Teaching and Learning with Data

Talk presented at ESRI GIS Education Conference, San Diego, 6 July 2013

This talk was aimed at an audience of higher ed and K-12 educators who use GIS (Geographic Information Systems) in their teaching practice. Their disciplines spanned from geography to agriculture to forestry to urban planning to oceanography, united by their common conviction that geospatial thinking around spatial data empowers students to answer questions and solve problems that they couldn’t otherwise get a handle on. The talk focused on helping students span the transition from working with small student -collected datasets to large professionally collected datasets. Kastens discussed why this transition is challenging and recommended two strategies for helping students across the transition. Challenges arise because students have to transition from small to large datasets, from simple and transparent tools to complex and opaque tools, from a situation in which they had embodied experience of the referent system to working with metadata as their only source of context, and from simple to complex lines of reasoning. Two suggested strategies are (a) to provide students with a hypothesis array of possible data interpretations to scaffold their data interpretation process, and (b) to design learning sequences in which students first collect and interpret a small student-collected data set in their own local natural or build environment, and then embed that data within a professionally-collected dataset which spans a larger time and/or space. 

Author:
Kim Kastens
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