"I was thinking that, but I wasn't sure..."

As I was working with a student the other day, I invited them to offer the answer to a question similar to one we’d worked on previously that session. Their initial response of “I don’t know” was, after I gave the answer, replaced by this expression of ambiguity: “I was thinking that, but I wasn’t sure.”

In my teacher brain, this comment brings up a visual of a hiker on the ridge looking down each side of the mountain, wondering which one will lead them home. You see, as we learn, our brain is creating models of the information as we try to put the pieces together in a way that’s coherent with what we’ve been taught. A neglected nuance of learning is that those models are often incorrect or incomplete - and that is totally normal!

In fact, this is why practice and feedback are so important to developing mastery - we need to test the models we’ve made up in our heads to see if they hold water when rubber meets the road. Too often, students are taught that the failure of a model they’ve constructed in their heads means they will never understand it, rather than learning they’re simply on the way to understanding it. As a result, students begin to avoid testing the models in their head so they don’t experience the shame and discomfort the “failure” implies for them.

Now back to my student’s comment: in their head, they were on the cusp of deciding which model (or side of the mountain) made more sense, but hadn’t committed. Now, I certainly encourage better navigation practices if you’re actually hiking, but we can all recognize that committing and starting down the mountainside will eventually lead to a clearer understanding of whether home was that direction or not. When I’m helping a student and they express this kind of ambiguity with a concept, I ask them to commit to a model in their head and then work through how to figure out if that model ends up making sense.

Long story short: encourage learners to commit to a mental model, test it, and seek support to create a more accurate model going forward.