THE WISCONSIN EARLY CHILDHOOD LONGITUDINAL DATA SYSTEM (WI EC-LDS) PROJECT

1. THE WISCONSIN EARLY CHILDHOOD LONGITUDINAL DATA SYSTEM (WI EC-LDS) PROJECT The Wisconsin Data Roundtable February 22, 2012

2. How are the children of Wisconsin doing?

3. Welcome and Introductions DPI Kurt Kiefer Assistant State Superintendent Jill Haglund EC Consultant, Office of Early Learning, staff to Governor’s Early Childhood Advisory Council (ECAC) June Fox Data Analyst Laura Paella Office Associate, Office of Early Learning DCF Jane Penner-Hoppe Policy Advisor and staff to Governor’s Early Childhood Advisory Council (ECAC) Hilary Shager Research Analyst Alyssa Bokelman Operations Associate and ECAC Staff DHS Linda McCartPolicy Director Angela Rohan Epidemiologist DWD Dennis Winters Chief Economic Advisor WCCF Dave Edie Early Education Policy Analyst and ECAC member National Elliot Regenstein, Chicago-based partner of Education Counsel Missy Cochenour, State Support Team (Applied Engineering Management) Susan Illgen, State Support Team (Applied Engineering Management)

4. Why have a coordinated data system? • A coordinated ECE data system can provide parents with the information they need to advocate on behalf of their children; educators with the information they need to serve those children; and policymakers with the information they need to manage the state's resources. • For parents, connecting data can make it easier for them to access services. This will be most important for parents and caregivers of the most vulnerable children, who will have the greatest need for service. • For educators and providers, linked data could help them understand the needs of the children they serve. Better understanding children’s needs will allow educators and providers to serve children more effectively – and potentially connect children to other available resources. • For many others – including state policymakers and researchers – bringing disparate data sources together can provide information about what is needed and what is available from a resource or policy level. This information can be used to manage resources more efficiently, and to better understand the impact of early childhood education.

5. Why have a coordinated data system? (cont'd) • The end goal is to improve child outcomes -- in part through better access to high-quality service -- and data is an essential tool in achieving that goal. • A coordinated data system should provide information that leads to changes in policy and practice that improve child outcomes. • We want data so that we can do things differently – and better. Data plays an essential role in any continuous improvement cycle. • In the words of the Georgia State Advisory Council on Early Childhood Education and Care: "Ultimately, the measure of a state data system is not what it collects but what it produces." • The national Early Childhood Data Collaborative (ECDC) has identified ten essential elements for a unified early childhood data system. • The elements focus on data about children, personnel, and programs. 5

6. The 10 Essential Elements

7. The 10 Essential Elements Survey of implementation • The ECDC surveyed states to determine how many of them have implemented the 10 essential elements. • The ECDC did not release full survey results in the first year. However, it reported that while most states collect data about children, program sites, and workforce, that data is uncoordinated. • The survey shows only one state (Pennsylvania) that can link data across all early care and education programs at the child and program site levels, and none can at the workforce level. • Many states are using state advisory council grants to advance their work in this area. • For most states, this has meant work on designing a linked system – one that is able to answer the state's most important questions, and that is technically sound.

8. Using Council Grants for Data Many states around the country are using council grants for data system design WA ME MT ND VT MN OR NH MA ID WI NY SD RI WY MI CT PA NJ IA NE NV OH DE IN IL UT MD CO WV VA KS MO CA KY NC TN AZ OK AR SC* NM GA AL MS TX LA FL Identified by the National Governors Association as prioritizing data systems in state advisory council grant AK Obtained council grant but without focus on data Did not apply for Council grant HI *South Carolina returned a portion of its state advisory council grant.

9. Objectives Learn more about the Wisconsin Early Childhood Longitudinal Data System Project Introduce essential questionsand create underlying questions Identify steps towards successful implementation from national guidance Understand what is currently possibly and start the conversation about what they would like to see from this project. Develop recommendations and next steps for the WI project team Understand how you fit into this work and begin to think about what role you would like to play moving forward. Others from the group: What were you hoping to learn and contribute today? Wi Data Round Table

10. Wisconsin EC LDS Project Overview: How are the children of Wisconsin doing?

11. Wisconsin Key Policy Questions • Are children, birth to 5, on track to succeed when they enter school and beyond? • Which children and families are and are not being served by which programs/services? • Which children have access to high-quality early childhood programs and services? • What characteristics of programs are associated with positive child outcomes for which children? • What are the educational and economic returns on early childhood investments?

