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Many states are redesigning their college remediation policies to increase postsecondary degree completion. In 2012, Tennessee began waiving college math remediation for high school students who completed a computer‐based remedial math course (SAILS) during their senior year. Using a regression discontinuity design, we find that the high school remedial course did not improve students' math achievement any more than the typical senior year math course (although it did allow students to avoid the cost and delay of remedial math in college). Using a difference‐in‐difference design, we find that completing SAILS boosted enrollment in college‐level math among first‐year community college students by nearly 30 percentage points, with nearly half of new enrollees passing the college‐level course. Such students had, however, only completed 1.5 additional college courses after two years. In 2015, Tennessee community colleges implemented “co‐requisite” remediation, allowing students to complete remediation alongside college‐level math. Under the co‐requisite policy, completing SAILS no longer produced any boost in college credits. Although both alternatives to pre‐requisite remediation produced modest gains for students and taxpayers, remediation requirements are not a primary driver of low degree completion rates.

Trends in power system simulation that demand computationally-intensive, physics-based models may impede the acquisition of useful results for applications like condition-based maintenance, electrical plant load analysis (EPLA), and the scheduling and tasking of finite generation and distribution resources. A tool that can quickly evaluate many scenarios, as opposed to intense, high fidelity modeling of a single operating scenario, may best serve these applications. This paper presents a behavioral simulator that can quickly emulate the operation of a relatively large collection of electrical loads, providing “what-if” evaluations of various operating scenarios and conditions for more complete exploration of a design or plant operating envelope. The presented simulator can provide time-series data of power system operation under loading conditions and usage assumptions of interest. Comparisons to field data collected from a microgrid on-board a 270-foot (82 meter) US Coast Guard medium-endurance cutter demonstrate the utility of this tool and approach.

Can a school or district improve student achievement simply by switching to a higher‐quality textbook or curriculum? We conducted the first multi‐textbook, multi‐state effort to estimate textbook efficacy following widespread adoption of the Common Core State Standards (CCSS) and associated changes in the textbook market. Pooling textbook adoption and student test score data across six geographically and demographically diverse U.S. states, we found little evidence of differences in average achievement gains for schools using different math textbooks. We found some evidence of greater variation in achievement gains among schools using pre‐CCSS editions, which may have been more varied in their content than post‐CCSS editions because they were written for a broader set of standards. We also found greater variation among schools that had more exposure to a given text. However, these differences were small. Despite considerable interest and attention to textbooks as a low‐cost, “silver bullet” intervention for improving student outcomes, we conclude that the adoption of a new textbook or set of curriculum materials, on its own, is unlikely to achieve this goal.

Teacher evaluation reform has been among the most controversial education reforms in recent years. It also is one of the costliest in terms of the time teachers and principals must spend on classroom observations. We conducted a randomized field trial at four sites to evaluate whether substituting teacher-collected videos for in-person observations could improve the value of teacher observations for teachers, administrators, or students. Relative to teachers in the control group who participated in standard in-person observations, teachers in the video-based treatment group reported that post-observation meetings were more “supportive” and they were more able to identify a specific practice they changed afterward. Treatment principals were able to shift their observation work to noninstructional times. The program also substantially increased teacher retention. Nevertheless, the intervention did not improve students’ academic achievement or self-reported classroom experiences, either in the year of the intervention or for the next cohort of students. Following from the literature on observation and feedback cycles in low-stakes settings, we hypothesize that to improve student outcomes schools may need to pair video feedback with more specific supports for desired changes in practice.

Since 1990, U.S. policymakers have worked to close gaps in academic achievement by income and race (e.g. with school finance reform and school accountability systems) even as rising income inequality and income-based residential segregation have threatened to widen them. Using estimates of the mean and variance in household income for sampled schools, we reconstruct the student-level relationship between achievement and household income in the National Assessment of Educational Progress (NAEP) from 1990 to 2015. We find that achievement at all levels of parental income rose substantially in 4th and 8th grade. In contrast to Reardon (2011), we find that achievement gaps narrowed substantially in 4th grade reading and math and in 8th grade math, while the gaps remained stable in 8th grade reading. As a robustness check, we used the March Current Population survey to impute income for dependent children by race, mother’s education, urbanicity and state and then calculated mean achievement for those same groups in the NAEP. Again, we found gaps in achievement narrowing between groups with high and low predicted mean household incomes. Our results challenge the prevailing understanding that income-based achievement gaps have widened in the United States over the last 30 years.

