January 22, 2025 from 8 to 9:00 p.m. ET / 5 to 6:00 p.m. PT
Teaching Data Literacy in Social Studies
No skill is more important for today's social studies student than data literacy. What are the charts and analytics experts and decision-makers rely on truly saying? How can we identify good, relevant data, and filter out the statistical noise? Sometimes the key is going slow. In this talk, Dr. Tamara Shreiner explores the latest research on how people read data visualizations and describes three different strategies for teaching data literacy: hierarchical questioning, slow analysis, and slow reveal. These strategies can be easily applied to data visualizations teachers are already teaching, but they may also inspire teachers to include data visualizations in lessons where they were previously absent.
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About Tamara Shreiner:
Tamara Shreiner is Associate Professor of History and Social Studies Education at Grand Valley State University in Allendale, Michigan, where she teaches social studies methods to elementary and secondary pre-service teachers. Shreiner's research focuses on disciplinary literacy in social studies with a special emphasis on data literacy. She is the author of numerous journal articles, including in Cognition & Instruction, Theory & Research in Social Education, Social Education, Journal of Social Studies Research, and the British Journal of Educational Technology. She recently published a book with Teachers College Press, Teaching Data Literacy in Social Studies: Principles and Practices to Support Historical Thinking and Civic Engagement.
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