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Workforce Outcomes of Program Completers in High-Needs Endorsement Areas

Emanuele Bardelli, Matthew Ronfeldt

Abstract: Purpose: For decades, federal and state agencies have identified teacher shortages in high-needs endorsement areas (HNEAs), including science, mathematics, and special education, as a critical problem. Many states have implemented policies and practices to recruit HNEA teachers, but little is known about how their workforce outcomes compare with other teachers. Research Methods: We leverage statewide longitudinal data in Tennessee to analyze the workforce outcomes of teachers prepared in the state between 2010 and 2016. We model our outcomes of interest using linear and logistic multilevel regression. Findings: We observe that the number of teachers who receive HNEA endorsements has increased over time even as the overall number of teachers prepared in the state has declined. HNEA teachers are employed at higher rates and retained at similar rates as other teachers. HNEA teachers have similar student achievement gains as non-HNEA teachers. Though HNEA and non-HNEA teachers also have similar first-year observation ratings, STEM (science, technology, engineering, and mathematics) and special education teachers improve at slower rates subsequently. Implications: Our results suggest that potential policy solutions to the recruitment, retention, and development of highly effective HNEA teachers might require policies targeted to individual HNEAs, as each area might have unique needs and challenges. The positive results on preparation and employment of HNEA teachers suggest that Tennessee’s policies to train, employ, and retain HNEA teachers have been largely successful. However, our findings also suggest that HNEA teachers may need additional supports in instructional development.
Keywords: HNEA / teachers / special education / mathematics / Tennessee / retained / science / model / endorsement

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