Comparison-Based Predictions and Recommendations for Army Maintenance Training Devices

摘要

This study is part of a larger project to evaluate the use of Comparison-Based Prediction (CBP) techniques as a method to estimate the effectiveness of new training devices and concepts, and to generate design recommendations. The goal of this effort was to CBP to predict the savings in training time that might be realized by introducing maintenance training devices into automotive courses for Army personnel. The intent was to learn about the strengths and weaknesses of the method when used by Army instructional personnel. A secondary goal was to use CBP to generate recommendations for improving the design of maintenance training devices. Predictions were generated separately for two prototype training devices, one developed by Grumman and one developed by Seville/Burtek for use in automotive courses at Aberdeen Proving Ground and Edgewood Arsenal. The approach used Subject Matter Experts (SMEs) to (1) identify appropriate comparison cases to be used to provide baseline data, (2) estimate differences between the prototype and the comparison cases and (3) generate predictions by adjusting the baseline data to account for the differences between the prototypes and comparison cases. Subject Matter Experts compared the two prototype training devices either to actual equipment trainers or to maintenance simulators procured for the Air Force.