WEBINAR ON BUILDING EARLY CHILDHOOD DATA SYSTEMS APRIL 20,

Building Early Childhood Data Systems Welcome/Introduction: Lee Kreader- Director, Research Connections, National Center for Children in Poverty Presenters: Rachel Demma- National Governors Association Michel Lahti- Muskie School of Public Service, University of Southern Maine Kathy Thornburg- Center for Family Policy & Research (University of Missouri) and Missouri Department of Education Amy Madigan- U.S. Department of Health and Human Services, Office of the Assistant Secretary of Planning and Evaluation Beth Caron- U.S. Department of Education, Office of Special Education Programs 2

Instructions for GoToWebinar Menu Window To hide Control Panel View Webinar in Full Screen Mode/Minimize Full Screen Mode To show Control Panel 3 To ask a question, please enter it into the question box. Technical assistance questions will be addressed as needed throughout the webinar. A Q&A session will take place at the end of the webinar.

Data for Action 2010: ECDC’s State Analysis of Early Care and Education APRIL 20,

The Early Childhood Data Collaborative A PARTNERSHIP OF  The Center for the Study of Child Care Employment at UC Berkeley  Council of Chief State School Officers  Data Quality Campaign  National Conference of State Legislatures  National Governors Association Center for Best Practices  Pre-K Now, a campaign of the Pew Center on the States The ECDC is supported through funding from the Birth to Five Policy Alliance, The Pew Charitable Trusts, and The David and Lucile Packard Foundation. Visit for more information. 5

About Data for Action 2010 Policymaking tool to support policymakers to use data in decisionmaking. Series of analyses that provide transparency about state progress to collect and use longitudinal data to improve student success. ECDC’s Inaugural State Analysis of Early Care and Education measures state-by-state progress toward implementing the 10 ECE Fundamentals. Visit for more information. 6

Critical Policy Questions Facing States How prepared is the early care and education workforce to provide effective education and care for all children? What policies and investments lead to a skilled and stable early care and education workforce?  Is the quality of programs improving?  What are the characteristics of effective programs?  Are children, birth to age 5, on track to succeed when they enter school and beyond?  Which children have access to high-quality early care and education programs? 7

What are "Early Childhood" Data? The ECDC recognizes that multiple domains are important to early childhood This framework focuses on the early care and education (ECE) domain—  Subsidized Child Care  Licensed Child Care  Early Intervention (IDEA Part C)  Early Childhood Special Education (IDEA Part B Section 619)  State Pre-kindergarten  State-funded Head Start or Early Head Start 8

10 FUNDAMENTALS of Coordinated State ECE Data Systems 9

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

1. Every State Collects ECE Data in at Least Some ECE Programs Many States Collect Child-, Program Site-, and ECE Workforce-Level Data by ECE Program Subsidize d Child Care Licensed Child Care Early Interventi on EC Special Education State Pre- K* State-Funded HS/EHS* # of States *Not every state administers state pre-k or state-funded Head Start/Early Head Start programs. 11

2. Data Are Uncoordinated Across ECE Programs No State Links Child-, Program Site-, and ECE Workforce-Level Data Across ECE Programs # of States 12

3. Data Gaps Remain, including Child-Level Development Data States Do Not Collect Child-Level Data on Development Across All ECE Program Subsidize d Child Care Early Interventi on EC Special Education State Pre- K* State- Funded HS/EHS* # of States *Not every state administers state pre-k or state-funded Head Start/Early Head Start programs. 13

4. Governance Matters When Linking to Other Systems States Link Child-Level ECE Data with K-12 and Other Key Data Systems That Are Located in the Same Agency # of States *Not every state administers state pre-k or state-funded Head Start/Early Head Start programs. 14

Recap: Inaugural State ECE Analysis 1. Every state collects ECE data on individual children, program sites and/or members of the ECE workforce. 2. Data are uncoordinated as almost every state cannot link child-, program site-, and ECE workforce-level data across all ECE programs. 3. Data gaps remain for ECE workforce-level data and child-level development data. 4. Governance matters because data linkages are most likely to occur between data systems located within the same state agency. States cannot answer basic questions about the state’s ECE systems. 15

