by Stephen Downes
May 15, 2015
AWS Launches Free Educate Service for Academics
Amazon has launched AWS Educate, a cloud service specifically for educators. "AWS Educate is Amazon’s global initiative to provide students and educators with the resources needed to greatly accelerate cloud-related learning endeavors and to help power the entrepreneurs, workforce, and researchers of tomorrow." No, it's not free; rates start at $200 per educator. As David Ramel notes, "AWS Chief Evangelist Jeff Barr explained in a blog post that this primarily will be enabled by four resources: grants of AWS credits for use in courses and projects; free content to embed in courses or to use as-is; access to free and discounted AWS Training resources; and online and in-person collaboration and networking opportunities."
Modeling repetitive behavior
Admittedly, citing this post is a bit of semantic cherry-picking, but I'll do it anyways. The lesson here is that if you add 'memory' to an otherwise random process, you an create complex behaviours. The 'memory' can be very limited - in this case, the author suggests it's "the bird is getting tired". Why is this important? It's because it shows a way very simple processes can lead to very complex behaviours, and "some of the constructs of 1960s-era formal language theory, such as the Chomsky-Schützenberger hierarchy, can be a source of confusion rather than insight when applied to simple patterns generated by simple and biologically-plausible mechanisms."
Weighing Up Anonymity and Openness in Publication Peer Review
Should the peer review process be open? I think so, and the result of this study support my view. "Substantiating our statements, and being accountable for what we say and how we say it when we are gatekeepers for publication, is decisive for me. That’s all the more important for people whose work or critique loses out because of status bias, and those who may be repelled from publishing and science by reviewer aggressiveness." Would I be linking to this post if it didn't support my views? Maybe not here. But I'd want it published. I would want to know about the relevant data (presumably there would have been some) arguing against my views. And one think I like about listing resources in this newsletter is that I am accountable for what I say about them - something one of the anonymous peer reviewers can say.
Key themes in national educational technology policies
I don't think there are any real surprises here, but it's worth validating our assumptions about what policies say with real information about what policies say. This post reports on "an analysis of over 800 policy documents related to the use of information and communication technologies (ICTs) in education from high, middle and low income countries around the world." Michael Trucano observes that "what appears to matter most to policymakers, at least according to the official policy documents that they draft and circulate related to ICT use in education, may not in fact be what *actually* matters." Policy initiatives covered vision and planning, infrastructure (especially power), teachers, skills, contents, assessment and equity. See also the World Bank's SABER project. Image: Wellcome.
On the Question of Validity in Learning Analytics
Good artcile outlining some core issues in learning analytics. For one thing, the author makes a useful distinction between 'reliable' and 'valid' analytics. "For learning analytics, it is entirely possible to have some kind of prediction that is highly statistically-significant and scores highly in all objective measures of performance but is still irrelevant to practice." Additionally, we have to ask questions about whether the results are generalizable, and whether the method was transparent. "Learning analytics undertaken without validity being accounted for would be ethically questionable, and I think we are not yet where we need to get to." Image: Nevit Dilmen.
ALT-MEMBER Responses to Jisc Private Consultation on Code of Practice for Learning Analytics
Association for Learning Technology (ALT),
This short document summarizes three major points from the consultation, recommending (quoted):
- (a) broad understanding of what is meant by Learning Analytics including teaching and assessment, with consideration for more varied role holders
- statements around ownership and access to data and analytics within the draft
- the inclusion of exemplars to illustrate good/bad practice or link to existing resources with illustrate these
As recommendations go, these are pretty bland. The text contains some more concrete (though less representative?) suggestions, for example, that "institutions should also make the algorithms transparent and/or clearly describe the processes involved in producing the analytics," that "The use of 'sensitive data' such as religious affiliation and ethnicity for learning analytics will be restricted and for clearly specified purposes," and that "students should be able to access all learning analytics performed on their data in meaningful, accessible formats."
Lessons Learned from a Chalkboard: Slow and Steady Technology Integration
Larry Cuban on School Reform, Classroom Practice,
Up to the final section, this account of the Japanese use of the chalkboard, which continues in schools even to this day, is well worth reading. It reflects an analysis and tradition surrounding the planning for and use of the chalkboard in the classroom, and in general, outlines a more roundabout attitude toward the use of technology in teaching. But the author then falls into stereotypes that undermine the article as a whole: "Not only do educators rarely discuss the rationale for which technologies might best support particular learning opportunities," he writes, "many US schools are consumed by a haphazard race to adopt the latest innovation." I don't really see evidence of this (and it's certainly not presented ion the article). If anything, US educators anguish over every technological innovation. And this article is more evidence of that.
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