The COP ShadowBox Training system is proven to help operators improve decision making. This project will help you learn to use the tools as well as teach others within your organization.
MacroCognition, LLC, a predecessor of Shadowbox, LLC, conducted a tutorial as part of the COP semi-annual meeting to instruct participants in how to utilize the Shadowbox Technique. A user’s manual was created for use in the tutorial and subsequently revised with feedback from the participants.
The petrochemical, oil, and gas industry faces a continual effort to capture the expertise of experienced operators, and use this captured knowledge to inform emergency and normative process management, and to equip novice process operators with the necessary skills to effectively troubleshoot and manage complex problems. In recent projects with the Center for Operator Performance (COP), MacroCognition LLC demonstrated that ShadowBox®, a scenario-based, cognitive skills training approach, accelerates and enhances novice operators’ abilities to identify critical problems during troubleshooting scenarios. In addition, qualitative findings indicated that operators preferred this method of training, describing it as realistic, relevant, challenging and engaging. To this point, MacroCognition LLC has developed and deployed ShadowBox, but this presents a bottleneck for many organizations. We propose to create a comprehensive user guide for trainers and supervisors to independently create and deliver cognitive training techniques such as Decision Making Exercises (DMX) and ShadowBox. These resources will include strategies for knowledge capture and transfer, and the organization and distribution of expertise using scenario-based methods. The user guide will also suggest methods to integrate ShadowBox and DMX training into an organization’s existing training modules (e.g., on-the-job training, simulation training). Lastly, we propose to develop Train-the-Trainer materials and a workshop.
Process control operators in the fuel and petrochemical industry rely on rules, procedures (e.g., checklists), and analytical tools to mitigate errors and improve operations, particularly in emergency situations. These tools serve as effective memory aids (reducing workload), safeguards against workflow interruptions, and training aids for novices. They also can facilitate team coordination. However, these procedural solutions are designed to work in well-ordered situations, not complex and dynamic settings that panel operators frequently experience. Moreover, procedural training tools don’t reflect the cognitive skills that are important to advanced skill development. It is common for process control operators to quickly make sense of evolving situations given limited, uncertain and sometimes ambiguous data. They have to rapidly analyze incoming information, parse critical information from noise, detect patterns and inconsistencies in the data, and anticipate up/downstream impacts. Simultaneously, they are required to prioritize goals, generate plans and restructure these plans given little information to work with. While these skills are critically important to operator performance, they are difficult to systematically capture and transfer within an organization. A large part of expertise moves beyond procedural and rule-based information and comprises of the cognitive and perceptual skills described above. But cognitive skills, as opposed to declarative methods (e.g., procedures, checklists) are difficult to train in the workplace for a number of reasons. First, they often require subject matter experts (SME) and/or trained facilitators engaging with trainees in one-on-one coaching, or in small groups where they can monitor trainee performance and provide individualized feedback. Secondly, cognitive skills involve tacit knowledge making them difficult to articulate in a relevant way. For example, expert operators spot anomalies in the data, forecast potential consequences, and prioritize their approach, but they do this quickly and they don’t typically talk about these cognitions. The industry faces a continual effort to capture the knowledge, skills, and abilities (KSAs) of experienced operators before they retire, and to use this captured knowledge to train new personnel. From a practical perspective, current training typically requires a facilitator or SME and in-house training, which can be costly and inefficient. ShadowBox (Hintze, 2008; Klein, Hintze, & Saab, 2013) was developed to provide cost-effective scenario-based training that addresses these limitations and can be adapted to accommodate various training objectives and workplace constraints.
- Develop efficient tools for rapid knowledge capture and provide a framework for creating cognitive skills training
- Craft knowledge transfer guide, including how to write scenarios, inject expert-informed feedback, and deliver cognitive skills training
- Develop and deliver a Train-the-Trainer module
- Final Reporting and Project Management