Nd:YVO4 has a high gain transition at 1.34 μm. It can be q-switched by the saturable absorber Vanadium:YAG, which has quick recovery, enabling repetition rates above 1 MHz. I demonstrated a 1.34 μm laser for LIDAR with 1.08 nsec pulse duration, 24 kHz repetition rate and 1.75 kW peak power, and in another configuration, 4.8 nsec pulse duration, 1.82 MHz repetition rate and 68 W peak power. Several intermediate cases are described as well. These lasers have part-for-part correspondence with green pointer lasers sold for under $5 which are the size of a penlight. The eye-safe class 1 power at 1.34 μm is 1.9 times that allowable in the 1.4-1.6 μm range.

In the 2011–12 school year, the Newark Public School district (NPS) launched a set of educational reforms supported by a gift from Facebook CEO Mark Zuckerberg and Priscilla Chan. Using data from 2008–09 through 2015–16, the authors evaluate the change in Newark students’ achievement growth relative to similar students and schools elsewhere in New Jersey. They measure achievement growth using a “value-added” model, controlling for prior achievement, demographics, and peer characteristics. By the fifth year of reform, Newark saw statistically significant gains in English language arts (ELA) achievement growth and no significant change in math achievement growth. Perhaps because of the disruptive nature of the reforms, growth declined initially before rebounding in later years. Much of the improvement was attributed to shifting enrollment from lower- to higher-growth district and charter schools.

Purpose: U.S. schools have traditionally been characterized by teacher privacy and independence, yet theory and empirical work suggest that peer observation and support—or “de-privatized instruction”—can help improve pedagogical practice. In this study, we investigate whether the introduction of video technology into a school—through a video-based teacher evaluation system called Best Foot Forward (BFF)—led to instructional de-privatization, even in the absence of program components designed to encourage de-privatization. Research Method: Eighty-five schools were randomly assigned to BFF or a control condition. After one school year, teachers and administrators completed Web-based surveys about their experiences. Findings: We find that BFF caused administrators to facilitate more peer support among teachers, made teachers more likely to share lesson videos with colleagues, led teachers to have more of their lessons seen by other teachers, and redistributed which teachers were providing instructional support to colleagues (with relatively newer teachers taking on a larger role in providing peer support). Implications: Results suggest that video technology may be an effective tool for efforts to improve instruction by increasing peer observation and support.

Many U.S. students arrive on college campus lacking the skills expected for college-level work. As state leaders seek to increase postsecondary enrollment and completion, public colleges have sought to lessen the delays created by remedial course requirements. Tennessee has taken a novel approach by allowing students to complete their remediation requirements in high school. Using both a difference-in-differences and a regression discontinuity design, we evaluate the program’s impact on college enrollment and credit accumulation, finding that the program boosted enrollment in college-level math during the first year of college and allowed students to earn a modest 4.5 additional college credits by their second year. We also report the first causal evidence on remediation's impact on students' math skills, finding that the program did not improve students’ math achievement, nor boost students’ chances of passing college math. Our findings cast doubt on the effectiveness of the current model of remediation—whether in high school or college—in improving students’ math skills. They also suggest that the time cost of remediation—whether pre-requisite or co-requisite remediation—is not the primary barrier causing low degree completion for students with weak math preparation.

In the 2011–12 school year, the Newark Public School district (NPS) launched a set of educational reforms supported by a gift from Facebook CEO Mark Zuckerberg and Priscilla Chan. Using data from 2...

There are three primary measures of teaching performance: student test-based measures (i.e., value added), classroom observations, and student surveys. Although all three types of measures could be biased by unmeasured traits of the students in teachers’ classrooms, prior research has largely focused on the validity of value-added measures. We conduct an experiment involving 66 mathematics teachers in four school districts and test the validity of all three types of measures. Specifically, we test whether a teacher’s performance on each measure under naturally occurring (i.e., non-experimental) settings predicts performance following random assignment of that teacher to a class of students. Combining our results with those from two previous experiments, we provide further evidence that value-added measures are unbiased predictors of teacher performance. In addition, we provide the first evidence that classroom observation scores are unbiased predictors of teacher performance on a rubric measuring the quality of mathematics instruction. Unfortunately, we lack the statistical power to reach any similar conclusions regarding the predictive validity of a teacher’s student survey responses.

