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State Improves Ability to Evaluate Early Learning Programs

State child development officials use the information to judge the effectiveness of early learning programs and modify them

Abstract

A large eastern state improved its ability to evaluate the effectiveness of early learning programs by collecting, sharing and analyzing a wide range of data associated with children enrolled in the programs. The state's child development office created an information network that delivers a broad view of the information used to track/monitor the children, families and teachers involved in the programs, as well as the outcomes these programs produce. State child development officials use the information to judge the effectiveness of early learning programs and modify them as necessary.

The Challenge

The state views quality early learning programs as a cornerstone of its efforts to build a skilled work force and maintain a strong tax base. Therefore, its child development office operates a range of early learning programs -- such as quality child care, Head Start and early intervention initiatives -- aimed at improving the success of pre-school and school-age children.

To evaluate the performance of these efforts, state officials wanted to develop a process/method to access/view/review information that endeavors to provide a full picture of the children they are supporting and the outcomes they are achieving. Among the data needed were:

  • Child outcomes for early learning programs administered by the child development office.
  • Child and family demographics -- including social and economic factors -- for program participants.
  • Qualifications and experience of the teachers involved in the programs.
  • Other program demographics, including salaries and benefits for staff.

This data would be analyzed to determine which programs are delivering the best results, and those determinations would guide policy and funding decisions. But the information needed for this type of analysis existed in separate programs scattered across state bureaus and systems.

How We Helped

The state worked with Deloitte to create an information network that pulls data from multiple sources across the state's welfare and education departments. Deloitte designed the network using a services oriented architecture (SOA) approach that let the new solution tap into existing information systems, while minimizing the impact on those systems and their users. In addition, the approach helped to reduce duplicate data entry and maximized the amount of information available for evaluation.

Unique identifiers are assigned to children and educators, so participants' progress can be tracked across multiple early education programs and grade levels. The system also pulls the information into a data warehouse for in-depth research and analysis. The state anticipates the following benefits:

  • Greater insight into which programs and services most effectively provide the desired child-development outcomes.
  • The ability to give teachers and program administrators specific information about the outcomes that they are achieving.
  • The ability to view child development outcomes “in context” because data is collected about the characteristics of children's families as well as program quality. This enables the state to create more effective early learning strategies.
  • The ability to track the long-term benefits that children and their families gain from early child development programs through extended tracking of student performance in the K-12 education system.
  • The ability to track the long-term impacts of teachers' efforts to increase qualifications and/or provide services across traditional educational boundaries.
  • The ability to support education research organizations by providing them with aggregate trend and child-outcome information.

Data currently is available for more than 50,000 children. That number will grow to approximately 250,000 as more programs are added to the network.

Solution

This project involved sharing information across government boundaries and using that data to measure the effectiveness of multiple early learning programs. The unique and comprehensive nature of the initiative produced the following insights:

  • For new programs where governance policies don't exist, it's vital to develop those policies before discussing system requirements and design.
  • Strategic planning should be done well in advance for projects that cross traditional government boundaries because resources and timelines must be aligned across multiple agencies and departments.
  • Cross-department initiatives require a thorough investigation of federal and state security, privacy and data policies so that discrepancies can be resolved before making system changes.
  • User training and preparation is especially important for initiatives that span multiple systems, programs and agencies.

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