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Approaching REL Central Work Through an Equity Lens

Central | August 15, 2022

Happy, diverse school students in group high fiving in classroom to celebrate teamwork or achievement

We know that a variety of factors, in and out of schools, influence student achievement, and we know that our education systems consistently serve some students less well than others. But do we know what factors we should focus on to ensure that all students have equitable opportunities to learn and succeed?

REL Central’s work takes place within collaborative partnerships with state, Tribal, and local education agencies, addressing high-priority challenges through applied research; training, coaching, and technical support; and dissemination of resources and evidence. We’re currently working with partners who are addressing pressing needs that range from teacher recruitment and retention, math achievement, early literacy, postsecondary and workforce readiness, and tools to help teachers implement evidence-based instructional practices in their classrooms. What all of these efforts have in common is an overarching focus on ensuring that all students are college-, career-, and life-ready and have meaningful choices after high school. Our work with partners is purpose-driven, grounded in culture and rigor, and focused on helping partners improve outcomes for students and educators over the next five years and beyond. As we launch our partnerships and begin this important work in collaboration with educators across the Central region, let’s pause for a moment to ask ourselves one crucial question.

Are we focusing on all of the right things?

As educators and researchers, we often consider our locus of control to be school policy, curriculum and instruction, and teacher quality, and although these are inarguably many of the right things to focus on, they may not be all of the right things. To make it more likely that all of our school-based efforts can work to raise achievement, let’s consider how a powerful predictor of achievement—income inequality—is often ignored or de-emphasized in our improvement efforts.

Amplifying improvement efforts by deeply understanding students’ needs

At REL Central, much of our current work focuses on supporting partners to effectively address inequitable opportunities in schools, which includes the opportunity gaps that children in poverty routinely experience. Decades of research have also made it clear that experiencing poverty (or attending a high-poverty school or living in a high-poverty neighborhood) is strongly correlated with low student achievement, particularly in math.1, 2 A substantial number of students live in poverty, attend a high-poverty school, or both—nearly one-fifth of all students nationwide.3

We have an opportunity to renew our energies to better address the needs of learners experiencing poverty.

Inequities in education aren’t new, but as schools work to make systemic improvements using Elementary and Secondary School Emergency Relief (ESSER) funds within the ongoing COVID-19 landscape and work, we have an opportunity to renew our energies to better address the needs of learners experiencing poverty

As educators, can we directly mitigate student poverty through systemic improvement?

When we don’t discuss the fact that poverty matters in almost every single classroom in America, we may unwittingly perpetuate the idea that achievement only happens in the classroom, and that teachers and school leaders are the primary influence on student outcomes. Research indicates that everything teachers, principals, and school systems do, combined, still only accounts for some of the variation in average student performance because there are so many other socio-demographic factors (family income, the education environment at home, access to out-of-school learning opportunities) and individual student factors that influence student learning and, particularly, performance on summative standardized exams.4, 5 But these factors play out in complex ways over the course of many years, and there are other adjacencies to consider: for example, health and nutrition and community-based learning. Are there ways, for instance, that we can substantively involve parents in math learning to help raise their children’s math achievement? Can we provide opportunities for rich out-of-school-time experiences for students in poverty? Can we do more to decrease learners’ anxiety about their futures so they can focus on the ambitious content we all want them to learn? We can all benefit from thinking more deeply about how and why income inequality matters and ways in which we might help alleviate the effects of inequality and poverty on learning while working on school-based transformations.

We know that improving education systems will improve outcomes for students, but we don’t yet know the limits of that improvement. Although we know that many factors outside of school control limit some students’ performance, we don’t know how much progress is possible at the individual student level. Teachers and school systems need to commit to what is possible while amplifying school-based initiatives by paying attention to what else influences performance. We are committed to working with our partners to use evidence and data to deeply understand what’s possible. We invite you to join us on this journey and look forward to keeping you updated along the way.

1 Balfanz, R., & Byrnes, V. (2006). Closing the mathematics achievement gap in high-poverty middle schools: Enablers and constraints. Journal of Education for Students Placed at Risk, 11(2), 143–159.

2 Pearman, II, F. A. (2019). The effect of neighborhood poverty on math achievement: Evidence from a value-added design. Education and Urban Society, 51(2), 289–307.

3 National Association of Secondary School Principals. (2020). Position statement: Poverty and its impact on students’ education.,the%20student%E2%80%99s%20ability%20to%20succeed%20in%20a%20school

4 Pipere, A., & Mierina, I. (2017). Exploring non-cognitive predictors of mathematics achievement among 9th-grade students. Learning & Individual Differences, 59, 65–77.

5 Stankov, L., & Lee, J. (2018). Non-cognitive predictors of academic achievement: Evidence from TIMSS and PISA. Learning and Individual Differences, 65, 50–64.


Phillip Herman

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