When you think often about the same thing, does it take up more of your brain? That assumption informs our cartoons and tee shirts:
But images of brain activity suggest the opposite. The colored sections below show active regions of the brain performing a complicated task for the first time, and then after an hour of practice:
As you get the hang of something, it takes less mental effort to continue it. We knew this: it’s why for centuries we’ve drilled our soldiers in reloading rifles, so they can conserve their working attention for other purposes, like staying alive and shooting.
As a skill or movement shrinks to its long-term minimum footprint, we can locate it precisely in a person’s brain:
I think about this sometimes. When my wife Cyndi first taught jazzercise, learning a routine took her days, the same pop song booming around the house while she recited its choreography. Fifteen years later, she picks up steps to the latest Macklemore and Ryan in about ten minutes, usually while playing Candy Crush on the other screen. Somewhere in her brain I picture a synapse she didn’t have before, whose only job is to represent a grapevine right and two pliés.
Food for thought: what if, along with locating neural networks for body parts and dance steps, you could locate them for ideas? Last year a Kyoto-based research team made news by reading dreams using the same technology — functional Magnetic Resonance Imaging (fMRI) — that produced the pictures here. They did it by first building up a glossary of visual associations, showing their waking subjects images from the web, then used those as references to read their minds while asleep.
This drew from work by a Berkeley team two years prior, which studied waking subjects as they watched movie trailers. Here’s a side-by-side clip of the actual trailer and what the fMRI guessed the subjects were seeing:
So, a blurry mess, but a start, like color TV circa 1939.
Since the brain activity varies from person to person, it represents ideas constructed by the brain as it learns over time. That makes research like this potentially useful to educators.
That is, the day may come when we don’t need testing, transcripts, and samples of student work to see if someone knows something. We can just look.
Which raises a question we can start answering right away: what would we look for?
When we off-loaded memory to writing, around five millennia ago, we changed the relative value of different intellectual skills. Memorization fell back in the sweepstakes, leaving room at the front for things like problem-solving and persuasion.
Our priorities shift again whenever we outsource some brainwork to technology. When my parents were in high school in the early 1950s, they learned to take square roots by hand. When I was that age my textbook listed two steps to derive a square root: (1) find a calculator and (2) press the √ key. An appendix at the back explained the manual procedure for the curious.
Today’s shifts put a new premium on collaboration, persistence, cross-cultural facility, and other ineffable capacities to productively make your way in a connected world.
But about that word “ineffable”: is what we want really so impossible to describe? If I can recognize the neural fingerprint of a chassé left or watching a fight scene, then can’t I also see whose brain is cooperating? And whose is still learning how?
Katharine Stewart, my counterpart in the University of North Carolina System, has a disciplinary background in medical psychology. She’s convinced these capacities aren’t ineffable at all, and that in fact we have been usefully effing them for quite some time. They appear increasingly in the higher ed lit as “non-cognitive” skills: resilience, grit, determination. She cites longstanding parallels from other realms of human development: K-12, social work, and corrections. Indeed, aren’t we just talking about variations on impulse control? Anger management? Deferred gratification?
Those who study education as a discipline may object to my casting this as breaking news, but it’s a fact that hardly any college faculty and administrators know this stuff. We were trained in our separate disciplines, not in learning.
Watching these separate strands of work – in fMRI and in the precision other fields have used to describe non‑cognitive learning – I think we can anticipate the day when they’ll connect. So if the question is “what would we look for?”, then part of the answer is these discrete parcels of unambiguous, identifiable dispositional learning.
Looking ahead to that day, there’s a third strand that needs to catch up, and that’s our relatively primitive approach to assessing learning in the disciplines. Because along with impulse control, cooperation, and a visibly frugal use of attention on practiced tasks, we also expect our college graduates to know a subject well. They still pick a major, and on that part of the new ground we’ve barely set foot.
Since we weren’t trained for any of this, faculty in departments tend to define learning (at least initially) in the simplest way possible, as recall. After that they grope, saying things like “we want our physics majors to think like physicists.” With continued effort, these groups eventually define what they mean in smaller units, the “tells” of physicist-style thinking that reveal proficiency beyond content knowledge. They may look for signs a student can pose a relevant question and then suggest a hypothesis and experiment to answer it – depending on the specialty within physics, maybe by using specific math or pieces of lab equipment.
The trick here is to come up with small, unambiguous signs of such proficiency, indicators that can be recognized as meaningful increments of learning, and recorded for academic credit. As I’ve written before, I think the Threshold Project has promise here.
At some future point the frontiers of these three kinds of work should touch each other, and we’ll have a clearer sense of our students’ learning in a variety of domains, and our institutions’ educational effectiveness:
That may seem unlikely, the idea that we’ll know if you’ve mastered say, writing movie dialogue, by boiling it down to discrete chunks of timing, verisimilitude, characterization, and wit, and checking whether the performance of such work takes up an appropriately small and efficient corner of your brain.
But to me, that’s no more reductive – or far-fetched – than evaluating illness with x-rays and blood tests. As educators we’re a lot like 18th century physicians, who diagnosed and prescribed with semi‑mystical assertions of “humors” and the like, telling patients they might feel better if they breathed smoke or bled into a bucket. Developing a handful of key understandings by hurling content knowledge at freshmen seems no more enlightened.
Or, in the words of my Texas colleague Marni Baker-Stein, we’re like amateur astronomers, on the eve of the discovery of the telescope.
I can’t wait to take a look.