The Time to Act is Now Articulate the critical policy questions that will drive the development and use of coordinated state ECE data systems. Evaluate current and future data collection and linkage needs based on the state’s critical policy questions. Strategically govern data collection and use, including ensuring the privacy, security and confidentiality of ECE data. 16

Contact the ECDC: The Center for the Study of Child Care Employment at UC Berkeley Marcy Whitebook, Fran Kipnis, Council of Chief State School Officers Tom Schultz, Data Quality Campaign Elizabeth Laird, Allison Camara, National Conference of State Legislatures Julie Poppe, National Governors Association Center for Best Practices Rachel Demma, Amanda Szekely, Pre-K Now, a campaign of the Pew Center on the States Albert Wat, Birth to Five Policy Alliance Helene Stebbins, Visit for more information. 17

Muskie School of Public Service Quality for ME Data System Allyson Dean, MA - Director, Maine Roads to Quality Univ. of Southern Maine Alan Cobo-Lewis, PhD University of Maine Michel Lahti, PhD – University of Southern Maine 18

Muskie School of Public Service A Partnership of: Maine Department of Health and Human Services and the Universities of Maine and Southern Maine THIS WORK IS SUPPORTED IN PART BY MAINE STATE DHHS AND THE FEDERAL, US DHHS, CHILD CARE DATA CAPACITY AND RESEARCH GRANT AWARDS. 19

QUALITY FOR ME GOALS: TO IMPROVE PROGRAM QUALITY TO ENHANCE PROFESSIONALISM FOR ECE PROVIDERS TO SUPPORT PARENT CHOICE OF HIGH QUALITY PROGRAMS 20

QUALITY FOR ME… DESIGNED AROUND SYSTEMS ALREADY IN PLACE & USE OF ADMINSTRATIVE DATA FOUR STEP LEVELS BY TYPE OF PROGRAM SPECIFIC STANDARDS IN EIGHT AREAS THAT RESEARCH HAS SHOWN TO BE PREDICTIVE OF HIGH QUALITY ALIGNED WITH ACCREDITATION STANDARDS AND PROVIDE FOR A PROGRESSION TOWARD THOSE STANDARDS 21

QUALITY FOR ME – THE BASICS Licensing compliance Membership in MRTQ Registry Online application based upon a self- evaluation Once the on-line application is submitted, the provider immediately receives feedback from the Quality for ME system regarding the anticipated Step level Portfolio of documentation (random) On-site Observations (random) 22

BENEFITS TO JOINING QUALITY FOR ME… Ability to accept Child Care Subsidy Vouchers and receive a payment differential based upon Step Level Assistance in paying for accreditation fees and cohort supports including facility improvement grants On-site technical assistance Scholarships to pursue early childhood education degrees Tax credits for parents and providers 23

The General Approach Web-based application to Maine’s Quality Rating System Linkage to licensing database and professional development registry  Relieves burden for all applicants  Improves data quality in QRS application  Feedback loop also improves data quality in linked database Criteria for achieving steps cross-walked with accreditation criteria Self-report on remaining items  About 50 specific questions if no accreditation  Reduced to just 5-10 questions depending on accreditation Immediate and specific feedback on how to move to next step in each area Individual and aggregate reports shared with R&R centers to facilitate Technical Assistance to child care programs 24

QRS Step in Each of Eight Areas: compliance history/licensing status learning environment/developmentally appropriate practice program evaluation staffing and professional development administrative policies and procedures parent/family involvement family resources authentic assessment QRS Step in Each of Eight Areas: compliance history/licensing status learning environment/developmentally appropriate practice program evaluation staffing and professional development administrative policies and procedures parent/family involvement family resources authentic assessment Criteria for achieving steps cross-walked with standards for the following: NAEYC Accreditation NAEYC Candidacy NAFCC Accreditation Nat'l After School Association Accreditation American Montessori Society Accreditation Head Start: Zero Non-compliance Issues at Last Review / All Non-compliance Issues at Last Federal Review Resolved Criteria for achieving steps cross-walked with standards for the following: NAEYC Accreditation NAEYC Candidacy NAFCC Accreditation Nat'l After School Association Accreditation American Montessori Society Accreditation Head Start: Zero Non-compliance Issues at Last Review / All Non-compliance Issues at Last Federal Review Resolved 25