We study the impact of a public school choice lottery in Charlotte-Mecklenburg schools on college enrollment and degree completion. We find a significant overall increase in college attainment among lottery winners who attend their first-choice school. Using rich administrative data on peers, teachers, course offerings, and other inputs, we show that the impacts of choice are strongly predicted by gains on several measures of school quality. Gains in attainment are concentrated among girls. Girls respond to attending a better school with higher grades and increases in college-preparatory course taking, while boys do not. (JEL D44, H75, I21, I23, J16)

Nearly every state evaluates teacher performance using multiple measures, but evidence has largely shown that only one such measure—teachers’ effects on student achievement (i.e., value-added)—captures teachers’ causal effects. We conducted a random assignment experiment in 66 fourth- and fifth-grade mathematics classrooms to evaluate the predictive validity of three measures of teacher performance: value-added, classroom observations, and student surveys. Combining our results with those from two previous random assignment experiments, we provide additional experimental evidence that value-added measures are unbiased predictors of teacher performance. Though results for the other two measures are less precise, we find that classroom observation scores are predictive of teachers’ performance after random assignment while student surveys are not. These results thus lend support to teacher evaluation systems that use value-added and classroom observations, but suggest practitioners should proceed with caution when considering student survey measures for teacher evaluation.

We have demonstrated a remote magnetometer based on sodium atoms in the Earth's mesosphere, at a 106-kilometer distance from our instrument. A 1.33-watt laser illuminated the atoms, and the magnetic field was inferred from back-scattered light collected by a telescope with a 1.55-meter-diameter aperture. The measurement sensitivity was 162 nT/$\sqrt{Hz}$. The value of magnetic field inferred from our measurement is consistent with an estimate based on the Earth's known field shape to within a fraction of a percent. Projected improvements in optics could lead to sensitivity of 20 nT/$\sqrt{Hz}$, and the use of advanced lasers or a large telescope could approach 1-nT/$\sqrt{Hz}$ sensitivity. All experimental and theoretical sensitivity values are based on a 60$^\circ$ angle between the laser beam axis and the magnetic field vector; at the optimal 90$^\circ$ angle sensitivity would be improved by about a factor of two., 15 pages, 15 figures, 4 tables

The evidence that productivity varies greatly across teachers has given rise to the idea that student achievement data should be included in performance evaluation, despite limited empirical evidence on subjective evaluation or the use of objective performance measures in U.S. public schools. In this paper, we examine the results of a randomized pilot program in which school principals were provided with estimates of the performance of individual teachers in raising their students' test scores in math and English. Our analysis establishes several facts consistent with a simple Bayesian learning model of employee evaluation in the presence of imperfect information. First, objective teacher performance estimates based on student data and principals' prior beliefs are positively correlated, and the strength of this relationship rises with the precision of the objective estimates and the precision of subjective priors. Second, principals who are provided with objective performance data incorporate this information into their posterior beliefs, and do so to a greater extent when the data are more precise and when their priors are less precise. Moreover, after the provision of performance data, the probability of job separation rises for teachers with low performance estimates, and, in line with this change in attrition patterns, student achievement exhibits small improvements the following year. These results suggest that objective performance data provides useful information to principals in constructing employee evaluations and using these evaluations to improve productivity.

Boston Teacher Residency (BTR) is an innovative practice-based preparation program in which candidates work alongside a mentor teacher for a year before becoming a teacher of record in the Boston Public Schools (BPS). The authors found that BTR graduates are more racially diverse than other BPS novices, more likely to teach math and science, and more likely to remain teaching in the district through Year 5. Initially, BTR graduates for whom value-added performance data are available are no more effective at raising student test scores than other novice teachers in English language arts and less effective in math. The effectiveness of BTR graduates in math improves rapidly over time, however, such that by their 4th and 5th years they outperform veteran teachers. Simulations of the program’s overall effect through retention and effectiveness suggest that it is likely to improve student achievement in the district only modestly over the long run.

Many people, experiences and structures contribute to an individual student’s achievement. Increasingly, the contribution of teachers has become a focal point as a number of studies have found large differences in teachers’ effectiveness at increasing student achievement. For example, Robert Gordon, Kane, and Douglas O. Staiger (2006) ranked teachers according to their historical ability to raise student achievement growth and found that students assigned to a top-quartile ranked teacher scored ten percentile points higher on standardized tests of achievement than otherwise similar students assigned a bottom-quartile ranked teacher. Other researchers have found similar-sized variation in teacher effects on student achievement (Jonah E. Rockoff 2004; Steven Rivkin, Eric Hanushek, and John Kain 2005; Daniel Aaronson, Lisa Barrow, and William Sander 2007). Unfortunately, beyond experience in the classroom, little is known about which skills, characteristics, and practices of a teacher cause these observed differences. This knowledge gap curtails the policy and management levers available for creating an effective teacher work force. In this paper we provide initial evidence on the relationship between classroom management and instructional skills and gains in student achievement. We do so using data from the Cincinnati Public School (CPS) system which, Using Student Performance Data to Identify Effective Classroom Practices

