Most public sources reporting air quality data either present the value without sufficient supports for deeper exploration of multiple pollutants or are robust data repositories that are too technical to be accessible to non-scientific audiences. Our findings indicate many people have little context for understanding how the Air Quality Index (AQI) is generated or what it measures. In response, we are creating a contextualized, visualization-based platform to support public audiences in exploring air pollution beyond the AQI by displaying contextualized multi-pollutant data.
In the Technology-Integrated Learning Environments (TILES) lab we explore how technology meditates human learning in a variety of formal and informal contexts. Work in this lab is grounded in the Learning Sciences and explores how technologies can augment social and individual learning in contexts including museums, citizen science, classrooms, and online.