Program Licensing MeDHHS, Augusta program license # contact info capacity license status license expiration type of program … Maine Roads To Quality (Prof Dev Registry) Univ of Southern Maine, Portland provider ID provider education provider training record license # of program where provider employed … Quality Rating System Univ of Maine, Orono program license # self-reported data calculated data … Maine Roads To Quality (Prof Dev Registry) Univ of Southern Maine, Portland program license # accreditation … Key Data Linkages 26

Improves Data Quality at Linked Databases 27

Immediate Feedback to Applicant 28

Immediate Feedback to Applicant (specific recommendations for each of 8 areas) 29

Data Usage… Monitor Enrollments and Characteristics of Programs ERS Scores – Focus on Areas of Strength and Improvement Monitor Program Progress through Step Levels Monitor Supports to Programs Infrastructure for Evaluation Projects:  Comparing QRS to non-QRS Sites  Investigate QRS Standards: Use of Child Level Assessments  Validation Study 30

Lessons Learned… Intention is to Build a System, an Infrastructure to Help Align ECE Programming Develop Working Partnerships with State Program Administrators and University Research Staff System Operation Requires Ongoing Attention - Keep it Valid and Reliable Importance of Translating Data from QRIS Monitoring into Information for Decision-making 31

Kathy Thornburg Center for Family Policy & Research, University of Missouri & Missouri Department of Education Building Early Childhood Data Systems 32

Building Early Childhood Data Systems Some Missouri facts: There is some funding for this work from the National Center for Education Statistics (IES Institute Educational Sciences) from the Longitudinal Data System Grant—Missouri Department of Elementary and Secondary Education. We have “a good start” on looking at the “P” in the P-20 system. The “P” group—prenatal to kindergarten entry—has included before and after school professionals, programs, etc. in everything we do, including this data work We have 2 groups that worked on this project to date: Council for Early Childhood/After-School Data AND Research Sub- Committee of the Council 33

Who is at the table? Persons from... Department of Social Services Department of Elementary and Secondary Education Department of Health and Senior Services Department of Mental Health Coordinating Board for Early Childhood Parents as Teacher National Office Child Care Aware ® of Missouri Center for Family Policy & Research Region VII Head Start Head Start-State Collaboration Office University Departments and Institutes (economics, public policy, human development) 34

Building Early Childhood Data Systems Today, I will share ideas and challenges related to 6 of the 10 Fundamentals  Unique identifiers  Child demographic and program participation information  Linking child data with K-12 and other data systems  Workforce linkages with programs and children  Workforce demographics  Privacy practices and policies 35

Unique Identifiers Missouri has 2 primary identifiers for children: Department Client Number (used by Dept. of Social Services and Dept. of Health and MO Student ID (used by Dept. of Education)  Issue: can they be linked easily?  Test: probabilistic matching of child records  Results: due at the end of the month Stay tuned! 36

Child Demographic and Program Participation Information Work of the Council to investigate possible datasets and key partners o MO PD partners are working to resolve unique program identifier issues Developed data marts that might be possible candidates for future analyses The next slide shows a chart that is a DREAM at this point—we are beginning to build linkages, but know there will be lots of issues as we move forward 37

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Linking Child Data with K-12 and Other Data Systems (The research sub-committee met to develop possible questions to answer in the future. We developed 30 descriptive questions.) Children: What types and quality of programs do young children and school-agers attend? Access: How many slots are available in various regions by program type and quality? Funding: What are infrastructure needs and costs for a statewide system for measuring and improving quality in EC/AS programs? Workforce: What are basic characteristics of providers, including education, training hours, wage, work hour benefits, length of time in program and field? How do wages differ by education/training, after controlling for experience? Quality: How do standards and measures of quality across different systems relate? (accreditation, QRS, Head Start standards) 39

