This fact sheet provides information about high school graduation rates for English learners (ELs) and all students in all state educational agencies (SEAs) except Puerto Rico. When interpreting these data, it is important to note that ELs are included in the “all students” category.

This fact sheet focuses on the five-year projections for teachers of English learners (ELs) reported by state educational agencies (SEAs).

Each year, states report the five most common languages spoken by English learners (ELs), along with the number of ELs who speak each language. This fact sheet summarizes the most commonly spoken languages in School Year (SY) 2022–23.

State education agencies are sitting on rich repositories of quantitative and qualitative assessment data.

Over the past two decades, federal education policies such as the No Child Left Behind Act and the Every Student Succeeds Act (ESSA) have sought to improve school performance through accountability systems.

This resource was created in collaboration with members of the State Leadership for Multilingual Learner (ML) Equity partnership, and offers guidance for state education agency (SEA) leaders who are interested in designing and implementing a statewide framework for multilingual learner (ML)

In this report, we examine how variation in English Learners (EL) reclassification policy complexity relates to the likelihood of reclassification eligibility, the timing of eligibility across grade levels, and policy adherence.

In this report, we explore how English Learner (EL) reclassification policies vary across states and the relationship between states’ policy structures and the characteristics of their EL populations.

The Civil Rights Data Collection (CRDC) is a mandatory survey of all public schools and school districts in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico.

This toolkit was created in collaboration with members of the State Leadership for Multilingual Learner (ML) Equity partnership. Within this document, we outline strategies for strengthening the ML educator pipeline.