When I came on board to NHSA at the end of May, my task was to reconsider how local Head Start programs' strengths and best practices could be showcased in the federal monitoring process. Despite several conversations with members of a data monitoring group associated with the organization, there were several complications associated with my initial task. One of them included the fact that the Office of Head Start is reconsidering its existing monitoring process for programs to find different ways to measure whether programs are in compliance and to measure their progress on the scale of Continuous Quality Improvement.
In addition to continuing to learn about the early childhood education landscape through webinars, presentations, and recent articles, I have pivoted my project to focus on the NHSA’s data analytics playbook. The playbook contains examples of how programs have used mandatory data collection to their advantage, organized in categories such as Education and Child Development, Health, Family and Community Engagement, Children with Disabilities, Pregnant Women, Human Resources, and Program Management. Within these categories are topics like how to improve enrollment and recruitment, what the most common reasons for absence are, and other topics that are generally pertinent to programs regardless of their size or geographic location for their assistance and referral.
My task is to hold conversations with data managers, technology managers, ERSEA managers, executive directors, and data coordinators, among others, to discuss how programs track and understand enrollment data and patterns and how programs measure progress against school readiness goals. After speaking with such individuals from around the country, I will identify unique practices that programs have pursued as a result of trends they have discovered through data collection. Additionally, I will write up such examples for the greater Head Start community to use, and categorize those on the playbook website in a way that is applicable and useful for all.
Source: https://data.nhsa.org/