by Stephen Downes
Mar 27, 2017
This is an argument that can't be ignored. It runs as follows: OER textbookss address the cost of higher education, and while cost is a significant problem, the low completion rate is an even more significant problem. Part of the reason for the low completion rate is poor learning strategy, a strategy that is entrenched with existing (and now OER) textbooks. Compare that to what paid learning materials provide: activities, interactivity, analytics, and more. So we should continue to pay for learning resources. It's a lovely argument and Robert S. Feldman should be commended.
But. First, neither publishers nor professors were not prepared to budge from the textbook model until free textbooks came online. Moreover, only some OERs are textbooks; the vast majority are learning resources that are out in front of publishers in addressing real learning needs and challenges. Finally, many features of progressive education - interactivity, constructionism, etc. - really work only with open learning resources. If we drop support for OER we lose all this, and we lose the main force for innovation in our field.
When I spoke at the London School of Economics a couple years ago, part of my talk was an extended criticism of the use of models in learning design and analysis. "The real issue isn’t algorithms, it’s models. Models are what you get when you feed data to an algorithm and ask it to make predictions. As (Cathy) O’Neil puts it, 'Models are opinions embedded in mathematics.'" This article is an extended discussion of the problem stated much more cogently than my presentation. "It's E Pluribus Unum reversed: models make many out of one, pigeonholing each of us as members of groups about whom generalizations -- often punitive ones (such as variable pricing) can be made.
A change in the way the 2015 PISA tests were administered may have resulted in changes in the outcome. “It remains possible that a particular group of students – such as students scoring [high marks] in mathematics on paper in Korea and Hong Kong – found it more difficult than [students with the same marks] in the remaining countries to perform at the same level on the computer-delivered tasks.”
Last week the U.S. Congress made moves to allow internet service providers (ISP) to track their customers. This is a lot harder to block than Facebook or Google; you can't use 'do not track' or anonymized browsing. Even encrypting your data still allows them to see where you go. As this story explains, there are really only two ways to stop ISPs from tracking your internet activities: route your traffic through a VPN, or use Tor. With a VPN, though, you're simply trusting a different host not to track. Tor, meanwhile, is effective - but now you may be flagged as a security risk.
I hear this sort of sentiment a lot, and also with respect to learning resource quality as well. The idea is to be sure you're depending on authoritative sources, or at the very least, reliable sources. But how is this established. "A close look at a precise set of signals can reveal a lot about journalistic quality," says the authors. What signals? Awards, newsroom size, years of operation. But wait, I say to myself. Awards can be manipulated, you have to pay to qualify, and they reward conformity and compliance, usually. Continue to the bottom and you see the advertisement for the data journalism awards. Coincidence? As it turns out, no. The author, Frederic Filloux, is affiliated with the awards, and is on the board of Global Editor News, the sponsor of the awards. OK, it's not Watergate. But this is how you evaluate whether whether journalism is credible.
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