Data-Driven Decision Making in Schools: Guidelines and Professional Development Effects

This set of work, which includes books published through the Data Wise Project at Harvard University and the What Works Clearinghouse at the U.S. Department of Education, focuses partly on the aggregation of what education practitioners and researchers regard as best practices for using data to improve student outcomes in schools. It also includes results from a randomized field trial of a data-driven decision making intervention in a large U.S. school district.

Report from Randomized Field Trial of a Data-Based Decisionmaking Professional Development Intervention

Cavalluzzo, L., Geraghty, T. M., Steele, J. L., Holian, L., Jenkins, F., Alexander, J. M., & Yamasaki, K. Y. (2014). Using data to inform practice and improve student performance in mathematics: Results from a randomized experiment of program efficacy. Alexandria, VA: CNA.
Our evaluation finds a positive effect of the Using Data intervention on teacher behavior after year 1 of the study. Specifically, teachers in the treatment group at the end of year 1 reported using data more frequently, exhibited higher levels of data literacy compared with control teachers, and held attitudes and beliefs that were more favorable toward data use for instructional improvement. We do not find an overall treatment effect of the UD program on schoolwide student performance on the annual state math assessment. Restricting the sample to the students of intent-to-treat (ITT) teachers at the end of year 2 (ie, limiting the sample to students of teachers who were in the randomized sample and offered the UD program from the beginning), also yields a null effect overall. However, students of ITT teachers from the block of lowestperforming schools at baseline show improvements in year 2 that are moderately sized and statistically significant (effect size = .40, p = .01). The weight of the evidence presented here indicates that Using Data improves teachers’ outcomes after one year, and improves the outcomes of their students in high-needs schools after two years. We conclude that further research and evaluation of the Using Data program are warranted.
Report

Publications from the Data Wise Project at Harvard

Edited and Co-authored Book

Boudett, K. P. and Steele, J. L., Editors. (2007). Data wise in action: Stories of schools using data to improve teaching and learning. Cambridge, MA: Harvard Education Press. ISBN-13: 978-1-891792-81-6**
Book

Book Chapter

Steele, J. L. and King, J. (2005). Planning to assess progress. Ch. 7 in R. J. Murnane, K. Boudett, & E. City (Eds.), Data wise: A step-by-step guide to using assessment results to improve teaching and learning. Cambridge, MA: Harvard Education Press. Pages 151-168. ISBN-13: 978-1891792670 Book

Steele, J. L., & Boudett, K. P. (2008). Leadership lessons from schools becoming “Data Wise.” Harvard Education Letter, 24(1), 1–3. In 2004, we began collaborating with a team of professors, school administrators, and graduate students to write Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Learning (Harvard Education Press, 2005). The book offers an eight-step approach to collaborative, evidence-based instructional improvement. Since then, schools all over the country have adopted the Data Wise approach. As we worked with many of them, we realized that teachers and administrators who are spearheading the Data Wise improvement process in their schools—-as well as those pursuing other approaches—- often encounter similar questions and obstacles. So we set out to develop case studies of eight of these schools, documenting the leadership challenges that school leaders typically face during each step of the improvement process, as well as the strategies they use to address them.
Article

Steele, J. L., & Boudett, K. P. (2008). The collaborative advantage. Educational Leadership, 66(4), 54–59.
The Data Wise Improvement Process is an approach to schoolwide instructional improvement developed by a team of educators in the Boston Public Schools and researchers at the Harvard Graduate School of Education (Boudett, City, & Murnane, 2005). We profiled eight schools around the United States (all of which are public schools and four of which serve primarily low-income students) in Data Wise in Action (Boudett & Steele, 2007). One theme cut across all eight schools as they worked on school improvement — they all used data collaboratively. The collaborative approach to data use yielded at least three major benefits for these schools: organizational learning, improved internal accountability, and a safety net for professional growth.
Article Alt Link

Publications from the U.S. Department of Education’s What Works Clearinghouse

Hamilton, L., Halverson, R., Jackson, S. S., Mandinach, E. B., Supovitz, J. A., Wayman, J. C., Pickens, C., Martin, E. S., & Steele, J. L. (2009). Using student achievement data to support instructional decision making (NCEE 2009-4067). Washington, DC: What Works Clearinghouse, U.S. Department of Education.
This guide offers five recommendations to help educators effectively use data to monitor students’ academic progress and evaluate instructional practices. The guide recommends that schools set a clear vision for schoolwide data use, develop a data-driven culture, and make data part of an ongoing cycle of instructional improvement. The guide also recommends teaching students how to use their own data to set learning goals.
Practice Guide