Measuring Effects of Spatial Visualization and Domain On Visualization Task Performance: A Comparative Study

Abstract

Understanding your audience is foundational to creating high impact visualization designs. However, individual differences and cognitive abilities also influence interactions with information visualization. Differing user needs and abilities suggest that an individual's background could influence cognitive performance and interactions with visuals in a systematic way. This study builds on current research in domain-specific visualization and cognition to address if domain and spatial visualization ability combine to affect performance on information visualization tasks. We measure spatial visualization and visual task performance between those with tertiary education and professional profile in business, law & political science, and math & computer science. We conducted an online study with 90 participants using an established psychometric test to assess spatial visualization ability, and bar chart layouts rotated along Cartesian and polar coordinates to assess performance on spatially rotated data. Accuracy and response times varied with domain across chart types and task difficulty. We found that accuracy and time correlate with spatial visualization level, and education in math & computer science can indicate higher spatial visualization. Additionally, we found distinct motivations can affect performance in that higher motivation could contribute to increased levels of accuracy. Our findings indicate discipline not only affects user needs and interactions with data visualization, but also cognitive traits. Our results can advance inclusive practices in visualization design and add to knowledge in domain-specific visual research that can empower designers across disciplines to create effective visualizations.

Investigating User Preferences towards Visualization Types with a Focus on Neuroticism and its Implications on Mental Health

“…The emphasis of this research is on in-depth examination into user preferences for various visualization patterns using the five-factor model (FFM) especially the neuroticism trait, a personality trait linked to a propensity for feeling unfavorable emotions including worry, tension, and despair [5]. It has been demonstrated that neuroticism has a considerable impact on a person's cognitive and emotional reactions to a variety of stimuli, including data visualizations [6].…”