Attention Does Not Improve Impaired Understanding Of Variability In Spatial Prediction

Herdener, Nathan; Wickens, Christopher D.; Clegg, Benjamin A.; Smith, Catharine L.

doi:10.1177/1541931218621054

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…Yet reallocation of resources either to the loading task (Experiment 2) or to adjustment (Experiment 1) did not negatively affect the variability calibration, even though such a cost would be expected if this variability learning were a resource-limited task. Furthermore, more recent research by Herdener, Wickens, Clegg, and Smith (2018) found that even explicitly directing attention to variability failed to improve estimation performance. In contrast, the application of what we call the mean-anchoring heuristic may serve to operate as a data-limited task.…”

Section: Resultsmentioning

confidence: 99%

Anchoring and Adjustment in Uncertain Spatial Trajectory Prediction

et al. 2018

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The aim of this study was to explore the impact of prior information on spatial prediction and understanding of variability. Background: In uncertain spatial prediction tasks, such as hurricane forecasting or planning search-andrescue operations, decision makers must consider the most likely case and the distribution of possible outcomes. Base performance on these tasks is varied (and in the case of understanding the distribution, often poor). Humans must update mental models and predictions with new information, sometimes under cognitive workload. Method: In a spatial-trajectory prediction task, participants were anchored on accurate or inaccurate information, or not anchored, regarding the future behavior of an object (both average behavior and the variability). Subsequently, they predicted an object's future location and estimated its likelihood at multiple locations. In a second experiment, participants repeated the process under varying levels of external cognitive workload. Results: Anchoring influenced understanding of most likely predicted location, with fairly rapid adjustment following inaccurate anchors. Increasing workload resulted in decreased overall performance and an impact on the adjustment component of the task. Overconfidence was present in all conditions. Conclusion: Prior information exerted short-term influence on spatial predictions. Cognitive load impaired users' ability to effectively adjust to new information. Accurate graphical anchors did not improve user understanding of variability. Application: Prior briefings or forecasts about spatiotemporal trajectories affect decisions even in the face of initial contradictory information. To best support spatial prediction tasks, efforts also need to be made to separate extraneous load-causing tasks from the process of integrating new information. Implications are discussed.

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Section: Resultsmentioning

confidence: 99%

Anchoring and Adjustment in Uncertain Spatial Trajectory Prediction

et al. 2018

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“…Because hurricane predictions have a large amount of uncertainty, communication to the public must make both the information and the uncertainty clear. However, people struggle to reason with uncertainty (e.g., Herdener et al, 2018), and have specific difficulties understanding current visualizations used to communicate hurricane predictions (e.g., Broad et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

“…Reliable and appropriately presented information about uncertainty can improve decision making (e.g., Kirschenbaum & Arruda, 1994;MacEachren et al, 1998MacEachren et al, , 2012Nadav-Greenberg & Joslyn, 2009). However, nonexperts are often poor at grasping spatial variability even when they directly experience a set of instances from a distribution (Herdener et al, 2016), including when the variability is their primary focus (Herdener et al, 2018). Wickens et al (2020) point to the general tendency to underestimate spatial variability, but also highlight how a range of factors influence the extent to which that occurs.…”

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Dynamic ensemble visualizations to support understanding for uncertain trajectories.

Witt¹,

Clegg

2022

Journal of Experimental Psychology: Applied

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When making decisions about uncertain spatial trajectories, such as storm forecasts, people rely on visualizations to support their understanding. Four experiments explored novel visualizations-dynamic ensembles. Nonexperts used visualizations to interpret probabilistic information about potential paths of a hurricane. Experiment 1 focused on global properties of the distribution, and showed dynamic ensembles imply a larger area at risk than traditional cones of uncertainty. Experiment 2 compared decisions with cones versus dynamic ensembles at specific individual locations. Dynamic ensembles offer more appreciation of risk outside the center of the distribution, and less abrupt in transitions from evacuation to nonevacuation choices. Experiment 3 compared decisions for dynamic ensembles versus static line ensembles. Similar evacuation rates across the two conditions suggest ensembles, rather than dynamics, are the more critical feature. Experiment 4 examined whether an additional dimension can be included in dynamic ensembles using color coding. Decisions reacted to this ancillary feature, with higher evacuation rates for locations threatened by more severe outcomes. Outcomes highlight the ability to systematically vary the level of risk communicated through the ensembles while also communicating the continuous nature of the risk. The overall findings show the viability of presenting uncertain spatial information using dynamic ensembles. Public Significance StatementCurrent approaches to showing the potential path of an incoming hurricane have well-known flaws, and this research investigates a new method to allow people to understand the areas that might be at risk. Findings from several experiments demonstrate that showing multiple, simultaneous, fast moving icons to illustrate the spread of possible tracks can provide a different sense of the possible threat, and specifically, these "zoomies" better convey risk that the storm will deviate from the most likely forecast path. Furthermore, these displays offer several design opportunities that could be used to communicate additional factors such as the magnitude of the storm and thus could afford a more complete communication of hurricane threats.

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“…Automation assistance tools are not provided to examine purely manual, unaided, tendencies (and the current standard automation system, ARPA, does not consider rules of the road in evaluating different proposed maneuvers). Our goal is to identify the compromising influences of uncertainty and, in particular, the human cognitive biases to underestimate that uncertainty in extrapolating continuous trajectories (Herdener, Wickens, Clegg, & Smith, 2016, 2018; that is, in this context, the future behavior of the hazard ship).…”

Section: Introductionmentioning

confidence: 99%

Nautical Collision Avoidance

et al. 2019

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Objective: Experimentally investigate maneuver decision preferences in navigating ships to avoid a collision. How is safety (collision avoidance) balanced against efficiency (deviation from path and delay) and rules of the road under conditions of both trajectory certainty and uncertainty. Background: Human decision error is a prominent factor in nautical collisions, but the multiple factors of geometry of collisions and role of uncertainty have been little studied in empirical human factors literature. Approach: Eighty-seven Mechanical Turk participants performed in a lower fidelity ship control simulation, depicting ownship and a cargo ship hazard on collision or near-collision trajectories of various conflict geometries, while controlling heading and speed with the sluggish relative dynamics. Experiment 1 involved the hazard on a straight trajectory. In Experiment 2, the hazard could turn on unpredictable trials. Participants were rewarded for efficiency and penalized for collisions or close passes. Results: Participants made few collisions, but did so more often when on a collision path. They sometimes violated the instructed rules of the road by maneuvering in front of the hazard ship’s path. They preferred speed control to heading control. Performance degraded in conditions of uncertainty. Conclusion: Data reveal an understanding of maneuver decisions and conditions that affect the balance between safety and efficiency. Application: The simulation and data highlight the degrading role of uncertainty and provide a foundation upon which more complex questions can be asked, asked of more trained navigators, and decision support tools examined.

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Attention Does Not Improve Impaired Understanding Of Variability In Spatial Prediction

Cited by 4 publications

References 9 publications

Anchoring and Adjustment in Uncertain Spatial Trajectory Prediction

Anchoring and Adjustment in Uncertain Spatial Trajectory Prediction

Dynamic ensemble visualizations to support understanding for uncertain trajectories.

Nautical Collision Avoidance

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