Schools and districts nationwide are being exhorted to use data to improve instruction. But what does that advice look like in practice?
That鈥檚 the question addressed by a new study that examined two midsize urban districts and two nonprofit charter-management organizations with records of improving student achievement over time and of grounding their decisionmaking in data.
While the effective use of data can look quite different from place to place, the researchers concluded, the school systems studied had all built a strong foundation for data use by setting specific, measurable goals for student performance at the system, school, and classroom levels, among other commonalities.
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鈥淭he more explicit and targeted the goals are, the more likely they are to provide focus for data-driven decisionmaking,鈥� says 鈥淎chieving With Data,鈥� conducted by the Center on 91制片厂视频al Governance at the University of Southern California and commissioned by the NewSchools Venture Fund, a San Francisco-based venture philanthropy.
The researchers spent part of the 2005-06 school year examining practices within each of four systems of schools: the Garden Grove, Calif., school district; the Aldine, Texas, school district; the New Haven, Conn.-based Achievement First charter-management organization; and Aspire Public Schools, a CMO based in Oakland, Calif.
They found that data-driven decisionmaking was made much easier when clear, grade-by-grade curricula were adopted systemwide, when high-quality materials were aligned to the curriculum, and when pacing guides clearly described the breadth and depth of content to be taught.
Both the Garden Grove and Aldine school districts, for example, have systemwide curricula, pacing guides, and instructional materials. Aspire has produced a set of instructional guidelines for science, language arts, humanities, and mathematics based on California content standards.
The researchers cautioned, though, that school systems must strike a balance between a core curriculum and enough flexibility for educators to use different instructional strategies based on what the data tell them.
Building a Culture
Each of the school systems also built a culture that values regular and consistent use of data. And all of them had invested in a user-friendly data-management infrastructure, focused on making data timely and accessible. Most also had a dedicated individual or team responsible for supporting data analysis and use by both central office and school personnel.
The four school systems also devoted time to selecting the right data to collect, including student test data, data on instructional practices, and data to monitor progress toward specific goals. All four systems, for example, used data from periodic, or interim, assessments aligned to content standards.
By drawing on a mix of data, school systems were able to use the information for multiple purposes鈥攊ncluding instructional, curricular, resource allocation, and planning decisions. Some sites also offered rewards and incentives for improved achievement that arose out of data-driven decisions.
In addition, each of the school systems invested in professional development to support the use of data, provided time for teacher collaboration, and connected educators across schools to share data and improvement strategies.
鈥淭he one big challenge was, in fact, getting all teachers to buy in and use data, and to have enough professional development so that the teachers could feel comfortable,鈥� Amanda Datnow, an associate director of the center and one of the report鈥檚 authors, said in an interview.
At the same time, she noted, some teachers have become enthusiastic data users. 鈥淲e went into schools and teachers would be literally meeting us with notebooks of information that they wanted to share with us,鈥� she said.
All of the school systems also developed tools and processes to help principals, teachers, and other staff act on data. These included explicit data-analysis protocols and goal-monitoring reports for administrators, teachers, and, in some cases, students.
Nonetheless, managing and prioritizing data continued to be a challenge. Particularly as school systems expanded the types of data collected and used for school improvement efforts, Ms. Datnow said, 鈥渘ot all of the data-management systems were ready to grow with their needs on the ground.鈥�
