The HG2S Training Blog

The archives collection  at Wired.com has a transcribed discussion between computer gurus Alan Kay and Danny Hillis that, surprisingly perhaps, includes a few comments about learning and education. It’s a worthwhile read in many respects but I’m plucking a couple quotes from it that relate specifically to knowledge, learning and pedagogy:

“There’s this interesting interplay between what you might call talent and how much of a meta-system we can put down on top of meager talents to learn how to do things. Two recent tennis champions, Ivan Lendl and Chris Evert, were not actual athletes. They were people who just learned how to play tennis. Some of the most natural tennis players, like Nastasi and Agassi, only do well when things are going well – they don’t have learned skills to drop back on. So in any given population maybe 5 to 20 percent have a natural hacker sort of talent; they are often not helped by pedagogy. Pedagogy is about getting the other 80 percent of people within hailing distance. So I’ve been very interested in taking some very important ideas and wondering how you get them in a state where the 80 percent can actually learn them in an operational way. And that’s why I keep coming back to computers.”

Interestingly the conversation concludes with:

“DH:

The question that I keep asking myself is, where is the next frontier? Where is that place that a new world is being constructed? Do you know any candidates?

AK:

I think the frontier has to do with human learning. Knowledge is not completely relative. There are a hundred or so powerful ideas that basically mean the difference between life and death, and I think one of our major jobs should always be to be true and get as many people enfranchised into them as possible.

DH:

But in fact, if you look at what’s happening, it seems just the opposite. We’re very much heading toward a two-class society, where either you’re somebody who sort of knows about, or feels empowered to deal with all of the complexity in society, or you’re one of the people that is a victim of it and is just on the receiving end of it all.

AK:

And I think the gap actually gets bigger as the leading edge of knowledge gets less intuitive.”

The full transcript by Steven Levy and Kevin Kelly can be viewed here.

In a note that could have been taken from one of Maria Montessori’s books, researchers in neuroscience, machine learning, education and psychology have convened to show that findings from a joint study suggest that “the prepared environment” might be supported by new scientific data.

“The ‘prepared environment‘ is Maria Montessori’s concept that the environment can be designed to facilitate maximum independent learning and exploration by the child.”

Terrence J. Sejnowski, Ph.D, researcher at the Computational Neurobiology Laboratory at the Salk Institute for Biological Studies and co-director of the Temporal Dynamics of Learning Center (TDLC) at the University of California, San Diego, echoes Montessori in his team’s findings. As quoted in Science Daily:

“To understand how children learn and improve our educational system, we need to understand what all of these fields [neurobiology, psychology, education, machine learning] can contribute. Our brains have evolved to learn and adapt to new environments; if we can create the right environment for a child, magic happens.”

The cross-disciplinary research points to a new science of learning that might influence the way classrooms are organized and run in the future. In particular, three guiding principles (or concurrent processes) emerge from the study:

1. Learning is computational
2. Learning is social
3. Learning is supported by neurological (perception-action) circuits

Research in machine learning and developmental psychology illuminate the computational complexity employed by learners who use statistical patterns and probabilistic models to infer rules of logic, relationships between words, syntax, and causal dependence between objects in the physical world.

Evidence that the three component processes happen concurrently is supported by the fact that learners do not calculate and compile statistical models of the environment indiscriminately but throttle the process using social cues from the people around them. Further, animal studies point to the presence of certain neurosteroids secreted during social interaction that promote learning.

Imitation also comes into play as a key factor:

“Imitation [presumably from others in the environment] accelerates learning and multiplies learning opportunities. It is faster than individual discovery and safer than trial-and-error learning.”

In essence, a social context fosters learning.

Brain circuits that support both actions and perceptions are directly involved with learning. As seen in language learning, for example, there is a complex mix of imitative, computational and articulatory processes that come into play as learning proceeds that might be further facilitated or enhanced at specific developmental periods. In general, neuroscientists have determined that there is considerable overlap in the systems brought into play during learning that support both perception and action. From Science:

“For example, in human adults there is neuronal activation when observing articulatory movements in the cortical areas responsible for producing those articulations. Social learning, imitation, and sensorimotor experience may initially generate, as well as modify and refine, shared neural circuitry for perception and action.”

Finally, experts in machine learning and artificial intelligence are taking advantage of the recent findings in social learning, computational modeling and the plasticity of the brain to design software that monitors and uses social cues and environmental factors to enhance learning. In the future this software may be used in tutorial programs or embedded in instructional robots that are specifically “tuned” to enhance teaching practices in classrooms.

References.

New Science Of Learning Offers Preview Of Tomorrow’s Classroom

Foundations for a New Science of Learning

New science of learning offers preview of tomorrow

From baby scientists to a science of social learning

www.public-health.uiowa.edu/icphp/ed_training/ttt/archive/2002/2002_course_materials/Cone_of_Learning.pdf

Adding to a growing body of research in learning that people can acquire new motor skills by watching alone, research at Dartmouth College shows that both viewing and doing are effective in learning new skills. In fact, according to the authors of the study “Human motor skills can be acquired by observation without the benefit of immediate physical practice.” [1] Furthermore, as reported in Science News:

“It’s been established in previous research that there are correlations in behavioral performance between active and passive learning, but in this study we were surprised by the remarkable similarity in brain activation when our research participants observed dance sequences that were actively or passively experienced,” says Emily Cross, the principal investigator and PhD student at Dartmouth.

Cross et al. tested the hypothesis using a video game to teach a series of dance steps after which they compared performances of both actively (rehearsed) and passively (observed) routines. Interestingly,

“We collected fMRI data before and after five days of both visual and physical training,” says Cross, “and there was common AON [Action Observance Network] activity when watching the practiced and observed dance sequences.” [2]

Further information on the study can be gotten here. Correspondence should be directed to researcher Scott T. Grafton.

[1] Cerebral Cortex 2009 19(2):315-326; doi:10.1093/cercor/bhn083

[2] Dartmouth College (2008, July 15). Passive Learning Imprints On The Brain Just Like Active Learning. ScienceDaily. Retrieved June 29, 2009, from http://www.sciencedaily.com­ /releases/2008/07/080714111425.htm