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Educator preparation, professional development, performance and evaluation
We develop a unifying conceptual framework for understanding and predicting teacher shortages at the state, region, district, and school levels. We then generate and test hypotheses about geographic and subject variation in teacher shortages using data on unfilled teaching positions in Tennessee during the fall of 2019. We find that teacher staffing challenges are highly localized, causing shortages and surpluses to coexist. Aggregate descriptions of staffing challenges mask considerable variation between schools and subjects within districts. Schools with fewer local early-career teachers, smaller district salary increases, worse working conditions, and higher historical attrition rates have higher vacancy rates. Our findings illustrate why viewpoints about, and solutions to, shortages depend critically on whether one takes an aggregate or local perspective.
Teachers’ attitudes and classroom management practices critically affect students’ academic and behavioral outcomes, contributing to the persistent issue of racial disparities in school discipline. Yet, identifying and improving classroom management at scale is challenging, as existing methods require expensive classroom observations by experts. We apply natural language processing methods to elementary math classroom transcripts to computationally measure the frequency of teachers’ classroom management language in instructional dialogue and the degree to which such language is reflective of punitive attitudes. We find that the frequency and punitiveness of classroom management language show strong and systematic correlations with human-rated observational measures of instructional quality, student and teacher perceptions of classroom climate, and student academic outcomes. Our analyses reveal racial disparities and patterns of escalation in classroom management language. We find that classrooms with higher proportions of Black students experience more frequent and more punitive classroom management. The frequency and punitiveness of classroom management language escalate over time during observations, and these escalations occur more severely for classrooms with higher proportions of Black students. Our results demonstrate the potential of automated measures and position everyday classroom management interactions as a critical site of intervention for addressing racial disparities, preventing escalation, and reducing punitive attitudes.
We document that recent generations of elementary school teachers are significantly more effective in raising student test scores than those from earlier generations. Measuring teachers’ value-added for Black and white students separately, the improvements in teaching for Black students are significantly larger than those seen for white students. The race-specific improvements in teacher quality are driven by white teachers. Analyses of mechanisms suggest that changing teachers’ biases may be one potential channel. Our results suggest reason for optimism since these teacher quality differences should lead to improved student learning and a narrowing of the Black-white test score gap over time.
The US teaching force remains disproportionately white while the student body grows more diverse. It is therefore important to understand how and under what conditions white teachers learn racial competency. This study applies a mixed-methods approach to investigate the hypothesis that Black peers improve white teachers’ effectiveness when teaching Black students. The quantitative portion of this study relies on longitudinal data from North Carolina to show that having a Black same-grade peer significantly improves the achievement and reduces the suspension rates of white teachers’ Black students. These effects are persistent over time and largest for novice teachers. Qualitative evidence from open-ended interviews of North Carolina public school teachers reaffirms these findings. Broadly, our findings suggest that the positive impact of Black teachers’ ability to successfully teach Black students is not limited to their direct interaction with Black students but is augmented by spillover effects on early-career white teachers, likely through peer learning.
Improving school quality in low and middle income countries (LMICs) is a global priority. One way to improve quality may be to improve the management skills of school leaders. In this systematic review, we analyze the impact of interventions targeting school leaders' management practices on student learning. We begin by describing the characteristics and responsibilities of school leaders using data from large, multi-country surveys. Second, we review the literature and conduct a meta-analysis of the causal effect of school management interventions on student learning, using 39 estimates from 20 evaluations. We estimate a statistically significant improvement in student learning of 0.04 standard deviations. We show that effect sizes are not related to program scale or intensity. We complement the meta-analysis by identifying common limitations to program effectiveness through a qualitative assessment of the studies included in our review. We find three main factors which mitigate program effectiveness: 1) low take-up; 2) lack of incentives or structure for implementation of recommendations; and 3) the lengthy causal chain linking management practices to student learning. Finally, to assess external validity of our review, we survey practitioners to compare characteristics between evaluated and commonly implemented programs. Our findings suggest that future work should focus on generating evidence on the marginal effect of common design elements in these interventions, including factors that promote school leader engagement and accountability.
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive paper examines preservice teachers' (PST) expressed motivation for pursuing a teaching career and its relationship with PST characteristics and outcomes. Using data from one of the largest teacher education programs in Texas, we use a natural language processing algorithm to categorize into topical groups roughly 2,800 essay responses to the prompt, "Explain why you decided to become a teacher.'' We identify 11 topics that largely reflect altruistic and intrinsic (though not extrinsic) reasons for teaching. The frequency of motivation topics varied substantially by PST gender, race/ethnicity, and certification area. While topics collectively explained little of the variance in PST outcomes, we found preliminary evidence that intrinsic enjoyment of teaching and prior experiences with adversity predicted higher performance during clinical teaching and lower attrition as a full-time K–12 teacher.
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage dialogic teaching practice that makes students feel heard. We conduct a randomized controlled trial in an online computer science course (n=1,136 instructors), to evaluate the effectiveness of our tool. We find that M-Powering Teachers improves instructors’ uptake of student contributions by 13% and present suggestive evidence that it also improves students’ satisfaction with the course and assignment completion. These results demonstrate the promise of M-Powering Teachers to complement existing efforts in teachers’ professional development.
The debate on the stringency of licensure exams for prospective public school teachers is on-going, including the recent controversial roll-out of the educative Teacher Performance Assessment (edTPA). We leverage the quasi-experimental setting of different adoption timing by states and analyze multiple data sources containing a national sample of prospective teachers and students of new teachers in the US. With extensive controls of concurrent policies, we find that the edTPA reduced prospective teachers in undergraduate programs, less-selective and minority-concentrated universities. Contrary to the policy intention, we do not find evidence that edTPA increased student test scores.
Teachers are the most important school-specific factor in student learning. Yet, little evidence exists linking teacher professional development programs and the strategies or activities that comprise them to student achievement. In this paper, we examine a fellowship model for professional development 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 two cohorts of teachers and school leaders to provide these 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 program significantly increased student proficiency rates in English language arts and math on state achievement exams. Student achievement benefitted from a more sustained duration of participation in the fellowship program, varied depending on the share of a school’s educators who participated in the fellowship, and differed based on whether fellows independently selected into the program or were appointed to participate by their school leaders. Taken together, findings from this paper should inform professional learning organizations, schools, and policymakers on the design, implementation, and impact of educator professional development.
This is one of the first studies of the mismatch between students’ test scores and teachers’ estimations of those scores in low- and middle-income countries. Prior studies in high-income countries have found strong correlations between these metrics. We leverage data on actual and estimated scores in math and language from India and Bangladesh and find that teachers misestimate their students’ scores and that their estimations reveal their misconceptions about students in most need of support and variability within their class. This pattern is partly explained by teachers’ propensity to overestimate the scores of low-achieving students and to overweight the importance of intelligence. Teachers seem unaware of their errors, expressing confidence in estimations and surprise about their students’ performance once revealed.