One out of every five students in California schools is currently an English Learner, also referred to as a multilingual learner (MLL). Despite progress in recent years, California still struggles to provide the resources and instruction necessary to fully support them – with the latest state assessments showing only around 10% of these students at grade level in English Language Arts or math. However, the state’s implementation of the Cradle-to-Career (C2C) Data System offers a significant opportunity to better understand how these students are faring, along with which schools, districts, and approaches contribute to their success in ways that other educators can learn from. To ensure this is possible, it is critical that state and C2C leaders design the system with an asset-based approach that highlights MLLs’ strengths, capabilities, and diverse experiences, while providing clear, actionable, and disaggregated data on their English Learner level status.
Multilingual Students are a Significant Share of California’s Students
Over 35% of students in our schools have been classified as English learners (ELs) at some point in their academic journey and roughly 40% of all students come from multilingual households, underscoring the substantial linguistic diversity within our state. However, MLLs are not a homogenous group. MLLs are identified as fitting into a few distinct categories based on their proficiency levels in English that helps determine the specific types of instruction and resources they should receive. As they progress in their learning, students are then “reclassified” as needed. To better understand the nuances of MLLs’ pathways and improve equity gaps along them, it is essential to have access to fully disaggregated data that includes key transition and reclassification points in an EL’s journey toward proficiency and academic success.
Why All Multilingual Students Need to Be Transparent in Data
Multilingual students bring incredible diversity to the classroom, which should be celebrated, supported, and leveraged in their learning experiences. By identifying the full range of EL classifications in the C2C data system, researchers, decision-makers, and communities will better understand the specific needs of multilingual students and be better equipped to advocate for evidence-based support. This data allows educators and policymakers to tailor instructional practices and policies to meet the specific needs of different linguistic groups and ensure MLLs have equitable college access. Such data can also uncover trends, bright spots, and disparities within MLL classifications, which are often masked by the broader EL categorical analyses, such as between newcomers and long-term English learners (LTELs), thereby informing targeted interventions and supports. In the long-term, transparent data for multilingual students will be crucial in supporting the state’s efforts to monitor and implement inclusive policies aimed at enhancing educational experiences and college access for all students.
Challenges with C2C’s Current Approach
Unfortunately, current plans for the C2C data system are insufficient, providing limited data on MLLs. Current plans do not include providing data on the full range of MLLs, such as LTELs, at-risk LTELs (ARLTELs), newcomers, dual language learners (DLLs), and dually identified ELs with a disability. Recent data shows that fewer LTELs and ARLTELs met or exceeded English language art standards and math compared to ELs, demonstrating a greater need for supports. Differentiating between these subgroups in the C2C Data System would help researchers, policymakers, and advocates to better understand their separate needs, pathways, postsecondary transitions, and outcomes.
Opportunity Lies Ahead
In the October 2024 meeting of the C2C Data and Tools Advisory Board, we were pleased to see a step forward in response to advocacy from EdTrust-West and Californians Together. The Data and Tools Advisory Board voted unanimously to advance the MLL proposal to the Office of C2C to conduct a study exploring the feasibility of including a fuller range of disaggregated data on MLLs in the C2C Data System. We are eager to see the outcome of the feasibility study, and we also implore C2C leaders and state policymakers to recognize how crucial this data is – and how infeasible it will be to try to boost academic success for hundreds of thousands of MLL students without this data.
In addition to the different classifications of EL-status, the state should also consider disaggregating data by Hispanic, non-Hispanic, and different linguistic groups among MLLs to provide insights into how these identities intersect with language acquisition. And lastly, C2C leaders should pioneer a statewide MLL pathways dashboard that also supports the collection and integration of such data in higher education and the workforce, as state-level MLL data continues to remain limited beyond high school.
Without expanding the proposed data on MLLs in the C2C, we run the risk of launching a new data system that stops short of truly being comprehensive and actionable for this significant student population. To stay informed with C2C updates and engage in C2C advocacy, consider joining the statewide Data for the People coalition—a coalition of organizations representing advocates, community members, parents and families, students, and educators, united by their dedication to leveraging data to increase racial equity in the education system. Together, we can ensure every MLL is visible within data so state leaders and educators can ensure all MLLs receive the resources necessary to academically succeed and be effectively prepared for a prosperous future.
