Rethinking American Indian And Alaska Native Data Collection In Higher Education (2024)

This brief by Janiel Santos and Amanda R. Tachine outlines significant considerations for enhancing data collection practices concerning American Indian and Alaska Native (AI/AN) populations in higher education. It emphasizes the importance of culturally sensitive methodologies that reflect the distinct identities and experiences of AI/AN communities. The brief advocates for the adoption of new federal standards to improve how data about AI/AN populations are collected and reported, which is crucial for formulating effective policies and educational practices that support these communities.

Main Takeaways:

• Complexity of AI/AN Identity: The report highlights the intricate nature of AI/AN identity, which includes political, legal, and cultural dimensions not fully captured by current federal racial and ethnic categories. Recent federal updates aim to enhance the granularity of this data.
• Historical Inadequacies in Data Collection: Traditionally, data collection methods have not adequately captured or represented the diversity within AI/AN populations, often leading to overgeneralized analyses that fail to address specific community needs.
• Importance of Tribal Consultation: Effective data collection requires ongoing consultation with Tribal communities to ensure data practices align with the unique values and requirements of these groups.
• Data Sovereignty: Emphasizes Indigenous Data Sovereignty, advocating for Tribal control over the collection, interpretation, and dissemination of data about their communities to ensure self-determination in research and policy-making.
• Methodological Recommendations: Suggests methodologies that include detailed race and ethnicity categories to improve the accuracy and utility of data collected, advocating for systems that allow the identification of AI/AN individuals with multiethnic backgrounds or those from non-federally recognized tribes.
• Policy Implications: The brief calls for policy adjustments that integrate these improved data collection practices, which are essential for creating informed, effective educational policies and practices that genuinely support AI/AN students.