Data in Head Start Programs
Data in Head Start Programs is a series of interactive online learning modules that includes a mixture of practical scenarios, real-life examples from the field, and tools and templates.
Data analysis is the process of examining data to extract useful information and support decision making. It involves a variety of techniques and methodologies to interpret data from different sources and formats. Head Start grant recipients need to apply data analysis for successful program planning.
Explore resources that support the use of data analysis in multiple areas of Head Start program planning and implementation.
Data in Head Start Programs is a series of interactive online learning modules that includes a mixture of practical scenarios, real-life examples from the field, and tools and templates.
Programs collect and use a variety of family related data. This set of resources assist programs to gather, analyze, and share data with families that includes their voices and honors their perspectives.
The partnership between parents and staff is fundamental to children's current and future success in school readiness and beyond. Discover how programs can share information with families about children's learning and progress toward school readiness outcomes.
Explore this resource to learn more about various data management strategies within the context of Head Start programs. Find out what quality data is and why it is important. Also, learn what makes data valid and reliable.
Explore this guide that describes how the CLASS® relates to school readiness, and how using it to collect and apply data, including case studies that show how programs have applied CLASS® for support and improvement.
Read how Head Start teachers in Minnesota created a statewide learning community that has not only studied the value of authentic assessment but has also built a state Head Start database that combines assessment, demographic, and classroom information.