1. P-20 Longitudinal Data Systems What is the information we need, how do we get it, what do we do with it? Elizabeth Laird & Helene Stebbins

2. Why Data? Why Now? Head Start Act of 2007 “ The State Advisory Council shall…develop recommendations regarding the establishment of a unified data collection system for public early childhood education and development programs and services throughout the state.” HR 3221: Early Learning Challenge Grant A coordinated data infrastructure that facilitates— uniform data collection about the quality of early learning programs, essential information about the children and families that participate in such programs, and the qualifications and compensation of the early learning workforce in such programs; and alignment and interoperability between the data system for early learning programs for children and data systems for elementary and secondary education.” State progress demonstrated by: increasing the percentage of disadvantaged children in each age group (infants, toddlers, and preschoolers) who participate in high-quality early learning programs; increasing the number of high-quality early learning programs in low- income communities;

3. Early Childhood Data Collaborative  Center for the Study of Child Care Employment at UC Berkeley  Council of Chief State School Officers  Data Quality Campaign  National Center for Children in Poverty  National Governors Association  National Council of State Legislatures  Pre-K Now

4. ECDC Goals:  Document current state early childhood data efforts, and the priorities of state policymakers and other key audiences for improving early childhood data systems and data use;  Generate a template of key policy questions, essential elements or capabilities of exemplary state early childhood data system, and actions to promote data- based decision making;  Create policy tools, resources, and services that build political will and support states to develop and use comprehensive early childhood data systems that link with K-12.

5. Theory of Action  Based on the DQC model with K-12 data  Start with the policy questions: design data systems to answer key “killer questions”: Resonate with policy leaders Illustrate the power of data  Identify essential elements necessary to answer the questions  Track state progress in collecting the essential data elements

6. Moving along the Accountability Spectrum Compliance Reporting Accountability (rearview mirror view—what we did well/not so well) Continuous Improvement (looking out the front window)

7. Opportunity to Leverage Federal Funding Source: Leveraging Federal Funding: A Roadmap for StatesLeveraging Federal Funding: A Roadmap for States Source: Leveraging Federal Funding: A Roadmap for StatesLeveraging Federal Funding: A Roadmap for States

8. Partnership Achieve, Inc.National Center for Educational Achievement Alliance for Excellent EducationNational Center for Higher Education Management Systems Council of Chief State School Officers NGA Center for Best Practices Education Commission of the States Schools Interoperability Framework Association The Education TrustNational Conference of State Legislatures National Association of States Boards of Education State Educational Technology Directors Association National Association of System Heads State Higher Education Executive Officers

9. Killer Policy Questions Which schools produce the strongest academic growth for their students? What achievement levels in middle school indicate that a student is on track to succeed in rigorous courses in high school? What is the state’s graduation rate, according to the 2005 National Governor's Association graduation compact? Which high school performance indicators (e.g., enrollment in rigorous courses or performance on state tests) are the best predictors of students' success in college or the workplace? What percentage of high school graduates who go on to college take remedial courses? Which teacher preparation programs produce the graduates whose students have the strongest academic growth?

10. 10 Essential Elements 1. Unique statewide student identifier 2. Student-level enrollment, demographic and program participation information 3. Ability to match individual students’ test records from year to year to measure growth 4. Information on untested students 5. Teacher identifier system with ability to match teachers to students 6. Student-level transcript information, including information on courses completed and grades earned 7. Student-level college readiness test scores 8. Student-level graduation and dropout data 9. Ability to match student records between the P-12 and postsecondary systems 10. State data audit system assessing data quality, validity, and reliability

11. Policy Questions and Elements Which schools produce the strongest academic growth for their students? 1, 3, 4 What achievement levels in middle school indicate that a student is on track to succeed in rigorous courses in high school? 1, 3, 6, 7 What is the state’s graduation rate, according to the 2005 National Governor's Association graduation compact? 1, 2, 8, 10 Which high school performance indicators (e.g., enrollment in rigorous courses or performance on state tests) are the best predictors of students' success in college or the workplace? 1, 3, 6, 7, 8, 9 What percentage of high school graduates who go on to college take remedial courses? 1, 8, 9 Which teacher preparation programs produce the graduates whose students have the strongest academic growth? 1, 3, 4, 5

12. Annual Survey—Data Systems 2005 2009 Source: 2009 Annual Progress Report on State Data Systems2009 Annual Progress Report on State Data Systems Source: 2009 Annual Progress Report on State Data Systems2009 Annual Progress Report on State Data Systems

