Towards a Closed-Loop Training System: Using a Physiological-Based Diagnosis of the Trainee's State to Drive Feedback Delivery Choices

摘要

Designers of a closed loop scenario based training systems must have specifications to drive the decisions of whether or not performance feedback is appropriate in response to student behavior, the most effective content of that feedback, and the optimal time and method of delivery. In this paper, we propose that physiological measures, when interpreted in conjunction with information about the learning objective, task environment and student performance, could provide the data necessary to inform effective, automated decision processes. In addition, we present an overview of both the relevant literature in this area and some ongoing work that is explicitly evaluating these hypotheses.