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I__. - International Military Testing Association

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requirements, but their number and complexity often makes trade off decisions<br />

difficult because there i.s no context for their Cost. The literature has not<br />

helped either. A U.S. Air Force review of 114 human factors studies from<br />

1958-72 Eound that the physical characteristics of the stimulus were most<br />

often the signif icant factors in performance outcomes and there were few<br />

interactions.<br />

But these studies tended to ignore the contribution of practice<br />

or individual differences. This general finding suggested the multivariate<br />

(holistic) approach that was subsequently employed by the Navy in over a<br />

decade of simulator research, ranging from carrier landing, to air-to-ground<br />

combat , to Vertical Take-Off and Landing (VTOL) studies. The strong inference<br />

suggested by the results of these later studies was that people accounted for<br />

the most variance in performance, followed by training manipulations, and then<br />

by equipment variations.<br />

In this work, what was surprising was the modest amount of performance<br />

variance that could be accounted for by equipment features. In partitioning<br />

the performance variances over numerous experiments, equipment accounted For<br />

15-20%) trials of practice accounted for lo-25%. and people accounted for<br />

50-80%, with error usually in the 25-50% range. Again, interactions were few<br />

and far between. This implied that these main effects could be traded off if<br />

you started with them in the first place! Thus was born Isoperformance. That<br />

is, because some pilots are simply better than others, because repeated hops<br />

are costly, and because costly changes in equipment features may produce<br />

minimal changes in performance, we should concentrate on trade-offs among<br />

these known relations to bring about desired goals rather than only one or<br />

another mechanism. After the relative contributions are determined, a price<br />

tag can be placed on all dimensions and the cheapest solution sought.<br />

Isoperformance is therefore designed to accomp.lish Personnel, Training and<br />

Equipment trade-offs. In the Isoperformance complete program, the term<br />

Personnel can represent such features as sensory capabilities, cognitive and<br />

information processing abilities, anthropometry, or test scores, such as the<br />

Armed Services Vocational Aptitude Battery (ASVAB) scores, (presently the<br />

default condition). The term Training can represent such features as<br />

practice, sequence and series effects, learning, training regima and<br />

schedules, or number of sessions. The default condition is trial of practice.<br />

Similarly, the term Equipment can represent new vs. old, smart vs. dumb.<br />

hi-fidelity vs. low-fidelity, or any general A vs. B conEiguration, which is<br />

the default condition. The data sources for estimates of the scale values for<br />

these variables can come from various origins, including lay opinion, the<br />

scientific literature, explicit experiments, or technical data bases.<br />

Isoperformance Curves<br />

Figure 1 presents an illustration of IsoperEormance using two categories<br />

and one equipment feature (the current technoloqy).<br />

The Personnel category is divided into high- and low- to medium- aptitude<br />

groups, the Training time allotted is 9 weeks, and the proport ion of people<br />

that is desired to complete the training successfully is set at 50%. One can<br />

see that it takes the high-aptitude group only 4 weeks to achieve the SM:~<br />

proficiency level that it takes the low- and mediurr-aptitude group to achieve<br />

in 8 weeks.

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