Transcript Document

1
WEBINAR ON
BUILDING EARLY
CHILDHOOD DATA
SYSTEMS
APRIL 20, 2011
Building Early Childhood Data Systems
2
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
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A Q&A session will take place at the end of the webinar.
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Data for Action 2010: ECDC’s
State Analysis of Early Care
and Education
APRIL 20, 2011
The Early Childhood Data Collaborative
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A PARTNERSHIP OF
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




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 www.ECEdata.org for more information.
About Data for Action 2010
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 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 www.ECEdata.org for more information.
Critical Policy Questions Facing States
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 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?
 Is the quality of programs improving?
 What are the characteristics of effective programs?
 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?
What are "Early Childhood" Data?
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 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

10 FUNDAMENTALS
of Coordinated State ECE Data Systems
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10 FUNDAMENTALS
of Coordinated State ECE Data Systems
1.
2.
3.
4.
5.
Unique statewide child identifier
Child-level demographic and program participation information
Child-level data on child development
Ability to link child-level data with K-12 and other key programs
Unique program site identifier with the ability to link with children
and the ECE workforce
6. Program site structural and quality information
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
9. State governance body to manage data collection and use
10. Transparent privacy protection and security practices and policies
1. Every State Collects ECE Data
in at Least Some ECE Programs
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Many States Collect Child-, Program Site-, and ECE Workforce-Level Data by ECE Program
50
45
47
46
43
# of States
ChildLevel Data
43
42
39
40
47
40 39
40
36
37
36
35
30
Program
Site-Level
Data
27
25
20
16
15
12
10
5
N/A
0
Subsidize
d Child
Care
Licensed
Child
Care
Early
Interventi
on
EC
Special
Education
State
PreK*
12
ECE
Workforce
-Level
Data
State-Funded
HS/EHS*
*Not every state administers state pre-k or state-funded Head Start/Early Head Start programs.
2. Data Are Uncoordinated
Across ECE Programs
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No State Links Child-, Program Site-, and ECE Workforce-Level Data Across ECE Programs
50
45
# of States
40
35
30
25
20
15
10
5
0
1
Child-level
1
0
Program site-level ECE Workforcelevel
3. Data Gaps Remain, including
Child-Level Development Data
13
States Do Not Collect Child-Level Data on Development Across All ECE Program
50
45
40
40
40
Yes
# of States
35
30
25
Plans to
Collect
19
20
15
10
5
0
0
1
2
3
0
5
2
Subsidize
Early
EC
State
Stated Child
Interventi
Special
PreFunded
on
K* Start/Early Head
HS/EHS*
*NotCare
every state administers
state pre-kEducation
or state-funded Head
Start programs.
4. Governance Matters
When Linking to Other Systems
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States Link Child-Level ECE Data with K-12 and Other Key Data Systems That Are Located in the
Same Agency
4
Subsidized Child Care
21
17
Early Intervention
9
Preschool Special Education
1
0
Link to K-12
34
Link to
Health
28
6
State-Funded Head Start
23
10
6
State Pre-K
29
Link to Social
Services
8
7
2
10
20
30
40
# of
States
*Not every state administers state pre-k or state-funded
Head Start/Early Head Start programs.
Recap: Inaugural State ECE Analysis
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1.
2.
3.
4.
Every state collects ECE data on individual children,
program sites and/or members of the ECE workforce.
Data are uncoordinated as almost every state cannot link
child-, program site-, and ECE workforce-level data across
all ECE programs.
Data gaps remain for ECE workforce-level data and
child-level development data.
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.
The Time to Act is Now
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 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.
Contact the ECDC:
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The Center for the Study of Child Care Employment at UC Berkeley
Marcy Whitebook, [email protected]; Fran Kipnis, [email protected]
Council of Chief State School Officers
Tom Schultz, [email protected]
Data Quality Campaign
Elizabeth Laird, [email protected]; Allison Camara,
[email protected]
National Conference of State Legislatures
Julie Poppe, [email protected]
National Governors Association Center for Best Practices
Rachel Demma, [email protected]; Amanda Szekely, [email protected]
Pre-K Now, a campaign of the Pew Center on the States
Albert Wat, [email protected]
Birth to Five Policy Alliance
Helene Stebbins, [email protected]
Visit www.ECEdata.org for more information.
Quality for ME Data System
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Muskie School of Public Service
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
Muskie School of Public Service
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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.
QUALITY FOR ME
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GOALS:
 TO IMPROVE PROGRAM QUALITY
 TO ENHANCE PROFESSIONALISM FOR ECE
PROVIDERS
 TO SUPPORT PARENT CHOICE OF HIGH
QUALITY PROGRAMS
QUALITY FOR ME…
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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
QUALITY FOR ME – THE BASICS
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 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)
BENEFITS TO JOINING
QUALITY FOR ME…
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 Ability to accept Child Care Subsidy Vouchers
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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
The General Approach
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 Web-based application to Maine’s Quality Rating System
 Linkage to licensing database and professional
development registry
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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
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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
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
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Key Data Linkages
Quality Rating
System
Univ of Maine,
Orono
program license #
self-reported data
Program calculated data
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
…
Maine Roads To Quality (Prof Dev
Registry)
Univ of Southern Maine, Portland
program license #
accreditation
…
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Improves Data Quality at
Linked Databases
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all eight areas.
If you have any questions regarding how or why Step values are
determined, please contact Allyson Dean with the Quality for Maine
program.
Immediate Feedback to Applicant
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Section Name
Steps
Compliance History/Licensing
Status
1
Learning
Environment/Developmentally
Appropriate Practice
2
Program Evaluation
1
Staffing and Professional
Development
1
Administrative Policies and
Procedures
4
Parent/Family Involvement
2
Community Resources
4
Child Observations
2
Overall the Program is at Step 1
Recommendations
Immediate Feedback to Applicant
Figure xx. Example of detailed automatic immediate feedback to provider on how to achieve
next steps in each area of QRS evaluation (abbreviated).
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Recommendations
Compliance History / Licensing Status
Current step is #1.
In order to move to step #2:

Your facility must have no substantiated serious violations in the past year.
Learning Environment / Developmentally Appropriate Practice
Current step is #2.
In order to move to step #3:

At least 50% of lead teachers (per program site) working with children ages 3-5 must have completed
the training on implementing curriculum based on Maine’s Early Childhood Learning Guidelines.
Program Evaluation
Current step is #1.
In order to move to step #2:

Your program must provide an opportunity to identify strengths and weaknesses that is inclusive of
staff, families, and administrators

Staff must be given feedback regarding the yearly self assessment
Staffing
and Professional Development
(specific
recommendations
for each of 8 areas)
Current step is #1.
In order to move to step #2:
Data Usage…
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 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
Lessons Learned…
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 System Operation
 Intention is to Build a
System, an Infrastructure
to Help Align ECE
Programming
 Develop Working
Partnerships with State
Program Administrators
and University Research
Staff
Requires Ongoing
Attention - Keep it Valid
and Reliable
 Importance of
Translating Data from
QRIS Monitoring into
Information for
Decision-making
Building Early Childhood Data Systems
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Kathy Thornburg
Center for Family Policy & Research,
University of Missouri
&
Missouri Department of Education
Building Early Childhood Data Systems
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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 SubCommittee of the Council
Who is at the table? Persons from . . .
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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)
Building Early Childhood Data Systems
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 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

Unique Identifiers
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 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!
Child Demographic and
Program Participation Information
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 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
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Linking Child Data with K-12 and
Other Data Systems
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(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)
Sample Analytic Questions
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 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?
Workforce Linkages—Programs and Children
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 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
Workforce Demographics
42
 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
Privacy Practices and Policies
43
 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
Thoughts toward Future Work
44
 “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
Building Early Childhood Data Systems
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Federal Interagency Efforts to Support
Early Childhood Data Systems
Amy Madigan
HHS
Beth Caron
ED
What are Early Childhood Data Systems?
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 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 highquality 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
Efforts Underway in ED and HHS
47
 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
ELDII Data Systems Study Group
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 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
Activities of the Data Systems Study Group
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 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
Key Challenges Identified
50
 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
Contact Information
51
 Rachel Demma- [email protected]
 Michel Lahti- [email protected]
 Kathy Thornburg- [email protected]
 Amy Madigan- [email protected]
 Beth Caron- [email protected]