In the last ten years, technology has changed the way we work and communicate with others — and it’s also changed how we interact in the classroom. In fact, some educators argue that technology can improve the classroom by eliminating the need for a physical one, and allow students to learn remotely, from wherever they do their best work. While it’s still too early to know if this is the most effective way to teach, it’s important to stay-to-update on these innovations in education and see what we can learn from them. In these TED talks, students and educators share their …

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A new MIT-designed open-source website might well be the Pinterest of microfluidics. The site, Metafluidics.org, is a free repository of designs for lab-on-a-chip devices, submitted by all sorts of inventors, including trained scientists and engineers, hobbyists, students, and amateur makers. Users can browse the site for devices ranging from simple cell sorters and fluid mixers, to more complex chips that analyze ocular fluid and synthesize gene sequences.

 

The site also serves as a social platform for the microfluidics community: Any user can log in to submit a design; they can also like, comment on, and download design files to reproduce a featured device or improve on it.

 

David S. Kong, director of the MIT Media Lab’s new Community Biotechnology Initiative, says the new site is designed to accelerate innovation in microfluidic design, which until now has followed a conventional, academically peer-reviewed route.

 

“There’s a familiar experience for people in microfluidics: You see a really amazing paper that shows you a design, but if you want to try to copy the design, the actual design files that are a critical part of reproducing or remixing a device are not shared in any systematic way,” Kong says. “As a result, researchers around the world are in parallel reinventing the wheel. It’s one of the reasons why open-source in general is a very powerful set of principles. It can really accelerate the diffusion of technology.”

 

Kong and his colleagues outlined the open-source platform in a paper published last week in the journal Nature Biotechnology. His co-authors are Todd Thorsen, Peter Carr, and Scott Wick of MIT’s Lincoln Laboratory; Jonathan Babb and Jeremy Gam in the Department of Biological Engineering; and Ron Weiss, professor of biological engineering and of electrical engineering and computer science.

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A monkey’s brain builds a picture of a human face somewhat like a Mr. Potato Head — piecing it together bit by bit. The code that a monkey’s brain uses to represent faces relies not on groups of nerve cells tuned to specific faces — as has been previously proposed — but on a population of about 200 cells that code for different sets of facial characteristics. Added together, the information contributed by each nerve cell lets the brain efficiently capture any face, researchers report June 1 in Cell.

 

 

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