A pilot study showed that students and experts identify the same features as important in time-series graphs. However, for experts, the shape of the graph elicits a large body of content knowledge regarding climate change. Thus, the difficult part of teaching students to ‘read' these graphs is developing this content knowledge.
A second study is testing the use of progressive alignment to teach fault recognition. Progressive alignment exploits the alignment of similar features to recognize differences. In our initial experiment only students with prior instruction in geology benefited from this technique. High performers tended to understand that movement is the defining feature of faults. This emphasizes the interplay between perception of salient features and content knowledge. Work in progress further explores this relationship, and in addition, integrates eye tracking to understand looking strategies employed by experts and novices.
In a third study, classic approaches to perception are exploited to investigate how experts and novices segment landscapes into salient categories. For example, experts and novices divide landscapes into similar common categories (e.g., lakes, mountains, and dunes). We hypothesize that only geoscientist will further sub-divide them into geologically important areas . Combining eye-tracking with location recall, these experiments are providing insight into visual search strategies, expert chunking, and development of salient features.
This work demonstrates the potential for combining cognitive science and geoscience education research to yield new insights into geoscience expertise and its development.
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