3214 Mechanical Engineering Building
The Naturalistic Decision Making and Simulation Laboratory covers a broad spectrum of research interests, primarily within the aviation and health care industries. Some recent areas of study include interruptions and distractions during surgery, simulated flight training, and cognitive ergonomics for universal design.
Current Research Projects:
Redesigning Weather Related Testing and Training of General Aviation Pilots
This project focuses on pilot decision-making and the development of scenario-based flight simulation training to fill holes that exist in root-level flight training, which cause human error to reverberate throughout the aviation system. Specifically, the study aims to improve issues with novice pilots inadvertently flying into inclement weather conditions, and the research methods utilize high fidelity simulation software that systematically replicates environmental factors from historical weather data and other standardized aeronautical information elements.
The technologies developed in this study over the past several years shift the traditional focus of flight simulation from mechanical replication toward the simulation of cognitive elements that can be utilized to teach information-processing skills more effectively during ab initio flight training, and the specialized tools can be employed to increase flight training efficiency and accuracy at all levels of training with any sophistication of simulation hardware.
Improving Cardiac Surgical Care: A Work Systems Approach
Over the past 50 years, significant improvements in cardiac surgical care have been achieved. Nevertheless, if improvements in surgical outcomes are to continue, quality and patient safety programs must focus on rectifying work systems factors in the operating room that negatively impact the delivery of reliable surgical care.
Our long-term goal, therefore, is to further improve cardiac surgical care by enhancing or re-engineering the surgical care process. The immediate goal of this project is to develop a methodology for reliably identifying work systems factors in the operating room that negatively impact surgical performance, so that future data-driven interventions for reducing errors and improving surgical care can be developed and evaluated.