Understanding representations of uncertainty, an eye-tracking study – Part 1: The effect of anchoring

• Published in: Geoscience communication (Online) 2023-09, Vol.6 (3), p.97-110
• Main Authors: Mulder, Kelsey J., Williams, Louis, Lickiss, Matthew, Black, Alison, Charlton-Perez, Andrew, McCloy, Rachel, McSorley, Eugene
• Format: Article
• Language: English
• Subjects: Cognition & reasoning; Communication; COVID-19; Data interpretation; Decision making; Decision theory; Earth science; End users; Environmental science; Extreme values; Eye movements; Heuristic; Hurricanes; Mental task performance; Pandemics; Rationality; Representations; Risk communication; Surveys; Tornadoes; Tracking; Uncertainty
• ISSN: 2569-7110; 2569-7102; 2569-7110
• DOI: 10.5194/gc-6-97-2023

Geoscience communicators must think carefully about how uncertainty is represented and how users may interpret these representations. Doing so will help communicate risk more effectively, which can elicit appropriate responses. Communication of uncertainty is not just a geosciences problem; recently, communication of uncertainty has come to the forefront over the course of the COVID-19 pandemic, but the lessons learned from communication during the pandemic can be adopted across geosciences as well. To test interpretations of environmental forecasts with uncertainty, a decision task survey was administered to 65 participants who saw different hypothetical forecast representations common to presentations of environmental data and forecasts: deterministic, spaghetti plot with and without a median line, fan plot with and without a median line, and box plot with and without a median line. While participants completed the survey, their eye movements were monitored with eye-tracking software. Participants' eye movements were anchored to the median line, not focusing on possible extreme values to the same extent as when no median line was present. Additionally, participants largely correctly interpreted extreme values from the spaghetti and fan plots, but misinterpreted extreme values from the box plot, perhaps because participants spent little time fixating on the key. These results suggest that anchoring lines, such as median lines, should only be used where users should be guided to particular values and where extreme values are not as important in data interpretation. Additionally, fan or spaghetti plots should be considered instead of box plots to reduce misinterpretation of extreme values. Further study on the role of expertise and the change in eye movements across the graph area and key is explored in more detail in the companion paper to this study (Williams et al., 2023; hereafter Part 2).