With all the talk about “science of” [reading | writing |computing | behaving] these days, there’s little wonder that people are interested in the human brain. Wait, though! What does “plasticity” mean?

The fundamental idea is that brains (and not just human brains...flatworms to porpoise) change on the basis of experience. Their brains get “rewired.” They learn! When conditions are X, they do M; when conditions are Y, they do N. …and when conditions are F, guess what, humans are likely to do P…just think about it. We may think that we are immune from learning, but we also have plasticity.

We might want to get more technical and consider how structures and functions in the brain change: lengths of dendrites, density of structures, blood flow, and more. But, what’s important here, for this note, is that the changes are pretty tightly correlated with experience. Factors such as aging, hormones, pathology, and more—especially including instruction—cause these biological changes. But, getting more techical is just a race down a rabbit hole.

In our article from 2007, Dan Willingham and I argued that the connections between neuroscience and education were often mis-aligned because the levels of analysis were quite different. Education must examine behavioral levels of analysis (e.g., classrooms), but neuroscience analyzes quite different levels (e.g., central nervous system events). Here’s the abstract:

Although many articles have addressed the relationship of neuroscience and education at a theoretical level, none has considered as a practical matter how one integrates neuroscientific data into a behavioral theory that uses hypothetical constructs. We describe 4 techniques by which researchers may do so: (a) direct observation of hypothetical constructs in the brain, (b) validation of hypothetical constructs through brain imaging, (c) using neural architecture to infer a behavioral architecture, and (d) using well-developed knowledge of brain function to select among competing behavioral theories. A detailed examination of these 4 techniques indicates that they are amenable to educational research and, indeed, have been used to inform research and theory. We argue that these techniques are not applicable to all educational research problems, but rather they are appropriate to relatively low-level behaviors (e.g., reading) rather than complex behaviors (e.g., classroom management).

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In particular, because Dan and I used it in our analysis, let me illustrate the pont with a swipe at reading again. As research (Shaywitz et al., 2003; Shaywitz et al., 2004) about the brain and reading reveals, systematic and explicit instruction in the alphabetic principle allows kids, including those whom we might predict to be “dyslexic” and those who already are experiencing reading problems, to learn to read.

And...AND...it changes their brains. That is, teaching causes brain plasticity. No joke!

So, let’s get over it. The brain doesn’t cause learning. Instruction causes learning. Learning changes the brain. Instruction promotes plasticity. Plasticity is a reflection of instruction.

Now, the next relevant questions are about how our instruction can cause better (or worse!) changes in learners’ brains.

You know where we can learn about that? Not the science of reading | writing | arithmetic. Sure, some folks who talk about the “science if X” say some useful (uhm) poop but there’s a better source:

We can learn it from the research about TEACHING! So, could we get back to the theme? Please teach our kids well!

Oh…and let me be sure to wish a happy b’day (7 Sep) to my late sister, Hannah. I’ll remember her with happiness and joy. May all you readers have such wonderful siblings as I have had.

Sources

Shaywitz, B. A., Shaywitz, S. E., Blachman, B. A., Pugh, K. R., Fulbright, R. K., Skudlarski, P., ... & Gore, J. C. (2004). Development of left occipitotemporal systems for skilled reading in children after a phonologically-based intervention. Biological Psychiatry, 55(9), 926-933.

Shaywitz, S. E., Shaywitz, B. A., Fulbright, R. K., Skudlarski, P., Mencl, W. E., Constable, R. T., K. R., Pugh, K. R., Holahan, J. M., Marchine, K. E., Fletcher, J. M., Lyon, G. R., & Gore, J. C. (2003). Neural systems for compensation and persistence: Young adult outcome of childhood reading disability. Biological Psychiatry, 54(1), 25-33.

Willingham, D. T., & Lloyd, J. W. (2007). How educational theories can use neuroscientific data. Mind, Brain, and Education, 1(3), 140-149. https://doi.org/10.1111/j.1751-228X.2007.00014.x