Data should be embedded in the work we do. Teams should look at contextual data, process data and outcome data as they make decisions. Clear feedback loops are necessary for leaders to have the information they need to be informed. Protocols for using data can help teams learn how to examine data the same way that a meteorologist systematically reviews data to create a forecast. It is not just about having a lot of data—but having the right data at the right time to help caring people make competent decisions.
FLX Community Schools considers three primary uses for data:
Community Schools needs statements can generate from academic data like proficiency on NYS tests or graduation rates. Beyond that, juvenile arrest rates, foster care placements, unemployment rates, household income, basic demographics, number of people who choose to vote and even the number of library users can all help a community school trace the pattern of strengths to build upon and weaknesses to support for young people and families. We should share concerns; when Public Health is worried about third grade reading levels and Public Schools are concerned about obesity and substance abuse, we share the work of youth development and family support. Data can help point to areas for common work.
Data for Monitoring Process:
Every practice we recommend has standards for fidelity. Simple “bean counting” are not often best for outcome measures, but can serve well as process measures. Process measures check for fidelity. Too often, we decide a program is not working when in actuality we are not working a program. “We do Second Step” or “We use Life Skills” are statements we are glad to hear—but are all the sessions taught? Are at-home materials sent to guardians? What checklist is used to make sure the key steps are taken to implement a practice. Essential checklists are even more important with frameworks. The Tiered Fidelity Inventory is the tool we recommend for generating data around the processes for use of a Multi-Tiered System of Supports. Before we can judge the effectiveness of a practice, we need to carefully attend to the details of accurately and fully implementing the practice. If we innovate and drift from fidelity to fit school culture, we should do so intentionally and with careful attention to the impact on outcomes. In short, we can only say that something works or does not work if we are actually doing that thing.
Outcome data should be tied to goals. Outcome data can be used to form SMART goals or to populate logic models. Careful use of outcome data are important. For example, it may be a school goal to reduce office referrals. That may be a worthwhile goal, but if the problem is rooted in inequity then the simplistic outcome of fewer referrals is a distractor from the root problem of disproportional referrals for students with disabilities or African American males.
“We are data informed. We are student driven.”
— Dr. Joseph Fantigrossi