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Session Type: Paper Session
As data become more prevalent and complex, the ways in which they might be used to inform decision-making across levels of education require more sophistication. This session showcases instrumentation to measure and characterize data literacy for educators. The ways in which data move through the education system are delineated and the impact of data use to inform progress of students is illustrated.
Confirmation of the Factor Structure of the Data Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA) Among Teachers in the Midwest - David A. Walker, Northern Illinois University; Todd Reeves, Northern Illinois University; Thomas J. Smith, Northern Illinois University
First-Year Impacts of the Early Warning Intervention and Monitoring System - Ann-Marie Faria, American Institutes for Research; Nicholas Andrew Sorensen, American Institutes for Research; Jessica Heppen, American Institutes for Research; Jill Bowdon, American Institutes for Research; Suzanne Taylor, American Institutes for Research; Ryan Eisner, American Institutes for Research; Shandu Foster, American Institutes for Research
Helping Administrators Get Data on How Teachers Use Data: The Teacher Data Use Survey - Jeff Wayman, Wayman Services, LLC; Stephanie B. Wilkerson, Magnolia Consulting, LLC.; Vincent Cho, Boston College; Ellen B. Mandinach, WestEd; Jonathan A. Supovitz, University of Pennsylvania
Initial Validation of the Preservice Data-Driven Decision-Making Efficacy and Anxiety Inventory - Karee E. Dunn, The University of Tennessee - Knoxville; Wen-Juo Lo, University of Arkansas; Denise Tobin Airola, University of Arkansas
Locating Data Use in the Microprocesses of District-Level Deliberations: A Methodological Approach - Alice Huguet, Northwestern University; Annie Allen, University of Colorado - Boulder; Caitlin Farrell, University of Colorado - Boulder; Cynthia E. Coburn; Debbie Kim, Northwestern University; William R. Penuel, University of Colorado - Boulder