As many states are slated to soon use scores derived from classroom observation instruments in high-stakes decisions, developers must cultivate methods for improving the functioning of these instruments. We show how multidimensional, multilevel item response theory models can yield information critical for improving the performance of observational instruments.
We extend this line of research by investigating teacher career and background characteristics, personal resources, and school and district resources that predict an array of instructional practices identified on a mathematics-specific observational instrument, MQI, and a general instrument, CLASS. To understand these relationships, we use correlation and regression analyses. For a subset of teachers for whom we have data from multiple school years, we exploit within-teacher, cross-year variation to examine the relationship between class composition and instructional quality that is not confounded with the sorting of "better" students to "better" teachers. We conclude that multiple teacher- and school-level characteristics--rather than a single factor--are related to teachers' classroom practices.
Although wide variation in teacher effectiveness is well established, much less is known about differences in teacher improvement over time. We document that average returns to teaching experience mask large variation across individual teachers, and across groups of teachers working in different schools. We examine the role of school context in explaining these differences using a measure of the professional environment constructed from teachers’ responses to state-wide surveys. Our analyses show that teachers working in more supportive professional environments improve their effectiveness more over time than teachers working in less supportive contexts. On average, teachers working in schools at the 75th percentile of professional environment ratings improved 38% more than teachers in schools at the 25th percentile after ten years.
Using data from elementary mathematics teachers, we examine the correspondence between self-reports and observational measures of two instructional dimensions--reform-orientation and classroom climate--and the relative ability of these measures to predict teachers' contributions to student learning.
In this study, we use value-added scores and video data in order to mount an exploratory study of high- and low-VAM teachers' instruction. Specifically, we seek to answer two research questions: First, can expert observers of mathematics instruction distinguish between high- and low-VAM teachers solely by observing their instruction? Second, what instructional practices, if any, consistently characterize high but not low-VAM teacher classrooms? To answer these questions, we use data generated by 250 fourth- and fifth-grade math teachers and their students in four large public school districts.Preliminary analyses indicate that a teacher's value-added rank was often not obvious to this team of expert observers.
This paper combines information from classroom-based observations and measures of teachers’ ability to improve student achievement as a step toward addressing the challenge of identifying effective teachers and teaching practices. The authors find that classroom-based measures of teaching effectiveness are related in substantial ways to student achievement growth. The authors conclude that the results point to the promise of teacher evaluation systems that would use information from both classroom observations and student test scores to identify effective teachers. Information on the types of practices that are most effective at raising achievement is also highlighted.
In this paper, the authors propose that an important determinant of value-added model choice should be alignment with alternative indicators of teacher and teaching quality. Such alignment makes sense from a theoretical perspective because better alignment is thought to indicate more valid systems. To provide initial evidence on this issue, they first calculated value-added scores for all fourth and fifth grade teachers within four districts, then extracted scores for 160 intensively studied teachers.Initial analyses using a subset of alternative indicators suggest that alignment between value-added scores and alternative indicators differ by model, though not significantly.
Educational interventions are often evaluated and compared on the basis of their impacts on test scores. Decades of research have produced two empirical regularities: interventions in later grades tend to have smaller effects than the same interventions in earlier grades, and the test score impacts of early educational interventions almost universally “fade out” over time. This paper explores whether these empirical regularities are an artifact of the common practice of rescaling test scores in terms of a student’s position in a widening distribution of knowledge. If a standard deviation in test scores in later grades translates into a larger difference in knowledge, an intervention’s effect on normalized test scores may fall even as its effect on knowledge does not. We evaluate this hypothesis by fitting a model of education production to correlations in test scores across grades and with college-going using both administrative and survey data. Our results imply that the variance in knowledge does indeed rise as children progress through school, but not enough for test score normalization to fully explain these empirical regularities.
Researchers have identified many characteristics of teachers and teaching that contribute to student outcomes. However, most studies investigate only a small number of these characteristics, likely underestimating the overall contribution. In this paper, we use a set of 28 teacher-level predictors drawn from multiple research traditions to explain teacher-level variation in student outcomes. These predictors collectively explain 28% of teacher-level variability in state standardized math test scores and 40% in a predictor-aligned math test. In addition, each individual predictor explains only a small, relatively unique portion of the total teacher-level variability. This first finding highlights the importance of choosing predictors and outcomes that are well aligned, and the second suggests that the phenomena underlying teacher effects is multidimensional.
The National Board for Professional Teaching Standards (NBPTS) assesses teaching practice based on videos and essays submitted by teachers. For this study, the authors compared the performance of classrooms of elementary students in Los Angeles randomly assigned to NBPTS applicants and to comparison teachers. The authors conclude that students assigned to highly-rated applicants outperformed those in the comparison classrooms by more than those assigned to poorly-rated teachers. Moreover, the estimates with and without random assignment were similar.
Center researchers John Papay, Martin West, Jon Fullerton, and Thomas Kane investigate the effectiveness of the Boston Teacher Residency (BTR) in their working paper Does Practice-Based Teacher Preparation Increase Student Achievement? Early Evidence from the Boston Teacher Residency. BTR is an innovative practice-based preparation program in which candidates work alongside a mentor teacher for a year before becoming a teacher of record in Boston Public Schools.