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

Autor: Stella D Tomasi, Jeanny Liu, Feng Cheng, Chaodong Han
Rok vydání: 2023
Předmět:
Zdroj: Information Visualization. :147387162311671
ISSN: 1473-8724
1473-8716
Popis: 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.
Databáze: OpenAIRE