计算机科学
可视化
认知负荷
信息可视化
人机交互
数据可视化
背景(考古学)
召回
视觉分析
认知
领域(数学分析)
创造性可视化
信息过载
数据科学
人工智能
认知心理学
万维网
心理学
古生物学
数学分析
数学
神经科学
生物
作者
Stella Tomasi,Jeanny Liu,Feng Cao,Chaodong Han
标识
DOI:10.1177/14738716231167180
摘要
Widely employed by innovative organizations, a well-designed simple data visualization has been shown to enhance user experience and aid in decision making; while a more embellished visualization may cause overload, it has the potential to create deeper processing and learning. Furthermore, individual characteristics may impact on how users seek information on these different types of visualization. This study proposes that thinking styles (analytical vs holistic) and domain expertise moderate the effects of data visualization types on decision performances in terms of decision accuracy, decision confidence, memory recall, and cognitive load. To test our hypotheses, an experimental study involving visual manipulations in the context of personal finance was conducted on two types of visualizations (simple and clutter). Results suggest that simple visualizations enhance decision accuracy and reduce cognitive load. We also find that cognitive load is further reduced when analytical thinkers are presented with simple visualizations. These findings can help designers understand how user characteristics may be considered when designing and evaluating visualizations for decision makers.
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