Rethinking Data for English Learners in the ESSA Era

Two New Reports from New America
Blog Post
Aug. 16, 2017

Did you know nearly 30 million U.S. adults use reading glasses? Without such an aid, it would be difficult for these individuals to derive meaning from the pages sitting before them. The lenses bring the information into focus.

When it comes to data on K-12 English learner (EL) students, there is a similar need for clarity. Overall, the view of EL outcomes is often blurry or distorted. This reality stems from a host of common misunderstandings and limitations to how most states collect, track, and report on the data.

Because of these gaps, it is extremely difficult for policymakers, advocates, and media professionals to get a clear picture of how ELs are faring. Many education leaders proceed with a fuzzy idea of what excellence for ELs looks like and how genuine successes would show up in the data. Worse yet, data metrics can misleadingly present ELs as a perennially failing group, reinforcing a mindset wherein students are framed as dragging down a school’s test scores.

In a new report published today, Seeing Clearly: Five Lenses to Bring English Learner Data into Focus, we offer a framework to help address these issues and enable more accurate, meaningful data usage for ELs. When parsing EL data, stakeholders should bear in mind that:

1. The EL subgroup is not static.
2. Learning a language takes time—but not forever.
3. ELs at different stages progress at different rates.
4. English skills impact academic performance.
5. Poverty affects most ELs and, as a result, their educational outcomes.

The new report—along with an accompanying one-pager—represents a translation and distillation of several principles that have been widely noted in the EL academic research into a more concise, curated format. It aims to build data literacy for both the readers on the “front end” interpreting the metrics (such as advocates and journalists shaping narratives) and the designers setting them on the “back end” (namely, state and local policy leaders).

As I write in the report, the issue is a particularly timely one in light of new flexibilities for setting EL outcomes, goals, and accountability metrics under the federal Every Student Succeeds Act (ESSA). As states continue to finalize ESSA plans by the September 18 deadline and move forward with their implementation, it is critical to build EL data literacy among a wider audience. Ensuring equity for ELs will require expanding the coalition of stakeholders who understand EL-related data beyond just technical experts in the ESSA era.

For example, the report highlights the critical fact that the EL population is not static. Every year, schools identify new students who qualify to “enter” EL status, and schools “exit” those who have achieved English proficiency. This “revolving door” nature of the EL subgroup can bias data interpretations against ELs. While identified as English learners, these students' limited English skills—by definition—interfere with their ability to excel academically. But once students achieve English proficiency, they are exited from the EL subgroup. Together, these factors create a “Catch 22,” an academic EL “gap that cannot go away.” More longitudinal data are therefore imperative to make accurate inferences by tracking outcomes of both current and former ELs over a longer arc of time.

Through consideration of this lens and the four others, the EL data framework can support policymakers—as well as educators, school leaders, parents, and advocates—in making more valid inferences to yield strategic action for ELs.

Of course, even the most thoughtfully designed data must be easily accessible to maximize the impact. Recent legislation from Oregon illustrates this combination of improved data quality and transparency, as I detail in a companion case study report, Pioneering Change: Leveraging Data to Reform English Learner Education in Oregon, also released today. The law linked EL data insights to the dispersal of millions in new funding to support the lowest-performing, highest-needs districts for ELs.

Oregon’s story illustrates how key data principles can manifest in concrete policy changes. For example, their reformed data systems use longitudinal metrics that factor in both current and former ELs. In addition, leaders selected metrics that focus on academic growth for current ELs—versus an achievement bar that would be developmentally impossible to meet. Leaders also considered outcomes and demographic data to more accurate diagnose the EL population’s needs, attending to poverty, homelessness, and student mobility. In Oregon, nearly 80 percent of ELs grow up in poverty, as the newly-required state report shows.

Because of the state policy shifts, changes are unfolding at the local level. Districts identified by the metrics are using the new state funding in a variety of ways: for professional development, parent engagement, hiring EL coaches, extended school days, and new instructional materials. Along with these school-based reforms, the state-generated EL data report is also shifting the status quo by creating broader, public visibility for ELs. Already, the report’s accessibility has enabled greater, more nuanced coverage of EL outcomes from local media outlets.

Oregon’s example and the EL data framework have implications both for viewing current data points and designing better systems going forward. The collection, interpretation, and use of English learner data is an issue of growing importance for education systems in every state across the nation. Ultimately, any meaningful vision of equity for English learners must start with accurate, clear data insights.