OLDaily

Podcasting Equipment Setup and Software I use on the 10-Minute Teacher
Vicki Davis, Cool Cat Teacher Blog, 2018/01/03

I always appreciate article like this describing the why and how of some aspect of education technology. In this case it's Vicki Davis describing the tools and methods she uses to broadcast a regular podcast (I've always been tempted - I love audio - but it would take more time than I have in a week). Just for fun, as well: try to guess the sponsor link in the article - she discloses that she has a sponsor link, but doesn't tell us who the sponsor actually is (which breaks the spirit of the  Federal Trade Commission regulation she says she's following in the disclosure, I think).

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10 Reasons for Optimism About Ed Tech in 2018
Matthew Rascoff, Learning Innovation, 2018/01/03

This article combines some much-needed optimism about educational technology (which has been in short supply lately) with some useful links. There's the HAIL Storm Network, Tsugi and NGDLE, Authorea (built on top of GitHub), and closer to the author's home at Duke, the OSPRI Lab's open source education technology project. 

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Dude, you broke the future!
Charlie Stross, Charlie's Diary, 2018/01/03

This is the text of science fiction writer Charlie Stross's address to the 34th Chaos Communication Congress in Leipzig in December. The speech rambles a bit but there are interesting reflections on how to predict the future (the key is combining the 85 percept of trends that will continue as expected and the small percentage that leave you wondering what happened), the role of corproations in society, the question of what AI wants, and what went wrong with it all (his explanation: the "mistake was to fund the build-out of the public world wide web—as opposed to the earlier, government-funded corporate and academic internet—by monetizing eyeballs via advertising revenue."). 

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Online Markdown Converter For Open Educational Resources
George Williams, Chronicle of Higher Education, 2018/01/03

The story here (buried in the third and last paragraph of this short article) is that "the University of Oklahoma Libraries has made available a Pandoc-based, web-hosted, open-source Markdown Converter." The idea behind 'markdown' is that it's a way of writing text that can be formatten (into bold, paragraphs, lists, etc) without the use of computing code (like HTML or the languages used to define PDFs and MS-Word documents). It makes entering text into (some) web-based forms a lot easier. That's it. Meanwhile, I'm wondering why the author refers to Lincoln, Ryan and Konrad only by their first names while Alex Gil gets the full first-and-last name treatment. (Update: figured it out: Lincoln, Ryan and Konrad are regular Chronicle bloggers, while Alex Gil is not.)

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A news site gave would-be commenters a quiz. Here’s what happened.
2018/01/03

The Columbia Journalism Review is not above writing click-bait headlines, it seems (rememeber when clickbait headlines were the biggest problems in social media?). The idea has merit on first glance: make sure people have read the story before they can comment by asking them simple questions about what the story said. This did reduce the number of comments, but did not keep commenters on track. And critics point out that making it more difficult to engage with the story does not encourage people to engage with the story. When my high school English teacher used the same tactic on me I boycotted a year's worth of content quizzes.

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People Are Not Talking About Machine Learning Clickbait and Misinformation Nearly Enough
Mike Caulfield, Hapgood, 2018/01/03

"In short," writes Mike Caulfield, "the social media audience becomes one big training pool for your clickbait or disinfo machine." True. But even without social media, there will be no shortage of data for the machines. Consider, for example, the content from our learning management systems. Or our loyalty card programs. Or the telephone listings. There are issues with the input end - biased training data, for example - but the real problems are happening at the application end. That's when this data is used by machine learning algorithms to perpetuate stereotypes, create fake news, teach falsehoods, etc., and this can't be solved by the technology. Nor even by teaching people how to spot fake news. It's a social problem. It's a governance problem.

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