OLDaily

5Rs for Open Pedagogy
Rajiv Jhangiani, 2019/05/07

They aren't the 5Rs you're probably thinking of. Here they are (quoted, paraphrased):

• Respect for the agency of students and creators
• Reciprocate by sharing resources, practices, and ideas
• Risk should not be ignored or glossed over
• Reach involves having an impact that extends well beyond the classroom
• Resist against the commodification of learning, surveillance capitalism, the neoliberal university, etc.

These are pretty good. I can get behind these. They're just as important as the other 5Rs. Related: Beyond Free: A social justice vision for open education.

Web: [Direct Link] [This Post]

Wiley to Acquire Knewton Assets
Rhea Kelly, Campus Technology, 2019/05/07

Remember Knewton? For a while it was touted as the model for learning analytics and adaptive learning for the future. Then it became, well, obscure. And today we read that Wiley "today announced it will purchase the assets of adaptive learning company Knewton." Assets. As in, what's left after a company fails. Read the history of Knewton as seen through the pages of OLDaily.

Web: [Direct Link] [This Post]

The Open Textbook Toolkit: Developing a New Narrative for OER Support
Mira Waller, Will Cross, Erica Hayes, 2019/05/07

This paper did not, as I had hoped, introduce an open textbook toolkit (except as a project for which they authors are preparing). Rather, it outline some of the research undertaken to determine what an open textbook toolkit would need to support. The focus is on materials for university psychology courses. Overall, the study replicates the earlier Babson study results, in essence, "the most significant barrier to wider (faculty) adoption of OER remains a faculty perception of the time and effort required to find and evaluate it.”

Web: [Direct Link] [This Post]

Nightmare Images Created by Monkey Brains Solve a Mystery About How We See
Yasmin Tayag, Inverse, 2019/05/07

When we look at an image, a set of interconnected neurons will fire. These, collectively, constitute what we are 'recognizing' about the image. But what does each individual neuron 'recognize' - that is, what sort of image is that particular neuron attuned to? The natural inclination is to say it's faces, or textures, or shapes - but no. Using a set of autogenerated images, researchers determined what an individual neuron reacts most to, and it's some sort of Gothic abstraction (pictured). "Experience, for one, must play a role in shaping the neuron’s preference ... yet, since the neurons didn’t evolve images of faces as we know them, perhaps their so-called vocabulary is looser than we thought, or perhaps it is not even fixed." The full paper is a pretty tough read, but this summary is a lot more accessible.

Web: [Direct Link] [This Post]

Distributed consensus revised – Part I
Adrian Colyer, The Morning Paper, 2019/05/07

This post takes you deep into the weeds of consensus systems, but it is well and clearly summarized by Adrian Colyer (who is really good at this). It's the first part of a PhD thesis by Heidi Howard on consensus algorithms. The challenge overall is to distinguish between properties that are essential to consensus algorithms, and properties that represent design choices. This would define the minimum criteria needed for an interconnected network to agree on a shared value even if parts of the network are subject to failure. This first part focuses on the classic Paxos algorithm (Colyer links back to part two of a previous ten-part series on consensus (all of this can be understood by anybody, but you have to take the time to step carefully through each iteration).

Web: [Direct Link] [This Post]

The Limitations of Language Apps
Jason Kottke, kottke.org, 2019/05/07

This relates to the debate between instructivist and inquiry-based learning, mentioned here today. The gist of this article, based on a NY Times article, is that language learning apps will help you learn a language, but only to a certain point. After that, instruction won't help; you need practice speaking the language in a much less structured manner with native speakers. "Tandem is one such service... other sites that help connect you with native speakers are Verbling and Italki, and HelloTalk." I think this is true generally. Instruction will get you to a certain level of knowledge very quickly (and naturally, that's where all the studies are focused), but if you want to become fluent in a discipline, instruction won't be sufficient (and if you've come to depend on instruction in order to learn, it might actually be harmful, because when you eventually need it, you won't know how to learn on your own).

Web: [Direct Link] [This Post]

Taking the inquiry out of Inquiry Maths
Andrew Blair, Inquiry Maths, 2019/05/07

This pair of articles illustrates quite nicely the debate between two very different approaches, the one based on the instructivist paradigm, the other based on the inquiry-based paradigm. I read Andrew Blair's first, but you can read the post he replies to, 'Teaching an Inquiry Maths Problem', by Naveen Rizvi. My preference is for the inquiry-based model, but that isn't the point here. Rather, it's that (as Blair states) the two approaches actually constitute two very different subjects that use the same subject matter. One - the instructivist approach - teaches mathematics as deductive and procedural, while the other - the inquiry approach - teaches it as inductive and experimental. One is based on logic and rules, the other is based on pattern recognition. If you just want to do math, then the instructivist approach will work fine. But if you want to be a mathematician, then you need the inquiry method.

Web: [Direct Link] [This Post]