HIGHLIGHTS
- New Profit and Massachusetts Department of Early Education & Care (EEC) are supporting early education and care program leaders.
- Selected Early Childhood Support Organizations (ECSOs) are partnering with local licensed providers.
- New Profit and EEC are funding the initiative, and Abt is leading the implementation and impact evaluation.
PROJECT
MA ECSO II
The Challenge
Many initiatives attempting to improve the quality of early education and care settings typically focus on teacher practice versus organizational capacity. The Massachusetts Early Childhood Support Organization initiative (MA ECSO) —a public-private partnership that includes New Profit, a venture philanthropy organization, and the Massachusetts Department of Early Education and Care (EEC) — seeks to improve the quality of educational programs by helping leaders provide job-embedded professional learning opportunities for their educators and use continuous quality improvement to inform and advance their programs. This initiative provides professional supports, resources, and financial incentives to programs with the goal of empowering leadership to support early educators in their provision of high-quality instruction that promotes positive outcomes for young children.
The Approach
Abt Global is evaluating the implementation and impact of this innovative statewide initiative through a series of informative surveys, interviews, and focus groups with ECSO and program staff. Additional insights are gleaned from the consolidation of implementation supports data that we collect and display in an interactive online dashboard for key staff to use, the analysis of classroom observation data, and the facilitation of fidelity measurement and goal-setting to aid in benchmarking implementation data.
The Results
In the second year of MA ECSO’s implementation, over 50 center-based programs across the Commonwealth are receiving supports from one of three ECSOs. We are currently learning to what extent delivered supports are aligned to the expectations of the model, and are helping to support model adjustments moving forward.
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