RESUMEN
The present review focuses on the development of a performance battery generation system that selects performance tests most applicable to particular jobs. First, a list or taxonomy of cognitive and performance skills that are involved in real-world jobs or missions is developed. Based on this list, an "armory" of performance tests probing those skills is identified. A new technique is then developed to select from that armory the minimum number of tests that optimally probe the demands of a specific job or mission. While specifics of these developments will continue to evolve, it is hoped that the general framework described here will help close the gap between laboratory testing and real-world tasks, and form the foundation of the way performance test batteries will be developed in the future.