Magnetic Poetry Creativity

I just opened my new box of Magnetic Poetry–those tiny refrigerator magnets, each with one word, that you can string together on your fridge when the creative urge strikes you. This isn’t the original set; it’s a new collection of words titled the “Creativity Kit.”

First, you have to peel the words apart; they come in sheets, each with between 10 and 20 words loosely connected together. But I don’t want to separate the words that were printed together (presumably at random) on this sheet:




WITHOUT FEAR                   SAUSAGE

TOO MUCH          SURE          REALITY


I can’t top that poem!

The Secret of San Francisco’s Entrepreneurial Success

I’ve been reading and re-reading an awesome article about San Francisco’s entrepreneurial culture, by Nathan Heller in the New Yorker magazine.* Heller spent some time shadowing Johnny Hwin, an entrepreneur and musician who he calls “one of the best-connected kids in San Francisco.” Heller’s article is driven by a puzzle he can’t figure out:

Hwin is “a collective kid who, for reasons I still didn’t understand, seemed to have mastered everything about the new Bay Area and how it worked….I didn’t understand how people like Hwin appeared to float above the exigencies of career….If I hoped to understand the first thing about American culture in this decade, I realized, I’d need to figure out exactly what was going on in San Francisco.”

Heller’s article is long and brilliantly written. To really get the full sense of what he learned, you really need to read the full article. But here I’ve excerpted some highlights:

The art and technology collective called the Sub…is part of a network of places where the new mode of American success is being borne out…..a blend of business and small-scale creative art.

Hwin has been working as a musician, a tech entrepreneur, and an investor in other people’s startups. His two-person band, Cathedrals, just released a debut single and is producing an album. He and a friend are managing investments of up to two hundred and fifty thousand dollars in private companies.

People who are young and urban and professionally diffuse [the three business card life] tend to regard success in terms of autonomy–designing your life as you want–rather than Napoleonic domination.

San Francisco’s young entrepreneurs appear less concerned about flaunting their earnings than about showing that they can act imaginatively, with conspicuously noble ethics. Hwin is into “creative, mindful living” in part because it helped his business interests.

In the second half of the article, Heller picks up on this theme of “business interests” blending with creative and mindful living, and begins to delve down into the underlying core of the culture:

In 1966, Hendrik Hertsberg wrote about San Francisco’s “new bohemianism” of the Hippies and the Beats. The youth, the upward dreams, the emphasis on lifestyle over other status markers, the disdain for industrial hierarchy, the social benefits of good deeds and warm thoughts–only proper nouns distinguish this description from a portrait of the startup culture in the Bay Area. It is startling to realize that urban tech life is the closest heir to the spirit of the sixties, and its creative efflorescence, that the country has so far produced.

But Heller’s article ends on a critical note:

The result is a rising metropolitan generation that is creative, thoughtful, culturally charismatic, swollen with youthful generosity and dreams–and fundamentally invested in the sovereignty of private enterprise…. I just sat there, wondering whether this was it, the kingdom of which we so wildly, and so effortlessly, dreamed.

I am not sure I agree with Heller’s critical tone. I know many of these people, and they believe there is no contradiction in doing good and doing well. I myself am a former hippie, Grateful Deadhead, Rainbow-gathering attendee, and now I’m advising corporations on innovation, and creating a university program in educational entrepreneurship…and I don’t see any contradiction. It’s not like the Yuppies of the 1980s, who were former hippies who worried they were selling out by wearing suits and selling junk bonds. Hwin doesn’t worry about selling out, because he is pure; it’s never crossed his mind. Heller’s article, although wonderful, seems like an early thought piece…like Heller is still mulling it over, still not sure what to make of this new cultural moment. Maybe none of us really are. There are strong parallels with David Brooks’ 2001 book Bobos in Paradise, referring to the “bohemian bourgeois,” the former hippies who became affluent and yet retained the same values. Heller certainly made me see things, and wonder about things, I hadn’t before. I hope Heller continues and turns this into a series of extended articles about entrepreneurship and modern America.

*Nathan Heller (2013, October 14). “Bay Watched.” The New Yorker Magazine, pp. 68-79.

