Although it was an extremely competitive year for the CSG honors student paper competition, judges still needed to choose one paper as the winner. The author of that paper was Kristie Socia of Michigan State. Kristie’s research examines how different map designs and different levels of temporal resolution influence the effectiveness of wildfire visualizations. Like the other two finalists, Kristie employed human subjects testing to explore how varying designs influenced map-reader’s abilities to complete map tasks. Here’s her summary:
An Empirical Investigation of Computational In-equivalence in Wildfire Visualization: Measuring User Performance with Small-multiples and Animation
By: Kristie Socia
My research empirically investigates the influences of map-design and temporal resolution on apprehension and the inference affordances of cartographic animation and static sets of small-multiple maps in the context of wildfire visualization. My goal was to gain insight on map-readers’ abilities, strategies, and preferences towards using animated maps and small-multiple maps to explore dynamic geographic processes. I conducted a human-subjects experiment to measure participants’ task accuracy, response time, and confidence between animated and small-multiple maps of an identical wildfire event. The results revealed the importance of both map design and temporal resolution; small-multiples and fine temporal resolution maps elicit more accurate and more confident responses from readers. While participants performed better overall with the small-multiple maps, they preferred the animated maps. The results of my research suggest that map type is an important factor that influences response time, while temporal resolution is significant for accuracy and confidence.