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

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3. DPI Kurt KieferAssistant State Superintendent Jill HaglundEC Consultant, Office of Early Learning, staff to Governor’s Early Childhood Advisory Council (ECAC) June FoxData Analyst Laura PaellaOffice Associate, Office of Early Learning DCF Jane Penner-HoppePolicy Advisor and staff to Governor’s Early Childhood Advisory Council (ECAC) Hilary ShagerResearch Analyst Alyssa BokelmanOperations Associate and ECAC Staff DHS Linda McCartPolicy Director Angela RohanEpidemiologist DWD Dennis WintersChief Economic Advisor WCCF Dave EdieEarly 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) 3

4. 4  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. Why have a coordinated data system?

5.  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. Why have a coordinated data system? (cont'd) 5

6. 6 1. Unique statewide child identifier 6. Program site data on structure, quality, and work environment 2. Child-level demographic and program participation information 7. Unique ECE workforce identifier with ability to link with program sites and children 3. Child-level data on development 8. Individual ECE workforce demographics, including education, and professional development information 4. Ability to link child-level data with K-12 and other key data systems 9. State governance body to manage data collection and use 5. Unique program site identifier with the ability to link with children and the ECE workforce 10. Transparent privacy protection and security practices and policies

7.  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. 7 Survey of implementation

8. 8 Many states around the country are using council grants for data system design Identified by the National Governors Association as prioritizing data systems in state advisory council grant Did not apply for Council grant Obtained council grant but without focus on data *South Carolina returned a portion of its state advisory council grant.

9. State Support Team 9/7/2015 Learn more about the Wisconsin Early Childhood Longitudinal Data System Project Introduce essential questions and 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 9 Objectives

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11.  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? 11

12.  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 Background 12

13.  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 13

14.  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 14

15.  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 15

16.  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? 16

17.  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 17

18.  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 18

19.  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? Key Policy Questions 19

20. ◦ 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 Existing Data Sources 20

21. 1. Unique statewide child identifier 2. Child-level demographic and participation information 3. Child-level data on child development 4. Link child-level data with K-12 and other key programs 5. Unique program identifier to link with children and workforce 6. Program site structural and quality information 7. Unique EC workforce identifier to link with sites and children 8. Individual-level data on EC workforce demographic, education and professional development information 9. Transparent privacy protection and security practices and policies 10. State governance body to manage data collection and use Fundamental Data Components 21

22.  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 22

23.  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 23

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 24

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

27. State Support Team 9/7/2015 Self Assessment Tool Graphic SLDS Webinar27 Early Childhood Self-Assessment

28. State Support Team 9/7/2015 SLDS Webinar28 Early Childhood Self-Assessment Tool

29.  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? 29

30. 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. 1. Are children, birth to 5, on track to succeed when they enter school and beyond? How are early learning programs influencing social-emotional development? What indicators are being used to measure children’s developmental progress? And what are the trends? 2. Which children and families are and are not being served by which programs/services? 3. Which children have access to high-quality early childhood programs and services? Do at-risk children have access to programs? What is the attendance pattern for each child? Which children are enrolled in multiple programs? 30

31. 31 4. What characteristics of programs are associated with positive child outcomes for which children? Are an increasing number of programs meeting established quality standards? What are the qualifications for program staff and providers? What is the staff to child ratio in programs? Are programs utilizing the Wisconsin Model Early Learning Standards? What curriculums are used by programs? 5. What are the education and economic returns on early childhood investments ? How do children enrolled in early learning programs do in K-12? (test scores, attendance, drop-out rates) Are children enrolled in early learning programs less likely to end up in the juvenile justice system? In the child welfare system? In the mental health system?

32. QuestionWhy This Question?Who—End UserFor What Purpose? Example: Is participation in prevention programs such as home visiting associated with better educational outcomes? We want to know whether children enrolled in home visiting programs succeed in school (for example, third grade test scores) Home visiting program management, Policy makers, Legislators, Public at large, Researchers Targeting and improving prevention programming, as well as improving educational outcomes 32

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34. Goals & Measurable Objectives Structures for Improvement Data System Tracks Results 34

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

38. 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 38

39.  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 39

40.  North Carolina’s 3 rd and 5 th 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 40

41.  All Maryland children are assessed in kindergarten  School readiness data drives quality improvement 41

42. 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. 42

43.  32-Point Jump in Readiness  81% of kindergarteners are fully school-ready, up from 49% in 2001-2002 and 78% last year. Source: Maryland State Department of Education 49 43

44.  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 Source: Maryland State Department of Education -Not Tracked in 2001-2002 or 2009-2010 44

45.  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 Achievement Gains for All Children Maryland Model for School Readiness, 2010-2011 45

46.  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 46

47. Source: Maryland State Department of Education  Maryland used school readiness data to target resources where improvement was needed.  Data drove their efforts. 47

48. Because every child is Pennsylvania’s future 48

49.  Percent of Children in High-Quality Early Childhood Programs 49

50. 50  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

51. 51  More children*, in high quality programs overall:  2002-2003: 18%  2005-2006: 28%  2006-2007: 38%  Creation of Office of Child Development and Early Learning between the PA Departments of Education and Public Welfare Helping fulfill Pennsylvania’s Promise for Children Because every child is Pennsylvania’s future *based on the percentage of 3 and 4 year olds with access to Head Start, STAR 3 & 4 programs, Preschool Early Intervention and state-funded pre-k.

