Strategies for supporting students’ explorations of big data

This presentation at AAAS' 2015 Annual Meeting focused on how  teachers and instructional materials can help students transition from working with small, student-collected datasets to large, complex, professionally collected datasets. Strategies include minimizing extraneous information and maximizing insight-rich information in the data visualizations; leveraging the skill set that students bring with them from working with self-collected data; and practicing the use of spatial, temporal and quantitative reasoning to connect claims with evidence.

 

Author:
Kim Kastens
Senior Advisor, Oceans of Data Institute
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