Performance Assessment, Cognitive Abilities, and Technology: An Application

The increasing technological sophistication of organizations and the concomitant requirement for individuals to process large quantities of information has raised questions concerning the efficacy of traditional approaches to performance assessment within the personnel subsystem. Traditional approaches to aptitude testing have focused on relating psychometric profiles to subsequent job performance. These approaches are subject to criticism in that they use static measures (test scores) to predict the dynamic processes of learning and are heavily influenced by prior experience without reflecting the ability to acquire new information. An alternative to traditional psychometric approaches to personnel selection is the use of rate parameters (reflecting change in performance over time) derived from relatively complex cognitive tasks as predictors of training success. The use of microprocessor-administered tasks to assess cognitive skills and abilities is an integral part of this alternative approach. The use of computer-administered Complex Experimental Learning Tasks (CELTS) for the assessment of learning abilities illustrates the computerized, rate-based approach to performance assessment. The purpose of this paper is to describe an initial study to determine the predictability of learning rate measures for performance assessment and to suggest needed future developments in training as well as job performance research.