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Early Childhood Data Use: State Demonstrations

Jaci Holmes, Maine

Phil Koshkin, Maryland Missy Cochenour, State Support Team

This interactive session will highlight the work of states using data from their SLDS. State examples will demonstrate the technology as well as the use of the data within the state.

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Session Objectives

• Knowing the intended users

• Designing to meet the needs of users

• Meeting privacy needs

• Understanding who makes the decisions (governance)

• Knowing what the users need to be able to use the data

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What does it mean to use EC Data?

DATA USE FRAMEWORK

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large images

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Data use Framework

CREATE

SUPPORT

PLAN

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Data Use Framework: PLAN

• Mission and Goals

– What is the point? CREATE

SUPPORT

PLAN

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Mission and Goals

– What is the point?

Data Use Framework: PLAN

CREATE

SUPPORT

PLAN

Identification and

prioritization of users

• Who are we serving?

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Mission and Goals

– What is the point?

Data Use Framework: PLAN

CREATE

SUPPORT

PLAN

Identification and

prioritization of users

• Who are we serving?

Identification of uses

• What types of decisions and/or

actions will the system inform?

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Stakeholder engagement

– How do we involve those

whom we intend to serve?

Data Use Framework: CREATE

CREATE

SUPPORT

PLAN

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Stakeholder engagement

– How do we involve those whom

we intend to serve?

Products/Resources

– What types of products/ resources will the SLDS generate?

Data Use Framework: CREATE

CREATE

SUPPORT

PLAN

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Stakeholder engagement

– How do we involve those whom

we intend to serve?

Products/Resources

– What types of products/ resources will the SLDS generate?

Delivery

– How will you deliver data to key users?

Data Use Framework: CREATE

CREATE

SUPPORT

PLAN

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User support

– How will users know how to use the system?

– How will users understand

the data provided by the

system?

– How will users know what

to do with the data

provided by the system?

Data Use Framework: SUPPORT

CREATE

SUPPORT

PLAN

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Evolution and Sustainability

– How do we continue to support

users and their needs as they

expand and evolve?

– How do we make the system an

essential resource for users?

– How do we ensure we have the

resources to continue meeting

users’ needs?

Data Use Framework: SUPPORT (continued)

CREATE

SUPPORT

PLAN

large images

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Data use Framework

CREATE

SUPPORT

PLAN

Mission & Goals

Identification &

Prioritization of Users

Identification of

Uses Stakeholder Engagement

Products/Resources

User Support Evolution &

Sustainability

Delivery

STATE EXAMPLES

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ME Critical Characteristics: • Governance structure in place across agencies (ED and Health &

Human Services) • Support of the Commissioner of Education and Health and

Human Services

Intended Users: • State level program administrators • EC Professionals in the field (all public stakeholders) Use Case: • Policy questions with aligned elements (descriptive and

inferential questions)

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Maine

Critical Questions Descriptive:

• What are the definable characteristics of our state’s B-5 programs?

Inferential:

• What characteristics of programs are associated with positive outcomes for which children?

Descriptive:

• What are the definable characteristics of Maine’s children who are entering grades K-2

Inferential:

• How prepared are all our children for kindergarten and K-2, as a whole and by subgroups? What have children encountered? What milestones have been reached?

Descriptive:

• What definable characteristics exist to measure state schools ability to receive kindergarteners?

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Maine

Inferential:

• How prepared are the State’s schools for meeting the needs of entering kindergarteners?

Descriptive:

• What are the definable characteristics of the state’s Birth-8 workforce?

Inferential:

• How prepared is the Birth-8 early childhood workforce to provide effective education and care for all children?

Overarching:

How are data being used now and how will data be used in the future to inform policy and resource decisions?

• How will policy decision impact outcomes?

• Will investments and initiatives improve outcomes?

• How will families be better served?

• How can we deliver services more effectively?

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Maine

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Maine

ME Lessons Learned:

• Stakeholder involvement in research questions

• Role of governance in the process

http://www.maine.gov/earlylearning

• Need for enhanced Data governance structure

• Need for trusted broker between departments

• Funding across agencies

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Maine

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Maine

Who are your intended users?

What are your critical questions?

What questions do you have from Maine’s examples?

