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Educator preparation, professional development, performance and evaluation
Counselors are a common school resource for students navigating complicated and con- sequential education choices. I estimate counselors’ causal effects using quasi-random assignment policies in Massachusetts. Counselors vary substantially in their effectiveness at increasing high school graduation and college attendance, selectivity, and persistence. Counselor effects on educational attainment are similar in magnitude to teacher effects, but they flow through improved information and assistance more than cognitive or non-cognitive skill development. Counselor effectiveness is most important for low-income and low-achieving students, so improving access to effective counseling may be a promising way to increase educational attainment and close socioeconomic gaps in education.
Teachers are critical to student learning, but adequately staffing classrooms has been challenging in many parts of the country. Even though teacher shortages are being reported across the U.S., teacher shortages are poorly understood. Determining and addressing teacher shortages is difficult due to the lack of data. Neither the federal government nor the majority of states have provided sufficient information on teacher shortages. To address this gap, we systematically examine news reports, department of education data, and publicly-available information on teacher shortages for every state in the U.S. We find there are at least 36,000 vacant positions along with at least 163,000 positions being held by underqualified teachers, both of which are conservative estimates of the extent of teacher shortages nationally. We discuss the implications of our findings for a robust data system, including more specific and consistent reporting of shortage, as well as implications for teacher preparation and education in the United States.
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource intensive in most educational contexts. We develop an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage teaching practice that supports dialogic instruction and makes students feel heard. We conduct a randomized controlled trial as part of an online computer science course, Code in Place (n=1,136 instructors), to evaluate the effectiveness of the feedback tool. We find that the tool improves instructors’ uptake of student contributions by 27% and present suggestive evidence that our tool also improves students’ satisfaction with the course and assignment completion. These results demonstrate the promise of our tool to complement existing efforts in teachers’ professional development.
In recent decades, U.S. education leaders have advocated for more intellectually ambitious mathematics instruction in classrooms. Evidence about whether more ambitious mathematics instruction has filtered into contemporary classrooms, however, is largely anecdotal. To address this issue, we analyzed 93 lessons recorded by a national random sample of middle school mathematics teachers. We find that lesson quality varies, with the typical lesson containing some elements of mathematical reasoning and sense-making, but also teacher-directed instruction with limited student input. Lesson quality correlates with teachers’ use of a textbook and with teachers’ mathematical background. We consider these findings in light of efforts to transform U.S. mathematics instruction.
School principals are viewed as critical mechanisms by which to improve student outcomes, but there remain important methodological questions about how to measure principals' effects. We propose a framework for measuring principals' contributions to student outcomes and apply it empirically using data from Tennessee, New York City, and Oregon. We find that using contemporaneous student outcomes to assess principal performance is flawed. Value-added models misattribute to principals changes in student performance caused by factors that principals minimally control. Further, little to none of the variation in average student test scores or attendance is explained by persistent effectiveness differences between principals.
Teachers are the most important school-specific factor in student learning. Yet, little evidence exists linking teacher professional learning programs and the various strategies or components that comprise them to student achievement. In this paper, we examine a teacher fellowship model for professional learning designed and implemented by Leading Educators, a national nonprofit organization that aims to bridge research and practice to improve instructional quality and accelerate learning across school systems. During the 2015-16 and 2016-17 school years, Leading Educators conducted its fellowship program for teachers and school leaders to provide educators ongoing, collaborative, job-embedded professional development and to improve student achievement. Relying on quasi-experimental methods, we find that a school’s participation in the fellowship model increased student proficiency rates in math and English language arts on state achievement exams. Further, student achievement benefitted from a more sustained duration of teacher participation in the fellowship model, and the impact on student achievement varied depending on the share of a school’s teachers who participated in the fellowship model and the extent to which teachers independently selected into the fellowship model or were appointed to participate by school leaders. Taken together, findings from this paper should inform professional learning organizations, schools, and policymakers on the design, implementation and impact of teacher professional learning.
The pursuit of multiple educational outcomes makes teaching a complex craft subject to potential conflicts and competing commitments. Using a dataset in which teachers were randomly assigned to students paired with videotapes of instruction, we both document and unpack such a tradeoff. Upper-elementary teachers who excel at raising students’ math test scores often are less successful at improving student-reported engagement in class (and vice versa). Further, the teaching practices that improve math test scores (e.g., cognitively demanding content) can simultaneously decrease engagement. At the same time, paired quantitative and qualitative analyses reveal two areas of practice that support both outcomes: active mathematics with opportunities for hands-on participation; and established routines and procedures to proactively organize the classroom environment. In addition to guiding practice-based teacher education, our mixed-methods analysis can serve as a model for rigorously studying and identifying dimensions of “good” teaching that promote multidimensional student development.
We examine the dynamic nature of student-teacher match quality by studying the effect of having a teacher for more than one year. Using data from Tennessee and panel methods, we find that having a repeat teacher improves achievement and decreases absences, truancy, and suspensions. These results are robust to a range of tests for student and teacher sorting. High-achieving students benefit most academically and boys of color benefit most behaviorally. Effects increase with the share of repeat students in a class suggesting that classroom assignment policies intended to promote sustained student-teacher relationships such as looping may have even larger benefits.
This study introduces the signal weighted teacher value-added model (SW VAM), a value-added model that weights student-level observations based on each student’s capacity to signal their assigned teacher’s quality. Specifically, the model leverages the repeated appearance of a given student to estimate student reliability and sensitivity parameters, whereas traditional VAMs represent a special case where all students exhibit identical parameters. Simulation study results indicate that SW VAMs outperform traditional VAMs at recovering true teacher quality when the assumption of student parameter invariance is met but have mixed performance under alternative assumptions of the true data generating process depending on data availability and the choice of priors. Evidence using an empirical data set suggests that SW VAM and traditional VAM results may disagree meaningfully in practice. These findings suggest that SW VAMs have promising potential to recover true teacher value-added in practical applications and, as a version of value-added models that attends to student differences, can be used to test the validity of traditional VAM assumptions in empirical contexts.