For MOOCs to Work, We Need to Talk

Online courses have proven they can attract thousands of students, but then almost all of them drop out before finishing the course. Well, guess what? Sitting at home alone and staring at a pre-recording lecture is just about the most boring thing ever, as Geoffrey Fowler writes in a Wall Street Journal article published on October 9, 2013. Learning scientists have known this for years: we have decades of research showing that engagement and social interaction result in more effective learning.* Fowler reports that MOOC developers are re-discovering the same thing:

“The most important thing that helps students succeed in an online course is
interpersonal interaction and support,” says Shanna Smith Jaggars, the assistant
director of Columbia University’s Community College Research Center. She has
compared online-only and face-to-face learning in studies of community-college
students and faculty in Virginia and Washington state. Among her findings: In
Virginia, 32% of students failed or withdrew from for-credit online courses,
compared with 19% for equivalent in-person courses.

Learning scientists have also known for decades that getting students to talk to each other, while they are learning, results in better learning.* MOOC developers are re-discovering this solid finding, as well:

One way to provide personal interaction at mass scale is to get students talking to each other. Several studies suggest that many students who spend more time contributing to course discussion forums end up performing better. More than answering specific questions, the boards send a message, says Mr. Ng [a co-founder of Coursera]: “You are not alone.”

A study of the online-only version of edX’s course Circuits and Electronics offered in the spring and summer of 2012 found a mild correlation between the number of posts people made in the discussion forum and their final grades. Some 52% of the students who earned a certificate for the course were active in discussion forums, according to the study by the Teaching and Learning Laboratory at MIT and Andrew Ho, an associate professor at Harvard.

I’ve been arguing that educational technology developers need to work more closely with learning scientists, so they don’t keep reinventing the wheel. (And even worse, reinventing the wheel after they spend millions of dollars first trying ineffective shapes like squares and triangles.) In the new master’s degree program I’m creating at the University of North Carolina–in educational innovation, technology, and entrepreneurship–we’re going to make sure students get a solid grounding in the learning sciences. That way, ed tech innovations will be much more likely to result in solid learning outcomes.

*Sawyer, R. K. (2006). The Cambridge Handbook of the Learning Sciences. Cambridge University Press.

Collaboration at Microsoft Research

Dharmendra S. Modha is a senior manager of cognitive computing at IBM Research, leading a team of scientists that is designing a radical new software ecosystem inspired by the human brain. Here’s what Modha says about this leadership experience, in today’s New York Times*:

This experience has taught me valuable management lessons. In the coming years, it seems likely that organizations of all kinds, from the private and public sectors, will need to collaborate with one another in order to succeed….new paths to innovation will require people from different disciplines to work together….The key is to channel a group of superstars so that all are pulling in the same direction.”

If you want to know how to manage effective collaboration, take a look at my book Group Genius: The Creative Power of Collaboration (Basic Books, 2007).

*Modra, 2013 (Sunday, October 13). When debate stalls, try your paintbrush. New York Times, page BU 8.

Thinking In New Boxes

Thinking in New Boxes is the title of a new book by Luc de Brabandere and Alan Iny of Boston Consulting Group. They write “Thinking outside the box is dead” and propose “thinking in new boxes processes” like: doubt everything; research; generate ideas; introduce reality; and implement and evaluate relentlessly.

In my 2013 book Zig Zag: The Surprising Path to Greater Creativity, with over 100 creativity techniques based in research, I make a similar point. In Chapter 4, on how to get yourself into the playful mindset where great ideas happen, I recommend “Find The Right Box” and I introduce a group of four practical techniques with this:

There’s a popular belief that creativity comes from the absence of constraints. People assume that if you’re not creative, it’s because you’re thinking inside the box—so all you need to do is to get rid of the box!

But research shows just the opposite: creativity is enhanced by constraints. They just have to be the right constraints. The techniques of this section show you how important it is to draw boundaries around the space in which you play. If you’re stumped for an idea, maybe you just need to play with different toys for a while; start a new game, with a different set of rules.

As the famous G. K. Chesterton put it: “Art consists of limitation. The most beautiful part of every picture is the frame.”

