Mathematica conducted AI/AN FACES 2015, the first national descriptive study of children and families in Region XI Head Start programs. Again in AI/AN FACES 2019, Mathematica will assess the strengths and service needs of children and families in Region XI.
Quality Rating and Improvement Systems (QRIS) are tools states use to assess, improve, and promote quality in early child care and education. The ratings can be used by parents in selecting child care, by providers as a benchmark to achieve better quality care, and by programs as an accountability measure for funding. States and municipalities that adopt these methods need support in determining the most useful ways to build and evaluate models. Mathematica has conducted an assessment of these systems, including helping states better understand the intended and unintended consequences of policy and implementation. We have also examined associations between quality features, thresholds and dosage and child outcomes in the Q-DOT project, and charted teachers’ use of child progress monitoring to improve instructional practice (Child Progress Monitoring). In addition, we have developed measures of family experiences in programs (Head Start Family Voices) and of child-adult interactions in infant/toddler care settings (Q-CCIIT).
American Indian and Alaska Native Head Start Family and Child Experiences Survey (AI/AN FACES)
Early Head Start Family and Child Experiences Survey: Baby FACES 2018
Mathematica has launched a new five-year descriptive study of Early Head Start, the Early Head Start Family and Child Experiences Survey (Baby FACES 2018), to guide program technical assistance, management, and policy.
Professional Development Tools for Improving Quality of Infant and Toddler Care (Q-CCIIT PD Tools)
Following on Mathematica's successful projects to develop and test a measure of the quality of caregiver-child interaction for infants and toddlers (Q-CCIIT), this work improves upon the quality of care by providing caregivers with strategies and tools via an interactive website.
Early Head Start Family and Child Experiences Survey (Baby FACES)
The Early Head Start Family and Child Experiences Survey (Baby FACES) is designed to be a rich source of data describing the experiences of children and their families in Early Head Start.
Measurement Development: Quality of Caregiver-Child Interactions for Infants and Toddlers
Mathematica developed a new measure to assess the quality of caregiver-child interactions for infants and toddlers in nonparental care. The measure can be used across child care settings, including center‐based and family child care settings, as well as single- and mixed-age classrooms.
Head Start: The Family and Child Experiences Survey (FACES)
Mathematica conducted the 2006 and 2009 FACES studies, and, for the most recent studies (2014-2018 and 2019), redesigned FACES to provide key data more rapidly and with greater frequency and to help researchers examine more complex issues and topics in greater detail and efficiency.
Evaluating Child Care Quality Rating Systems (QRS)
Mathematica's assessment involved gathering, analyzing, and organizing information to inform each piece of the QRS logic model. We also helped states better understand the full picture, the interactions that can occur, intended and unintended consequences of policy and implementation.
Head Start Family Voices Pilot Study
Head Start and Early Head Start aim to increase the school readiness of young children in low-income families. To better understand the experiences of participating families and staff, Mathematica developed interviews to collect qualitative data from these individuals.
Child Care and Early Education Quality Features, Thresholds, and Dosage and Child Outcomes
Mathematica explored the associations between quality early care and child outcomes, examining whether certain thresholds of quality or dosage need to be met or what particular aspects of quality need to be present within different age groups and types of care settings.