Information visualizations are popular due to their usefulness in deriving insights (analytic "vis") and conveying those insights to an audience. Without better ways to describe their specific goals and evaluate if they are achieved, communicative visualization designers often rely on generic heuristic advice (e.g., which chart types or encodings to use, which narrative technique, etc.). Designing this way emphasizes how easily insights or data can be decoded from the visualization but may not address the underlying intent of the designer. Because the goal is not simply for the audience to “read,” designers can benefit from better articulating and testing the influence they have (or want) on the audience’s mental model. That is, designers should express how the audience should learn something with, or about, the data. Existing learning objective (LO) taxonomies (e.g., Bloom’s) have strong correspondence to visualization goals. 

The project aims to: 

1. Identify suitable learning objective formulations for communicative vis 
2. Identify the most effective test formats to evaluate the visual relative to the LO 
3. Create a set of tools to support the practical and rapid and efficient creation of LOs and test materials for "bespoke" (i.e., one-off) visualizations