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Retention of Digital Skills Following Distributed and Traditional Training

机译:分布式传统培训后数字技能的保留

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摘要

As digital systems proliferate in the Army, there is a need for commanders to understand how to best maintain these critical warfighter skills. In the present report, skill retention for the Force XXI Battle Command Brigade and Below (FBCB2) digital system was investigated following traditional face-to- face training and distributed learning (dL) training. This second type of training was examined because little is known about training digital skills using this method. Operator skills were measured immediately and eight weeks following the training. There were no differences in overall performance between the dL and traditional students at baseline suggesting this system can be trained effectively in a dL environment. Both groups also showed similar rates of forgetting after the eight-week retention interval. Overall performance declined significantly from 71% of steps correct at baseline to 62% correct eight weeks later. Characteristics of the digital system and of the participants contributed to forgetting. These findings indicate that FBCB2, and presumably other digital systems can be effectively trained in a dL environment. Additionally system and individual characteristics that contribute to skill decay were identified and can be used to both improve system training and system design.

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