Sample Analytic Questions Children: How do early childhood educational experiences relate to school readiness/achievement in early elementary grades? Access: How prevalent are multiple arrangements for child care? What motivates these choices? Funding: to what extent does early childhood program dosage (half day, school day, full day) predict school readiness/achievement in early elementary grades? Workforce: Does investing in increasing the education level of teachers improve programs as well as children’s outcomes? Quality: Which elements/aspects of EC/AS programs contribute to which kind of child outcomes? 40

Workforce Linkages—Programs and Children Missouri has a workforce registry that collects demographic, employment, education, and training data on professionals working with young children and youth One attempt at matching these data to the Department of Labor data—90% match rate Increase understanding of employment trends of our workforce to the overall industry Next steps: 1—wage analysis in relation to education level, years of experience 2—linking program, teacher, and child data 41

Workforce Demographics Missouri’s Registry is voluntary (except for some state contracts requiring it) Verified education and training information ~ 40% of licensed population is in the registry SOON—all training will have to be approved and the attendance records will be exchanged from the Workshop Calendar to the Registry 42

Privacy Practices and Policies All members of the Council and Research Committee signed confidentiality agreements that were notarized We need more MOU’s or a governance structure for shared data for specific research questions Cross agency agreements are needed to support foundational administrative program management across agencies—polices related to privacy will be key 43

Thoughts toward Future Work “P” crosses so many agencies—need for a data dictionary Do we identify the research questions and see if the data are available OR define data and determine what research can be done OR a combination? Connect more data sets to allow for more questions to be answered Council monies will allow us to work with Head Start programs to get some of their data into the state system 44

Building Early Childhood Data Systems Federal Interagency Efforts to Support Early Childhood Data Systems Amy Madigan HHS Beth Caron ED 45

What are Early Childhood Data Systems? Working definition:  Policies, processes and structures used to coordinate and connect administrative and other sources of data across early childhood programs to support the provision of high- quality programs; promotion of healthy development and positive outcomes for children (birth to age 8) and families; and creation of successful transitions to school. Create linkages both horizontally and longitudinally  Among early childhood programs  Between early childhood and health and social services  To and from the K-12 education system 46

Efforts Underway in ED and HHS US Department of Education  Statewide Longitudinal Data Systems Grants  National Education Data Model  Privacy Technical Assistance Center  Early Childhood Outcomes Center US Department of Health and Human Services  Child Care State Research Capacity Cooperative Agreements  Early Childhood State Advisory Councils Early Learning and Development Inter- Departmental Initiative: Data Systems Study Group 47

ELDII Data Systems Study Group Six ELDII Study Groups: Program Standards, Early Learning Standards and Assessment, Workforce and Professional Development, Family Engagement, Health Promotion, and Data Systems Data Systems Study Group Mission – To support the development, implementation, use and sustainability of coordinated early childhood data systems by:  Gathering information about the state of the field and the state of the States  Building internal capacity and knowledge of early childhood data systems  Identifying strategies to implement at the federal level Comprised of federal staff across multiple agencies in HHS and ED including offices responsible for administering federal early childhood programs and data systems efforts 48

Activities of the Data Systems Study Group Briefings on federal initiatives, grant programs, and demonstration projects Met with experts and States  Early Childhood Data Collaborative  MD, IL, CT, MA, PA, OR, FL, SC… and others… Session at Early Childhood 2010 Conference Developed a list of critical characteristics of a high- quality early childhood data system 49

Key Challenges Identified Funding, funding, funding… Understanding HIPAA and FERPA regulations Data sharing between Head Start, other early childhood programs, and K-12 Utilizing unique identifiers for children, staff, and providers Differences across federal offices in reporting requirements, data elements and data definitions 50

Contact Information Rachel Demma- Michel Lahti- Kathy Thornburg- Amy Madigan- Beth Caron- 51