Archive for the ‘innovation’ Category

Source: The University of Chicago Magazine

“Chicago is not alone in this act of reimagination. In embarking on the Odyssey initiative, it joins a growing number of colleges and universities that have found the means, over the past decade, to ease the burden of undergraduate debt for poorer students. Princeton became the first, abolishing loans for low- and moderate-income undergrads in 1998 and then for all financial-aid recipients in 2001. This past year Amherst and Davidson followed suit, announcing they would replace all need-based loans with grants. A dozen others—Harvard, Yale, Stanford, Penn, Rice, the University of North Carolina, and the University of Virginia among them—have initiated some form of loan relief for low- and moderate-income students. “It really does change things,” says Robin Moscato, Princeton’s director of undergraduate financial aid. Since 2001 the percentage of Princeton students on aid has risen from 38 to 55. The number of incoming freshmen with a family income of less than $55,000 has more than doubled. “When you get right down to it, it’s fundamentally a great thing,” Moscato says, “in terms of access to the university and openness of the applicant pool. I think all of us who have set off down this road are going to see lasting benefits beyond the college experience, as far as students having more choices after they graduate because they’re not weighed down by undergraduate debt.”

Advertisements

“The 19th century philosopher Immanuel Kant believed strongly in the notion of dignity, which he defined as treating people as ends in themselves, rather than as means to an end.” (excerpt)

via How To Create A Culture Of Change | Digital Tonto.

“Rather than placing tech leaders on a pedestal, we should put their successes in context, acknowledging the role of government not only as a supporter of basic science but as a partner for new ventures. Otherwise, it is all too easy to denigrate public-sector investment, eroding support for government agencies and training programs and ultimately putting future innovation at risk. As Mazzucato puts it, “It’s precisely because we admire Musk and think his contributions are important that we need to get real about where his success actually comes from.” (excerpt)

via Putting Elon Musk and Steve Jobs on a Pedestal Misrepresents How Innovation Happens | MIT Technology Review.

The real value of bitcoin and crypto currency technology | Blockchain Blog.

I recognize that this could politicized, and that’s not my intention for sharing this. Educators, after all, work best when they approach educating with an open mind (or open mindset) and flexibility. This is a reason education is both an art and a science. On the other hand, we should be careful about being “early adopters”. We should explore new ideas and tools, but we should approach these explorations with awareness and with special attention to measuring (somewhat objectively) what we hope to achieve against what was actually achieved (somewhat objectively).

 

The Neurocritic: Against Initiatives: “don’t be taken in by the boondoggle”.

 

Here’s Professor Leah Krubitzer, who heads theLaboratory of Evolutionary Biology at University of California, Davis:

“From a personal rather than scientific standpoint, the final important thing I’ve learned is don’t be taken in by the boondoggle, don’t get caught up in technology, and be very suspicious of “initiatives.” Science should be driven by questions that are generated by inquiry and in-depth analysis rather than top-down initiatives that dictate scientific directions. I have also learned to be suspicious of labels declaring this the “decade of” anything: The brain, The mind, Consciousness. There should be no time limit on discovery. Does anyone really believe we will solve these complex, nonlinear phenomena in ten years or even one hundred? Tightly bound temporal mandates can undermine the important, incremental, and seemingly small discoveries scientists make every day doing critical, basic, nonmandated research. These basic scientific discoveries have always been the foundation for clinical translation. By all means funding big questions and developing innovative techniques is worthwhile, but scientists and the science should dictate the process.”

 

Jeremy Howard: The wonderful and terrifying implications of computers that can learn | Talk Video | TED.com.

 

Jeremy Howard: The wonderful and terrifying implications of computers that can learn:

“The Machine Learning Revolution is going to be very different from the Industrial Revolution, because the Machine Learning Revolution, it never settles down. The better computers get at intellectual activities, the more they can build better computers to be better at intellectual capabilities, so this is going to be a kind of change that the world has actually never experienced before, so your previous understanding of what’s possible is different.” |

Talk Video | TED.com – http://go.shr.lc/1BpUQhQ

Bicycle – Wikipedia, the free encyclopediaen.wikipedia.org “Urban cyclists in Copenhagen at a traffic light”

James Mapes – Imagination, Creativity & Innovation – YouTube.

