Publications & Resources
CRESST Shiphandling Automated Assessment Engine: Underway Replenishment (UNREP)
Alan D. Koenig, John J. Lee, and Markus R. Iseli
The U.S. Navy is looking to automate the assessment of shiphandling skills to allow for less supervised practice which in turn should reduce instructor load. As part of a broader initiative at the Surface Warfare Officers School (SWOS), CRESST has been working to develop this capability using an automated assessment engine (AAE), which infers student shiphandling proficiency based on meaningful, observable actions taken in the shiphandling simulator, the Conning Officers Virtual Environment (COVE). Ultimately, four separate instances of the AAE will be deployed at SWOS, one for each of the core shiphandling skill areas (called evolutions): Mooring to a Pier, Underway Replenishment (UNREP), Getting Underway from a Pier, and Harbor Transit. This report describes the rubrics and inference model (a Bayesian network) used in the AAE for the UNREP evolution.
Koenig, A. D., Lee, J. J., & Iseli, M. R. (2016). CRESST shiphandling automated assessment engine: Underway replenishment (UNREP) (CRESST Report 853). Los Angeles: University of California, Los Angeles, National Center for Research on Evaluation, Standards, and Student Testing (CRESST).