Interactivity to improve visual analysisin groups with different literacy levels

The study presented in this paper investigates how two groups, with different literacies, perceive interactive visualizations by using statistical tests. A prototype with interactive visualizations created with Microsoft Power BI has been used. Validation was made with quantitative and qualitative metrics tested with ANOVA single factor. Three of the variables showed statistically significant differences between groups: accuracy, complexity, and comprehension. This highlights the importance of data literacy in comprehending visualizations, leading to a gap between both groups. The line, pie and bar chart were considered the best visualizations for both groups, and the worst was the bubble chart. Regarding the interactive component, the filter and the slider had a good evaluation among both groups. Using this study, organizations will be able to create appropriate visualizations for different audiences.