Behavioural Measurement of Cognitive Workload

Abstract

Everyday we are faced with a myriad of tasks to complete, ranging from the most simple to highly complex. Our ability to complete such tasks is limited by inherent mechanisms which allow us to focus our attention and perceive the optimal amount of information needed to do so. As more information becomes available, and as a result of our propensity to multitask, these cognitive limits are pushed and stretched. In doing so, we often ignore important task relevant information, or our performance is inhibited. To fully understand the interplay of these factors, we need to be able to measure and evaluate workload. In this thesis I investigate the construct of cognitive workload, which is inherently limited by our overall capacity, through a measure used predominantly in applied driver distraction literature. From this, I present a body of work that expands upon theoretical underpinnings and new applications of this measure. In the theoretical stream, I show the usefulness, reliability, and applicability, of this measure in lab-based scenarios, whilst in the applied stream, I show three novel uses of the measure in both theoretical and real-world scenarios, as well as developing analyses applicable to such scenarios. The research in this thesis has implications and applications across a broad range of research areas, ranging from theoretical, in areas such as methodological development, to highly applied, in areas such as aviation environment evaluation. In the interest of openness and replicability, all data (from student cohorts), analysis and further appendices from this thesis can be found at https://osf.io/ayp6d/.