Stay-Home Mandates Impact on Teacher Turnover Across Schools with Different Needs: Gaining Nuances of Educational Disparities in a Digital Society

• In Event: Topics in Comparative and International Education: large language models, teaching indigenous languages, digital education, and teacher turnover

Proposal

Relevance

Teacher turnover disrupts the learning opportunities and pace of the affected students (Simon & Johnson, 2015). Estimates indicate that teacher turnover has remained relatively constant over time in the United States in both the pre and post pandemic periods. For example, in 2012-2013, 7.7% of teachers in primary and secondary schools left this profession, whereas in 2021-2022, this estimate was 7.9% (Taie & Lewis, n.d.). Although informative, these estimates do not allow measure how schools with differing levels of need may experience teacher turnover when an external shock is present. This study addresses this gap in the literature by examining the impact of the Covid-19 pandemic on teacher turnover when considering schools with different needs assessment as described by the New York State Education Department (NYSED). This analysis is relevant for at least two reasons: (a) schools with different needs are likely to experience turnovers rates with different magnitudes, (b) there is limited academic research on teacher turnover rates that considers both the levels of financial school needs and relies on quasi-experimental design methods to offer less biased estimates of the impact of an external factor. Accordingly, the purpose of this study is to offer a comprehensive and rigorous analysis of the impact of the Covid-19 pandemic on teacher turnover rates relying on officially reported and publicly available data in New York state.



Theory/Context

Across the globe most education systems required students and teachers to participate in the teaching and learning process virtually from March 2020 to August 2021. That is, stay-home mandates shifted in-person learning to online classes. This abrupt transition required teachers to adjust to unexpected working conditions, teaching in new ways that not only required preparing and offering digital materials (Zamarro et. al., 2022) but also having to deal with students who may not have the resources to take full advantage of this new teaching/learning medium. These challenges increased psychological effects such as stress and anxiety on teachers (Diliberti et al., 2021; Zamarro et al., 2022) and also raised concerns about potential growth in teacher turnover and shortages (Goldberg, 2021; Lavery, 2020).

Variations in teacher turnover rates have been reported by several researchers as a function of contextual school attributes. For example, researchers have shown that teacher turnover is likely to happen in schools with a high ratio of underrepresented racial/ethnic groups and students from low-income backgrounds (Ingersoll, 2001; Lankford et al., 2002; Papay et al., 2017; Scafidi et al., 2007). Similarly, Simon & Johnson (2015) argue that teachers in high poverty areas leave school not due to student characteristics but due to poor working conditions which disturb them from teaching and students from learning. Based on this evidence it is expected that poor working conditions, as captured by school needs and the impact of stay-home mandates may accentuate teachers’ turnover rates.

Inquiry

With the brief contextualization, the research question is Has the Covid-19 pandemic, and its associated stay-home mandates, had any effect on turnover decided by teachers in school districts with high Need/Resource index? To address this question this study employs a Difference-in-Differences (DD) approach to estimate teacher turnover in New York school districts. A particular focus of this study is placed on the differential impact across districts of varying socioeconomic status while considering school student demographics and organizational characteristics.

Our dependent variable is teacher turnover rates in each school. This indicator is measured by the NYSED as the count of teachers in the prior school year who did not return to a teaching position in the current school year expressed as a percentage. Similarly, the main independent variable is the Need to Resource Capacity (NRC) Index also measured by the NYSED. This index captures a school’s ability to meet the needs of its students with local resources. For example, a school with both estimated poverty and combined wealth ratio equal to the State average would have a need/resource capacity index of 1.0. The NYSED categories included in our analyses are: (1) High N/RC: New York City, (2) High N/RC: Large City Districts, (3) High N/RC: Urban-Suburban Districts, (4) High N/RC: Rural Districts, (5) Low N/RC Districts. Using these classification, we will measure how schools in categories 1 to 4 compare in their turnover rates when compared with schools classified as low need—schools with the lowest financial need in New York state.  



Findings/Argument

Our analytic strategy consists of comparing turnover rates of group 5 against groups 1 to 4 to offer comprehensive estimates of the impact of this external shock on turnover rates across schools with high needs but located in different areas across the state. Our estimator is based on difference in differences in the form of Δ𝑌=[𝐸(𝑌ℎ𝑝_i1 − 𝑌ℎ𝑝_i0)] − [𝐸(𝑌𝑙𝑝1−𝑌𝑙𝑝0)] with 1 and 0 capturing the pre- and post-time frames and hp_i and lp indicating high need and low need index. The 𝑖 subscript in hp is added to indicate that we rely on the four different need categories described above. Additionally, we will assess for potential variations in the compositional attributes of the schools, and we will also control for time-based placebo or falsification tests (see Gonzalez Canche, 2022).

Preliminary findings (Figure 1 https://cutt.ly/deEX904o) indicate that turnover rates in low need schools are consistently the lowest across all academic years. Note that the database required to complete these analyses is complete (see Table 1) and we foresee no issue in addressing our research question and purpose.

Contribution

In accordance with the conference’s theme “Envisioning Education in a Digital Society” this study assesses the impact of online education “forced” by stay-home mandates on teacher turnover. Specifically, this study was designed to leverage a natural experiment wherein an external shock impacted all schools in the analytic sample. This external shock, therefore, opened the possibility of measuring the potential differential impact of stay-home mandates on teacher turnover when considering teachers’ working conditions, as measured by standardized school needs indexes in the state of New York. Although our analyses are based on a single state, we expect that the resulting understandings apply to other contexts.

Authors

• REIKA FUJII, Graduate School of Education, University of Pennsylvania

• Manuel Sacramento Canche, The University of Pennsylvania