In building our Early Care and Education (ECE) Workforce Compensation Strategies Database, our team at the Center for the Study of Child Care Employment (CSCCE) invited states to tell us about their efforts to collect data on the impact of their compensation strategies, but we received few responses to this particular question. This lack of information led us to wonder what data states are collecting about how these initiatives are working for educators and whether states know if their strategies are screening some people in and others out.
Some states analyze data on how programs used stabilization grants for early educator compensation, like North Carolina where approximately 90 percent of programs opted to allocate some stabilization grant funds to compensation. However, many states struggle with collecting and analyzing information on how early educators themselves have been impacted by recent compensation initiatives. As states seek to make progress on compensation, we join the Administration for Children and Families (ACF) in urging policymakers to utilize workforce data collection as a foundational step to ensure public resources are aligned with educators’ needs.1See the section “Using data to support child care workforce compensation” in Administration for Children and Families, U.S. Department of Health and Human Services (2022). Information Memorandum: Using CCDF to Improve Compensation for the Child Care Workforce. https://www.acf.hhs.gov/sites/default/files/documents/occ/CCDF-ACF-IM-2022-02.pdf.
To encourage states to collect workforce data, we have identified common challenges and opportunities, informed by efforts with seven states in our Bold on Early Educator Compensation Learning Community and through years of work at CSCCE on early childhood data systems.
The early care and education system lacks comprehensive workforce data.
Key Elements of a Strong ECE Workforce Data System
A robust state data infrastructure on early care and education collects information about individual ECE workforce members and, at a minimum, includes demographic characteristics (i.e., gender, race, ethnicity), information about education level, and employment information such as wages and benefits received from the employer.
A workforce data system should include:
- Data collection that is inclusive of all educators and settings;
- Regularly updated and cleaned data (e.g., updates when educators move home or change employer, removal of duplicate entries);
- Data collected across a number of demographic and professional characteristics so that data can be disaggregated to understand disparities within the workforce (e.g., wage differences by setting, race/ethnicity, age of children taught);
- A mechanism to access information from individuals, not just providers/directors (data from program directors and owners can be useful but are not a substitute for accurate information directly from educators themselves to ensure policies are shaped by their experiences);
- Data that can be made publicly available to facilitate further research/learnings (e.g., de-identified data to support research studies on policies); and
- State agency staff who have the capacity and training to maintain the data infrastructure and analyze and interpret the data or work with partners to do so.
Even when this information exists, workforce data are often siloed across agencies or funding streams (e.g., child care, pre-K, Head Start).
As a result, states may patch together existing workforce data or limit data collection only to certain segments of the ECE workforce. Having such piecemeal data makes it hard to reach all educators and may deepen existing inequities as some members of the workforce are left out. Missing a full picture of the workforce has already impeded implementation of one of the most significant compensation strategies in a generation. The District of Columbia passed groundbreaking legislation to bring infant-toddler educator pay to parity with pre-K teachers but initially struggled to implement the equity fund payments due to limited centralized data on the workforce. As a result, the D.C. task force recommends data collection as part of their two-phase strategy for implementing compensation policies.
This example highlights the need for states to build an inclusive workforce registry, like the one in Ohio that covers teaching staff and directors in all licensed center- and home-based child care settings as well as pre-K and Head Start settings.2 See “Workforce Data” in McLean, C., Austin, L.J.E., Whitebook, M., & Olson, K.L. (2021). Early Childhood Workforce Index – 2020. Center for the Study of Child Care Employment, University of California, Berkeley. https://cscce.berkeley.edu/workforce-index-2020/state-policies-to-improve-early-childhood-educator-jobs/early-childhood-educator-workforce-policies/workforce-data/ . Additionally, the ability to be represented in a statewide data system that influences or facilitates access to public resources should be free and accessible for early educators. To boost registry participation in Wisconsin, the WECA Shared Services network covers costs for family child care members to join and assists with sign-up,3For more examples and state-by-state information on inclusiveness of registries and surveys, see Table 3.9A “Progress on Workforce Data, by State, 2020” in Workforce Data and Appendix 3 of the 2020 Early Childhood Workforce Index. playing a key role in collecting information on home-based educators and connecting them with financial relief paid via the registry. WECA’s efforts notwithstanding, participation in a registry should not be held behind a paywall that some may not be aware of or able to afford.
The creation of a system that is easy for educators to access and update can result in more robust data and reduce administrative burden.
Many states that have created ECE workforce data infrastructure struggle to reach and engage educators to keep the data updated. As a result, educator data may fail to accurately reflect the current workforce. By making it easier for educators to access the system and update their information, agencies can reduce administrative burden.
The following recommendations emerged through conversations with state leaders as part of CSCCE’s Bold on Early Educator Compensation Learning Community:
- Build trust through minimizing reporting requirements and explaining to educators why certain reporting requirements exist;
- Keep the data input process consistent to help users build habits and confidence navigating what can often be an unruly process;
- Pre-populate data whenever possible to make it easier to fill out online forms;
- Offer support in multiple languages for people navigating data input and applications to promote equitable access and inclusion of all educators, many of whom speak a language other than English; and
- Connect to users through shared services networks and community-based nonprofits that regularly engage educators, supporting educators in navigating data collection systems and compensation initiatives, while creating feedback channels to improve those systems.
Research partnerships can enhance state efforts to analyze workforce data.
State agencies may lack the capacity to carry out in-house data cleaning and analysis of workforce data but can build out these efforts through research partnerships with universities, foundations and other non-profit research centers. For example, the Virginia Department of Education, the Virginia Early Childhood Foundation, and researchers from the University of Virginia established a partnership in 2019 when the state was awarded Preschool Development Birth Through Five (PDG B-5) funds.4Other examples of research partnerships in the field include the 2019 workforce study conducted by University of Massachusetts, Boston researchers for the state’s Department of Early Care and Education and the workforce study conducted by Child Care Services Association for the North Carolina Division of Child Development and Early Education. This research-policy partnership rolled out the Teacher Recognition Program, a financial incentive program designed to support teacher retention with a randomized controlled trial to study the impact of PDG B-5. The study collected teacher-level data (demographics, employment status verification, education level, and compensation levels) to evaluate the impact of the program on teacher retention. The striking finding that the financial incentives cut turnover rates in half, from 30 percent to 15 percent, compelled expansion of the program.
For too long, the early care and education workforce has been invisibilized and excluded from policies and data analysis about them.
Understanding the needs of early educators and how policies impact them goes beyond quantitative data. While collecting basic demographic and employment information about early educators is critical, any formal data from a workforce survey or registry are no substitute for directly engaging educator communities and truly listening to their lived experiences. Qualitative and community-based participatory research methods are additional tools to document the experiences of educators. Crucially, sharing data with the community from whom input is gathered and engaging them as experts is an essential step in centering the experiences, intellect, and leadership of educators themselves and engaging them as partners in policymaking. We are inspired by an ongoing project in which Child Care Aware of Washington state, convenes a group of 25 early educators with diverse experiences to inform policy for early educator compensation, drawing on the National Equity Project’s framework for Liberatory Design.5Liberatory Design is a framework that disrupts inequity in complex systems design by using an equity practice, human-centered design, and complex systems theory to shift power and build agency and knowledge in those participating in the design process.
Gathering up-to-date data and input from early educators about their compensation, working conditions, and resources they might need signals that “we are paying attention, and we care.” We urge state agencies to build out inclusive workforce data collection as a fundamental step towards developing effective policy that properly supports and rewards early educators.