In my last post, I made an extended analogy between today’s ed tech and 19th Century medicine. My core argument was that effective ed tech cannot evolve without a trained profession of self-consciously empirical educators any more than effective medication could have evolved without a profession of self-consciously empirical physicians.
In this post, I’d like to go beyond analogies and look at the actual state of some cutting-edge cognitive science. I want to do this for several reasons. First, a lot of educators are skeptical or even cynical regarding the potential relevance of this work to the ways that they think about teaching. This is completely understandable, particularly given that most educators hear about this sort of research through product commercials or hyperbolic media puff pieces. By exploring the science in some detail, I want to show that having a basic understanding of even foundational research that has no direct classroom applications can stimulate the thinking of classroom educators in useful ways.
Second, I want to show that even educators with no background in science or math can achieve an empowering level of cognitive science literacy with a reasonable investment of time (like the time it takes to read a long blog post, for example).
And finally, I want to show that, after we strip away the hype and the ennui it engenders, we can recover a sense of wonder about the science while maintaining a sense of realism about its practical applicability. I have chosen to characterize the methodological paper I’ll be explaining as an attempt to create a “microscope of the mind.” That’s dangerously close to “robot tutor in the sky that can semi-read your mind” territory. I hope to demonstrate that there is a non-hyperbolic sense in which we can believe that analogy to be a reasonable one.
Here’s how I’m going to do it:
I am going to explain a research study on cognitive neuroscience. It’s not a big, sexy paper that gets coverage in outlets like Wired. It’s a methodology study. I’m going to explain enough of the basic underlying concepts in math, physics, and cognitive psychology for you to be able to get the gist of the paper and judge its significance for yourself. I’m going to explain how fMRIs work and what machine learning is. And I’m going to explain the larger context of why the researchers tried this particular experiment and how it is relevant to our larger understanding of how people learn. Along the way, I will touch on topics as diverse as theology, Russian literature, and the miracle of selfies, but always with the goal of showing how the science can be accessible, interesting, and relevant to non-scientists.
This is not a short read, but I hope that it will reward your effort.