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Facilitated Discussion

Critical Maryland data system characteristics: • Early Childhood is all under one agency • Use of partnerships for data gathering (e.g., QRIS) Intended users: • State agency/program administrators • Policymakers, researchers, advocates Main approach to data use: • 6 critical questions and sub-queries tied to data sources

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Maryland

Maryland State Department of Education – Division of Early Childhood Development

Early Childhood Data Warehouse Policy Questions

CHILDREN

Main Policy Question 1: Are children, birth to age 5, on track to succeed in K-12?

Query 1A. Are kindergarten readiness levels increasing or decreasing? Are differences in readiness levels associated with at-risk children? With gender? With race/ethnicity? With prior enrollment in different types of early care programs?

Dataset(s): (1) MMSR Kindergarten Assessment individual child records. Query 1B. How do kindergarten readiness levels among children participating in the child care subsidy

program compare with readiness levels among non-subsidy children? Has this comparison changed over time?

Dataset(s): (1) MMSR Kindergarten Assessment individual child records. (2) CCATS individual child subsidy voucher records.

Query 1C. To what extent is enrollment in high-quality ECE programs correlated with higher school

readiness levels? Is this correlation increasing or decreasing? Does the correlation vary in relation to at-risk children? To gender? To race/ethnicity?

Dataset(s): (1) High-quality program records. (2) CCATS individual child enrollment and attendance records. (3) MMSR Kindergarten Assessment individual child records.

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Maryland

Main Policy Question 1 (continued)

Query 1D. To what extent do assessed school readiness levels correlate with later school success? Is this

correlation increasing or decreasing? Does the correlation vary in relation to at-risk children? To gender? To race/ethnicity? To prior enrollment in different types of early care programs?

Dataset(s): (1) K-12 MSA scores – individual child records. (2) MMSR Kindergarten Assessment individual child records. (3) CCATS individual child enrollment and attendance records. (4) Head Start program site enrollment records.

Main Policy Question 2: Which children have access to high-quality ECE programs? Query 2A. What is the distribution of child enrollment across all types of early care and education

programs? Has this distribution changed over time? Dataset(s): (1) High-quality program records. (2) ELIS licensed child care enrollment records. (3) Public

Pre-K enrollment records. (4) Head Start program site enrollment records. Query 2B. How does the utilization of child capacity (i.e., capacity vs. enrollment) in high-quality licensed

child care programs compare with capacity utilization in programs not rated as high-quality? Dataset(s): (1) High-quality program records. (2) CCATS licensed child care program records. (3) ELIS

licensed child care enrollment records.

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Maryland

Main Policy Question 2 (continued)

Query 2C. Is child enrollment in high-quality programs correlated with differences in child demographics such as at-risk status, gender, or race/ethnicity?

Dataset(s): (1) High-quality program records. (2) CCATS individual child enrollment and attendance records. (3) Public Pre-K enrollment records.

PROGRAMS

Main Policy Question 3: Is the quality of Maryland’s early care programs improving?

Query 3A. What proportion of licensed child care programs are rated as high-quality? Where are the high-quality programs located? How do the current proportion and distribution of high-quality programs compare with previous years?

Dataset(s): (1) CCATS licensed child care program records. (2) High-quality program records. Query 3B. Does licensed child care program participation in a quality rating and improvement system

(QRIS) affect child enrollment in that program? Does the existence of a QRIS affect enrollment in non-participating programs?

Dataset(s): (1) High-quality program records. (2) CCATS licensed child care program records. (3) ELIS licensed child care enrollment records.

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Maryland

Main Policy Question 3 (continued)

Query 3C. Are State investments to improve the quality of licensed child care programs correlated with increased school readiness levels? How much have State investments increased or decreased?

Dataset(s): (1) Early Childhood program grants and incentives records. (2) CCATS Maryland Child Care Credential Program records. (3) MMSR Kindergarten Assessment individual child records. (4) High-quality program records. (5) CCATS licensed child care program records. (6) CCATS individual child enrollment and attendance records.

Query 3D. By fiscal year, program type, and location (county), compare the number of Early Childhood programs that have access to MSDE funding and program support.

Dataset(s): (1) Early Childhood program grants and incentives records. (2) CCATS Maryland Child Care Credential Program records. (3) CCATS licensed child care program records.

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Maryland

Main Policy Question 4: What are the characteristics of effective programs?

Query 4A. How do licensed child care programs enrolling a high proportion of children assessed as ‘fully ready for school’ compare with programs enrolling a low proportion of children assessed as ‘fully ready’ in: (a) average teaching staff retention rate; (b) proportion of credentialed or degreed teaching staff; (c) child capacity utilization rate; and (d) critical compliance rate? Is this comparison affected by program type or county?

