A Framework for Incorporating Affective Learning in Virtual Training Environments

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.