Enabling Automated AAR Development by Abstracting Data Collection from Analysis
David C. Yu, Randy Jensen, Oscar Bascara, Nancy Harmon, Usmc Pmtrasys Orlando · 2007
Simulation based training provides not only the benefits of immersion and interactivity during exercises, but also the prospect of automated after action review. As trainees interact with the system and with each other through various interfaces, the resulting body of data can be used to automa tically draw instructional conclusions that go well beyond traditional measures of effectiveness . However, complex team training architectures often incorporate or support an entire suite of tools and interfaces with diverse protocols and data conventions. This presents a technical challenge for the development of decision -oriented automated after action review, which can be solved with an