Sure, ShadowBox is great, and makes high fidelity simulation even better, but what about LOW fidelity or generic simulation?
Dr. Gary Klein and Joseph Borders were tasked with determining how Shadowbox would work with a generic simulator, rather than the plant specific in the previous project. A loaner simulator was supplied to CITGO for use in the project. Unfortunately, lack of familiarity with simulator operation bogged the project down. A slight performance improvement (10%) was identified for use of Shadowbox with the simulator versus without.
The objective of this effort is to examine whether the Shadowbox technique can be combined with low-fidelity simulation to improve operator decision making.
Can the Shadowbox technique be combined with low-fidelity simulation to improve operator decision making in an experiential environment?
NOTE: This project was executed as an additional phase to the ShadowBox Training Method II project. The contract for Shadow Box Training Method II was modified to reflect additional funds and time as required for this phase. The contract can be found on the ShadowBox Training II project webpage.
In a previous project with the COP, this researcher team explored high fidelity simulator training procedures and investigated how ShadowBox can supplement that technology. They designed four training scenarios centered on troubleshooting combustible issues in the furnace subsystem of an ethylene cracking plant. The scenarios were created and delivered on a high fidelity, full-scope simulator.
As operators worked through each training exercise, the simulation was paused at various points to ask cognitive directed questions (e.g., what information are you seeking, what are your priorities/goals, cues to monitor, actions to take). Operators responded to the prompts on paper and provided their reasoning. After completing the simulation, the training operator restarted the scenario and walked them through the optimal (expert) response as well as alternative options. In doing this, they discussed the cognitive decision probes, and the operators compared their responses with the trainer’s solutions. The decision process concluded with the trainee recording lessons learned and/or insights from the scenario exercise.
Findings from this study suggest that, as operators were exposed to more ShadowBox-simulation exercises, operators completed the scenarios faster and, on average, they produced a 25% improvement in identification of the root cause of the problem. This project was an initial attempt to integrate cognitive skills training into existing simulator exercises. For the current effort, the researcher shall create a similar methodology using a low-fidelity crude oil unit simulator.
MacroCognition LLC will provide the following project deliverables:
1. Methodology for creating scenarios using low fidelity simulation
2. The two scenarios that we design on the crude oil simulator will be delivered in some format that is accessible to CITGO (e.g., ShadowBox software)
3. Final project report will include quantitative and qualitative results from the pilot evaluation