Comparing Learning Curves of Experts and Novices: A Novel Approach to the Study of Simulator Effectiveness and Fidelity

Abstract

We describe a new approach to the study of simulator fidelity and training efficiency. It is based on comparing learning curves of novice trainees and domain experts in a simulator. The major claim is that if a simulator represents a relevant environment for the training of the operational task, domain experts performance should show a major advantage over novice trainees. Two measures of domain expert performance are important in the evaluation of the simulator. One is the distance (in training hours or sessions) between performance levels of novices and domain experts. It reflects the difficulty of the measured ability and the predicted amount of training required by novices to reach expert levels. A second measure, which represents simulator fidelity, is the distance between expert performance and performance asymptote in the simulator. The approach has been successfully applied in the study of a desktop, partial task flight simulator.