Kusumastuti Sarah A, Pollard Kimberly A, Oiknine Ashley H, Dalangin Bianca, Raber Tiffany R, Files Benjamin T
IEEE Trans Vis Comput Graph. 2023 Sep;29(9):3949-3960. doi: 10.1109/TVCG.2022.3173889. Epub 2023 Aug 1.
Information uncertainty is ubiquitous in everyday life, including in domains as diverse as weather forecasts, investments, and health risks. Knowing how to interpret and integrate this uncertain information is vital for making good decisions, but this can be difficult for experts and novices alike. In this study, we examine whether brief, focused practice can improve people's ability to understand and integrate bivariate Gaussian uncertainty visualized via ensemble displays, summary displays, and distributional displays, and we examine whether this is influenced by the complexity of the displayed information. In two experiments (N=118 and 56), decision making was faster and more accurate after practice relative to before practice. Furthermore, the performance improvements transferred to use of display types that were not practiced. This suggests that practice with feedback may improve underlying skills in probabilistic reasoning and provides a promising approach to improve people's decision making under uncertainty.
信息不确定性在日常生活中无处不在，包括天气预报、投资和健康风险等各种领域。知道如何解读和整合这些不确定信息对于做出明智决策至关重要，但这对专家和新手来说都可能很困难。在本研究中，我们考察简短、有针对性的练习是否能提高人们理解和整合通过集合显示、汇总显示和分布显示呈现的二元高斯不确定性的能力，并且我们考察这是否受到所显示信息复杂性的影响。在两项实验（N = 118和56）中，相对于练习前，练习后决策速度更快且更准确。此外，性能提升转移到了未练习过的显示类型的使用上。这表明有反馈的练习可能会提高概率推理的潜在技能，并为改善人们在不确定性下的决策提供了一种有前景的方法。
