SBIR-STTR Award

The effectiveness of current Virtual Environment training systems can be greatly enhanced by integrating affective components into those systems. In the proposed effort, a theoretical model that we developed for utilizing auditory feedback to modify the user's affective state will be expanded upon to include visual and haptic modalities. This will provide a foundation for incorporating affective components into training systems. Next a pragmatic analysis of existing affective state assessment approaches will be carried out in order to select approaches that are suitable for use in deployable systems. Current systems do not encode training instructional context so, in effect, they operate without a lesson plan. As part of this effort we will devise a scheme for encoding instructional context so that training outcomes as well as expected affective states for each state of learning can be specified in training systems. Finally, a specification will be developed for a prototype system that capitalizes on an existing training simulation framework that we have been developing for a number of years and is currently used in deployed and commercial systems. This approach will minimize risk and development time and will greatly enhance the commercialization potential of this technology.

Keywords:
Affective Learning, Training, Virtual Envrionements

Changes in modern warfare have resulted in frequent and lengthy deployments for US military personnel. These changes necessitate the development of training alternatives to the costly and time consuming live training exercises. One alternative to live training is the use Virtual Environment (VE) based immersive training systems. Current VE based systems focus exclusively on incorporating the psychomotor and cognitive aspects of learning. This may lead to decrements in learning outcomes due to the lack of an affective learning component in those systems. If training systems are to be effective, they must consider the user’s affective state as a key component in learning. Through a process of affective state detection and induction, VE based training system can better approximate the real-world experiences encountered by soldiers upon deployment in the field. In Phase 2, VRSonic will design and develop an immersive VE system that incorporates affective learning. Specific activities in phase 2 include 1) Investigating affective state detection algorithms, 2) Expanding the VE lesson plan concept into a selected domain, and 3) Developing the affective state integration mechanism. Ultimately, VRSonic will build a working run-time system that integrates affective cues in immersive training systems.

Keywords:
Affective Learning, Virtual Environments, Training