Developing High Fidelity Synthetic Task Research Environments Using Gaming Technology

Game technology can efficiently produce Synthetic Task Environments for training, research and assessment. Typically this technology is exploited with an entertainment-oriented game engine. However a fully functional STE requires features outside the engine's original design. This compels engineers to work around the architecture and deliver code which is compromised and complex. The system becomes more unstable as more features are added. Some features can never be added. A direct approach avoids these problems. We prefer to build an engine that produces Synthetic Task Environments empowered by game technology. Its clean architecture supports new features without instability. The Works game engine was built to serve the needs of research and training. We propose to demonstrate the value of this approach. In our study, we will measure the ability of the engine to efficiently deliver training outcomes. Two new components will be added to the engine: The first is a set of metrics designed to facilitate formative and summative performance assessment (i.e., provide feedback with respect to overall performance, component performance, and incremental learning progress).. The second is a game design tool which enables trainers, researchers and subject matter experts to design a game framework to deliver specific results.