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Novice teachers improve substantially in their first years on the job, but we know remarkably little about the nature of this skill development. Using data from Tennessee, we leverage a feature of the classroom observation protocol that asks school administrators to identify an item on which the teacher should focus their improvement efforts. This “area of refinement” overcomes a key measurement challenge endemic to inferring from classroom observation scores the development of specific teaching skills. We show that administrators disproportionately identify two teaching skills when observing novice teachers: classroom management and presenting content. Struggling with classroom management, in particular, is linked to high rates of novice teacher attrition. Among those who remain, we observe subsequent improvement in these skills.
Does student-teacher match quality exist? Prior work has documented large disparities in teachers' impacts across student types but has not distinguished between sorting and causal effects as the drivers of these disparities. I propose a disparate value-added model and derive a novel measure of teacher quality---revealed comparative advantage---that captures the degree to which teachers affect student outcome gaps. Quasi-experimental changes in teaching staff show that the comparative advantage measure accurately predicts teachers’ disparate impacts: a teacher with a 1 standard deviation in revealed comparative advantage for black students increases black students' test scores by 1 standard deviation and has no effect on non-black students' test scores. Teacher removal and teacher-to-classroom re-allocation simulations show substantial efficiency and equity gains of considering teachers’ comparative advantage.
Targeted instruction is one of the most effective educational interventions in low- and middle-income countries, yet reported impacts vary by an order of magnitude. We study this variation by aggregating evidence from prior randomized trials across five contexts, and use the results to inform a new randomized trial. We find two factors explain most of the heterogeneity in effects across contexts: the degree of implementation (intention-to-treat or treatment-on-the-treated) and program delivery model (teachers or volunteers). Accounting for these implementation factors yields high generalizability, with similar effect sizes across studies. Thus, reporting treatment-on-the-treated effects, a practice which remains limited, can enhance external validity. We also introduce a new Bayesian framework to formally incorporate implementation metrics into evidence aggregation. Results show targeted instruction delivers average learning gains of 0.42 SD when taken up and 0.85 SD when implemented with high fidelity. To investigate how implementation can be improved in future settings, we run a new randomized trial of a targeted instruction program in Botswana. Results demonstrate that implementation can be improved in the context of a scaling program with large causal effects on learning. While research on implementation has been limited to date, our findings and framework reveal its importance for impact evaluation and generalizability.
The impact of test-optional college admissions policies depends on whether applicants act strategically in disclosing test scores. We analyze individual applicants’ standardized test scores and disclosure behavior to 50 major US colleges for entry in fall 2021, when Covid-19 prompted widespread adoption of test-optional policies. Applicants withheld low scores and disclosed high scores, including seeking admissions advantages by conditioning their disclosure choices on their other academic characteristics, colleges’ selectivity and testing policy statements, and the Covid-related test access challenges of the applicants’ local peers. We find only modest differences in test disclosure strategies by applicants’ race and socioeconomic characteristics.
Public schools are currently a source of major political conflict, specifically with regard to issues related to LGBT representation in the curriculum. We report on a large nationally representative survey of American households focusing on their views on what LGBT topics are and should be taught, and what LGBT-themed books should be assigned and available. We report results overall and broken down by demographic, partisan, and geographic variables. We find that Americans report that they largely do not know what topics are being taught in schools, but they do not think LGBT topics are being taught to elementary children. There is widespread opposition to teaching about LGBT issues in elementary school, with more mixed support in high school. Voters are much more opposed to LGBT-themed books being assigned to students than available to them. There are very large splits in attitudes toward LGBT issues in schools, especially along political and religious lines and across states and counties based on partisan lean. We discuss implications of these findings for education policy and urge greater understanding of Americans' views about controversial topics in the curriculum.
Prior research has clearly established the substantial expected payoffs to investments in early childhood education. However, the ability to deliver early childhood programs differs across communities with access to high quality programing especially hard to establish in rural communities. We study one program, Early Steps to School Success, to understand whether the provision of home visiting and book exchange programs in rural Kentucky can influence kindergarten readiness. Linking program data with the state longitudinal data system in Kentucky we create multiple comparison groups by matching children on known program qualification indicators to estimate whether Early Steps program participation was related to school readiness. Our estimates suggest that program participation resulted in small improvements to children’s kindergarten readiness, as measured by the Brigance kindergarten readiness assessment overall score and sub-scores in language, cognitive, and physical development. Results are not sensitive to our choice of comparison group, though they appear driven by the experiences of children who participate from birth through age five or from ages three-to-five only. Our findings suggest that the Early Steps home visiting intervention may be a worthwhile intervention for improving kindergarten preparedness for children living in rural contexts.
We investigated the effectiveness of a sustained and spiraled content literacy intervention that emphasizes building domain and topic knowledge schemas and vocabulary for elementary-grade students. The Model of Reading Engagement (MORE) intervention underscores thematic lessons that provide an intellectual structure for helping students connect new learning to a general schema in Grade 1 (animal survival), Grade 2 (scientific investigation of past events like dinosaur mass extinctions), and Grade 3 (scientific investigation of living systems). A total of 30 elementary schools (N = 2,870 students) were randomized to a treatment or control condition. In the treatment condition (i.e., full spiral curriculum), students participated in MORE content literacy lessons from Grades 1 to 3 during the school year and wide reading of thematically related informational texts in the summer following Grades 1 and 2. In the control condition (i.e., partial spiral curriculum), students participated in MORE lessons in only Grade 3. The Grade 3 lessons for both conditions were implemented online during the COVID-19 pandemic school year. Results reveal that treatment students outperformed control students on science vocabulary knowledge across all three grades. Furthermore, we found positive transfer effects on Grade 3 science reading (ES = .14), domain-general reading comprehension (ES = .11), and mathematics achievement (ES = .12). Treatment impacts were sustained at 14-month follow-up on Grade 4 reading comprehension (ES = .12) and mathematics achievement (ES = .16). Findings indicate that a content literacy intervention that spirals topics and vocabulary across grades can improve students’ long-term academic achievement outcomes.
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.
‘QuantCrit’ (Quantitative Critical Race Theory) is a rapidly developing approach that seeks to challenge and improve the use of statistical data in social research by applying the insights of Critical Race Theory. As originally formulated, QuantCrit rests on five principles; 1) the centrality of racism; 2) numbers are not neutral; 3) categories are not natural; 4) voice and insight (data cannot ‘speak for itself); and 5) a social justice/equity orientation (Gillborn et al, 2018). The approach has quickly developed an international and interdisciplinary character, including applications in medicine (Gerido, 2020) and literature (Hammond, 2019). Simultaneously, there has been ferocious criticism from detractors outraged by the suggestion that numbers are anything other than objective and scientific (Airaksinen, 2018). In this context it is vital that the approach establishes some common understandings about good practice; in order to sustain rigor, make QuantCrit accessible to academics, practioners, and policymakers alike, and resist widespread attempts to over-simplify and pillory. This paper is intended to advance an iterative process of expanding and clarifying how to ‘QuantCrit’.