Improving performance in high risk environments using guided distraction and iconic cues. This project tests a novel strategy to assist operators in high-risk automated environments, in order to maintain their performance in low workload situations. Using guided distraction, this project will be able to show improvements in attention to critical tasks and in overall system performance, thereby reducing the potential for error.
Choice models for learning and memory. Life is filled with familiar choices that often require quick decisions about objects in the environment and the contents of memory. This project examines how we learn to make rapid and accurate choices and how we quickly asses the level of confidence we have in recognition decisions based on our memories.