ABSTRACT
Human Performance Measurement (HPM) focuses on supporting assessments that enable instructors to better manage training scenarios and provide instruction to students. Research has demonstrated that human performance is a multidimensional, multilevel construct composed of KSAs for both individuals and teams. Due to the complexity of performance and assessment, HPM should consider four attributes to aid instructors in robust performance assessment. PMs in simulation-based training can be described based on the type of data available: automated (computer-based) and observational. Automated measures utilize logic or algorithms to provide results or summary data to aid instructors in the evaluation of student performance. Observational measures depend upon instructors making behavioral observations, either in real time or after the training has ended. A key element of automated HPM is to provide performance values based on a defined scale, which is then available for instructors to interpret based on context.
