Presentation at American Geophysical Union Conference in San Francisco, December 2013
To be climate literate, students must be data-literate. To connect with the evidence behind scientists’ assertions about climate change, students (and other novices) must be able to distinguish long-term trends from short-term variability in graphs, recognize the distribution of sea surface temperature or precipitation changes on maps, and discern important patterns in animations that display changes over time. Although the development of cyberinfrastructure for accessing near digital, sharable, real-time and archived earth systems data has the potential to transform how climate science is taught by connecting students directly with evidence to support their understanding, online interfaces to scientific data are typically industrial-strength—built by scientists for scientists—and their design can significantly impede broad use by novices.
To inform efforts at bridging scientific data portals to the classroom, Education Development Center, Inc. (EDC) and the Scripps Institution of Oceanography conducted an NSF-funded 2-year interdisciplinary review of literature and expert opinion pertinent to making interfaces to large scientific databases accessible to and usable by student learners and their instructors. The >70 cross-cutting and specific guidelines in our project report are grounded in the fundamentals of Cognitive Load Theory, Visual Perception, Schemata formation and Universal Design for Learning. The components of the human visual system and associated cognitive processes are highly specialized and have evolved in response to survival demands of the three-dimensional world humans have lived in for thousands of years. Because the use of two-dimensional representations, such as maps and graphs, and the use and navigation of Web interfaces has developed quite recently in human history, our visual perception system is not specifically adapted to these tasks.
Therefore, it’s critical to understand how to design two-dimensional media to take advantage of the strengths of our highly evolved and complex visual system and to compensate for its weaknesses. Looking at the design of data interfaces through this lens helps us understand, for example, why red stands out (finding ripe berries in a bush), why movement grabs our attention (hunting and avoiding predators), and why variations in light luminance and shading work better than variations in color hue for perceiving shape and form. This presentation, through specific examples, explained how to avoid the pitfalls and make scientific databases more broadly accessible by (1) adjusting the cognitive load imposed by the user interface and visualizations so that it doesn’t exceed the amount of information the learner can actively process; (2) drawing attention to important features and patterns; and (3) enabling customization of visualizations and tools to meet the needs of diverse learners.