Zoom In! Learning Science with Data

The world we live in is increasingly data-driven. The knowledge that our society gains from collecting and processing data touches every facet of our lives, from our health and safety to the development of innovative technologies to solve the world's energy crisis. Equipping students with the skills needed to thrive in this world requires educational tools that engage students in using data to construct knowledge and solve problems.

Zoom In! Learning Science with Data will integrate two learning technologies—EDC’s Zoom In and Concord Consortium’s Common Online Data Analysis Platform (CODAP)—to build high school students’ skills in using data to investigate significant questions in biology and earth science. The integrated learning platform will deliver six curriculum modules in which students will interact with a rich data set as they examine a particular scientific phenomenon—for example analyzing finch body measurements to document evolution in action—and learn and use specific data literacy skills. The project builds on EDC’s successful work using the Zoom In platform to foster evidence-based inquiry and explanation in social studies, adapting this approach to support data-focused inquiries in biology and earth science at the high school level. The Zoom In! modules and digital tools explicitly support teachers in leading students through data-driven inquiry, meeting the needs of high school teachers now increasingly required to teach important data skills in the context of their regular science instruction.

This project centers on the question of whether engagement with a rich digital curriculum supplement improves high school students’ learning of data literacy skills and concepts in the context of regular science instruction. To answer this question the project takes a multi-phase approach, in which researchers will develop and iteratively refine a set of six instructional units, associated digital tools, and teacher professional development materials (Years 1 & 2), and then evaluate their potential to improve data science learning in high schools serving students from a range of socio-economic backgrounds through a small-scale test of efficacy (Year 3).

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