52.  Clear succinct goals  Measurable objectives  Branding the effort for public buy-in  Infrastructure that aligns funding and resources both public and private  Solid data system to measure results  Regular reports on progress to public and policy makers 52

53. State Support Team 53 Art of the Possible What is a Dashboard? “Dashboard is an executive information system user interface that (similar to an automobile's dashboard) is designed to be easy to read.”executive information systemautomobile's dashboarddesigned

54. State Support Team 54 Art of the Possible http://dashboard.ed.gov/dashboard.aspx U.S. Education Dashboard

55. State Support Team 55 Art of the Possible http://dashboard.ed.gov/dashboard.aspx Rhode Island DataHub

56. State Support Team 56 Art of the Possible http://dashboard.ed.gov/dashboard.aspx Missouri State Department of Education

57. State Support Team 57 Art of the Possible http://dashboard.ed.gov/dashboard.aspx Head Start Program Data

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59. State Support Team 9/7/2015 Planning for EC data system development cannot be accomplished without the right stakeholders engaged in the work. What is a stakeholder? Do they contribute data? Are they users of data? What is their function and role? Is there a cross-section of state and program stakeholders? A stakeholder is any individual who is served by the data, has a clearly defined role and function, and represents a necessary and important sector for the project. Group 1: Engaging Stakeholders and Building Sustainability

60. State Support Team 9/7/2015 While it is necessary to include a variety of stakeholders, keeping them engaged --and engaged at the right time -- can be a challenge. How will stakeholders interact with one another? Do stakeholders know why they are engaged in the process? What happens when there are changes in staffing or leadership? How does the project team communicate to stakeholders? Group 1: Engaging Stakeholders and Building Sustainability

61. State Support Team 9/7/2015 Capacity is the state’s ability to not only take on the task of including EC data in the SLDS, but also the degree to which it can. Assessing capacity includes: Analyzing existing resources necessary to accomplish the task, Determining which state programs are collecting and reporting data, Determining what additional resources might be necessary, and Analyzing the knowledge base of stakeholders essential to the project’s success. In a nutshell, identifying capacity is much like putting a large wish list through a vetting process to develop a realistic and achievable scope for the project. Group 1: Engaging Stakeholders and Building Sustainability

62. State Support Team 9/7/2015 What is Data Governance? It establishes responsibility for data, organizing program area staff to collaboratively and continuously improve data quality through the systematic creation and enforcement of policies, roles, responsibilities, and procedures. Why does is Data Governance Important? Defined key policy and program questions about early learning Coordination between state agencies and programs administering early childhood services and collecting data Improved understanding and quality of data collected, reported, and used by multiple agencies and early childhood programs Reduced agency and program staff burden Improved communication, collaboration, and relationships Group 2: Data Governance and System Design 62

63. State Support Team 9/7/2015 System Design focuses on how the data system will be created and implemented. Introduction to data models Logical Conceptual Physical Introduction to implementation options: Centralized Federated SLDS Webinar63 Group 2: Data Governance and System Design

64. 64 Central Principles of Data Governance Inter-agency/program approach to managing information, from collection through use Clear, distinct roles for and relationships among program areas, IT, and leadership All programs and/or agencies contributing data to the effort are represented Program area ownership of information – it’s NOT an IT initiative Common definitions across programs and/or agencies Inter-agency/program data governance coordinator

65. 65 Intended Outcomes of Data Governance for EL Sector Defined key policy and program questions about early learning Coordination between state agencies and programs administering early childhood services and collecting data Improved understanding and quality of data collected, reported, and used by multiple agencies and early childhood programs Reduced agency and program staff burden Improved communication, collaboration, and relationships between: Programs/agencies ↔ IT Agencies ↔ Programs

66. 66 Agency and Program Executive Leadership Agencies, Program(s), IT, Providers Program staff Responsible for infra-structure that collects, stores & reports data DPC DMC Roles & Groups Escalation Implementatio n

67. Identify participating agencies/programs Establish executive sponsors and data policy committee Develop and enact data governance policy Identify data governance coordinator Identify data stewards/managers for each agency or program Identify other members of data management committee (e.g., IT representation) 67 Initial Steps to Establish Data Governance

68. Parents What web-based resources will be available to help parents access services (early care and education, screenings and referrals, and more)? How will information be conveyed to parents who lack web access? What individualized information will parents receive about their child? What resources will be available to parents to help them understand data about their child? Practitioners How will we ensure that practitioners have access to professional development that helps them use data effectively? How will we redesign preservice opportunities to ensure that new practitioners are able to use data effectively? How will data use be embedded in workforce competencies? How will programs be redesigned to reflect new expectations for data use? How will we expect practitioners to use data to connect across different sectors, and what supports can we put in place to make that happen? Policymakers What entity or entities will be responsible for releasing reports based on coordinated data? What reports must or should be formally submitted to the governor and legislature? What outreach is necessary to help policymakers contextualize new data, and how should that outreach evolve as the system is designed, built, and then brought on-line? What support will state agency leaders and staff need in order to use data effectively? Others What research efforts should be launched when coordinated data is available? What data capacity will be necessary among other key audiences, like municipal officials, business leaders, and the philanthropic community? 68

69.  Thank you! Today your contributions have made a significant impact on this project and helped us inform our next steps.  What you can expect next: ◦ A report summarizing the findings and contributions of the day. ◦ An invitation to complete an electronic survey, link to be sent by e-mail, to ask about your participation today. ◦ Ongoing communication on project will be publically available, including a website with updates and key documents. ◦ Ongoing collaboration is essential. 69