| Popis: |
This work explores how people with different backgrounds perceive and interpret info-graphics when those graphics contain information about data quality (e.g., errors or inconsistencies in the data that the info-graphic is based on). Right now, info-graphics are reserved for communicating fairly simple information. If we can find ways to better communicate data quality for different populations then we can improve the design of info-graphics that represent complicated data. This study investigates how different manipulations of the representation of data or model uncertainty influence people's interpretation of the information presented in specific types of charts (social networks, bar charts - skill meters, and traditional charts - points with bars showing mean and standard deviation) |
