I’ve been taking an online course lately through edX called “Deep Learning Through Transformative Pedagogy” and I’ve already found a mission for academic educators to sort out for us practitioners to improve our teaching outcomes. As an aside, I’ve been trying to sort out what the course-runners really mean by “deep learning” (in the same way I’ve been trying to sort out what Project Zero means by the word “thinking” as I read their book on Making Thinking Visible). It’s all very hand-wavey. End digression.

Here’s the project:

What’s the relationship between the idea of conceptual models as neuroscience and psychology understands them today and what we actually teach in the classroom?

What can we do to support our students’ ability to modify their existing beliefs and to incorporate new ideas into old belief patterns?

As I understand things, experts in neuroscience speak in physical terms of neuroplasticity and in our brain’s ability to modify its structure as we have new experiences. They often speak metaphorically in analogue to that physical view of our brains about our having conceptual models of the world. The models are like complex algorithms, and they exist to interpret our experiences and to make predictions about the world as it unfolds in our ongoing experiences. They would perhaps say that deep learning is about learning to aggregate the facts into models, to revise those models according to experiences that generate instances of cognitive dissonance – and to resolve those differences with as little disruption to the rest of the cognitive model as possible. This allows for integration across knowledge areas (since our brain doesn’t compartmentalize knowledge as a university building might) as well as belief-revision as we experience new and surprising things. This all sounds, frankly, like W.V. Quine’s “web of belief” concept of cognition from the 50s and in Word and Object (1960). There’s something to this.

We classroom teachers seem most often to be thinking in terms of teaching students to apply skills that come structured thinking patterns. Put in terms that seem to link to the neuroscientific approach to thinking (as I understand it, and however underdeveloped my view is)… we want to teach students to analyze their experiences and modify their beliefs and thinking patterns in light of those experiences. Come what may, we hope our students don’t wind up with grossly out-of-whack beliefs (where “out of whack” is determined by a learner’s belief patterns – we hope that those belief patterns non-accidentally match the world).

I wonder most sincerely what the connections are between what is called by practitioners deep learning and what neuroscience has to say about belief patterns, though it will always likely be put in terms of metaphorical analogues. I want a more careful spelling out of the relationships between, say, conceptual predictive models and what can be taught in a classroom.

Anyone have any leads on this project?

Has someone already developed lists of teachable skills that really, truly, and explicitly tie to what we think we know about belief patterns and the way we help students to develop stable and non-accidentally accurate belief patterns?