Previous studies have used the mental models construct as an ex-post explanation for poor performance on complex tasks, but the effects have remained untested. This experimental study measured and tested the role of mental models in a complex decision environment. Participants worked on a product lifecycle simulation under one of two levels of complexity for three blocks of 40 trials before measures of mental models were assessed. Immediately following the measures, participants completed another three blocks of 40 trials. Ten weeks later, participants completed another three blocks of 40 trials each. The results indicate that ability and task complexity are significant predictors of mental model accuracy, and that mental model accuracy and complexity are significant predictors of performance. Mental model accuracy is also related to the decision heuristics employed on the task, and the decision heuristics are related to performance. The results suggest there is potential to increase performance in complex decision environments by up to 50% through improving decision making. Validating these measures of mental model accuracy will enable researchers to incorporate this variable into their study designs in future research, and begin to identify levers for improving causal inferences, mental model accuracy, decision heuristics and performance.

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Date created

• 2005 July 17-2005 July 21

Type

• Document

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• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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cc5bb0ac12a5b68b26b1583548898dae

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3c582e6f5cf305ef0030c7471b499022

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23d738ba88f8333bc39725f9cb5bd0b8

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Collection

System Dynamic Society Records

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Collecting area

• This collection is part of the University Archives