The role of individual characteristics: How thinking style and domain expertise affect performances on visualization

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Information Visualization Pub Date : 2023-04-12 DOI:10.1177/14738716231167180
S. Tomasi, Jeanny Liu, Feng Cheng, Chaodong Han
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引用次数: 0

Abstract

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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个人特征的作用:思维风格和领域专业知识如何影响可视化表现
创新组织广泛采用精心设计的简单数据可视化,可以增强用户体验并有助于决策;虽然更加修饰的可视化可能会导致过载,但它有可能创建更深入的处理和学习。此外,个人特征可能会影响用户如何在这些不同类型的可视化上寻求信息。本研究提出,思维风格(分析与整体)和领域专业知识在决策准确性、决策信心、记忆回忆和认知负荷方面调节了数据可视化类型对决策表现的影响。为了验证我们的假设,对两种类型的可视化(简单和混乱)进行了一项涉及个人理财背景下视觉操作的实验研究。结果表明,简单的可视化可以提高决策的准确性,减少认知负荷。我们还发现,当分析思想家被呈现出简单的可视化时,认知负荷会进一步降低。这些发现可以帮助设计师了解在为决策者设计和评估可视化时如何考虑用户特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Information Visualization
Information Visualization COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
5.40
自引率
0.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. This journal is a member of the Committee on Publication Ethics (COPE).
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