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Standards, accountability, assessment, and curriculum
The COVID-19 pandemic has put virtual schooling at the forefront of policy concerns, as millions of children worldwide shift to virtual schooling with hopes of “slowing the spread”. Given the emergency shift to online education coupled with the large increase in demand for virtual education over the last decade it is imperative to explore the impacts of virtual education on student outcomes. This paper estimates the causal effect of full-time virtual school attendance on student outcomes with important implications for school choice, online education, and education policy. Despite the increasing demand for K-12 virtual schools over the past decade little is known about the impact of full-time virtual schools on students’ cognitive and behavioral outcomes. The existing evidence on the impact of online education on students’ outcomes is mixed. I use a longitudinal data set composed of individual-level information on all public-school students and teachers throughout Georgia from 2007 to 2016 to investigate how attending virtual schools influences student outcomes. I implement a variety of econometric specifications to account for the issue of potential self-selection into full-time virtual schools. I find that attending a virtual school leads to a reduction of 0.1 to 0.4 standard deviations in English Language Arts, Mathematics, Science, and Social Studies achievement test scores for students in elementary and middle school. I also find that ever attending a virtual school is associated with a 10-percentage point reduction in the probability of ever graduating from high school. This is early evidence that full-time virtual schools as a type of school choice could be harmful to students’ learning and future economic opportunities, as well as a sub-optimal use of taxpayer money.
Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers, but conventional classroom observations are costly, prone to rater bias, and hard to implement at scale. Using nearly 1,000 word-to-word transcriptions of 4th- and 5th-grade English language arts classes, we apply novel text-as-data methods to develop automated, objective measures of teaching to complement classroom observations. This approach is free of rater bias and enables the detection of three instructional factors that are well aligned with commonly used observation protocols: classroom management, interactive instruction, and teacher-centered instruction. The teacher-centered instruction factor is a consistent negative predictor of value-added scores, even after controlling for teachers’ average classroom observation scores. The interactive instruction factor predicts positive value-added scores.
While teacher evaluation policies have been central to efforts to enhance teaching quality over the past decade, little is known about how teachers change their instructional practices in response to such policies. To address this question, this paper drew on classroom observation and survey data to examine how early career teachers’ (ECTs’) perceptions of pressure associated with teacher evaluation policies seemed to affect their enactment of ambitious mathematics instruction. As part of our analysis, we also considered the role that mathematical knowledge for teaching (MKT) and school norms regarding teaching mathematics shape the potential influence of teacher evaluation policies on ECTs’ instructional practices. Understanding how the confluence of these factors is associated with teachers’ instruction provides important insights into how to improve teaching quality, which is one of the most important inputs for student learning.
With 55 million students in the United States out of school due to the COVID-19 pandemic, education systems are scrambling to meet the needs of schools and families, including planning how best to approach instruction in the fall given students may be farther behind than in a typical year. Yet, education leaders have little data on how much learning has been impacted by school closures. While the COVID-19 learning interruptions are unprecedented in modern times, existing research on the impacts of missing school (due to absenteeism, regular summer breaks, and school closures) on learning can nonetheless inform projections of potential learning loss due to the pandemic. In this study, we produce a series of projections of COVID-19-related learning loss and its potential effect on test scores in the 2020-21 school year based on (a) estimates from prior literature and (b) analyses of typical summer learning patterns of five million students. Under these projections, students are likely to return in fall 2020 with approximately 63-68% of the learning gains in reading relative to a typical school year and with 37-50% of the learning gains in math. However, we estimate that losing ground during the COVID-19 school closures would not be universal, with the top third of students potentially making gains in reading. Thus, in preparing for fall 2020, educators will likely need to consider ways to support students who are academically behind and further differentiate instruction.
Castañeda v. Pickard (1981) mandated that educational programs for emergent bilinguals be tested for program efficacy. Since English language development (ELD) curricular materials are one part of an instructional program, we assess this mandate by examining the effectiveness of ELD materials in Texas. Using local linear matching, we find that schools that do not purchase any ELD curricula have significantly lower English language proficiency scores relative to schools that purchase state-adopted ELD materials. These results are robust across various matching models—inverse probability weights with regression adjustment, kernel matching, and nearest neighbor matching--and a comparative interrupted time series design. There is no significant difference between schools that adopt the two most popular ELD curricula—Rigby On Our Way to English and National Geographic Reach. This study suggests that emergent bilinguals (EBs) who attend schools that have instructional materials that explicitly foreground English language proficiency standards outperform those in schools that do not have such materials.
