Computer-Adaptive Assessment of Temperament to Support Personnel Selection and Classification Decisions

We propose using our recently developed IRT model for scoring multidimensional pairwise preference items as the basis for a computerized adaptive assessment of personality that is designed to be fake resistant. The items will consist primarily of pairs of personality statements from different dimensions that are matched on social desirability. A respondent's task will be to choose the statement in each pair that is "more like me." Our Phase I research has demonstrated that our item response theory model can successfully recover normative scores from simulated pairwise preference data when multiple personality dimensions are assessed. In addition, our Phase I research identified a set of important and non-overlapping temperament dimensions that are important for performance in military and civilian jobs. In Phase II, we will implement adaptive item selection to increase measurement accuracy and decrease testing time. The name of the software to be developed is the Tailored Adaptive Personality Assessment System or TAPAS.