For reasons (that elude me, except ongoing curiosity), I’ve been looking at ‘content’. That, of course, has meant models, and examples, and feedback. However…my co-director at the LDA*, Matt Richter, chides me that schemas are a goal of learning. And, of course, I was steeped in schemas as a grad student in cog psych. On the other hand, I’ve pushed for mental models as the complement to examples (and the basis for feedback). So how do I reconcile schemas versus mental models?
I got a boost on my recent explorations via this post from Paul Kirschner distinguishing between the two. His characterization of schemas is as fixed knowledge about the world, while models are systems reflecting the dynamics. He also talks about how misconceptions can come from either, and they’re separate, suggesting they’re distinctive.
My searches, however, led me to this other piece by David Didau that argues that they’re not functionally dissimilar. They’re conceptually distinct, but functionally you need a combination. Which makes sense, because there’re interrelations.
The reconciliation I’m finding is that we need models that explain how the world works. As I’ve maintained, you have to predict the way the world reacts to this perturbation versus that one, and then decide which outcome is better. However, you can’t really do that until you know what the elements are, and the relationships between them.
The argument then becomes how you teach. And I reckon you kind of build them iteratively, actually, because you need some to explain some, and then some more to explain some more. Which isn’t all that unfamiliar. I use ‘builds’ to help people see how a model is built, by exposing the diagram bit by bit.
That is, ultimately, that it’s not about schemas versus mental models, it’s about schemas and mental models. Which is a good resolution. Of course,
* Our society for evidence-informed L&D.
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