Enhancing Soldier Performance: A Nonlinear Model of Performance to Improve Selection Testing and Training

Advanced U.S. Army technology and hardware systems place a higher cognitive demand on the individual soldier than ever before. Sophisticated weaponry and hostile mission environments of modern conflict threaten to overwhelm the capacities of the human operator. New selection and training instruments are being developed to (a) select people most likely to perform well under high cognitive demands, (b) identify weaknesses in people, and (c) alter or train the person to improve response to the increased cognitive work load. The primary goals of this Phase I SBIR effort were to develop a new conceptual model and to suggest new testing and training approaches to handle the cognitive complexity of many Army tasks. Such approaches may enhance the identification and training of people to perform cognitive tasks efficiently during conditions of extremely high work load. To begin this process, a general nonlinear model of performance was first developed by exploring performance theory; this theoretical orientation was then translated into practical assessment and training tools to select and enhance people likely to excel at tasks demanding particular combinations of skills. A nonlinear approach to combining these procedures into a practical test battery and a specific training approach based on this model were proposed. AH-64 Aircraft, Function analysis, Modeling, Task analysis, Aviator work load, Longbow Apache, NASA-TLX, Work load prediction, Crew station design, Mission analysis, Pilot-vehicle interface