|Title:||Teacher Working Conditions and Equitable Student Outcomes|
|Principal Investigator:||Miller, Luke||Awardee:||University of Virginia|
|Program:||Improving Education Systems [Program Details]|
|Award Period:||4 years (07/01/2020 - 06/30/2024)||Award Amount:||$1,399,996|
Co-Principal Investigators: Piver-Renna, Jennifer; Player, Daniel; White, Rachel
Purpose: In order to close persistent achievement gaps along lines of race and ethnicity and economic disadvantaged status, all students must be taught by an effective teacher. Improving working conditions can help accomplish that because these conditions define the school context in which teachers do their work and facilitate teachers realizing the intrinsic rewards they seek. This project will explore the relationships between working conditions, teacher retention, and equitable student outcomes.
Project Activities: The researchers will conduct mixed methods research that will (1) characterize schools' working conditions, creating working conditions profiles, and assess their association with teacher retention and equitable student outcomes, (2) document how districts and schools are making use of data on working conditions to affect positive change, (3) describe how working conditions support or hinder teachers' efforts to meet the needs of English learners, (4) assess the degree to which working conditions differentially predict teacher retention in rural schools by teachers' prior exposure to rural communities.
Products: The research team will provide preliminary evidence of what types of working conditions correlate with teacher retention and student outcomes. Researchers will also produce peer-reviewed publication(s) and a series of research briefs highlighting the associations between working conditions and teacher job satisfaction.
Setting: The data will include all schools, statewide in Virginia.p>Sample: The sample will include all students (grades 4 through 12) and teachers (prekindergarten to grade 12), as well as selected principals and division officials.
Factors: The researchers will explore teacher working conditions including the factors captured by the Virginia Working Conditions Survey. This survey contains multiple measures of working conditions under four domains: professionalism; teaching, instruction, and student support; school and community supports; and safety.
Research Design and Methods: The researchers will conduct a series of mixed methods studies that draw on survey and administrative data as well as semi-structured interview and focus group data with teachers, principals, and district officials. The first phase of research will include data collection through the administration of the Virginia Working Conditions Survey followed by qualitative data collection (focus groups and interviews). These data will be analyzed in a series of studies and sub-studies that leverage various statistical analyses to address question about the relationship among working condition factors and teacher and student outcomes.
Control Condition: Due to the nature of the research, there is no control or comparison condition. Instead we will compare outcomes across profiles of the working conditions present in schools.
Key Measures: In addition to results from the Virginia Working Conditions Survey, the researchers will collect the following outcome measures: (1) student scores on statewide mathematics and reading exams in grades 4 through 8, (2) high school student progression through pipelines of college-preparatory mathematics and science courses, (3) observed teacher retention, (4) teachers' stated retention intentions, and (5) teacher job satisfaction. Other key explanatory measures include the percent of a teacher's students who are English learners and teachers' prior exposure to rural communities.
Data Analytic Strategy: The researchers will conduct descriptive analyses. They will transcribe, code, and analyze will all focus group and interview data for patterns. In addition, depending on the particular study, the researchers will conduct latent profile analysis to identify working conditions profiles, multinomial logistic regression to assess how they are associated with contextual factors, teacher-level logistic and multivariate regression to explore the association between the profiles and teacher retention, student- and school-level multivariate regressions to assess the relationship between the profiles and equitable student outcomes, and bivariate and multivariate analytics to explore local data use and teacher job satisfaction, respectively.
Related Project: Developing a Research and Policy Agenda to Improve School Climate in Virginia (R305H170016)