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Equity in Education: A Journey or the Destination?

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Equity, or ensuring that each student has what they need to be successful in school, is a commendable goal. But is it attainable? How can we truly know if our efforts have created the conditions for every child to reach their potential?

Just asking this question makes me nervous. Educators aren’t supposed to share their doubts. Yet I recall a person from the Department of Education visiting my prior district. This was in the heyday of No Child Left Behind. At one point when we were discussing the challenges of the testing rules with reading and mathematics, the representative asked the group of educators he was addressing, “How many of you believe that every child should be proficient?” He raised his hand as he raised this question.

A deliberate person by nature, I did not immediately respond to this straw poll and affirm it. Based on what, these exams? I thought. If we say yes, are we setting our kids up for failure and creating test-prep factories in our efforts? But everyone else was raising their hand, so I did too.

I don’t want the concept of equity to be lumped with these platitudes and political talking points. It’s too important. So there has to be a way to describe equity and determine at what level it has been achieved in schools, beyond only a definition. We have to make the abstract concrete. Otherwise, we leave the determination for student success up to everyone except the people actually in the classrooms and school. Equity becomes unattainable.

I believe equity is a journey, an ongoing experience that we are constantly monitoring to evaluate our course and adjust as needed. This monitoring requires data. In Shane Safir’s book The Listening Leader, she describes three sets of data that educators can look to when assessing their school’s journey toward a collective capacity for achieving equity (p. 19).

  • Satellite Data – Large scale results that help to identify trends and patterns of student achievement and equity, including standardized test scores and district benchmarks.
  • Map Data – Medium scale results that focus our attention on student skill acquisition in subject areas, including reading levels, fluency checks, student perception surveys, and screener results.
  • Street Data – Small scale results that help identify student misconceptions of key skills, including student nonverbal cues, student interviews, running records, observation notes, and work artifacts.

As I head into my fourth year in my current role as an elementary principal, once again re-engaging in this data analysis process, it is helpful to have these geographical metaphors for describing data. It reminds me that our work is never done and that we have to constantly renew ourselves in light of the most current assessment results along with more promising instructional practices that might be available now.

For example, I recently collected and curated data about our ELA test scores for the last three years. I compared our student cohort labeled “economically disadvantaged” with the student group that was not. Below is how the groups compared from 2015-2016 to 2017-2018. (F/R stands for “free/reduced lunch”, the metric used in schools to denote economically disadvantaged.)

This is satellite data. It tells us little about specific students’ abilities as readers and writers, even if we did an item analysis. But what it does tell us is that we have a persistent gap that seems to be associated with poverty. Our map data does not reveal much in this area as educators are not privy to which children live in poverty, and for good reason.

Several questions come up for me. First, why do our ELA scores reveal a significant gap while our mathematics scores do not? Second, how much of this distance is a result of poverty alone? Third, what influence might we as a faculty have in reducing the gap?

Before we start making assumptions, such as inferring that what we do in mathematics is transferrable to literacy, it helps to have a lens for looking for data that leads to the right conversations for change. Safir offers five principles for identifying our purpose when looking at data (p. 18).

  1. Local accountability – Work to create a culture of local, peer-to-peer accountability for results.
  2. Timeliness – Build teacher capacity to collect daily informal data about student misconceptions.
  3. Experiential data – Value people’s experience – students and adults – as a form of evidence.
  4. Formative vs. punitive – Don’t use data as a hammer; use it purely for improvement.
  5. Alternative assessments – Multiple forms of data tell a story about students that paper-and-pencil assessments can’t.

This is street data. As Safir notes, “These are examples of Level 3 data that help teachers navigate the complex path to learning.” Looking through this lens, we can balance external accountability with internal, collective responsibility.

I’d like to share more about our school’s experience in using this type of data, but we are only in the beginning stages of this work. For example, we are purchasing tablets for upper elementary teachers to collect and curate informal data such as conferring notes during readers-writers workshop. Also, multiple teachers are using digital portfolio applications to communicate student work with families and a broader audience. Once we view this information as just as important as larger data points in guiding our students’ journey toward success, I believe we will create real momentum toward that perpetual destination we call equity.


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