This is, as the title suggests, a huge list of OER textbooks - 12 or so per page in this (42 page PDF), so maybe 500 texts, organized into subject groupings. What I wish (not to take away in any way from the effort this represents): the author names were written fully, rather than in the Lastname,I format; shot descriptions of each text to aid searching; database with harvest format so the list could be maintained (and used) on an ongoing basis.
This is a really detailed (89 page PDF) exploration of the topic. "This guide, with a foreword by Maren Deepwell and Joe Wilson, is a comprehensive summary of how we went about creating Citizen Maths, an open online maths course and service. The guide shares our design principles and the techniques we used to put them into practice. Our aim is to provide – with the appropriate ‘translation’ – a resource that will be useful to to other teams who are developing online education initiatives." The guide follows through the implementation of a set of design principles, including an analysis of need, context, learning model ("Our aim is to give thousands of learners the feeling that they are in a one-to-one tutorial"), coherence and consistency, and sustainability. There's even discussion of the course logo, colour scheme, fonts, 'talking heads', 'talking hands', and 'talking applications'.
I ran across this concept last summer and let it slip by, but I don't want to overlook it. The idea is that the brain functions not as an intelligence or thinking instrument, but as a prediction machine. This article collects a number of resources that revolve around that idea. This is important because the function of predicing can be very different, and the requirements much lower, than for intelligence or cognition. That said, I think Julie Dirksen minsinterprets the idea in her post, and in particular, every word in the sentence "our brains use embodied simulation to construct meaning" is wrong in its own distinct way (I should write an article on just this sentence one day). You don't need any of that cognitive overhead to make predictions. In all fairness though, she's summarizing a TED talk from Anil Seth, which is the source of some of the error. That sat, the post is worth a look, and the concept definitely worth a think.
"This article," writes Zsolt Olah, "is about why you can’t motivate humans, and the 5 design steps you should go about it." Wait - you can't motivate students? There goes about ten tons of educational theory! But this proposition is advanced by Susan Fowler in her book on the topic. The idea is that you can't motivate them because they're already motivated. "People spend significant amount of informal learning time on YouTube, social media, forums; they’re asking peers constantly for answers. They are engaged and motivated," writes Olah. Ah, but the methodology that follows reads as something similar to Gagne's nine events (reduced to five). Grab attention, challenge them, engage them, then, um, motivate them, and finally, inspire! There is a useful link to a chapter on motivation from Julie Dirksen's book on learning design with a focus on four elements: technology acceptance, user efficacy, modelling and practice, and social proof.
You might be interested in this presentation of what I would consider a folk theory of cognition. Presented as a video by Kevin Thorn, it describes two tracks of perception and information processing - words and images. These correspond to verbal and pictorial representations, first in working memory, then in long-term memory. Why, I wonder, would we separate knowledge into two distinct types? And where are the other senses, like tactile and kinesthetic? And why would learning be depicted as nothing more than memory? Anyhow. You might also be interested in Thorn's other videos, including a 19-part (so far) series of lengthy videos (22.5 hours total) on Storyline Live. Thorn also has a blog, but with only three posts per year he leaves the readers wanting.
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