Learning Science from Scientific Data

Sunday, 15 February 2015: 8:00 AM-9:30 AM
Room LL21D (San Jose Convention Center)
Today, large online datasets allow students to explore uncharted scientific territory, experiencing the excitement of science while learning firsthand the methods of science. Students -- those who will be citizens as well as those who will be scientists -- need to understand how science is done, the strengths of its methodologies, and the limits of its knowledge. These goals are emphasized in the Next-Generation Science Standards for K-12 education, as well as the 2012 recommendations of the  U.S. President's Council of Advisors on Science and Technology for undergraduate education. This symposium examines how widely available large datasets generated by modern science are being used to teach science at all levels. Working with data is becoming a primary methodology for introducing the methods and content of science. What are the advantages of teaching with large data, and do these experiences change students’ learning? What responsibilities do science educators have to bring data-driven science learning to the classroom? How can data analysis tools and pedagogic practices guide and facilitate students’ paths from novice to expert scientists? To address these questions, this session brings together experts in science education and learning with those who are treading this path in the classroom.
Cathryn A. Manduca, Carleton College
Cathryn A. Manduca, Carleton College
Graham Hatfull, University of Pittsburgh
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