Using active and former English learner data when creating a balanced picture of bi/multilingual students

August 19, 2022

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The summer months provide multiple opportunities for school and district leaders to review data from the previous school year and focus on goal setting that will inform the outcomes of the forthcoming year. One student population that should certainly be part of these conversations is that of bi/multilingual learners — but most specifically, English learners (ELs). Unfortunately, the common story of EL data is that students are perpetually underperforming and in need of unending language support. Sadly, this is factual by design.

It is important for educators to recognize that EL data is meant to present a picture of language need, so that once students have met English language proficiency (ELP) they are no longer included in the active EL category. In order to develop informed goals and make decisions about EL programming, it is essential that educators balance their EL data by including students who have met ELP — also known as former ELs. The category of ever ELs is also used when combining data of students who are active and former ELs.

Through interviews that informed the research at C-SAIL, education administrators expressed frustration when utilizing EL data because it only showed students as underperforming. Part of this is due to the national definition of ELs, which limits the data to only students who are active ELs and who have not met ELP. This category also includes students who are further identified as long-term ELs (LTELs), which are those who have not met ELP after five years of receiving services.

In her article Be(com)ing an LTEL: Challenging policies and practices in the education of long-term English learners, Mariana Castro looks further at the LTEL classification and related challenges experienced by students and educators alike. In this publication, she points to how previous data reports of active ELs were missing the scores of former ELs and were ultimately unable to show success stories of bilingual education services. These days, by leveraging the Every Student Succeeds Act (ESSA, 2015), school, district, and state education leaders can now incorporate former ELs into accountability measures and view the impact of services on students who have gone through language programs. This is a key opportunity to broaden the EL data to include both students receiving EL services and those who have achieved ELP.

The truth of the matter is that success stories of how bilingual services lead to high performing former ELs are rarely part of the conversation. English Learners in Chicago Public Schools, a report produced by the UChicago Consortium on School Research, drew the same conclusion. “Publicly-reported statistics often make it look as if EL students are consistently behind non-EL students — but on average, students who began as ELs actually had similar achievement and growth, and higher attendance, compared to students never classified as ELs” (de la Torre et al., 2019, p. 2). With that in mind, and in order to paint a full, balanced picture of ELs and the long-term benefits of receiving EL services, it is important for us to also consider the data for ever ELs.

Here are some tips to keep in mind as schools and districts draw goals and make decisions on bi/multilingual learners — including ELs and language programs:

  • Review active EL data with the understanding that scores reflect students in need of language supports
    • Disaggregate active EL data into newcomer students and students who have received most or all of their schooling in the U.S. in order to make appropriate decisions for each group’s EL services (i.e., newcomer ELs are in need of language services that are different to the needs of ELs who were born/raised in the U.S. and who struggle to be reclassified)
  • Analyze former EL data to see how students are performing after they have exited EL services
    • Extend former EL data to include all students in grades 1–12 who were once ELs
    • Disaggregate former EL data by program type and model to observe the impact of different bilingual/EL services on students years after having exited the EL designation
    • Disaggregate former EL data by demographic characteristics (including race, ethnicity, SLIFE [Students with Limited or Interrupted Formal Education], and economic status) to gain insights into the performance of students beyond the EL program by demographics
  • Combine and analyze active and former EL data to obtain a full picture of EL performance
  • Compare the data categories listed above with never ELs, as appropriate, to create paths for meaningful gains of active and former ELs

As schools and districts conduct their data reviews this summer, it is important to move beyond looking only at active EL data and incorporate former EL data to create a balanced picture of ELs. In creating this full picture of bi/multilingual student performance, education administrators can make informed decisions and eliminate the perception that ELs are a perpetually underperforming student group. As a resource for program evaluation and questions to consider when reviewing the data of bi/multilingual learners, check out Chapter 9 of the English Learner Tool Kit (2019), “Tools and resources for evaluating the effectiveness of a district’s EL program.” This resource includes a series of questions on page 3 and tools on pages 5–15.

About the author

Samuel Aguirre is the director of WIDA Español and assistant director of consortium relations. In this position, Sam bridges Spanish language development with English language development to support bilingual education of students in the U.S. and abroad. His life experiences as an emergent bilingual in the U.S., work as an educator in the classroom, advocate working with culturally and linguistically diverse communities and director of multilingual services at a state education agency provide a strong foundation for his role at WIDA.

About the reviewers

Mariana Castro serves as deputy director for the Wisconsin Center for Education Research and as lead developer in various projects related to multilingual development. Her current research is related to language practices of multilingual students, curriculum and instruction in dual language immersion programs and teacher professional learning through the lenses of social justice and advocacy.

Nelson Flores is an associate professor of educational linguistics at the University of Pennsylvania Graduate School of Education. He has collaborated on several research projects focused on the education of bilingual students in U.S. schools. His most recent collaboration has been with The Center on Standards, Alignment, Instruction, and Learning (C-SAIL), where he is studying the historical development and contemporary implementation of standards-based reform for students officially classified as English learners.

About the research

This article was written using data from research conducted at The Center on Standards, Alignment, Instruction, and Learning (C-SAIL) and funded through a grant from the Institute of Education Sciences (IES) of the U.S. Department of Education.


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