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Standards, accountability, assessment, and curriculum
State testing programs regularly release previously administered test items to the public. We provide an open-source recipe for state, district, and school assessment coordinators to combine these items flexibly to produce scores linked to established state score scales. These would enable estimation of student score distributions and achievement levels. We discuss how educators can use resulting scores to estimate achievement distributions at the classroom and school level. We emphasize that any use of such tests should be tertiary, with no stakes for students, educators, and schools, particularly in the context of a crisis like the COVID-19 pandemic. These tests and their results should also be lower in priority than assessments of physical, mental, and social–emotional health, and lower in priority than classroom and district assessments that may already be in place. We encourage state testing programs to release all the ingredients for this recipe to support low-stakes, aggregate-level assessments. This is particularly urgent during a crisis where scores may be declining and gaps increasing at unknown rates.
A recent literature provides new evidence that school resources are important for student outcomes. In this paper, we show that school finance reform-induced increases in student performance are driven by those states that had test-based accountability policies in place at the time. By incentivizing school improvement, accountability systems (such as the federal No Child Left Behind act) may raise the efficiency with which additional school funding gets spent. Our empirical approach leverages the timing of school finance reforms to compare funding impacts on student test scores between states that had accountability in place at the time of the reform with states that did not. The results indicate that finance reforms are three times more productive in low-income school districts when also accompanied by test-based accountability. These findings shed new light on the role of accountability incentives in education production and the mechanisms supporting the effectiveness of school resources.
The public narrative surrounding efforts to improve low-performing K-12 schools in the U.S. has been notably gloomy. Observers argue that either nothing works or we don’t know what works. At the same time, the federal government is asking localities to implement evidence-based interventions. But what is known empirically about whether school improvement works, how long it takes, which policies are most effective, and which contexts respond best to intervention? We meta-analyze 141 estimates from 67 studies of turnaround policies implemented post-NCLB. On average, these policies have had a moderate positive effect on math but no effect on ELA achievement as measured by high-stakes exams. We find evidence of positive impacts on low-stakes exams in STEM and humanities subjects and no evidence of harm on non-test outcomes. Some elements of reform, namely extended learning time and teacher replacements, predict greater effects. Contexts serving majority-Latinx populations have seen the largest improvements.
Teacher evaluation policies seek to improve student outcomes by increasing the effort and skill levels of current and future teachers. Current policy and most prior research treats teacher evaluation as balancing two aims: accountability and skill development. Proper teacher evaluation design has been understood as successfully weighting the accountability and professional growth dimensions of policy and practice. I develop a model of teacher effectiveness that incorporates improvement from evaluation and detail conditions which determine the effectiveness of teacher evaluation for growth and accountability at improving student outcomes. Drawing on empirical evidence from the personnel economics, economics of education and measurement literatures, I simulate the long-term effects of a set of teacher evaluation policies. I find that those that treat evaluation for accountability and evaluation for growth as substitutes outperform policies that treat them as complements. I conclude that optimal teacher evaluation policies would impose accountability on teachers performing below a defined level and above which teachers would be subject to no accountability pressure but would receive intensive instructional supports.
A common rationale for offering online courses in K-12 schools is that they allow students to take courses not offered at their schools; however, there has been little research on how online courses are used to expand curricular options when operating at scale. We assess the extent to which students and schools use online courses for this purpose by analyzing statewide, student-course level data from high school students in Florida, which has the largest virtual sector in the nation. We introduce a “novel course” framework to address this question. We define a virtual course as “novel” if it is only available to a student virtually, not face-to-face through their own home high school. We find that 7% of high school students in 2013-14 enroll in novel online courses. Novel courses were more commonly used by higher-achieving students, in rural schools, and in schools with relatively few Advanced Placement/International Baccalaureate offerings.
College completion rates declined from the 1970s to the 1990s. We document that this trend has reversed--since the 1990s, college completion rates have increased. We investigate the reasons for the increase in college graduation rates. Collectively, student characteristics, institutional resources, and institution attended do not explain much of the change. However, we show that grade inflation can explain much of the change in graduation rates. We show that GPA is a strong predictor of graduation rates and that GPAs have been rising since the 1990s. We also find that increases in college GPAs cannot be explained by student demographics, ability, and school factors. Further, we find that at a public liberal arts college, grades have increased over time conditional on final exam performance.
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.