12. Background • Governor’s Early Childhood Advisory Council • 2010 Wisconsin Early Childhood System Assessment Report reported: “While the state collects many types of data related to early childhood, we don’t have the capacity to connect it, track children’s progress, or use it to assess the system.” • Key Objective for 2011-12 • Create a comprehensive longitudinal data system to track child outcomes and improve decision-making

13. What can a comprehensive early childhood longitudinal data system do? • Collect and maintain detailed, high-quality child-, staff-, and program-level data • Link these data to one another across entities (collections or data warehouses), over time • Enable the data to be accessible through reporting and analytic tools

14. Foundation upon which to build • Federal State Longitudinal Data System (SLDS) program and other national guidance • WI Act 59 (2009) • Requires establishment of a P-20 longitudinal data system (LDS) • 3 federal grants awarded to WI-Department of Public Instruction (DPI) • US Department of Education LDS Grant Program • Latest grant includes funding to develop a high quality plan for incorporating early childhood data

15. Components of DPI’s Current LDS • A comprehensive data warehouse storing student and school data from a variety of sources • Links to post-secondary data • A security application (Access Manager) that ensures only authorized personnel view confidential data • Secured reporting tools; e.g., Multi-Dimensional Analytic Tool (MDAT) that allow authorized users to analyze and provide access to data, including student records • Public reporting on WI Information Network for Successful Schools (WINSS) and in School Performance Reports • Professional development

16. Linking across systems • Do children receiving WI Shares subsidies who attend higher quality child care (as designated by YoungStar) have better educational and health outcomes than those who attend lower quality child care? • Do children of families who receive W-2 benefits fare better in school than children in poor families who do not participate in W-2? • Do they receive more preventative health services? • How do infants and toddlers in foster care fare when they enter school? • Is participation in prevention programs such as home visiting associated with better educational outcomes? • How can we improve data sharing methodologies between departments? • How can we leverage technology advances from other data systems?

17. The WI EC-LDS: First Steps • EC-LDS Project Team • DCF, DPI, DHS, DWD • ECAC Steering Committee • Hired staff at DPI • Project Coordinator, Carol Noddings Eichinger • Data Analyst, June Fox • Project Charter • Signed by DCF, DPI, DHS Administrators

18. Project Charter Objectives • Analyze current early childhood data environment • Establish data sharing methodologies • Create a work plan to begin data sharing and analysis process • Develop strategies for data governance, long term system usage, and sustainability

19. Key Policy Questions • Are children, birth to 5, on track to succeed when they enter school and beyond? • Which children and families are and are not being served by which programs/services? • Which children have access to high-quality early childhood programs and services? • What characteristics of programs are associated with positive child outcomes for which children? • What are the educational and economic returns on early childhood investments?

20. Existing Data Sources • Subsidized Child Care (WI Shares, YoungStar) • Licensed Child Care • Individuals with Disability Education Act: (IDEA) Part B and Part C • Individual Student Identifier System (DPI) • Head Start/Early Head Start • Home Visiting • Health (immunization, Vital Records, etc) • Tribal Health Data Collection • AFDC/TANF (CARES) • Child Support (KIDS) • SNAP/Food Stamps (CARES) • Child Protective Services (WiSACWIS) • Medicaid/BadgerCare (CARES) • Workforce and Corrections data

21. Fundamental Data Components • Unique statewide child identifier • Child-level demographic and participation information • Child-level data on child development • Link child-level data with K-12 and other key programs • Unique program identifier to link with children and workforce • Program site structural and quality information • Unique EC workforce identifier to link with sites and children • Individual-level data on EC workforce demographic, education and professional development information • Transparent privacy protection and security practices and policies • State governance body to manage data collection and use

22. Current Project Team Activities • Continue to develop and implement work plan • Continue to develop and implement communication plan • Conduct data systems survey • Work with national SLDS state support team • Explore ad hoc research projects • Build partnerships

23. Expected Outcomes • High quality information about young children and the services they receive • Ability to measure children’s progress across programs and over time • Ability to document which services are effective for which children and target resources accordingly • Increased cross-agency collaboration and communication • Increased accountability

24. “The simple act of describing something can galvanize action. What gets counted gets noticed. What gets noticed, gets done.” --Glenn Fujiura, University of Illinois

25. National Guidance on Building an Integrated System

26. One paradigm for tracking the progress towards an integrated EC data system Missy Cochenour

27. Early Childhood Self-Assessment Self Assessment Tool Graphic SLDS Webinar

28. Early Childhood Self-Assessment Tool SLDS Webinar

29. Wisconsin Key Policy Questions • Are children, birth to 5, on track to succeed when they enter school and beyond? • Which children and families are and are not being served by which programs/services? • Which children have access to high-quality early childhood programs and services? • What characteristics of programs are associated with positive child outcomes for which children? • What are the educational and economic returns on early childhood investments?

