Knowledge is recognition, but what leads to greater skill in recognition. This post considers that question. " Pattern recognition depends on the ability to see what is the same and the ability to see what is different. Further, it depends on being able to make connections between different types of information and on being able to apply transformations to different types of data... Pattern recognition skills can be built up by actively working with patterns of different types. There are several approaches to this. The six modular operators help one work with many basic organizational patterns (split, substitute, exclude, augment, invert, port)." Interesting. Worth noting.
Paul A. Kirschner and Mirjam Neelen aren't too shy to accuse people of being eduquacks, and they base this assessment on their own fidelity to what they call "evidence-informed learning design". They're not wrong, but they're not exactly right either. To a degree they recognize the difficulty in our field: it "doesn’t usually deliver the quality of evidence that clinical practice does. This is simply because we’re dealing with so many variables that are extremely hard to (all) control. Literally, what worked with a class today at 9 AM won’t necessarily have the same effects on a different class at 3 PM." True. But even worse, while there are generally accepted accounts of what might be called 'healthy', our views on what constitutes 'educated' are very different. And because of this, it becomes very difficult to compare evidence from one theory against another; they are, literally, incommensurate.
This is a really good piece of advice that, so far as I know, doesn't show up in a traditional educational curriculum anywhere. The advice is simple: don't believe everything you think. That voice inside your head sometimes lies, sometimes fools itself, and is sometimes simply wrong. This article talks about overconfidence bias but the lesson applies to underconfidence as well - that voice may be saying you can't do it, but that voice could be wrong. That voice could be saying other people are so much better than you, but that voice doesn't know any more than you do. When you think something - think again. Subject your own thoughts to a sober second opinion. Trust yourself - but verify.
Why would Microsoft buy GitHub? Anil Dash looks at "the cost of acquiring developers for a platform" as one explanation and suggests that "the far greater value comes from radically increasing the number of people who can create software, while improving the quality of software." Both are good reasons but my explanation is a bit different. It's this: Microsoft has finally acquired its social network technology, so it can challenge Facebook and Twitter, but crucially, it's also a distributed consensus mechanism for creating works collaboratively. Git is a directed acyclic graph (DAG) that has been used and tested over time. It creates an ordering of contents, and also creates a way for contents to converge with each other. This is really important, and in my view if properly applied gives Microsoft the core technology it needs to compete in social networks - and more.
ISTE - the International Society for Technology in Education - is the largest ed tech conference in the United States, and this week it has announced its intention to become something more. There are two major announcements: first, a set of "new standards for education leaders, which focus on equity, digital citizenship, team and systems building, continuous improvement and professional growth, the organization announced," and second, a partnership with D2L to create something called ISTE-U, which will be a professional learning hub for ISTE members. A number of courses are listed, many being developed in partnership with organizations like Google. The courses themselves cost money and "are eligible for graduate-level credit at an additional fee ... at Dominican University of California."
The set of five AIs had a lot of time to practice, and this made all the difference. " By using a huge stack of 256 graphics processing units (GPUs) with 128,000 processing cores, the researchers were able to speed up the AI’s gameplay so that they learned from the equivalent of 180 years of gameplay for every day it trained. One version of the bots were trained for four weeks, meaning they played more than 5,000 years of the game." That kind of practice will give you some skills, even if you aren't working with the biggest brain.
This is a quick summary of some recent research from Lisa Feldman Barrett on emotions. According to Barrett, there aren't distinct emotions (like anger, sadness or happiness). Rather, what we have is "a survival system that evaluates our surroundings to create a unique emotional landscape." According to the article, "The thing you call anger isn’t a distinctly programmed thing, but it’s a concise information point, and it gets updated by each new experience." It's a primitive prediction system. "The seeming irrationality of a well-tuned emotional system, within the right context, can fill in gaps that reason misses."
This is a back-and-forth between Athabasca University and University Affairs magazine. In the original “Online learning isn’t as inclusive as you may think,” University Affairs authors Erin Clow and Klodiana Kolomitro argue that in online learning things like netiquette are set by the instructor, while "community guidelines in a 'traditional' in-person classroom are often set through a collaborative process where both students and faculty are actively engaged." I have never actually seen that in an in-person classroom, but that's what they say. Anyhow, the Athabasca University authors reply that "Virtual learning environments have continued to grow over the last decade and what may have been considered difficult before has now changed."
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Copyright 2018 Stephen Downes Contact: firstname.lastname@example.orgThis work is licensed under a Creative Commons License.