Brain Imaging: What Good Is It?

You’ve no doubt seen those colorful pictures of the brain, with different sections of the brain colored yellow, red, green, and blue–a rainbow pattern of colors spread out across the brain. These images are generated by a brain imaging technology called “functional magnetic resonance imaging” or fMRI for short. fMRI can detect the relative degree of brain activity in a very small region of the brain, approximately 3 millimeters cubed. These little imaginary cubes are called “voxels”; and then, using some expensive and fancy technology, researchers can measure the brain activity in each voxel while you’re engaged in a specific mental task. To communicate the results, each of the voxels is assigned a color based on how much the neurons inside it are firing. Scientists, journalists, and trade book authors are really excited about this technology, because it seems to give us a window into what is really going on when we’re thinking. National funding agencies have been granting lots of money to this sort of research (and it’s not cheap, because it requires expensive machines that are often located inside the medical school, because they’re also used for clinical diagnoses).

So what good is it? More and more scholars are asking this question, and we’re seeing a growing backlash. Knowledgeable scholars have been arguing that we haven’t learned much from this expensive brain imaging. Adam Gopnik, writing in The New Yorker magazine, recently reviewed three new books that all argue “that brain science promises much and delivers little.” The books are A Skeptic’s Guide to the Mind, by Robert A. Burton; Brainwashed: The Seductive Appeal of Mindless Neuro-Science, by Sally Satel and Scott O. Lilienfeld; and Neuro: The New Brain Sciences and the Management of the Mind, by a pair of cognitive scientists, Nikolas Rose and Joelle M. Abi-Rached. (Not included in this review is the 2011 book Neuromania: On the Limits of Brain Science, by Paolo Legrenzi, Carlo Umilta, and Frances Anderson.) As Professor Roger Carpenter writes, in a letter supporting Gopnik’s review, this “is indeed neo-phrenology, and, intellectually, represents a regression to the nineteenth century.” (Sep. 23, 2013, pp. 12-14)

In 2011, I published a scientific article titled “The cognitive neuroscience of creativity,”* and I came to the same conclusion about the limits of brain imaging. The first challenge is that you have to learn a lot of technical detail to really understand how little information the technology provides. For example, in my article I reported that fMRI, which indirectly measures neuronal activity by measuring blood flow to each voxel, is in fact only measuring changes in blood flow above a baseline state of 1 percent to 3 percent. That means that even when your neurons are firing like crazy, you won’t see more than a 3 percent increase above a baseline state (i.e., sleeping or daydreaming). Second, when neurons start firing, the blood flow doesn’t increase until 4 to 6 seconds later. Third, when neurons become more active, they draw in more blood, but blood flow also increases over a larger area that extends to a few millimeters distant, where there may not be any increase in neuronal activity.

Fourth, different people’s brains operate in different ways–not everyone’s brain responds to a given task in exactly the same way. Even for a single person, their brain responds differently to the same task on each occurrence of the task. So researchers have everyone do the task tens or hundreds of times, and then they take a statistical average across all of the tasks. And after that, they average across everyone’s brain. So those colorful pictures you are seeing represent an average–and it doesn’t mean that every person, every time, displays exactly that activation pattern.

And finally, the colorful pictures hide a very important fact: The entire brain is active pretty much all of the time. Neurons are always firing, at least a few times every second. The brain is a complex system, and every cognitive activity is widely distributed across the neocortex. If you showed those pictures in a magazine, it would look like a jumbled mess. So researchers do what’s called paired image subtraction–they get the average brain activity in one task, and then they get another average, of brain activity in some comparison baseline task, and they subtract out the activity of the baseline task.

Are you confused yet? I said there were a lot of technical details. (And the above is a highly simplified version.) But all this led me to draw the following conclusions in my 2011 article:

1. For the most part, brain imaging has discovered facts that were already known from classic experimental cognitive psychology. We have no breakthrough surprises; no 1970s experimental findings have been overturned.

2. All thought involves many regions of the brain. There is no such thing as “the brain location for creativity” or anything else.

