Association for Public Policy Analysis & Management

In recent years, district policymakers and practitioners have worked to determine how best to improve the quality of their teacher labor forces through the use of multiple measure teacher evaluation and support systems. Ideally, a system of teacher evaluation and support would increase teacher quality by improving individual teachers’ performance and enhancing average teacher achievement through the selective retention of effective teachers and deselection of ineffective teachers. There exists a limited set of evidence to support this theory of action, all from well-established and rigorous evaluation and support systems that include several observations of teacher practice, the use of achievement-based measures of student achievement and the attachment of high-stakes personnel decisions to teacher performance and improvement (Dee & Wyckoff 2013; Steinberg & Sartain, 2015; Taylor & Tyler, 2012). However, with the onset of new federal and state requirements that relax requirements for states and districts to implement rigorous multiple measure teacher evaluation and support systems, many district systems have shifted focus and today look quite different than the “first wave” systems studied in the past.

In this paper we examine the Los Angeles Unified School District’s (LAUSDs) new teacher evaluation system, the Educator Development and Support: Teachers (EDST), and its impact on the quality of the teacher labor force within the district. The EDST is a relevant case of a new “second wave” teacher evaluation and support system, based primarily on principals’ observations of teachers’ practice (teachers are observed once a year, and less frequently than under first wave systems) and assessments of teachers’ contributions to professional practice. Teachers’ contributions to student achievement on standardized tests are not included in EDST’s multiple measures. We utilize a panel of linked student and teacher-level administrative data that includes student, school, and teacher characteristics, including indicators of teachers’ EDST participation and performance. To identify the impact of EDST participation on student performance, we use teacher fixed effects models to examine whether teacher performance changed as a result of participation in EDST during its first three years of scale-up (2013-14 to 2015-16). To estimate the relationship between EDST participation and selective teacher retention, we use multinomial logistic regression predicting teacher retention within the same school and within LAUSD in the three years following EDST evaluation, controlling for teacher and school characteristics.

We find evidence that the primary impact of EDST on teacher quality occurs through its influence on teacher attrition and retention. Specifically, teachers with higher observational ratings are more likely to be retained within LAUSD in the three years following participation than lower performing teachers. However, participation in EDST does not appear to impact teacher’s contributions to student learning in either the year of participation or during the following two years. Considered together, these results suggest that EDST-style evaluations can influence the distribution of teacher quality primarily through greater retention of higher quality teachers rather than through improvement in the existing labor force.