30. Wisconsin's Key Early Learning Data Questions Wisconsin has identified five key policy questions to inform the development of a unified data system.  Those questions are broad, and at the Roundtable stakeholders are being asked to develop some more specific sub-questions for the data system.  The idea is to identify questions that, if we knew the answers, we could change policy and practice to improve outcomes for young children.  This handout includes several suggested sub-questions, but Roundtable participants are encouraged to propose additions, subtractions, and amendments.  These sub-questions will be discussed in the morning breakout sessions.

32. Morning break out Session Activity

33. LUNCH : What is Possible: Demonstration of Other State’s Dashboards and Reports

34. EXAMPLES:STATE EARLY CHILDHOOD SYSTEMS Goals & Measurable Objectives Structures for Improvement Data System Tracks Results

35. North CarolinaSmart Start

36. Vision: Every child will arrive at school healthy and ready to succeedClear measurable outcomes set

37. Smart Start Structure • Public-private partnership • Comprehensive approach • State level and county nonprofits • Collaboration as its hallmark • Data system to track results

38. Smart Start Results All studies found that Smart Start works: • Children are healthier, have better language and math skills and fewer behavior problems than all other children • Children are more likely to be immunized on time and have a primary health provider

39. Smart Start Results • 5-star child care rating system helped drive quality • Child care teachers are better educated- 80% have college level education • 78% of all children in child care are in 3, 4, or 5 star rated programs • 70% of children who receive subsidies are in 4 or 5 star rated programs

40. Smart Start Results • North Carolina’s 3rd and 5th grade test scores- most improved in the nation • Duke University study: Smart Start’s approach improved third grade reading and math scores and lowered the special education placement for children

41. Maryland School Readiness Project • All Maryland children are assessed in kindergarten • School readiness data drives quality improvement

42. About the MMSRHow Maryland Assesses School Readiness The Maryland Model for School Readiness (MMSR) • Assessment: what each kindergartener knows and is able to do in 7 domains of learning • Children are identified as: • Fully Ready • Approaching Readiness: Partially ready, needs some instructional. • Developing Readiness: Not Ready, needs considerable.

43. More Children Fully School-Ready Maryland Model for School Readiness, 2010-2011 • 32-Point Jump in Readiness • 81% of kindergarteners are fully school-ready, up from 49% in 2001-2002 and 78% last year. 49 Source: Maryland State Department of Education

44. Achievement Gains for All ChildrenMaryland Model for School Readiness, 2010-2011 • Major Increases Among African-American & Hispanic Children • 76% of African-American kindergarteners are fully school-ready in 2010-2011, rising from 37% in 2001-2002 • 70% of Hispanic children are now fully school-ready—a 31-point readiness gain from 2001-2002 • Not Tracked in 2001-2002 or 2009-2010 Source: Maryland State Department of Education

45. Achievement Gains for All ChildrenMaryland Model for School Readiness, 2010-2011 • 39-point Increase Among Low-Income Children • 73% of kindergarteners from low-income households rose to full readiness in 2010-2011, up from 34% in 2001-2002 and 69% the year before. Source: Maryland State Department of Education

46. Achievement Gains for All ChildrenMaryland Model for School Readiness, 2010-2011 • 26-point Jump Among Children with Disabilities • 56% of children with disabilities are fully ready in 2010-2011, making a substantial 26-point gain from 2001-2002. Source: Maryland State Department of Education

47. Achievement Gains for All ChildrenMaryland Model for School Readiness, 2010-2011 • Maryland used school readiness data to target resources where improvement was needed. • Data drove their efforts. Source: Maryland State Department of Education

48. Pennsylvania:System for Early Learning and Child Development Because every child is Pennsylvania’s future

49. Key Pennsylvania Outcome Measure • Percent of Children in High-Quality Early Childhood Programs

50. Focus on Quality Programs • PreK • Head Start and Early Head Start • Special Education • Keystone STARS (similar to YoungStar), but 67+% of child care centers are participating • Home visiting Helping fulfill Pennsylvania’s Promise for Children Because every child is Pennsylvania’s future