3. You can’t use brain imaging to make claims about causation, such as “activation in this part of the brain caused you to have a creative insight,” because the activated areas might not play a critical role in performing the task; they might be “listening” or monitoring some other brain area that is actually responsible.

4. Because the brain imaging results are always averaged over many trials and many subjects, it is incorrect to interpret the studies as showing that “creativity is located in the anterior cingulate cortex” (or wherever).

5. Higher cognitive functions, like creativity, are complex and involve many parts of the brain simultaneously. They can’t be reduced to one small location in the brain. And when you think about it, that’s just common sense.

Perhaps new technologies will emerge in the future that can address some of these issues. But whatever new brain imaging technology emerges, these five points will still apply. I’ll certainly keep following this research, and if I see some exciting new finding about creativity and the brain, you’ll read it here!

*Sawyer, Keith. 2011. The cognitive neuroscience of creativity: A critical review. Creativity Research Journal, 23(2), 137-154.

Teaching Day at George Washington University

Today I was the second invited keynote speaker at GWU’s annual Teaching Day. The first keynote speaker was the legendary psychologist K. Anders Ericsson, famous for his studies of expertise and the finding that it generally takes 10,000 hours of deliberate practice to attain a world-class level of expertise (discussed in many books, but most famously in Malcolm Gladwell’s book Outliers).

WP_20131004_003Professor Ericsson’s talk was fascinating, and deeply grounded in his research. He has studied a wide range of experts, from chess players to ice skaters, to violinists and pianists, to medical doctors, to school teachers…on and on. And no matter what type of expertise he studies, he finds that there is essentially NO evidence that talent is innate–no evidence that people become experts because they have a natural ability in the area. Instead, what he finds repeatedly is that anyone can attain world-class expertise if they invest the time. The reason why most people do not become experts, according to Professor Ericsson, is that it takes a LOT of time and effort to attain expert level performance. The type of practice that gets you there–“deliberate practice”–is effortful and demanding. It involves a lot of failure, which means you have to have a strong desire and keep going through the 10,000 hours of failure and intense effort.

In fact Ericsson’s research is consistent with the creativity research. Creativity researchers have found that every exceptional creator has invested the 10,000 hours of hard work and deliberate practice. The world’s top creators don’t just stumble into great ideas; they invest the time and they pay their dues. The bad news is that there are no shortcuts to creativity, no shortcuts to expert performance. The good news is that high levels of performance are accessible to all of us, if only we invest the time and effort.

WP_20131004_004GWU asked me to talk about “The schools of the future: Educating for creativity.” We now know a lot about how to teach in ways that foster creative learning outcomes. And it turns out that teaching for creativity is the exact opposite of what goes on in many university classrooms: big lectures where professors deliver information to students, who are expected to absorb the information, take notes and study them later, and then prove they’ve absorbed it by taking an exam. I call this uncreative style of teaching “instructionism”. In contrast, to develop creative graduates, we need to engage students in active learning, where they are working on a complex, real-world problem, designed by the instructor so that as they solve the problem, they learn the required disciplinary content knowledge. It works even better if the students work in teams, and if they develop visible products along the way. That way, they can receive frequent constructive advice and critique from the instructor and from their fellow students.

After my talk, I spoke with several different professors at GWU. I learned that many of them have developed research-based teaching strategies aligned with these learning sciences principles. In particular, GWU professors are using “learning assistants” and group project-based learning–in physics classes, and in biology classes. And they’ve documented impressive gains in student learning compared to the traditional lecture. I’m not surprised; researchers have found this over and over again (if you’re not convinced, Google “Carl Wieman Nobel Prize in physics” or “Peer led team learning”).

At the morning’s breakfast meeting about “The future of the university” we talked about the new possibilities opened up by the Internet, for example the possibility that physical campuses will go away, to be replaced by Internet-based lectures and exams. To date, too few of these new technologies are grounded in learning sciences research. I’m leading a new program at the University of North Carolina, with the goal of grounding ed tech innovations in the learning sciences. That’s the best way to help our students learn most effectively. I don’t know how the Internet will transform schooling. But I will make one prediction: One hundred years from now, no one will be lecturing any more.