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STRATA: Observer-based Measurement Agent Research Support

机译:sTRaTa:基于观察者的测量代理研究支持

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When learning to perform a task it is critical to have opportunities to practice the required behaviors. However, to be maximally effective, it is also the case that such practice needs to be accompanied by meaningful feedback to guide learning. Moreover, when considering how best to measure performance for feedback, it is critical to realize that there are multiple classes of performance measurement that are each essential, and unique, in their own right, including systems-based and observer-based measures. In the work reported here, we address this issue by focusing on a system that enables the collection and the integration of systems-based and observer-based measures. By providing an ability to collect and represent these measures in a common format, we have enabled the use of a wide range of feedback for trainees in simulation-based environments. Not only can complex measures be taken, but observer-based feedback can be integrated quickly and seamlessly, bypassing the traditional time associated with manual processing of observations.

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