Adapting to workload in complex environments: Insights from evidence accumulation models of decision making

Abstract

The aim of this thesis is to examine how individuals manage workload in complex environments. I used formal models of decision making, known as evidence accumulation models, to quantify how individuals adapt in response to workload. The models assume that the individual samples evidence from the environment until a threshold amount of evidence is accumulated, triggering an overt response. The models can quantify latent cognitive processes that are relevant to workload, such as the rate of information processing, response caution, response biases, quality of information and encoding time. In Chapter 1, I provide an overview of the relevant workload literature and describe the architectures of evidence accumulation models. In Chapter 2, I test whether standard evidence accumulation models can account for performance in a relatively complex applied decision making task which varied time pressure and stimulus difficulty. In Chapter 3, I examine how individuals respond to distinct time pressure factors including stimulus complexity, the number of stimuli, as well as time available to classify stimuli. In Chapter 4, I extend the investigation by using a dual-task paradigm to understand the causes of dual-task performance interference and how people adapt to having to multitask in a time pressured environment. In Chapter 5, I discuss the findings as a whole, detailing the theoretical and practical implications of the thesis, as well as limitations and directions for future research.