After increasing in the 1970s and 1980s, time to bachelor’s degree has declined since the 1990s. We document this fact using data from three nationally representative surveys. We show that this pattern is occurring across school types and for all student types. Using administrative student records from 11 large universities, we confirm the finding and show that it is robust to alternative sample definitions. We discuss what might explain the decline in time to bachelor’s degree by considering trends in student preparation, state funding, student enrollment, study time, and student employment during college.
Important educational policy decisions, like whether to shorten or extend the school year, often require accurate estimates of how much students learn during the year. Yet, related research relies on a mostly untested assumption: that growth in achievement is linear throughout the entire school year. We examine this assumption using a data set containing math and reading test scores for over seven million students in kindergarten through 8th grade across the fall, winter, and spring of the 2016-17 school year. Our results indicate that assuming linear within-year growth is often not justified, particularly in reading. Implications for investments in extending the school year, summer learning loss, and racial/ethnic achievement gaps are discussed.
High school graduation rates have increased dramatically in the past two decades. Some skepticism has arisen, however, because of the confluence of the graduation rise and the starts of high-stakes accountability for graduation rates with No Child Left Behind (NCLB). In this study we provide some of the first evidence about the role of accountability versus strategic behavior, especially the degree to which the recent graduation rate rise represents increased human capital. First, using national DD analysis of within-state, cross-district variation in proximity to state graduation rate thresholds, we confirm that NCLB accountability increased graduation rates. However, we find limited evidence that this is due to strategic behavior. To test for lowering of graduation standards, we examined graduation rates in states with and without graduation exams and trends in GEDs; neither analysis suggests that the graduation rate rise is due to strategic behavior. We also examined the effects of “credit recovery” courses using Louisiana micro data; while our results suggest an increase in credit recovery, consistent with some lowering of standards, the size of the effect is not nearly enough to explain the rise in graduation rates. Finally, we examine other forms of strategic behavior by schools, though these can only explain inflation of school/district-level graduation rates, not rational rates. Overall, the evidence suggests that the rise in the national graduation rates reflects some strategic behavior, but also a substantial increase in the nation’s stock of human capital. Graduation accountability was a key contributor.
How should schools assign students to more rigorous math courses so as best to help their academic outcomes? We identify several hundred California middle schools that used 7th grade test scores to place students into 8th grade Algebra courses, and use a regression discontinuity design to estimate average impacts and heterogeneity across schools. Enrolling in 8th grade algebra boosts students’ enrollment in advanced math in 9th grade by 30 percentage points and 11th grade by 16 percentage points. Math scores in 10th grade rise by 0.05 standard deviations. Women, students of color, and English-language learners benefit disproportionately from placement into early Algebra. Importantly, the benefits of 8th grade algebra are substantially larger in schools that set their eligibility threshold higher in the baseline achievement distribution. This suggests a potential tradeoff between increased access and rates of subsequent math success.
A huge portion of what we know about how humans develop, learn, behave, and interact is based on survey data. Researchers use longitudinal growth modeling to understand the development of students on psychological and social-emotional learning constructs across elementary and middle school. In these designs, students are typically administered a consistent set of self-report survey items across multiple school years, and growth is measured either based on sum scores or scale scores produced based on item response theory (IRT) methods. While there is great deal of guidance on scaling and linking IRT-based large-scale educational assessment to facilitate the estimation of examinee growth, little of this expertise is brought to bear in the scaling of psychological and social-emotional constructs. Through a series of simulation and empirical studies, we produce scores in a single-cohort repeated measure design using sum scores as well as multiple IRT approaches and compare the recovery of growth estimates from longitudinal growth models using each set of scores. Results indicate that using scores from multidimensional IRT approaches that account for latent variable covariances over time in growth models leads to better recovery of growth parameters relative to models using sum scores and other IRT approaches.