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American Indian and Alaska Native Head Start Family and Child Experiences Survey (AI/AN FACES)
Since its founding five decades ago, Head Start has served as the nation’s premier federally funded early childhood intervention. Focusing on children in the years before formal schooling, often from families with multiple risks, it has served as a natural and national laboratory for a wide range of basic, prevention, early intervention, and program evaluation research. Since 1997, the Head Start Family and Child Experiences Survey (FACES) has been a major source of descriptive information on Head Start and preschool children ages 3 to 5 years old who attend the program. There are 12 regions for federal management of Head Start. FACES gathers data on Head Start programs, staff, children, and families from Regions 1 through 10, which are the 10 geographically based Head Start regions nationwide. In 2013, the U.S. Department of Health and Human Services, Administration for Children and Families, funded Mathematica Policy Research to prepare and conduct the American Indian and Alaska Native Head Start Family and Child Experiences Survey (AI/AN FACES 2015)—which focused on Region XI, or programs operated by federally recognized tribes. This first national descriptive study of children and families in Region XI Head Start programs provides data to assess the strengths and service needs of both AI/AN and non-AI/AN children and families in Region XI and in turn help inform policies and practices.
AI/AN FACES 2015
AI/AN FACES 2015 is a descriptive study of children and families who attended Region XI AI/AN Head Start programs in the 2015-2016 program year. Nearly two years of extensive planning preceded AI/AN FACES 2015, with advice from members of a Workgroup that consisted of tribal Head Start directors, researchers, and federal government officials. Together, members of the AI/AN FACES 2015 Workgroup discussed and provided input on the AI/AN FACES 2015 design, its implementation, and how the findings would be disseminated with tribal voices at the forefront. Members provided advice on (1) the key research questions and information needs; (2) the population of interest (contributing to the overall sample design); (3) appropriate measures to assess the growth and development of children and to describe characteristics of children’s homes and families, Head Start classrooms, and programs; and (4) research methods and practices that would be culturally grounded and effective in tribal communities. The Workgroup members also identified target audiences for dissemination products, the formats best suited to communicate with those audiences, key topics of interest for reporting, and appropriate context for tribal data.
The AI/AN FACES 2015 study consists of a nationally representative sample of Region XI AI/AN Head Start programs, classrooms, and children. It represents all children―AI/AN and non-AI/AN―in Region XI. A total of 1,049 children and their families participated in AI/AN FACES 2015 from 73 classrooms in 21 Start programs. Data collection occurred in fall 2015 and spring 2016, following each community’s protocol for tribal review and approval. At both time points, the study assessed the skills and developmental outcomes of children, surveyed parents about their family characteristics and home and community experiences, and asked children’s teachers to describe children’s social-emotional skills and diagnosed disabilities. In spring 2016, observations of children’s classrooms took place, and teachers, center directors, and program directors completed surveys.
In collaboration with members of the Workgroup, Mathematica prepared reporting products and presentations to share AI/AN FACES 2015 findings with tribal community partners, researchers, and other stakeholders. A restricted-use dataset is available for additional analyses by qualified researchers in order to further provide critically needed information about Region XI Head Start programs and the children and families they serve. Researchers may review the special requirements to apply for access at Child Care and Early Education Research Connections.
Educational Testing Service served as a subcontractor for Mathematica.
Additionally as part of the AI/AN design work, Mathematica led the AI/AN Early Childhood Needs Assessment Design Options project, to address the information gap on early childhood services need in tribal communities. A Community of Learning of tribal service providers, early childhood researchers, and federal partners was formed to collaborate on a needs assessment framework and design topics. Mathematica prepared a set of design topics for potential future studies that may inform a national assessment of the unmet need for early childhood care, education, and home visiting services (prenatal to age 5) in tribal communities. Three design topics of interest were identified: (1) describing the population of AI/AN children and families and their participation in early childhood services based on existing data sources, (2) understanding service organization and delivery systems in AI/AN communities, and (3) assessing key features needed to support AI/AN communities’ capacity for conducting early childhood needs assessments for future training and technical assistance. Mathematica also explored implementing the first design topic with six data sets--conducting a data source review, compiling published information from those data sources publically available, and analyzing two of the data sources. A design report and technical report document this work.
AI/AN FACES 2019
AI/AN FACES 2019 follows a similar design as AI/AN FACES 2015, with guidance from members of a Workgroup comprised of tribal Head Start partners, researchers, and federal staff. The study is designed to provide descriptive information about Region XI children and their parents and children’s experience with programs, centers, classrooms, and teachers. AI/AN FACES 2019 will collect data from a nationally representative sample of the children and families in Region XI AI/AN Head Start programs to examine the developmental progress of children over the program year and their experiences during Head Start. Approval from the appropriate tribal authorities will be obtained for each selected program. The study will be carried out in ways sensitive to and respectful of the diverse nature of tribal cultures, building on the culturally informed implementation developed for AI/AN FACES 2015.
In fall 2019 and spring 2020, the study will assess the skills and developmental outcomes of 800 children from 22 programs, survey their parents, and ask children’s teachers to describe children’s social-emotional skills and diagnosed disabilities. In spring 2020, observations of children’s classrooms will take place, and teachers, center directors, and program directors will complete surveys. Recruitment of programs will begin in fall 2018 reflecting the time needed to ensure recruitment is respectful and responsive to each community’s needs and approval process.
Similar to AI/AN FACES 2015, Mathematica will analyze the data from each wave of the study and prepare a series of products, with guidance from Workgroup members on analysis and dissemination to ensure appropriate context for tribal data. A restricted-use dataset will be available for additional analyses by qualified researchers in order to further provide critically needed information about Region XI Head Start programs and the children and families they serve. Researchers may review the special requirements to apply for access at Child Care and Early Education Research Connections.
Educational Testing Service will serve as a subcontractor for Mathematica.
Survey Methodology Highlights
Technological innovations in data collection increase the accuracy and timeliness of data management and analysis. AI/AN FACES continues to use many of the innovations introduced in FACES 2014 (web-based, dual-screen administration of computer-assisted direct assessments of the study children, as well as web instruments for staff and parents). AI/AN FACES asks each data collection site a standard set of questions about their internet strength and availability in order to determine whether to deploy a web-based version or an offline version of the child assessment. This measure reduces the possibility of not being able to collect data in remote regions due to lack of internet access. Additionally, AI/AN FACES makes a concerted effort to conduct culturally responsive research.
AI/AN FACES trains field staff on cultural considerations and understanding, and integrates video highlights and interactive discussions about working in AI/AN communities into trainings.
Ashley Kopack Klein