Representations of Recently Learned Conceptual Knowledge in the Mind and Brain
 

Abstract: Understanding how the mind of an expert differs from that of a novice has long been a focal point in cognitive science. Over the years, more research has begun to explore not only these two endpoints of learning, but rather to fill out more details along the trajectory. Recent work in my lab has aimed to examine the types of knowledge representations that form early on in this process, as a novice learner is beginning to grasp new concepts and connect them to their previously learned knowledge. Working with experts in domains as broad as mechanical engineering and American Sign Language instruction, our lab has developed novel learning paradigms and neuroimaging analysis techniques to characterize and quantify the learning that occurs on an individual level. In this talk, I will describe our approach that leverages large-language models and machine learning algorithms to analyze both behavioral and neural data, indicating what types of features learners tend to latch onto and how well they can understand complex concepts at the early stages along the path to eventually becoming experts (or at least leaving their novicehood behind).