How retention and mobility rates differ for teachers of colour

ABSTRACT

This paper examines factors associated with the retention and mobility of teachers of colour in one state in the USA, with a special focus on beginning and novice teachers. We examine year-by-year retention and mobility rates for four time periods, beginning in 2015–16. We use logistic regression models to investigate the relationship between retention and mobility status and a number of variables thought to influence teacher retention and mobility. We find that full-time status and years of teaching experience consistently predict retention and mobility, with large differences in predicted probabilities. We also find statistically significant differences in the retention and mobility rates of Latinx teachers compared to Black teachers. The paper concludes with policy implications for teacher education and induction, and a call for more complex analyses of the retention and mobility of teachers of colour, including the expanded use of disaggregated data by individual racial and ethnic groups.

KEYWORDS:

• Multivariate statistical methods
• recruitment and retention
• teacher induction
• teacher race/ethnicity

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Throughout this paper, we use the language ‘teachers of colour.’ We acknowledge that this terminology has limitations, and that other language is also used at times, including BIPOC (Black, Indigenous and People of Colour). We note that there is no universal agreement in the USA on terminology, and we endeavour to use the most specific language (that is, identifying specific racial and ethnic identities) whenever possible in our discussion.

2. Exiters may have retired, re-entered the system in subsequent years, left Washington state to teach in another U.S. state, or completely left the profession. It is not possible to distinguish voluntary and involuntary departures. It is not possible to determine whether teachers who left the state continued to be employed as teachers elsewhere.

3. Please note that Table 1 uses different data sources, and there is a two-year time difference.

4. Native American/Alaska Native teachers were not included in this analysis due to very small sample sizes in each of the years examined.

Additional information

Funding

This work was supported by the Washington State Office of Superintendent of Public Instruction.

Notes on contributors

Ana M. Elfers

Ana M. Elfers is a research associate professor in the area of Educational Foundations, Leadership and Policy at the University of Washington, Seattle. Her scholarship and teaching focus on education policy, teaching quality, leadership, and the teacher workforce.

Margaret L. Plecki

Margaret L. Plecki is Professor Emerita in the area of Educational Foundations, Leadership and Policy at the University of Washington, Seattle. Her research and teaching expertise focuses on education policy and leadership, teacher retention and mobility, and mixed methods research design. In addition to her academic expertise, she also has worked as a special education teacher and a school district administrator.

Young Won Kim

Young Won Kim is a Ph.D. candidate in Measurement and Statistics at the University of Washington’s College of Education. His research centers on the intersection of conventional statistical methods (e.g., multilevel, latent variable, and social network analysis) and machine learning.

Ni Bei

Ni Bei is a Ph.D. candidate in the Measurement and Statistics program at the University of Washington. Her research focuses on the intersection between response process data and statistical analyses (e.g., item response theory, social network analysis). Her substantive interests center on how these methodologies can promote data-driven educational policy and practice.