Effect of Visualization Training on Uncertain Spatial Trajectory Predictions

Objective: The goal of this study was to explore the ways in which visualizations influence the prediction of uncertain spatial trajectories (e.g., the unknown path of a downed aircraft or future path of a hurricane) and participant overconfidence in such prediction. Background: Previous research indicated that spatial predictions of uncertain trajectories are challenging and are often associated with overconfidence. Introducing a visualization aid during training may improve the understanding of uncertainty and reduce overconfidence. Method: Two experiments asked participants to predict the location of various trajectories at a future time. Mean and variance estimates were compared for participants who were provided with a visualization and those who were not. Results: In Experiment 1, participants exhibited less error in mean estimations when a linear visualization was present but performed worse than controls once the visualization was removed. Similar results were shown in Experiment 2, with a nonlinear visualization. However, in both experiments, participants who were provided with a visualization did not retain any advantage in their variance estimations once the visualization was removed. Conclusions: Visualizations may support spatial predictions under uncertainty, but they are associated with benefits and costs for the underlying knowledge being developed. Application: Visualizations have the potential to influence how people make spatial predictions in the presence of uncertainty. Properly designed and implemented visualizations may help mitigate the cognitive biases related to such predictions.

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