Educator preparation, professional development, performance and evaluation

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.

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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.

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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.

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While a growing body of literature has documented the negative impacts of exclusionary punishments, such as suspensions, on academic outcomes, less is known about how teachers vary in disciplinary behaviors and the attendant impacts on students. We use administrative data from North Carolina elementary schools to examine the extent to which teachers vary in their use of referrals and investigate the impact of more punitive teachers on student attendance and achievement. We also estimate the effect of teachers' racial bias in the use of referrals on student outcomes. We find more punitive teachers increase student absenteeism and reduce student achievement. Moreover, more punitive teachers negatively affect the achievement of students who do not receive disciplinary sanctions from the teacher. Similarly, while teachers with racial bias in the use of referrals do not negatively affect academic outcomes for White students, they significantly increase absenteeism and reduce achievement for Black students. We find the negative effects of both more punitive and more biased teachers persist into middle school and beyond. The results suggest punitive disciplinary measures do not aid teachers in productively managing classrooms; rather, teachers taking more punitive stances may undermine student engagement and learning in both the short- and long- run. Furthermore, bias in teachers' referral usage contributes to inequities in student outcomes.

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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.

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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.

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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.

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Growing literature documents the promise of active learning instruction in engaging students in college classrooms. Accordingly, faculty professional development (PD) programs on active learning have become increasingly popular in postsecondary institutions; yet, quantitative evidence on the effectiveness of these programs is limited. Using administrative data and an individual fixed effects approach, we estimate the effect of an active learning PD program on student performance and persistence at a large public institution. Findings indicate that the training improved subsequent persistence in the same field. Using a subset of instructors whose instruction was observed by independent observers, we identify a positive association between training and implementation of active learning teaching practices. These findings provide suggestive evidence that active learning PD has the potential to improve student outcomes. 

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The unprecedented challenges of teaching during COVID-19 prompted fears of a mass exodus from the profession. We examine the extent to which these fears were realized using administrative records of Massachusetts teachers between 2015-16 and 2021-22. Relative to pre-pandemic levels, average turnover rates were similar going into the fall of 2020 but increased by 17 percent going into the fall of 2021. The fall 2021 increases were particularly high among newly hired teachers (31 percent increase), but were lower among Black and Hispanic/Latinx teachers (5 percent increases among both groups). Ethnoracial diversity of new hires increased during the pandemic, in part due to reduced professional licensure requirements. Together, these changes led to small increases in the overall ethnoracial diversity of Massachusetts teachers, but improvements to early-career retention will be needed to ensure long-term stability and diversity within the workforce.

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Instructional coaching is an attractive alternative to one-size-fits-all teacher training and development in part because it is purposefully differentiated: programming is aligned to individual teachers’ needs and implemented by an individual coach. But, how much of the benefit of coaching as an instructional improvement model depends on the specific coach with whom a teacher works? Collaborating with a national teacher training and development organization, TNTP, we find substantial variability in effectiveness across coaches in terms of changes in teachers’ classroom practice (0.43 standard deviations). The magnitude of coach effectiveness heterogeneity is close to average coaching program effects identified in other research. These findings suggest that identifying, recruiting, and supporting highly skilled coaches will be key to scaling instructional coaching programs.

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