Cutting Through the "Data-Driven" Mantra
Different Conceptions of Data-Driven Decision Making
High-stakes accountability policies such as the federal No Child Left Behind legislation require districts and schools to use data to measure progress toward standards. In doing so, such policies assume that practitioners can and will use data to enhance decisionmaking and improve teaching and learning. However, educators use and make sense of data in different ways and with different rigor and frequency. Drawing on earlier RAND Corporation studies, the authors investigate the different ways in which educators understand the concept of data-driven decisionmaking (DDDM), the factors that enable or constrain DDDM, and associated implications for policy and practice. The authors conclude that if policymakers want to encourage educators to pursue DDDM — particularly its more-complex forms — they should focus policy supports on improving the availability, timeliness, and comprehensiveness of data; helping educators access external resources; and providing professional development options, including training. Finally, policymakers must acknowledge that the DDDM process is not straightforward.
Reprinted with permission from Evidence and Decision Making: Yearbook of the National Society for the Study of Education, Volume 106, Issue 1, Chapter 5, pp. 105-131. Copyright © 2008 National Society for the Study of Education.
- Copyright: RAND Corporation
- Publisher: Center on Education Policy
- Availability: Web-Only
- Pages: 27
- Document Number: RP-1372
- Year: 2007
- Series: Reprints
Originally published in: Evidence and Decision Making: Yearbook of the National Society for the Study of Education, Vol 106, Issue 1, Chapter 5, pp. 105-131, 2007.
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