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Techniques for Modeling Human Performance in Synthetic Environments: A Supplementary Review
By Frank E. Ritter, Nigel R. Shadbolt, David Elliman, Richard M. Young, Fernand Gobet, and Gordon D. Baxter
Editor: Frank E. Ritter
Improved technology and automation are being advocated as the solution to problems of lagging productivity and human error. However, the very technology that is sought to improve productivity and reduce human crewmembers' workload often has the opposite effect. An alternative is human-centered automation that aids and supports the human crewmember. To design it requires an expanded view of workload as a strategic task management problem, contrasted with the more traditional view of workload as competition for a limited pool of processing resources at any one time. We introduce a theoretical framework for understanding human cognitive processing that builds on active theories of perception, connectionist theories of associative knowledge structures, and schema theories of comprehension. The framework addresses mechanisms of attention, situation awareness, and real-time management of multiple streams of activity. The implications of this framework for the successful management of complex multi-task systems are discussed and examples from the recent literature are presented suggesting personnel selection as well as training and design alternatives. These alternatives are directed at improving information sampling, reducing processing complexity, making information conform to human memory structures, scheduling to avoid overload, and adaptive computer-aiding procedures. Throughout the monograph, suggestions are made for substantive research to extend the limited existing literature and to focus on the theory and application of human cognitive processing.