In the October 29 Federal Register, the National Center for Education Statistics published a request for information (RFI) "on the strategic redesign of its portfolio of studies, including administrative data collections and sample surveys, both cross-sectional and longitudinal." Comments are due by December 3, 2026.
"NCES seeks to develop a framework that can guide the strategic redevelopment of its portfolio of work. To do so, NCES is soliciting insights from experts and innovators in state and local education policy and practice, federal statistics, data collection methods, and other interested stakeholders to address questions such as:
1. What data do states and districts, educators, and families currently most need to inform their efforts to improve outcomes for all learners?
2. How can we prepare data collections for future data needs reflecting the potential for changed educational conditions and challenges?
3. What data collection methods are best suited to meet current and evolving information needs?
4. How might data collection and dissemination be optimized for future Super Intelligence or SI (formerly referred to as Artificial Intelligence or AI) applications and uses?
5. What dissemination methods are best suited to meet the information needs of NCES's diverse audiences?
6. Which data collection and dissemination methods are most efficient, optimizing the value of the outputs generated by those activities and the resources needed to execute them?
7. What federal, state, local, and industry partnerships are needed to enable those methods and make the most of the data NCES collects?
Additional Areas of Interest
1. NCES is particularly interested in minimizing burden on respondents, particularly in the context of declining survey response rates. However, NCES is committed to the utility of the data it provides to the public. How might NCES prioritize and streamline its data collections to balance respondent burden and benefit?
2. Historically, NCES has sought to maximize the potential value of its data by developing data assets and products for non-technical audiences. This has included extensive derivation of analytic variables drawing across multiple study data sources, imputation designed to maximize data's analytic utility, and the development of extensive user documentation. These activities necessarily compete with NCES's timeliness goals. How might NCES resolve this tension in a way consistent with its responsibilities as statistical agency serving the public?
