Simulations, a group of assessment methods that evaluate applicants’ performance on tasks that are physically or psychologically similar to the tasks required on the job, are increasingly being used as part of selection systems around the globe. They are built on the premise of point-to-point correspondence, the idea that prediction is improved to the extent that there is overlap between the predictor measure and criterion domain. As a group, their value is well understood. Simulations have been found to be among the best predictors of job performance to date and they have been shown to provide incremental validity beyond measures of cognitive ability. Further, they have the potential to exhibit smaller subgroup mean differences than other assessments, to lead to positive applicant reactions and engagement, and can be used as an effective tool for recruitment and branding.

Advances in technology have made simulations easier and more cost-effective to develop, improved their fidelity and prediction, expanded construct measurement and enhanced applicant reactions. The cutting-edge simulations of today will rapidly become outdated and replaced by fully immersive serious games. With the rapid proliferation in use, a gap between research and practice has started to open up. For example, questions related to the potential for the introduction of construct irrelevant variance, the optimal balance between fidelity and utility and cross-cultural validity generalization needs to be addressed. Despite these gaps, simulations represent the only assessment that can simultaneously measure the complex interaction of traits required for job performance and offer perhaps the most potential for improving and expanding the science of measurement and selection. As the types and uses of simulations expand, it will be important to bridge these research gaps and ensure that the science keeps pace with practice.

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