13. Ensure Data Use

14. Annual Survey—Data Use

15. Next Steps for Questions, Elements, and Actions  Vet draft killer questions and essential data elements with stakeholders  Finalize questions, elements, and actions  Survey states on data collection and use  Build momentum to improve state data collection on young children

16. DRAFT ECDC Killer Questions 1.Are children, birth to age five, on track to succeed at school entry and beyond? 2.Which children have access to high quality early care and education programs? 3.Is the quality of programs improving? 4.What are the characteristics of effective programs? 5.What is the cost per child of a high quality program? 6.What policies and investments lead to a skilled and stable early childhood workforce? 7.How prepared is the workforce to provide effective education and care for all children?

17. DRAFT ECDC Essential Elements Child-Level Data 1.Unique statewide child identifier that links across programs and key databases 2.Child-level demographics, risk(s) exposure, enrollment, and attendance 3.Child-level assessment data across multiple domains matched over time to measure growth 4.Ability to match child-level early childhood data with K-12 and beyond

18. DRAFT ECDC Essential Elements Program-Level Data 5.Unique site/program identifier with the ability to link to individual children served 6.Site-level structural, staffing, and quality information 7.Site-level revenue and cost data Workforce/Teacher-Level Data 8.Unique teacher/provider identifier with ability to link to individual children served 9.Teacher-level demographics, education and training, and workplace characteristics 10.Inform on education and training supports and content available to teachers/providers

19. Draft ECDC Actions for Use EXPAND the ability of state early childhood data systems to link across systems and agencies and across the P-20/W education pipeline. 1.Link state early childhood data systems with other agencies like health and social services and with K-12, postsecondary education, and the workforce. 2.Create stable, sustained support for robust state early childhood data systems. 3.Develop governance structures to guide data collection, sharing and use. 4.Build interoperable state data repositories (e.g., data warehouses) that integrate child, program, workforce, financial and facility data.

20. Draft ECDC Actions for Use ENSURE that data can be accessed, analyzed and used, and communicate data to all stakeholders to promote continuous improvement. 4.Implement systems to provide all stakeholders timely access to the information they need while protecting individual privacy. 5.Create developmental progress reports with individual child data that provide information teachers, providers, and parents can use to improve child outcomes. 6.Create reports that include aggregate longitudinal statistics on early childhood systems linked with K-12 and groups of children to guide program- and state-level improvement efforts.

21. Draft ECDC Actions for Use BUILD the capacity of all stakeholders to use longitudinal data for effective decisionmaking. 8.Develop a purposeful research agenda and collaborate with universities, researchers and intermediary groups to explore the data for useful information. 9.Implement policies and promote practices, including professional development and credentialing, to ensure that teachers and providers know how to access, analyze and use data appropriately. 10.Promote strategies to raise awareness of available data and ensure that all key stakeholders, including state policymakers, know how to access, analyze and use the information.

22. Outstanding Questions 1.Which children and programs are included in the state data system(s)? 2.How can we measure progress towards states collecting data on program quality without defining quality for states? 3.How do we convey the importance of protecting privacy of individual children while promoting data use? 4.How do we address the validity of child assessments? 5.Should individual teachers be linked to individual sites and/or individual children?

23. Future ECDC Activities  Build partnerships among stakeholders  Communicate policy questions and data elements, and track state progress  Provide state-based policy and advocacy assistance  Conduct state and federal advocacy work to improve coordination and alignment

24. Contact the ECDC: 5/11/2015 24 CSCCEMarcy Whitebook, mwhbk@berkeley.edu andmwhbk@berkeley.edu Fran Kipnis, frankipnis@berkeley.edufrankipnis@berkeley.edu CCSSOTom Schultz, thomass@ccsso.orgthomass@ccsso.org DQCElizabeth Laird, Elizabeth@DataQualityCampaign.org Elizabeth@DataQualityCampaign.org NCCPHelene Stebbins, helene.stebbins@verizon.nethelene.stebbins@verizon.net NGARachel Demma, RDemma@NGA.ORGRDemma@NGA.ORG NCSLJennifer Stedron, jennifer.stedron@ncsl.orgjennifer.stedron@ncsl.org Pre-K NowAlbert Wat, awat@pewtrusts.orgawat@pewtrusts.org