7. Emphasize Continuous Improvement as the Goal of Data Collection

For years, education policy debates have focused on increasing the transparency and accountability of American public education. In early education, this has taken the form of considerable public investment in building systems for evaluating and monitoring the quality of programs. The purpose of any evaluation process should be to drive quality improvement. Results can inform classroom practice, guide the design of pre-service and in-service training, and inform investment in quality improvement and human capital at the state and federal levels.

Approach teacher evaluation as an opportunity to improve instruction. Evaluation systems should treat teachers as the professionals they are by being focused first and foremost on professional growth. In addition to providing data on professional needs and areas for growth, teachers should have the opportunity to work with their leadership teams to set goals and reflect on their practice with peers and mentors. Principals and center directors must have the knowledge, expertise, and resources to match teachers with the help they most need. This may include individualized coaching, use of video for reflection and improvement, or visits with colleagues with specific strengths. Teachers who are consistently identified as effective should be identified as instructional resources for peers and should be recognized and rewarded with a formal teacher leader role and additional compensation. Similar strategies can be adapted for cohorts of family child care providers or teachers from child care centers using data from environmental rating scales, classroom observations, or quality rating and improvement systems.

Use valid and reliable measures to gauge student learning and empower teachers to use data to improve their practice. States must ensure that each child-level assessment is appropriate and used solely to measure the discrete skill the tool was designed to measure. States should provide teachers technical and content expertise, time, and flexibility for explaining how to use formative and observational student-level data to inform instructional practices. Data literacy among teachers and administrators is important at the early and elementary levels across all settings.

Use quality rating and improvement system data to inform strategy. QRIS are not only important for providing quality ratings to families, but also for their role in guiding policy and program improvement. States should use program evaluation data to support strategic investments in professional development, coaching, professional learning communities, teaching resources, and content specialists. Data can also be used to inform quality improvement projects targeted to deficits or strengths identified by program evaluation tools and providers can be offered the opportunity to work in cohorts to improve their practice.

Close DLL data gaps. Dual language learners represent an estimated 32 percent of the young child population in the U.S., yet we lack comprehensive data on how these children are being served. Only one-third of state pre-K programs collect information about language use in the home—such as through a home language survey—and track DLL enrollment. That means a majority of state pre-K programs may be operating with little to no information on the languages DLLs speak and on their skills and knowledge in these languages. But the data gaps do not stop there: a majority of state QRIS lack indicators related to DLLs, while popular tools used to measure teacher-child interactions, such as the CLASS, have been criticized for failing to take DLLs’ specific needs into account. State policymakers should adopt a uniform protocol to identify DLLs and collect this data across state early education programs, screen for language abilities in both English and the home language, adopt and prioritize DLL-related indicators in QRIS, provide technical assistance and outreach to linguistically diverse providers to encourage their participation in QRIS, and seek additional measures of classroom quality to fully capture the experiences of DLLs.

Monitor and report DLL outcomes over the long term. National, state, and district level data reveal disparities in academic outcomes for students who are classified as dual language learners. While these data points are vital to track, more attention needs to be paid to how DLLs perform over the long term once they achieve English language proficiency. DLLs are a unique subgroup in that the classification is intended to be temporary: ideally, all DLL students will achieve proficiency in English and shed the label. At the same time, the subgroup is dynamic, with different students entering and exiting each year. Strong accountability systems should (1) report all DLL outcomes, disaggregated by former and current status and (2) include an “ever-DLL” group to track the entire group of current and former DLLs over their PreK–12 years. Several states, including Illinois, Washington, and Oregon, have begun reporting on the performance of former DLLs. These data reveal that former DLLs perform at similar levels, and sometimes outperform, their never-DLL peers on standardized tests of English language arts and mathematics, on average.

Use high-quality data to promote continuous quality improvement and continuity across systems. States should be intentional about sharing data across government agencies and use data as a critical tool to deliver the best possible services to families. Families should have the option to share their personal information with other programs so that once they provide data, they can be notified of all services for which they are eligible regardless of their entry point, and assisted with enrollment. Agencies should employ technologists to ensure applying for and using government benefits is efficient and user-friendly. The government should employ best practices for ensuring data privacy and secure data storage. An emphasis on data for continual learning and improvement should be the focus of its collection. States and school districts can facilitate data sharing at the provider level when children transition from early learning settings to schools. Elementary schools receiving children from child care providers, Head Start, or state pre-k should have access to student information that they can use for individualized planning and staffing to better support incoming students.

• New America resources:
  • Dual Language Learner Data Gaps (policy paper)
  • Seeing Clearly: Five Lenses to Bring English Learner Data into Focus (policy paper)
  • Rethinking the English Learner Achievement Gap (blog post)
  • Indispensables for Quality Pre-K (web resource)
• Other resources:
  • Migration Policy Institute, Quality for Whom? Supporting Diverse Children and Workers in Early Childhood Quality Rating and Improvement Systems
  • Stanford Center for Education Policy Analysis, The Effects of Accountability Incentives in Early Childhood Education