Teacher Preparation and Teacher Retention: Examining the Relationship for Beginning STEM Teachers

• In Event: 63.076 - Stemming STEM Teacher Attrition: Implications From Evidence-Based Retention Efforts Across the Continuum for Preparation Programs

Abstract

Objectives: Our first objective was to examine the odds of beginning STEM teachers being hired in a high-needs schools (as defined by a high proportion of students living in poverty) who are from different routes to certification, including university-based undergraduate, university-based graduate, out-of-state, emergency certification, and five types of alternative certification programs (ACPs) - district-based, education region service centers, community colleges, privately managed, and university-based. Our second objective was to compare the attrition/turnover rates of beginning STEM teachers in high-needs schools by route to certification. We also examined the effects of both personal- and school- characteristics on all outcome variables.

Theoretical framework/Rationale: Beginning teacher attrition/turnover has negative effects on student outcomes (Ronfeldt, Loeb, & Wyckoff, 2013) and creates substantial fiscal costs for districts (Ogundimu, 2014), with both effects more acute for high-needs schools (Ronfeldt, et al., 2013). ACP teachers disproportionately teach in high-needs schools and are more likely to leave their initial schools than are traditionally prepared teachers (e.g., Koedel, Parsons, Podgursky, & Ehlert, 2015; Lincove, Osborne, Mills, & Bellows, 2015). Few studies of beginning STEM teachers, however, examine either their placement in high-need schools or their attrition/turnover from high-need schools. This study fills this research gap.

Methods: To examine employment, we utilized logistic regression analysis with a dependent variable of 1 if a beginning STEM teacher was employed in a high-need school and 0 otherwise. The logistic regression model was:

Odds of Being Hired in High-Need School = b0 + b1(Personal Characteristics) + b2(School Characteristics) + b3(Geographic Locale) + b4(Certification Route) + b5(Year) + error

To examine attrition, we estimated a series of discrete-time hazard models with a dependent variable of one if a teacher left teaching (attrition) or left a school (turnover) and a value of zero otherwise. Our discrete-time hazard model was:

𝑙𝑜𝑔𝑖𝑡 ℎ(𝑡ij)= 𝜶′j𝐷j+𝐴𝐶𝑃i𝛽1+𝑋ij𝛽2+𝑆ij𝛽3+𝜃i

A logit transformation of hazard for a teacher i in time j is a function of time indicator α’j, ACP status ACPi, teacher characteristics Xij, school characteristics Sij, and region indicators θi.

Data: This study relied on data that included teacher certification, employment, personal characteristics, school characteristics, and school achievement for 2004 through 2015. We examined attrition/retention over a five-year time-period.

Results: We found teachers of color (ToC) and teachers from ACPs had greater odds than White teachers and traditionally prepared teachers, respectively, to be hired in high-need schools across all years. Interestingly, for beginning STEM teachers in high-need schools, we found ToC to have lower odds of leaving the profession and the school while ACP teachers had greater odds of leaving the profession and the school.

Scholarly significance: We find high-need schools are more likely hire beginning STEM teachers from ACP programs and, thus, are more likely to experience greater teacher instability. Given teacher stability is associated with positive school outcomes, particularly for students in poverty and students of color (Ronfeldt, et al., 2013; Ogundimu, 2014), de-regulating teacher preparation may have deleterious effects on students in high-need schools. Policymakers should be extremely cautious in expanding ACPs given the potential harm to such students.

Authors

• Ed Fuller, The Pennsylvania State University

• Andrew Pendola, Auburn University