Think about a weighing scale. You know that it’s going to tell you how much you weigh when you step on it, and that’s probably it. To reach that conclusion you’re mostly using the occipital cortex, in the back of your mind.
Then somebody shows you a diagram of how a scale works, and the physics behind it. As they explain how it works, the way you think about a weighing scale changes. Now scientists can tell exactly which parts of your brain are activated before, during, and after you learn a process, thanks to a study out of Carnegie Mellon University to be published in the journal NeuroImage.
Researchers used fMRIs to examine activation patterns in brains as the subjects learned the physics behind different tools, including a weighing scale, a fire extinguisher, and a trumpet.
After each step, researchers asked the subjects to think about the object. And after each step, the patterns of thinking changed. The machine they used was able to identify a person’s level of understanding of a concept based on a snapshot of their brain at that moment, co-author Robert Mason tells Quartz. The parts of the brain that you use when learning a physics concept broadly move from the back to the front, Mason says. That’s because while learning the brain is engaged in causal reasoning. By the time people fully understand a concept, he explains, they’re using the frontal cortex, also known as your brain’s executive network, where complex thinking happens.
The findings could have implications for student testing and measuring knowledge. Standardized tests compare a student’s knowledge to an answer sheet. Often that can involve what’s known as ”teaching to the test,” or engaging students in rote memorization and test-taking exercises, instead of exercises to master the concepts. What if instead, you could measure an expert’s brain when they think about the topic, or the teacher’s brain, and then compare the students’ fMRI’s? That would be a true test of comprehension, Mason says. “We may be able to assess how well a person’s brain has learned a concept by matching it to the expert’s brain.” (That said, this would be extremely expensive, he notes, and is unlikely to actually happen.)
More practically, the process could be used to test and improve teaching methods, Mason says. The machine can tell how a brain should look at each level of learning. So if students aren’t understanding a concept, scientists would be able to pinpoint exactly where in the learning process that’s happening, and adjust their instruction accordingly.