Instrumenting a Perceptual Training Environment to Support Dynamic Tailoring

Simulation-based practice environments would be more valuable for learning if they supported adaptive, targeted responses to students as they proceed thru the experiences afforded by the environment. However, many adaptation strategies require a richer interpretation of the student’s actions and attitudes than is available thru the typical simulation interface. Further, creating extended interfaces for a single application solely to support adaptation is often cost-prohibitive. In response, we are developing “learner instrumentation middleware” that seeks to provide a generalized representation of learner state via reusable algorithms, design patterns, and software.