Dr Elizabeth Argyle from the Institute for Aerospace Technology (IAT) will present:

Title: "Designing for Situation Awareness: Perspectives from Weather Forecasting"

Situation awareness (SA) is regarded as a critical component of forecast decision making, and is commonly conceptualized as the degree to which information is perceived, understood, and projected into a future context.  In order to develop SA and predict weather events, forecasters integrate information from many sources, including personal experience, climatological records, meteorological observations, and numerical model predictions.  As loss of SA can contribute to increased workload and decreased forecast lead time and spatial accuracy, it is of particular importance to understand how decision support design can be manipulated to promote SA.  This work took place during the development of a novel suite of flash flood prediction models; the present discussion will focus on two studies that sought to describe the relationship between SA and the visual design of the model outputs.

 First, we examined the effects of data aggregation techniques on flash flood detection in a geospatial visualization interpretation task.  Representing multiple data points with an aggregate of their characteristics can be necessary when developing overviews of large datasets.  Using a Signal Detection Theory framework, the study identified a significant effect of aggregation technique on error rates, decision bias, and sensitivity.  The second study was motivated by recent developments in weather forecasting automation.  Here, we examined the role of an automated detection aid on situation awareness and information scanning behaviour.  Using eye tracking, we also identified a correlation between eye tracking variables and outcomes from a probe-based measure of SA.  Findings contributed to evidence-based recommendations for visualization design, while also extending current understanding of relationship between visualization design and SA in uncertain, dynamic decision making environments.

Elizabeth received a PhD in industrial and systems engineering from the University of Oklahoma in 2016. Her research interests include human-computer interaction, situation awareness in sociotechnical systems, decision making under uncertainty, and optimization. As a Research Fellow in the IAT, her work explores transformative technologies and methods for managing safety, efficiency, and reliability in aerospace operations.