A formative approach to developing synthetic environment fidelity requirements for decision-making training

Area of Science:

• Cognitive Science
• Human-Computer Interaction
• Simulation and Training

Background:

• Effective decision-making training requires realistic synthetic environments.
• Current approaches may not adequately capture the complexities of real-world decision processes.
• Designing novel training simulations necessitates a robust framework.

Purpose of the Study:

• To present a new methodology for creating design specifications for decision-making training synthetic environments.
• To develop a model that identifies pertinent information for decision-makers within these environments.
• To establish a framework applicable to both new and existing simulation designs.

Main Methods:

• Modelling real-world constraints governing decision-making activity.
• Focusing on potential future states of the decision-making process.
• Developing an actor- and event-independent domain model.
• Analyzing relationships between information elements and environmental understanding.

Main Results:

• A robust model of decision-making constraints was developed.
• The approach identifies key information pertinent to decision-makers.
• The model is applicable across various scenarios and adaptable to different actors.
• The methodology provides a foundation for designing and evaluating synthetic training environments.

Conclusions:

• The proposed approach offers a systematic way to design synthetic environments for decision-making training.
• It enhances the identification of critical information for training purposes.
• The methodology is valuable for creating novel training simulations and assessing existing ones.