Driver's License Data Can Help States Better Understand Education and Workforce Pathways. State Implementation Guide
保存先:
| 出版年: | Data Quality Campaign (2025) |
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Data Quality Campaign
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| オンライン･アクセス: | Citation/Abstract Full text outside of ProQuest |
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| 抄録: | Statewide longitudinal data systems (SLDSs) often rely on personal identifiers to securely link individual-level data across early childhood, K-12, higher education, and the workforce. However, different sectors use different types of personal identifiers which can make accurately connecting records difficult. Driver's license data offers a single verifiable record that can be used to fill gaps in other records and accurately connect data across sectors, enabling a state to resolve inconsistent data and improve matching and data quality within its SLDS. State leaders are then able to provide higher-quality education-to-workforce information and trend data that empower individuals to make informed decisions and select education and training opportunities that meet their educational, financial, and geographic needs. This brief from the Data Quality Campaign and Data Integration Support Center (DISC) at WestEd is intended to help state leaders understand the utility and risk of including driver's license data in their SLDS matching process and answers a number of related questions. [This brief was prepared with the Data Integration Support Center at WestEd.] |
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| ソース: | ERIC |