With the evolving nature of high‐technology workplaces, personnel are continually confronted with new, complex systems. Possession of accurate mental representations or “mental models” of these systems should enhance workers' understanding and use of the equipment. Incorporating mental model assessment, diagnosis, and instruction into training requires the selection of an appropriate measure of mental model knowledge. Because there is no agreed‐upon measure of this knowledge, selection can be difficult. This study evaluated four mental model measures, with performance as the criterion. Three of the evaluated techniques were predictive of performance; two of these were independently predictive. Determining the relationship between a knowledge representation and performance can offer valuable information for designing and evaluating a training intervention.
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Rowe et al. (1995) studied this question.
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