Can Cognitive Theory Guide Human Factors Measurement?

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Abstract
This paper considers four questions about measurement in human factors proposed by David Meister. The fundamental problem of measurement is deciding what to measure. Theory can help answer this question by telling us where to look in complex system environments. Measuring theoretical parameters (such as d1 and beta from signal detection theory) may prove more helpful than measuring only different types of errors. Measurement in human factors must provide meaningful assignments of numbers to objects that satisfy both tribes: scientists and practitioners. It must also deal with the problem of emergent levels. Human factors must create its own brand of theory to meet its unique measurement requirements. One possible solution might be using combinations of sub-models based upon cognitive theory and network simulation. Such a theoretical human factors model could have both scientific rigor and operational utility.

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