Session Information
09 SES 12 A, Exploring Teacher Factors and Educational Contexts: Implications for Practice and Policy
Paper and Ignite Talk Session
Contribution
It is widely accepted that teachers are one of the most important school-level inputs for student academic success. Most educational research focuses on teacher effectiveness in terms of their contribution to student test scores, but there is a growing need to examine the teaching profession as an outcome in itself. A teacher workforce characterized by high turnover rates will not only negatively impact schools via administrative burdens as well as students and their educational futures, but also the teachers themselves via their working conditions and professional satisfaction.
There is a longstanding link between low-SES schools and teacher turnover, but this literature mostly comes out of the USA, with some exceptions. Disproportionate teacher turnover rates often affect lower-SES schools and classrooms in particular (Bacolod, 2007; Bonesrønning, Falch & Strøm, 2005; Hanushek et al., 2004; Feng, 2009; Glassow, 2023), impeding organizational and administrative school functioning, and potentially contributing to longer-term student behaviours such as college attendance and high school completion (Jackson, 2018). Moreover, high turnover rates may be symptomatic of worsening working conditions and professional satisfaction which have been documented in a number of education systems (Ball, 2016; Craig, 2017).
There is therefore a need to document the extent to which teachers mirror socioeconomic demographics of schools and concrete ways in which to democratize access to teacher competence in Sweden. This is a pertinent issue due to the demographic changes occurring in Sweden over the past several decades, the rising school inequality in the country (Karbownik, 2020; Yang Hansen & Gustafsson, 2016). The present study seeks to contribute to this gap in knowledge and examine whether changes in school composition (by family education level or language spoken by the students) results in changes in teacher turnover rates. Using teacher and student register data, the study first examines in a descriptive fashion whether there are growing differences between schools in terms of teacher turnover rates. Next, using a panel data model, the link between changes in student school composition and teacher turnover are explored. Whether or not causal conclusions can be made from such an approach will also be explored in the paper.
Allensworth, Ponisciak and Mazzea (2009) outline several main reasons teachers cite their dissatisfaction with certain schools: principal effectiveness, dysfunctional administration, challenging students, low salary, and limited autonomy which may be due to additional accountability practices. Vagi and Pivarova (2017) consolidate the literature employing theoretical frameworks for teacher mobility and offer person-environment fit theory (Dawis, 1992) as a theory which may encapsulate the myriad of environmental and personal factors which may be relevant for teacher mobility. While the focus of the study is on the role of socioeconomic composition of schools and classrooms in teacher mobility behaviours, person-environment fit theory allows for an accurate estimation of factors which may bias results unless they are under control, or unless proper methodologies are used which account for unobserved heterogeneity. Dawis (2004) highlights that job satisfaction or work stress are the result of successful or mismatched employees, respectively.
Against this background, the main research questions of the study are:
1) Are between school turnover rates growing in Sweden over the past several decades?
2) Do changes in socioeconomic and migration demographics of schools result in higher turnover rates? Specifically, do schools with a higher proportion of students with main languages other than Swedish exhibit a significantly higher proportion of teachers who leave?
3) Does this change depending on teacher qualifications? For example, are more experienced teachers more or less likely to leave as a result of these changes?
Method
The data come from the teacher and student registry from the Swedish National Agency for Education between the years 2000 and 2013. The information is collected yearly. This registry includes all teachers employed in Swedish schools and not just a sub-sample. It contains information on teachers’ qualifications (education, specialization, experience, certification) as well as their working conditions (workplace, permanent vs. fixed-term status, and workload). The data are matched to the pupil registry for lower and upper secondary schools. Since the teachers cannot be linked to students but only to schools, the analysis concerning the socioeconomic composition is conducted at the school-level. OLS regressions may be biased due to unobserved differences between schools and their association with the model residuals. Educational researchers are increasingly becoming aware of the advantageous of approaches using fixed effects. The analysis is conducted in posit (formerly known as RStudio) using the plm package (Croissant & Milo, 2008). Panel data techniques are employed, which account for time-invariant unobserved heterogeneity associated within the teachers (the subjects). The restriction of variation to within individuals over time account for all factors at the individual level which are constant. The remaining variation is the change in school characteristics over time. The odds of changing schools will be regressed on school characteristics related to parental education and migration composition. The analysis controls for time-varying characteristics at the school-level, such material resources or other factors, such as geographic location. The analysis also considers effect heterogeneity, in terms of whether or not the link between school composition and teacher turnover changes as a function of teacher characteristics. In a final step, the reduction in variation imposed by the fixed effects is investigated by transforming the estimate by the within-unit standard deviation, and within-unit standard deviations are presented for each school.
Expected Outcomes
The study expects to find a link between student socioeconomic composition and teacher mobility, whereby schools with higher proportions of students with the right to Swedish language education and lower parental education levels experiencing higher turnover rates. A general positive trend of increasing inequality in teacher turnover between schools is also expected. It is more difficult to speculate about the effects across teacher characteristics, as research is mixed, highlighting the need for this study to shed more light on the issue (Glassow, 2023). The study will provide valuable empirical evidence regarding dimensions of inequality which are often overlooked. First, the fact that the working conditions of teacher may be becoming more unequal across job settings, and second, how this affects school functioning and cohesion from an organizational perspective.
References
Allensworth, E., Ponisciak, S., and Mazzeo, C. (2009). The schools teachers leave: teacher mobility in Chicago public schools. Consortium on Chicago School Research, 1-52. Bacolod, M. (2007). Who teaches and where they choose to teach: college graduates of the 1990s. Educational Evaluation and Policy Analysis, 29, 155-168. Ball, S. (2016). Neoliberal education? Confronting the slouching beast. Policy Futures in Education, 14, 1046–1059. Bonesrønning, H., Falch, T., & Strøm, B. (2005). Teacher sorting, teacher quality, and student composition. European Economic Review, 49, 457-483. Craig, C. (2017). International teacher attrition: multiperspective views. Teachers and Teaching, 23, 859-862. Croissant, Y., & Millo, G. (2008). Panel data econometrics in R: The plm package. Journal of Statistical Software, 27, 1–43 Dawis, R. V. (2004). Job satisfaction. In J. C. Thomas (Ed.), Comprehensive handbook of psychological assessment, Vol. 4. Industrial and organizational assessment (pp. 470–481). John Wiley & Sons, Inc.. Feng, L. (2009). Opportunity wages, classroom characteristics, and teacher mobility. Southern Economic Journal, 75, 1165-1190. Glassow, L. (2023). Teacher turnover and performance-based school accountability: a global issue? Journal of Education Policy, forthcoming. Hanushek, E. A., Kain, J. F., & Rivkin, S. G. (2004). Why Public Schools Lose Teachers. The Journal of Human Resources, 39, 326-354. Jackson, C.K. (2009). Student demographics, teacher sorting, and teacher quality: Evidence from the end of school desegregation. Journal of Labour Economics, 27, 213-256. Jackson, C.K. (2018). What do test scores miss? The importance of teacher effects on non test score outcomes. Journal of Political Economy, 126, 2072-2107. Karbownik, K. (2020). The effects of student composition on teacher turnover: evidence from ad admission reform. Economics of Education Review, 75. Vagi, R., & Pivovarova, M. (2017). "Theorizing teacher mobility": a critical review of literature. Teachers and Teaching, 23, 781-793. Yang Hansen, K., and Gustafsson, J.E. (2016). Causes of educational segregation in Sweden –school choice or residential segregation. Educational Research and Evaluation, 22, 23-44.
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