Sunday, October 9

What would I see if I rode on a beam of light?

Before Einstein, scientists would observe and record something, and then find the right mathematics to explain the results. Einstein comes along and reverses the process by finding a beautiful piece of mathematics based on some very deep insights into the way the universe works and then makes predictions about what ought to happen in the world.

Behold the power of human creativity.

Mihaly Csikszentmihalyi wrote that the creative process normally takes five steps (Creativity, 1996, p. 79):
  1. Preparation: becoming immersed in problematic issues that are interesting and arouses curiosity.
  2. Incubation: ideas churn around below the threshold of consciousness.
  3. Insight: the "Aha!" moment when the puzzle starts to fall together.
  4. Evaluation: deciding if the insight is valuable and worth pursuing.
  5. Elaboration: translating the insight into its final work (Creativity is 99% perspiration and 1% inspiration - Edison).
The physicist Freeman Dyson wrote two papers that were published in Physical Review that brought together Richard Feynman and Julian Schwinger's theories of quantum mechanics. After Dyson's papers, Feynman and Schwinger's ideas became understandable and thus led to the two being awarded the Noble prize in physics. There is no doubt in most minds that the two would never have been awarded the prize if it was not for Dyson being able to explain and connect their ideas.

Dyson's story is interesting as it fits the five steps of creativity:
  1. Preparation: He goes to Princeton to study under the greats. He gets personally acquainted with the two central figures, recognizes the two theories are connected, and then goes through a six month period of directed preparation.
  2. Incubation: He spends two weeks relaxing
  3. Insight: and is hit with the "Aha!" of how to explain and connect the two.
  4. Evaluation: He then spends another six months creating, evaluating,
  5. Elaboration: and elaborating two papers that are accepted by the editors of Physical Review.
Fred Stratton (CEO of Briggs & Stratton) once said that genius lay in the ability to see how two things that nobody else sees as related are indeed related. This ability to recognize distant analogies unlocks a world of potential -- Edison recognized that space and time are not absolute; while Dyson recognized a connection between Feynman and Schwinger's two theories when no one else could.

The Learning Process in the Knowledge Economy

Skills needed in this so called "knowledge economy" go beyond rote memory to the next level -- the ability to think both critically and creatively.

Yet traditional learning systems have typically been centralized and operate on the principle that learners are unable to decide what they need to learn, thus the system does it for them, which in turn creates a vicious cycle -- put the learners in a system that does very little to encourage critical thinking, formal reasoning, or meta-learning; then tell them they are unable to decide what they need to learn, thus others will have do it for them. And this carries on from schools to the business world.

This central control is is closed to the possibility that people need to have a say in what they learn. It is closed to the next step in the learning process -- building a variety of experiences in order to build a strong knowledge base; which then creates the possibility for building a context or connection that no one else has created before. This is how problems are solved and novel ideas are created.

Learning needs to follow a similar process as Csikszentmihalyi's Five Steps of Creativity:
  1. Preparation: A two step process:
    • Rote learning in order to create the building block of logic -- the means to use rules to make inferences, choose courses of action and answer questions.
    • The collecting of information (called ontologies) -- In philosophy, an ontology is a theory about the nature of existence, of what types of things exist; ontology as a discipline studies such theories. The most typical kind of ontology has a taxonomy and a set of inference rules.
  2. Incubation: A period to reflect and interact with others.
  3. Insight: Making new connections.
  4. Evaluation: Metacognition - planning, setting time lines, and allocating resources (Schank & Abelson, 1977) for new "connections." It also designs strategies for accomplishing goals once they have been set.
  5. Elaboration: Turning the idea into reality.
Our learning systems have performed a good job with the first step of "Preparation", yet it seems quite hesitate to go beyond this by riding the beam of light rather than just observing it.

This Tuesday (October 11, 2005) on PBS -- Einstein's big idea: The Legacy of E = mc2

1 comment:

David Grebow said...

Donald, the changes are even more far reaching if you compare elements of the preceding Agricultural and Industrial Economies to the Knowledge Economy, and then extrapolate onto the topic of learning.

For example, the Industrial Economy was modeled after the Prussian Army experiements in gathering large groups together and rapidly training them to kill.
So it was highlighted by command and control, hierarchical top-down models, uniforms, grades and rigid categories of jobs, tests for knowledge not know-how,and more.

The Knowledge Economy is characterized much differently: connect and collaborate (versus command and control); no uniforms; assignments that change rapidly versus job descriptions set in stone; emphasis on a history of performance versus the Ivy League School you attended; matrixed versus linear organizational structures; and more.

So the Knowledge Economy is slowly molding education to its needs the same way that the previous two economic paradigms molded education to their needs. We are in that transitory period where the artifacts of the old are slowly (but surely) being replaced by the digital technology of tomorrow.

The nature and essence of capitalism is to have the educational system serve the needs of the prevailing economy. John Taylor Gatto is a great thinker in this area. The odd thing about these transition periods - in the previous one, for example, public education was looked at as a really bad idea - is that the old models merge and converge with the new models, often clashing, sometimes in harmony, and always temporarily until the new model of learning takes over.

And I agree with your thesis that the old model only went as far as Preparation. The new model will, one way or another, in the schoolplaces and workplaces of the world, learn to accomodate incubation, insight, evaluation, and elaboration and more. AND they will use new technolgy to teach and make it so. Why? Because the new Knowledge Economy will run on creativity and innovation.

Corporate education will focus on what I named "The Corporate IQ" - increasing the value of the corporate brain, and it's ability to creatively compete in the new economy. Making the company the smartest in its industry, because only the smartest companies will win.