Research has shown that the predictive strength of indicators may vary across contexts, underscoring the salience of the local experience.
Across the country, many K-12 school districts have implemented early warning systems that use readily available data to identify students who are at risk of failing to achieve a desired outcome, such as graduating from high school on time. These systems allow educators to intervene early to keep students on track.
But which indicators should they use? Often districts start with common measures from research, such as a 10 percent absence rate. But is that the right cut point in every district? Are there other local data that would pinpoint students more effectively and allow optimal use of district resources?
The guide lays out a seven-step process for creating local indicators, starting with reviewing possible measures, moving through exploratory analyses of local data, and examining the reliability of different indicators or composites to inform local decisions. At each step, templates are provided to illustrate how data can be analyzed and displayed. The templates are also available as Word documents so they can be tailored to local contexts. Developed by researchers at the American Institutes for Research, the guide draws on several years of work partnering with districts to help them look at their local data in new ways. Now others can follow a similar process. Download the templates here.
Along with the guide, REL West has created an animated video summary that highlights the key steps in the process. This video overview can help educators get the big picture of how the process will unfold.
