OLDaily

The Pragmatic Theory of Truth
John Capps, Stanford Encyclopedia of Philosophy, 2019/03/25

While most educators know John Dewey as one of the founders of progressive education, in the wider world he is known (along with William James and Charles Sanders Pierce) as one of the three leading lights of pragmatism, and in particular, the pragmatic theory of truth. This article, just posted in the SEP, outlines that philosophy. "By focusing on the practical dimension of having true beliefs, Peirce plays down the significance of more theoretical questions about the nature of truth. In particular, Peirce is skeptical that the correspondence theory of truth—roughly, the idea that true beliefs correspond to reality—has much useful to say about the concept of truth." The article as a whole leans toward a positivist interpretation of pragmatism, equating it in places to verificationism, but I think that my be too strong a reading of the pragmatists.

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Democratic-erosion.com: an Open Pedagogy network
Gardner Campbell, 2019/03/25

Gardner Campbell points readers toward this interesting project called Democratic Erosion. It's essentially a network that has gathered around a common co-created curriculum on the topic. Here's the curriculum (which has a number of articles well worth a read). There are different ways to join the network but the main way is to "Teach a full semester on democratic erosion." Campbell's post includes a video interview with he Brown University professor who started the course, Rob Blair.

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Remixing the Open Logic Text
Justin Weinberg, Daily Nous, 2019/03/25

According to this article, the Open Logic Project is "an open-source, collaborative logic text that has several nice features. One is that the material is modular: it can be remixed into individual open-source texts on specialized subjects. There are now a few examples of this."  For examples see the Project Builds and there are some preliminary instructions here.

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Don’t Pee on My Leg and Call it Science!
Gary Stager, Stager-to-Go, 2019/03/25

I have to say, Gary Stager is not wrong here: " Social media and the nonsense masquerading as education journalism have become inundated with a flaming brown paper bag full of articles out to prove that phonics and penmanship instruction are crucial 21stCentury skills, class size does not matter, constructivism is a failed pedagogical strategy, there are no learning styles, not everyone “needs to code,” all kids need to be above the norm, and that standardized testing is objective, reliable, and valid... Free advice: Forbes, the McKinsey Group, anyone associated with Clayton Christensen, TED Talks and EdSurge are not credible sources on education reform, pedagogy, or learning theory even if they accidentally confirm our own biases once in a while. They are libertarian hacks hell-bent on dismantling public education."

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Open Pedagogy – A three day seminar at Digital Pedagogy Lab
Dave Cormier, Dave’s Educational Blog, 2019/03/25

I'm sure this description of his open pedagogy workshop will have people lined up at Dave Cormier's door, and for good reason. I'm sure it's an excellent experience. I can't hlp but notice there's no tech more complex that scissors and tape used in the workshop. That's one way to make sure you know the tech will work. I really have mixed feelings about zero-tech workshops on tech subjects like digital pedagogy. The medium is the message, and the main message being sent is that the tech can't be trusted.

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Mathematics for Machine Learning
Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong, Cambridge University Press, 2019/03/25

There are many many reasons why I would recommend this book (421 page PDF). But what makes me link to it here is the simple introductory paragraph on page 12: "The goal of machine learning is to design general-purpose  methodologies  to  extract  valuable  patterns  from  data... To achieve this goal, we design that are typically related to the process that generates data... Learning can be understood as a way to automatically find patterns and structure in data by optimizing the parameters of the model." Another 409 pages explaining this concept follow. Not light reading. This Reddit thread has some other suggestions as well.

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