OLDaily

The Rare Home-Improvement Show That Spotlights Skilled Workers
Margaret Tucker, The Atlantic, 2019/05/28

I did a top-to-bottom renovation of my house in Moncton in 2016 before I sold it, converting it from an old house that wouldn't sell to a house that sold for $80,000 more than it was valued. New roof, new porch, wiring, plastering, painting. I contracted the work and did a lot of it myself. I won't say I was taught by 'This Old House', but I was taught by years of reno shows, YouTube videos, trial & error - and one high school carpentry class. Here's the photo proof. I was especially proud of the wainscotting. And of being able to learn and do skilled and physically demanding work on my own. We need more content that focuses on skilled workers, and less content that focuses on celebrities and stars. Not just in home and garden television, but everywhere. Because everybody should have this sort of independence.

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A Gentle Introduction to Object Recognition With Deep Learning
Jason Brownlee, Machine Learning Mastery, 2019/05/28

A while back I demonstrated how an AI API can be used to automatically generate an image caption. But how does the AI work? This article gives you a nice gentle overview of the development of such systems over the last five years. If you want to play with code, there are links at the bottom of the article to walk-through demos. But for the casual reader this article nicely lays out some different approaches and offers an accessible was to describe how they work.

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Ed-Tech Retro-Futurism and Learning Engineering
Matt Crosslin, EduGeek Journal, 2019/05/28

There's probably no hope of dissuading people from using the term 'learning engineering' - and if people really want to use the term for something new, that's fine. But as Matt Crosslin writes, "there seems to be a very prominent strain of learning engineer that are trying to make the case for 'learning engineering' replacing 'instructional design' / 'learning experience design' / etc or becoming the next evolution of those existing fields." Why do this? There are dozens (probably hundreds) of papers and presentations describing what is now being attributed to 'learning engineering'. "I am still not clear if some learning engineers are claiming to have preceeded ID, to be currently superseding ID, or to have been the first to do what they do in the Ed-Tech world before ID. If any of those three, then there are problems." Image: Towards Data Science.

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The Pursuit of Patterns in Educational Data Mining as a Threat to Student Privacy
Kyriaki H. Kyritsi, Vassilios Zorkadis, Elias C. Stavropoulos, Vassilios S. Verykios, Journal of Interactive Media in Education, 2019/05/28

I have often been assured that the data I submit on some survey or another will be stored anonymously. I always laugh and say, "everyone will know it's me." And it's true - it's not hard at all to pick my submission out from a crowd. It's usually one of a kind. It's this kind of risk that the study published here analyzes and quantifies. For example, if the only 24-year old male in the class failed, everyone knows who it was that failed. Or that the person who made six posts got a score of 6,5 (illustrated).This risk is typically left unanalyzed and not communicated to study participants. "The ‘trade-off’ between preserving privacy and preserving the value of information or preventing utility loss upon data anonymisation is a challenge, requires numerous data records and of course, analysts with certain skills.

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Digital Media’s impact on learning in daily life: a different view on eLearningusing means of videography
Otto Petrovic, Proceedings of the 2nd International Conference on Networking, Information Systems & Security, 2019/05/28

What makes this paper (9 page PDF) interesting is that it's based on "recorded video sequences of informal learning processes in the context of media usage, called ‘learning episodes’." The learning episodes were saved as screen-capture videos by the students themselves - "77 learners captured, annotated, and edited 373 learning episodes." Some additional episodes were captured by researchers. The objective was to capture digital media's 'alteration method', that is, "digital media’s influencing mechanism on learning in daily life." The outcomes are described as "create and delete" ("means of production of digital media are omnipresent."), "arrange and link", and "transmit and access". The outcomes show learners how important it is to associate resources from different sources, and to exerrcise a high degree of self-autonomy, while teachers should see the importance of merging the informal and formal learning contexts. The paper could have used an edit, but the content is good stuff.

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Mona Lisa frown: Machine learning brings old paintings and photos to life
Devin Coldewey, TechCrunch, 2019/05/28

As this article (with accompanying 5-minute video) notes, a "new paper by Samsung’s Moscow-based researchers, however, shows that using only a single image of a person’s face, a video can be generated of that face turning, speaking and making ordinary expressions — with convincing, though far from flawless, fidelity." So, for example, we can have (relatively convincing) video of the Mona Lisa having an animated conversation. Maybe she could be an art teacher.

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Learning Analytics beyond the LMS: Enabling Connected Learning via Open Source Analytics in “the wild”
Kirsty Kitto, Zak Waters, Simon Buckingham Shum, Mandy Lupton, Shane Dawson, George Siemens, Beyond LMS, 2019/05/28

This is quite a good report (55 page PDF) and worth reading in full. It came to my attention just today, though it's dated 2018. It's an outcome of the Beyond LMS project run by several universities in Australia. It doesn't mince words, and while it finds that learning analytics can be effective, they are brittle, context-specific, serve the wrong users, prone to misinterpretation and the subject of conflicting specifications. So, business as usual in the learning technology standards space. As the authors state, a more modular solution is necessary, a more flexible data structure is necessary, and a more open codebase is required (note that the report contains links to numerous GitHub repositories containing their own work, so kudos to them).

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