Scientists have developed a novel artificial intelligence (AI) that can measure how well students understand a concept based on their brain activity patterns. The study, published in the journal Nature Communications, is one of the first to look at how knowledge learned in school is represented in the brain. To test knowledge of concepts in STEM, researchers from Dartmouth College in the US examined how novices and intermediate learners’ knowledge and brain activity compared when testing mechanical engineering and physics concepts. They then developed a new method to assess their conceptual understanding.
Twenty-eight students participated in the study, broken into two equal groups: engineering students and novices. Engineering students had taken at least one mechanical engineering course and an advanced physics course, whereas novices had not taken any college-level engineering or physics classes. At the start of the study, participants were provided with a brief overview of the different types of forces in mechanical engineering. In an fMRI scanner, they were presented with images of real-world structures (bridges, lampposts, buildings, and more) and were asked to think about how the forces in a given structure balanced out to keep the structure in equilibrium.
Before the fMRI session, participants were also asked to complete two standardized, multiple-choice tests that measured other mechanical engineering and physics knowledge.Before the fMRI session, participants were also asked to complete two standardized, multiple-choice tests that measured other mechanical engineering and physics knowledge.”Based on the similarities in brain activity patterns, our machine learning algorithm method was able to distinguish the differences between these mechanical categories and generate a neural score that reflected this underlying knowledge,” he said.
“Presumably, this acquired knowledge must be reflected in new patterns of brain activity,” said Kraemer.
“However, we currently don’t have a detailed understanding of how the brain supports this kind of complex and abstract knowledge, so that’s what we set out to study,” he said.
“The idea here is that an engineer and novice will see something different when they look at a photograph of a structure, and we’re picking up on that difference,” said Kraemer.