Virtual Reality Training System Development Guidance Tool for Multimodal Information Fidelity Level Selection

Ensuring that training systems are based on operationally, theoretically, and empirically driven requirements is a key component to improve VE system effectiveness because it focuses on the specific training needs and goals at contextually appropriate task and expertise levels. Although requirements form the basis of system design, their full implementation (i.e., complete realism to the operational environment) is usually limited by practical issues (e.g., cost technological capability). Furthermore, while a high fidelity option may present the most realistic representation of the operational environment, designers should consider a few issues before implementation: 1) Is the high fidelity option meeting the targeted training goals?, and 2) Are there practical, lower cost alternatives offering sufficient levels of functional fidelity to reach the same training goals? In addition to operational context, research theory and empirical findings on multimodal cues and fidelity can help generate viable alternative design solutions and opportunities to augment or enhance VE training system design. To address these issues, this effort proposes to develop the Tool for the Optimization of Multimodal Cues in Advancement of Training System Design (TOMCAT). This tool will partially automate two important components for successful design of VE training systems: 1) Context - helping users define operational/contextual system requirements by identifying critical tasks with their required cues and presentation fidelity ; 2) Optimization (of the requirements) - integrating theoretical, empirical and cost benefit findings to help users select a system both cost-effective and training task centered.