Impact of Individual Differences on User Experience with a Real-World Visualization Interface for Public Engagement

Abstract

There is increasing evidence that the effectiveness of Information Visualization (Infovis) is affected by the user needs and abilities. For instance, cognitive abilities (e.g., perceptual speed, working memory) [e.g., 1-4] have been shown to impact users' performance and satisfaction with a given visualization. These findings suggest that it can be valuable to develop visualization systems that can provide personalized support targeting specific user characteristics. Furthermore, recent research [e.g., 3,5] has shown that eye tracking data can be leveraged to identify the elements of a visualization for which specific user differences hinder user experience or performance, thus providing concrete information on which specific personalized support could be helpful for different users (e.g., users with low perceptual speed may benefit from help in processing legends [1]). Though these findings are encouraging toward the design of user-adaptive or customized visualizations, they are generally related to either fictional tasks or research prototypes. So, it is unclear if existing results on the value of user-adaptive visualizations can transfer to real-world settings.