As yet underdeveloped is the psychology of human learning as it pertains to manual control tasks in fully dynamic, multi-degree-of-freedom domains. While we currently possess the capacity to teach these tasks, we are unable to predict how well people will do in these domains or how rapidly they will learn.
The project studies human performance and acquisition of sensorimotor tasks in real and virtual environments. Human motion data and performance of various skills by performers who exhibit linear performance gains will be analyzed and compared to data for subjects who rapidly acquire skill and exhibit nonlinear performance gains. This data will inform the development of more accurate models of sensorimotor skill acquisition, and doing this should lead to improved understanding of training methods in human motor learning domains.
