# The Correlation between Users' Cognitive Characteristics and Visualization Literacy
## 2 Background
### User Characteristics and Visualization  
Researchers in the information visualization community have investigated how user characteristics affect visualization use. In particular, the line of prior work focused on the effects of perceptual abilities, cognitive abilities, and personality, among many user characteristics, on the users' abilities to read visualizations.  
Some researchers endeavored to find a connection between perceptual abilities and visualization use. In particular, they were interested in perceptual speed (e.g., speed in completing simple tasks involving visual perception: for example, recognizing a figure appearing on the left from a set of five similar objects on the right). One of the common findings was that the perceptual speed of users was correlated with and significantly influenced visualization task performance in terms of speed and accuracy [20; 21; 22; 23]. Furthermore, the effects of individuals' perceptual speed on task performance were different depending on visualization types. For example, users with high-perceptual speed performed better with bar charts and colored boxes views on information seeking tasks; in contrast, users with low-perceptual speed performed better with radar charts [20; 22].  
More extensive studies have been conducted to investigate the roles of cognitive abilities (e.g., spatial rotation ability, visual working memory, and verbal working memory). [PERSON] and [PERSON] [24] examined the effects of spatial rotation ability on information retrieval tasks with a node-link visualization. They showed that spatial rotation ability is moderately correlated with the tasks, and different navigation strategies emerged between high- and low-spatial ability user groups. [PERSON] et al. [23] explored the effects of various cognitive abilities on a 3D visualization task identifying a 3D object from orthogonal projections. They found that visual memory and spatial rotation ability correlated with only the accuracy of task performance. [PERSON] and [PERSON] [20] compared the effects of cognitive abilities on different visualization types (i.e., colored boxes view and radar view); however, no significant interactions occured with the visualization types. One interesting finding by [PERSON] et al. [22] was that an individual's visual working memory and verbal working memory affected his/her preference for visualization types; for instance, users with high-visual working memory generally preferred radar charts to bar charts. In addition, the roles of spatial rotation ability, visual working memory, and verbal working memory have been inspected with visualization training approaches [25] and highlighted interventions [26].  
As shown in the previous work, researchers have been searching for evidence that user characteristics have a significant effect on visualization use and preference. However, most studies have considered very limited target visualizations and associated visualization tasks. For these reasons, it may not be enough to generalize and extend the findings to other visualization types. Furthermore, previous studies have investigated derivative user characteristics (e.g., perceptual speed, spatial rotation ability, visual working memory, locus of control, and expertise). As [PERSON] [27] and [PERSON] et al. [28] argued, other relevant user cognitive characteristics should be examined to expand the understanding of user characteristics in data visualization.