Assessing Affective Objectives for Communicative Visualizations
2026-04-01 • Human-Computer Interaction
Human-Computer Interaction
AI summaryⓘ
The authors explore how setting clear goals helps design visualizations that communicate better. They focus on affective goals, which relate to how people feel or change attitudes, and are harder to measure than cognitive goals like remembering facts. They propose a way to pick tools from different fields to measure these feelings effectively. They show how their method works by evaluating designs that mix stories and visuals to influence emotions.
Learning ObjectivesCognitive ObjectivesAffective ObjectivesVisualization DesignAssessment MethodsPersonal NarrativesPsychological TheoriesEvaluation FrameworkUser AttitudesCommunicative Visualization
Authors
Elsie Lee-Robbins, Eytan Adar
Abstract
Using learning objectives to define designer intents for communicative visualizations can be a powerful design tool. Cognitive and affective objectives are concrete and specific, which can be translated to assessments when creating, evaluating, or comparing visualization ideas. However, while there are many well-validated assessments for cognitive objectives, affective objectives are uniquely challenging. It is easy to see if a visualization helps someone remember the number of patients in a clinic, but harder to observe the change in their attitudes around donations to a crisis. In this work, we define a set of criteria for selecting assessments--from education, advocacy, economics, health, and psychology--that align with affective objectives. We illustrate the use of the framework in a complex affective design task that combines personal narratives and visualizations. Our chosen assessments allow us to evaluate different designs in the context of our objectives and competing psychological theories.