According to Thomas Arnett, "the 'collective action' approach will likely flounder at creating the pipeline of excellent personalized learning teachers that the field needs." This is because "when new innovations are still stretching to meet our expectations, the best strategy for pushing a product’s performance forward is for a single entity to control all the interdependent pieces of the solution." He draws a parallel between the development of teachers and the development of touchscreens. It's hard to imagine a more tone-deaf analogy, save perhaps the reference to training for a particular charter school network in New York City. Teachers are not "a product" and personalization may yet be something that resembles art more than it does manufacturing.
Britain's Jisc has launched a new podcast called "What the EdTech?" hosted by Laura Kidd. The first episode features guests "Eric Stoller, education consultant and thought leader, Sarah Knight, head of change - student experience at Jisc, and Kardi Somerfield, senior lecturer in digital marketing and advertising at The University of Northampton."
The argument documented here is familiar, but it's still a point of frustration for researchers working in the humanities and social sciences when they are compared with peers in technology, engineering and mathematics. Simply, the former receive much fewer citations because citations, and papers themselves, play a different role in those disciplines. So it's silly to compare researchers based on citation counts or H-indices. This, for example, is a big difference between me and other researchers in the same building: "Scholars position their approach not through a comprehensive literature review but by way of strategic citations." The 'literature review' approach to science has always seemed odd to me. Don't you actually know the important papers in your field after having worked in it for 15 years? Also, literature reviews actually miss some of the most important work in a field. But - I recognize - it's a perspective thing.
According to this article, "Pearson is drawing criticism after using its software to experiment on over 9,000 math and computer science students across the country." The experiment was disclosed in a paper presented on Tuesday (not Wednesday, as was incorrectly reported by Gizmodo). "Some students received 'growth-mindset messages,' while others received 'anchoring of effect' messages. (A third control group received no messaging at all.)" According to the paper's abstract, " Results indicate increased persistence in the growth mindset condition, and a decrease in persistence for the anchoring condition, relative to control." The suggestion here is that the students did not know they were the subjects of an experiment, which would be a violation of research ethics. (This was first reported in EdWeek, but thei link currently is failing due of an invalid SSL certificate. It was presented at an AERA conference, but you really have to dig to view the listing for the paper delivered by Daniel M. Belenky, Yun Jin Rho, Mikolaj Bogucki and Malgorzata Schmidt).
This article is about a Chinese e-learning application called Rain Classroom. "Services (rain) made possible by big data analytics (the cloud) are utilized in classrooms or for self-learning (rain irrigating the soil). More data on teaching and learning is generated and collected then uploaded to the cloud again (evaporation), completing the cycle." It's used in more than 2,300 universities in China "and there are plans to expand this to colleges overseas and also more high school classrooms at home." The same company. The same company operates the MOOC platform XuetangX.
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Copyright 2018 Stephen Downes Contact: email@example.comThis work is licensed under a Creative Commons License.