Dataset(s): (1) MMSR Kindergarten Assessment individual child records. (2) CCATS individual child enrollment and attendance records. (3) CCATS licensed child care program records. (4) CCATS licensed child care program staff records. (5) CCATS Maryland Child Care Credential Program records. (6) ELIS licensed child care enrollment records. (7) ELIS licensed child care inspection records.

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Maryland

WORKFORCE

Main Policy Question 5: How prepared is the ECE workforce to provide effective education and care for all children?

Query 5A. How does the current rate of compliance by licensed child care programs in meeting minimum teaching staff qualifications and continued training requirements compare with previous rates of compliance?

Dataset(s): (1) CCATS licensed child care program records. (2) ELIS licensed child care inspection records.

Query 5B. How does the proportion of highly qualified teachers in high-quality programs compare with the proportion in programs not rated as high-quality?

Dataset(s): (1) High-quality program records. (2) CCATS licensed child care program records. (3) CCATS licensed child care program staff records. (4) CCATS Maryland Child Care Credential Program records.

Query 5C. How does retention of teachers in high-quality programs compare with retention in programs not rated as high-quality?

Dataset(s): (1) High-quality program records. (2) CCATS licensed child care program records. (3) CCATS licensed child care program staff records.

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Maryland

Main Policy Question 5 (continued)

Query 5D: To what extent are child care program staff prepared to provide appropriate supervision and care to children in need of developmental supports?

Dataset(s): (1) CCATS licensed child care program records. (2) CCATS licensed child care program staff records. (3) CCATS approved training records. (4) ELIS licensed child care inspection records.

Query 5E. Is there a relationship between the ability of licensed child care programs to maintain qualified staffing levels and the expansion of Maryland’s public pre-K system?

Dataset(s): (1) CCATS licensed child care program records. (2) CCATS licensed child care program staff records. (3) ELIS licensed child care inspection records. (4) Public Pre-K program records.

Main Policy Question 6: What policies and investments lead to a skilled workforce?

Query 6A. To what extent has the proportion of highly qualified child care teachers increased as the result of Maryland’s Child Care Credentialing Program? What is the geographical distribution of highly qualified teachers, and how has that distribution changed over time? Across program types?

Dataset(s): (1) CCATS licensed child care program staff records. (2) CCATS Maryland Child Care Credential Program records.

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Maryland

Query 3A. What proportion of licensed child care programs are rated as high-quality? Where are the high-quality programs located? How do the current proportion and distribution of high-quality programs compare with previous years?

TASK:

By fiscal year, compare the number and percentage of licensed programs by program type, jurisdiction, and quality rating (i.e., rated as high-quality, or not rated as high-quality). Note: “Licensed high-quality program” = EITHER (1) a Head Start program, OR (2) a program that is: Accredited, Participating in Maryland’s QRIS program at Level 2 or higher, or Approved by MSDE as a pre-school education program (i.e., an approved nursery school) STEPS: 1. From the EC_FACILITY table, select all program records with EC_LICENSE_STATUS=Active. 2. Identify all programs selected in Step 1 that also appear in the HIGH_QUALITY_PROGRAM table and

have a LICENSE_EXPIRATION_DATE that is still in the future. 3. To determine if a program was in operation during a given fiscal year, identify all program records

selected in Steps 1 and 2 where OPERATION_FIRST_APPROVED_DATE occurs on or before June 30 of the applicable fiscal year and LICENSE_EXPIRATION_DATE occurs after July 1 of the applicable fiscal year (= July 1 – June 30, inclusive, for each year).

4. By statewide and jurisdiction, express the number of programs outputted per Step 2 as percentages of all programs with EC_LICENSE_STATUS=Active according to fiscal year. Display as multi-year statewide and county-level bar charts or trend-lines.

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Maryland

Lessons Learned

• System development: ln-house vs. Contractor

• Make sure your data modeling schema is suited to the intended use of your system.

• Start with the “do-able” – deconstruct “big” questions to begin building queries around the data that you have.

• Plan for system sustainability.

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Maryland

Would you say that the questions align to the intended users identified at the beginning?

Which state model may align more to your state?

What questions do you have from the Maryland model?

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Facilitated Discussion

Thank you!

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