What Geoscience Experts And Novices Look At, And What They See, When Viewing Data Visualizations

Main Article Content

Kim A. Kastens
Thomas F. Shipley
Alexander P. Boone
Frances Straccia

Keywords

, Geoscience Education Research, Data Skills, Eye-Tracking, Perceptual Learning, Expert-Novice

Abstract

This study examines how geoscience experts and novices make meaning from an iconic type of data visualization: shaded relief images of bathymetry and topography.  Participants examined, described, and interpreted a global image, two high-resolution seafloor images, and 2 high-resolution continental images, while having their gaze direction eye-tracked and their utterances and gestures videoed. In addition, experts were asked about how they would coach an undergraduate intern on how to interpret this data.  Not unexpectedly, all experts were more skillful than any of the novices at describing and explaining what they were seeing.  However, the novices showed a wide range of performance.  Along the continuum from weakest novice to strongest expert, proficiency developed in the following order: making qualitative observations of salient features, making simple interpretations, making quantitative observations.  The eye-tracking analysis examined how the experts and novices invested 20 seconds of unguided exploration, after the image came into view but before the researcher began to ask questions.  On the cartographic elements of the images, experts and novices allocated their exploration time differently:  experts invested proportionately more fixations on the latitude and longitude axes, while students paid more attention to the color bar.  In contrast, within the parts of the image showing the actual geomorphological data, experts and novices on average allocated their attention similarly, attending preferentially to the geologically significant landforms.   Combining their spoken responses with their eye-tracking behavior, we conclude that the experts and novices are looking in the same places but “seeing” different things.

Downloads

Download data is not yet available.
Abstract 49 | PDF Downloads 42