Online Test-Takers Feel Anti-Cheating Software’s Uneasy Glare
Natasha Singer, New York Times, 2015/04/09
More on ProctorTrack, the service that stares at you through your camera while you take an online exam. Not surprisingly, students don't like it. More...
Mean What You Say: Defining and Integrating Personalized, Blended and Competency Education
Susan Patrick, Kathryn Kennedy, Allison Powell, International Association for K-12 Online Learning (iNACOL), 2015/04/09
The School Improvement Network sponsored a post in EdSurge linking to this white paper, and the paper is heavy with self-referential linking (so take some of it with a grain of salt) but it is on the whole worth a read as an outline of the major elements (and supporting technologies) for personalized learning. More...
Digitally Connected: Global Perspectives on Youth and Digital Media
Sandra Cortesi, Urs Gasser, Social Science Research Network, 2015/04/09
This open (I think; it uses an SSRN redirection service) online book contains the proceedings of a conference funded by an array of charitable institutions and United Nations agencies that only an institution like Harvard can assemble. More...
Los Angeles Police Department taught the Canadian way when it comes to using force
Kim Brunhuber, CBC News, 2015/04/09
What's interesting is not that the Los Angeles police are now using training methods employed by the RCMP, but rather, the manner in which training is now being conducted. More...
The Math Ceiling: Where’s your cognitive breaking point?
Ben Orlin, Math With Bad Drawings, 2015/04/09
"A student who can answer questions without understanding them is a student with an expiration date." You'll understand. More...
The 60,000 Times Faster Claim Gets Dialed Back to 1982
Alan Levine, CogDogBlog, 2015/04/09
Have you heard this? "We can process visuals 60,000 times faster than text?" In my own mind I would question it right away because of its overt employment of a computer metaphor to talk about cognition, which to me is prima facie questionable. More...
Machine Learning Algorithm Mines 16 Billion E-Mails
Press Release, MIT Technology review, 2015/04/09
I'll leave aside the question of where they got 16 billion emails and pause for a moment to ponder the implications of this: "Human e-mailing behavior is so predictable that computer scientists have created an algorithm that can calculate when an e-mail thread is about to end." (I really thing 'created' is the wrong word here - I think the appropriate word is 'found'.) If we're that predictable, what does it say about us. More...
GNU social: Federation against the social model of Twitter
Manuel Ortega, Las Indias in English, 2015/04/10
I haven't seen GNU Social but it might be worth looking it, as it offers a networking model more akin to the one I favour. "The Facebook and Twitter socialization model, the FbT model, is like a large plaza where everyone can shout their slogans, while barely listening to each other," says this article, which can be contrasted to (what it called) the federation model, in which "the intimate relationship between the value of a conversation and the trust that has already been established within the nodes. More...
Integrating Social Learning in the Workplace
Sahana Chattopadhyay, ID & Other Reflections, 2015/04/10
Important advice: "The catch is that “social learning” cannot just be implemented or enforced. One cannot inset social learning in the training calendar and feel happy about it." It's not the sort of thing that can be imposed from the top down, writes Sahana Chattopadhyay. More...
Innovation and the Novelty Factory
Tim Klapdor, Heart | Soul | Machine, 2015/04/10
À propos of my recent talk on innovation, "Horace Dediu posits a taxonomy which I think is extremely useful to help discern innovation and reduces some confusion:
Novelty: Something new
Creation: Something new and valuable
Invention: Something new, having potential value through utility
Innovation: Something new and uniquely useful
Why is this useful? It helps distinguish actual innovation from mere novelty. More...
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