The Texas Education Agency’s Texas Student Data Systems hosts the states’ P-20 longitudinal data system A P-20 longitudinal data system (LDS) “integrates unit-level, high-quality student, staff, and program data that are linked across entities and over time” and spans sectors from multiple early childhood programs to higher education or beyond. Source: Institute of Education Sciences. (n.d.)., which includes early childhood data (e.g., public/private pre-K data, assessment results, and staff) since 2019 in addition to other raw and aggregate data from the Public Education Information Management System. The system functions as a central data warehouse and links collections of data across agencies, including data submitted to the reporting tool, the Early Childhood Data System. The system links demographic, program, and individual data spanning childhood education, K-12, higher education, and workforce. The individual data is deidentified with a unique identifier. Data is available internally for agencies and authorized users.
The Texas Student Data System has been in development since the early 2000s (S.B. 1 (2002-2003) ),but has included early childhood data only since 2019. The system is largely funded by federal grants and the Michael and Susan Dell Foundation.
Sources:
Texas Student Data System (n.d.). Infographic.
Texas Public Education Information Resource. (n.d.). TPEIR Home Page.
Texas Education Agency. (n.d.). Early Childhood Data Collection Requirements.
The State of Texas. (2003). Text of Conference Committee Report Senate Bill No. 1 (General Appropriations Act).
Connections to Key Early Learning Study at Harvard (ELS@H) Findings:
Strong infrastructure and systems – including governance structures and data systems – are key aspects of high-quality early education and care. And research suggests there is a need for more accessible, affordable, and high-quality early education within a mixed-delivery system; strengthening infrastructure and systems is one important way states and cities can take action to address these needs and accomplish these goals.
Findings from the Early Learning Study at Harvard (ELS@H) that connect to the need for more robust infrastructure and systems, including data systems:
- Families rely on a range of formal (e.g., Head Start, center-based care, public pre-K) and more informal (e.g., home-based, relative care) early education settings; when choosing a setting for their child, families balance many logistical constraints and personal preferences.
- But for many families – and especially low- and middle-income families – early education choices remain tightly constrained due to issues of affordability and supply.
- No one early education setting type is inherently of higher quality than another; children develop and learn well in every setting type, and in the study, all setting types showed room to grow in quality.
- We have learned a great deal from this groundbreaking, large-scale study. Nevertheless, there is still much to learn about what children, families, and educators need, and about what “works” – for whom and under what circumstances – across all the diverse settings where young children learn and grow.