I would also add that the imagination also has a weird aspect to it. On the one hand, imagination is “informed” by our senses and perceptions, but it also *informs* our senses and perceptions, or extends our senses and perceptions in palpable ways.

My statement is not occult. It has to do with how we experience or perceive physical space as virtual phenomena.

For example, when driving my sedan and driving my minivan, there are two different experiences of my physical space as an extension of my personal space. As you recall, our personal space differs depending on culture but it is defined by a sense of closeness and our sense of being “too close” to a person or object (since defining of personal space is different depending on culture, there must be a cognitive/learned facet to this defining of personal space http://www.npr.org/blogs/codeswitch/2013/05/05/181126380/how-different-cultures-handle-personal-space ).

As part of becoming skilled at driving my sedan as well as my minivan, I develop a perceivable extension of my personal space. While driving my sedan, I can *perceive* how closely I’m driving to the yellow lines and guardrail in the road or can *perceive* how much space I have allowing my threading between another car and an obstruction (like when passing a car that is about to make a left turn and i have to avoid dropping off the road shoulder). That sense of space is adjusted when I’m driving the minivan.

This estimation is not complex though. I know now, after reading some of Maguire and Mullally’s work on imagining space, that I use reference points on the sedan– as well as on the minivan—to inform and to define the perceived space of my minivan and sedan as two slightly different mental images. The perceptions manifest as a quasi-visual image in my mind’s eye but also as that experience of personal space, that *nearly invaded* personal space that isn’t quite felt on my skin, but rather as the nearly-personal closeness to the vehicle’s “skin”.

This is learned perception (creative) in that it was developed intentionally from trial and error and a bit of low-level reflection. But the space is defined as a virtual space because it is not exact. It’s fuzzy– and just how fuzzy it is depends on how intently and intentionally I re-orient my mental models of the two vehicles.

Exploring these ideas have led me to the awareness of an interestingly dynamic interplay of mental models/imagery and imagination. We create mental models which also informs our imagination. Our mental models help us to predict future behaviors, but mental models also inform our understanding of experiences. Our reflections on retrospective imaginings (memories) are informed by the stories we tell ourselves about ourselves but also by the stories we tell to others about how things “really” work. These narratives may seem to be informed by our mental models, but our mental models are informed by other narratives that are in turn informed by our mental models.

Powerful FreeRunning Stunts Chase Style – YouTube.

Can this become an Olympic event? It’s already featured in many favorite action movies. It is obviously similar to gymnastics, but the urban landscape adds to the excitement. What do you think?

This short article makes one think. For one, if you define technology to include any technique or tool, computer based or not, you realize that there are some interesting patterns connected with new educational perspectives, new research implications, etc.

 

Hype Cycle Research Methodology | Gartner Inc..

 

Excerpt from webpage:

How Do Hype Cycles Work? (http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp)

Each Hype Cycle drills down into the five key phases of a technology’s life cycle.

Technology Trigger: A potential technology breakthrough kicks things off. Early proof-of-concept stories and media interest trigger significant publicity. Often no usable products exist and commercial viability is unproven.

Peak of Inflated Expectations: Early publicity produces a number of success stories—often accompanied by scores of failures. Some companies take action; many do not.

Trough of Disillusionment: Interest wanes as experiments and implementations fail to deliver. Producers of the technology shake out or fail. Investments continue only if the surviving providers improve their products to the satisfaction of early adopters.

Slope of Enlightenment: More instances of how the technology can benefit the enterprise start to crystallize and become more widely understood. Second- and third-generation products appear from technology providers. More enterprises fund pilots; conservative companies remain cautious.

 

Plateau of Productivity: Mainstream adoption starts to take off. Criteria for assessing provider viability are more clearly defined. The technology’s broad market applicability and relevance are clearly paying off.

by Michael Blanding

 

Why do outlet stores exist? The answer may seem obvious to most shoppers—they are places where companies get rid of factory seconds or outdated merchandise at fire-sale prices. Read: bargains, bargains, bargains. And indeed, that may have been the case when the stores first appeared in the 1930s, usually located in rural areas near the factory and selling damaged or irregular clothing, often to employees themselves.Even though most apparel manufacturing has long ago moved overseas, outlet stores have continued to exist—despite not having any “outlet” to speak of. And far from just selling cast-off merchandise, some companies even design specific product lines for sale there. So what’s going on?

via Why Do Outlet Stores Exist? — HBS Working Knowledge.