Data Driven Equity

Often, when we think of moving the equity needle on our campuses, we talk in terms of implicit bias, diverse representation and personal responsibility. We don't often connect it to data. Data tells you which teachers are having discipline referral problems within certain populations. Data tells you which teachers are closing gaps for Black and Brown students more quickly. Data tells you which apps are positively impacting intervention and extension for special populations. For example, because ST math is a game based program that requires no language based skills, it works well for ELs and students who are reading below grade level. How are we using data to create equitable learning environments? Male students typically have more office referrals. Is it that boys are "bad" or is it that schools have designed a system for sedentary, compliant learning while socializing boys to be anything but sedentary and compliant? Using a Strength Based Lens How do we use the information we have to drive action? First, find out what's working, and which teachers are succeeding. Use peer observations to build cultural competencies across your campuses and districts. Add accountability discussions and mentoring to learning walks so that you can impact student learning and behavioral outcomes by replicating behaviors and strategies of successful teachers. I'll be talking more to administrators the rest of this year about campus and district equity initiatives, and how to move them from reflection to data driven action. Make sure to recommend SmallBites to your favorite admin team or school board so we can all be better together, one small bite at a time. Watch the interview with Dana Cole in its entirety here. Learn more here: MacPherson, Kelly-Robin St. John, "Reducing Disproportional Discipline Referrals for African American Male Students at The Elementary Level" (2016). Dissertations, Theses, and Masters Projects. Paper 1499449719. http://doi.org/10.21220/W44H2H