Mental Workload: Assessment, Prediction and Consequences

Abstract

I describe below the manner in which workload measurement can be used to validate models that predict workload. These models in turn can be employed to predict the decisions that are made, which select a course of action that is of lower effort or workload, but may also be of lower expected value (or higher expected cost). We then elaborate on four different contexts in which these decisions are made, with non-trivial consequences to performance and learning: switching attention, accessing information, studying material, and behaving safety. Each of these four is illustrated by a series of examples.