OLDaily

A new tool to help teachers as digital learning designers
Diana Laurillard, Eileen Kennedy, The BERA Blog, 2018/10/30

On the one hand, I'm not enthusiastic about the tool itself. It feels like a metadata editor of old - " the aims and objectives, intended learning time, number of learners, overall sequence of teaching-learning activities (TLAs), different types of learning that each of these elicits, text to guide what learners do, group size, presence or not of the teacher, and linked resources (digital or other)." On the other hand, the idea of a scaffold that helps people design MOOC learning content is appealing in concept. The authors ask, "Could a learning design have the same recognition as an outcome of scholarship and research as does a journal article?" Not if it's limited and structured like this. But I think a more flexible scaffold could provide some more insightful designs that may indeed gain wider recognition.

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An Unending Copyright Dispute
Lindsay McKenzie, Inside Higher Ed, 2018/10/30

This article covers a "decade-long legal battle between Georgia State University and three publishers over what constitutes "fair use" of course materials." As Kevin Smith, dean of libraries at the University of Kansas, comments in this article, " “The saddest thing about this case is that, after 10 years, it continues to chew over issues that seem less and less relevant. Library practices have evolved during that time, and publishing models have changed. Open access and the movement toward open educational resources have had a profound impact on the way course materials are provided to students." True. But it is telling that publishers continue to pursue this pointless lawsuit through to its bitter end.

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Most preschool math, literacy apps not designed to help children learn
Jonathan Kantrowitz, Education Research Report, 2018/10/30

The research referenced in this article is unfortunately behind a paywall (grrr) so I cannot verify my feeling that it is the academic equivalent of an opinion column. The research selected the top 10 preschool math and literacy apps and evaluated them against a set of criteria (for example, " feedback, increasing complexity, guided play, developmental appropriateness and instructive value) and the conclusion drawn that "few supplied in-play guidance on how to complete tasks, rephrased instructions if the initial ones were not understood or offered rewards that advanced learning." But do children - especially young children - learn by following instructions, or do they (as I think) learn by mimicking and imitating? And (to me at least) it seems just wrong to say " Youngsters under 5 process information very differently from older kids" - not because they aren't different, but becuase we're not computers; none of us "process information".

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Which Will Dominate Online Tutoring: AI or the Gig Economy?
Henry Kronk, eLearning Inside, 2018/10/30

In the race to the bottom, they question posed in the title is key. While most pundits focus on the future role of AI, the gig economy shows no sign of slowing down. “Contract jobs in the education field seem to be keeping pace with the overall growth in flexible work we’ve seen in recent years,” said Brie Reynolds, director of online content at FlexJobs, according to Education Dive. “Education and training is consistently among the top career fields for the number of flexible jobs posted each month."

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Personalization by Paper and Non-Mechanical Teaching Machines
Audrey Watters, Hack Education, 2018/10/30

Audrey Watters digs up a fascinating definition of 'teaching machines' (and implicitly, I would say, of what constitutes 'teaching'). Quoted from her text:

• First, continuous active student response is required, providing explicit practice and testing of each step of what is to be learned.
• Second, a basis is provided for informing the student with minimal delay whether each response he makes is correct
• Third, the student proceeds on an individual basis at his own rate.

I've seen the research supporting explicit practice and immediate feedback. But the whole concept seems needlessly instructivist. And it raises the question in my mind - is the problem with teaching machines that they are machines, or that they are instructivists?

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