Unraveling Beginning Secondary CTE Teacher Turnover in Pennsylvania Schools Using Survival Analysis.

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Title: Unraveling Beginning Secondary CTE Teacher Turnover in Pennsylvania Schools Using Survival Analysis.
Authors: Jeong, Seong Ji1, Fuller, Edward J.1, Threeton, Mark D.1
Source: Career & Technical Education Research. Aug2026, Vol. 51 Issue 2, p54-78. 25p.
Abstract: This study examines how teacher and school characteristics influence the risk of leaving the initial school of employment among beginning secondary Career and Technical Education (CTE) teachers in Pennsylvania. Using administrative data on 2,595 beginning secondary CTE teachers, we employed survival analysis to identify factors associated with teacher turnover from their schools of origin in Pennsylvania. Black teachers, those with lower educational attainment, and part-time teachers were associated with a higher risk of leaving their schools compared to their counterparts. Teachers employed in Career and Technical Centers (CTCs) were at higher risk of turnover than those in comprehensive high schools. Teachers specializing in STEM/technical fields exhibit higher turnover risk than those in business or service disciplines, although this effect was not significant once school characteristics were controlled for. Our findings highlight the importance of targeted retention interventions and school-level supports to enhance workforce stability among beginning CTE teachers. This study offers valuable insights for school leaders, policymakers, departments of education, and other stakeholders interested in the factors that influence CTE teacher departures. [ABSTRACT FROM AUTHOR]
Copyright of Career & Technical Education Research is the property of Career & Technical Education Research and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Unraveling Beginning Secondary CTE Teacher Turnover in Pennsylvania Schools Using Survival Analysis.
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  Data: <searchLink fieldCode="JN" term="%22Career+%26+Technical+Education+Research%22">Career & Technical Education Research</searchLink>. Aug2026, Vol. 51 Issue 2, p54-78. 25p.
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  Data: This study examines how teacher and school characteristics influence the risk of leaving the initial school of employment among beginning secondary Career and Technical Education (CTE) teachers in Pennsylvania. Using administrative data on 2,595 beginning secondary CTE teachers, we employed survival analysis to identify factors associated with teacher turnover from their schools of origin in Pennsylvania. Black teachers, those with lower educational attainment, and part-time teachers were associated with a higher risk of leaving their schools compared to their counterparts. Teachers employed in Career and Technical Centers (CTCs) were at higher risk of turnover than those in comprehensive high schools. Teachers specializing in STEM/technical fields exhibit higher turnover risk than those in business or service disciplines, although this effect was not significant once school characteristics were controlled for. Our findings highlight the importance of targeted retention interventions and school-level supports to enhance workforce stability among beginning CTE teachers. This study offers valuable insights for school leaders, policymakers, departments of education, and other stakeholders interested in the factors that influence CTE teacher departures. [ABSTRACT FROM AUTHOR]
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  Group: Ab
  Data: <i>Copyright of Career & Technical Education Research is the property of Career & Technical Education Research and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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