U.S. can improve data collection on AI/AN college students
Briefly

Native American student enrollment dropped 40% from 2010 to 2021, leaving only 107,000 AI/AN undergraduates out of 15.4 million. Research from Brookings Institute and others reveals that federal data significantly undercounts Native populations due to inadequate sampling and data practices that obscure Native identities. Estimates suggest as many as 80% of Native students are incorrectly classified. New federal standards introduced in May 2024 may enhance data accuracy, but concerns remain about the Trump administration's commitment to data transparency, potentially hindering progress in accurately supporting Native students.
For too long, Native American students have been severely undercounted in federal higher education data, with estimates suggesting that up to 80 percent are classified as a different race or ethnicity.
This chronic data collection failure renders Native students invisible in federal data systems and prevents clear assessments of the resources necessary to support student success.
The second Trump Administration has demonstrated reluctance to prioritize data transparency, which could further jeopardize these efforts and stall progress.
Federal measures of race and ethnicity in postsecondary education data undercount the total population of Native American students, in part due to insufficient sampling.
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