' stance ignores the undeniable interactions and 'entanglement' of ourselves with our environment. I have written previously that it is about the tools." Skillen also links to a related paper for those interested in these issues in the Physical Education domain: Digital technology and teacher digital competency in physical education: a holistic view of teacher and student perspectives .

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Promoting the full potential of Open Educational Resources (OER) in the Lebanese educational community
Joumana Assaf, Loubna Nehmeh, Siham Antoun, Pedagogical Research, 2022/10/05

This paper (17 page PDF) surveys instructors in Lebanon on the state of their knowledge of and practice using open educational resources (OER). From my perspective, the results are consistent with what we see in similar countries around the world: teachers are increasingly using online resources, including OER, to supplement traditional learning materials, searching especially for videos, and are willing to share their own work, but question the credibility of OER in general and are not clear about the concept of OER, and especially copyright and licensing.

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The use and application of learning theory in learning analytics: a scoping review
Mohammad Khalil, Paul Prinsloo, Sharon Slade, Journal of Computing in Higher Education, 2022/10/05

The rise of learning analytics has opened anew the question of theory versus data in research. But in a field like education where there is no real agreement on theory, "it is not clear which theories inform our research and praxis... even the notion of 'learning theory' is less definite than might first be thought." Or so it seems; that's what this paper investigates. It becomes an exercise in how you name things and how you count things. The authors note "the dominance of Self-Regulated Learning (SRL) in informing learning analytics research," but note "theories arising from the broader family of Cognitivism are Cognitive Load Theory, Cognitive Theory, Meta-cognition, and Distributed Cognition," which were counted separately. It's a good discussion, especially the 'implications' section near the end, but as the authors note, "we cannot use these findings to generalize to the whole field of learning analytics," due to the unrepresentative nature of the sample.

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