HCApr 1

Assessing Affective Objectives for Communicative Visualizations

arXiv:2604.0118332.7
AI Analysis

This work addresses a specific gap in visualization design for researchers and practitioners, but it is incremental as it builds on existing assessment methods without introducing a new paradigm.

The paper tackles the challenge of assessing affective objectives in communicative visualizations by defining criteria for selecting validated assessments from multiple fields, and demonstrates its framework in a complex design task to evaluate different designs against objectives and theories.

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.

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