Federal education grants depend on an underlying framework of demographic, geographic, and economic statistics to distribute funding to states. This interactive pathway reveals those direct connections. Trace how Title I relies on SAIPE poverty estimates, how IDEA allocations are linked to population estimates (PEP), and how Perkins V is shaped by BEA per-capita income data. By mapping how administrative data flows into federal formulas, the Atlas highlights the real-world significance of these collections.
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Carl D. PerkinsCharter School GrantsIndividuals with Disabilities Education Act (IDEA)Title I, Part ATitle I, Part DTitle II, Part ATitle III, Part ATitle IV, Part ATitle VFederal grant
Title III, Part A funds supplemental language instruction educational programs and activities for English learners (ELs) and immigrant children and youth. The goal is to help ELs attain English proficiency and meet state academic standards. It also includes a separate sub-allocation for LEAs experiencing significant increases in immigrant students.
Title III, Part A grants are based on the share of a state's EL population compared to the country's EL population (80%), using the Common Core of Data, and the share of a state's immigrant child and youth population compared to the country's population (20%), using the CCD.
20 U.S.C. § 6811
Federal education data are collected across various agencies and programs, making it difficult to see how the pieces fit together. The Data Atlas brings these collections into a unified guide, detailing each dataset’s purpose, connections, and relevance to K–12 policy.
We built the Data Atlas by starting with the questions that matter. Select a question to discover what each federal dataset can tell you and how it connects to real-world policy issues.
Federal education grants depend on an underlying framework of demographic, geographic, and economic statistics to distribute funding to states. This interactive pathway reveals those connections, showing how administrative data flow into federal funding formulas and highlighting the real-world significance of these collections.
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