A Systematic Review of Empirical Measures of Workload Capacity

Abstract

The usability of the human-machine interface is dependent on the quality of its design and testing. Defining clear criteria that the interface must meet can assist the implementation and evaluation process. These criteria may be based on performance, the quality of users’ experience, error prevention, or the broad utility of the interface. In this article, we motivate the use for workload capacity as an empirical measure of usability. We first describe generic and specific uses for workload measures in terms of adaptive interfaces. We then carry out a systematic review of how workload capacity has been empirically measured, based on 172 relevant literature sources from psychology, neuroscience, engineering, and computer science. We then analyse and report on how workload capacity and related constructs, such as perceptual load, attention, and working memory have been defined and measured in these sources. We discuss similarities and differences between constructs and identify opportunities for integrating real-time workload capacity measures into dynamic interfaces.