The charter school landscape includes a variety of organizational models and a few national franchises. The nation’s largest network of charter schools is the Knowledge is Power Program (KIPP), with 80 schools operating or slated to open soon. KIPP schools target low income and minority students and subscribe to an approach some have called No Excuses (Abigail Thernstrom and Stephen Thernstrom 2003). No Excuses schools feature a long school day and year, selective teacher hiring, strict behavior norms, and encourage a strong student work ethic. KIPP schools have often been central in the debate over whether schools alone can substantially reduce racial achievement gaps. Descriptive accounts of KIPP suggest positive achievement effects (see, e.g., Jay Mathews 2009), but critics argue that the apparent KIPP advantage reflects differences between students who attend traditional public schools and students that choose to attend KIPP schools (see, e.g., Martin Carnoy, Rebecca Jacobsen, Lawrence Mishel, and Richard Rothstein 2005). There are few well-controlled studies of KIPP schools that might help sort out these competing claims, and none that focus on KIPP. This paper reports on a quasi-experimental evaluation of the only KIPP school in New England, KIPP Academy Lynn. KIPP Lynn opened in the fall of 2004 and is the only charter school in Lynn, Mass., a low income city north of

We use six years of data on student test performance to evaluate the effectiveness of certified, uncertified, and alternatively certified teachers in the New York City public schools. On average, the certification status of a teacher has at most small impacts on student test performance. However, among those with the same certification status, there are large and persistent differences in teacher effectiveness. This evidence suggests that classroom performance during the first two years, rather than certification status, is a more reliable indicator of a teacher's future effectiveness. We also evaluate turnover among teachers with different certification status, and the impact on student achievement of hiring teachers with predictably high turnover. Given relatively modest estimates of experience differentials, even high turnover groups (such as Teach for America participants) would have to be only slightly more effective in their first year to offset the negative effects of their high exit rates.

There is little causal evidence on the effect of economic and policy outcomes on voting behavior. This paper uses randomized outcomes from a school choice lottery to examine if lottery outcomes affect voting behavior in a school board election. We show that losing the lottery has no significant impact on overall voting behavior; however, among white families, those with above median income and prior voting history, lottery losers were significantly more likely to vote than lottery winners. Using propensity score methods, we compare the voting of lottery participants to similar families who did not participate in the lottery. We find that losing the school choice lottery caused an increase in voter turnout among whites, while winning the lottery had no effect relative to non-participants. Overall, our empirical results lend support to models of expressive and retrospective voting, where likely voters are motivated to vote by past negative policy outcomes.

We study the relationship between school characteristics and housing prices in Mecklenburg County, North Carolina, between 1994 and 2001. During this period, the school district was operating under a court-imposed desegregation order and drew school boundaries so that students living in the same neighborhoods were often sent to very different schools in terms of racial mix and average test scores of the students. We use differences in housing prices along assignment zone boundaries to disentangle the effect of schools and other neighborhood characteristics. We find systematic differences in house prices along school boundaries although the impact of schools is only one-quarter as large as the naive cross-sectional estimates would imply. Part of the impact of school assignments is mediated by differences in the characteristics of the population and the quality of the housing stock that have arisen on either side of the school assignment boundary.

School choice programs are intended to improve student achievement, by allowing for better matches between students and schools. It is not clear, however, that academic achievement will improve if parents make school choice decisions over both academic and nonacademic school attributes (Justine S. Hastings et al., 2005, 2006). Indeed, many randomized studies of impacts of school choice find little or no effect of school choice on academic outcomes. For example, initial evaluations of randomized voucher experiments in Milwaukee and New York City found modest academic impacts on eligible students (John F. Witte et al., 1995; Daniel P. Mayer et al., 2002). More recently, evaluations of public school choice lotteries in Chicago and Charlotte have found no difference between the average lottery winner and loser in academic outcomes such as test scores (Julie Cullen et al., 2003; Hastings et al., 2006). When parents are choosing schools for academic and nonacademic reasons, school choice may increase utility but not necessarily improve academic outcomes. There is growing evidence that educational interventions may have heterogeneous treatment effects by gender. Analysis of the Moving To Opportunity demonstration, in which parents were randomly given the opportunity to move to nonpoverty neighborhoods, found improvements in education, mental health, and criminal behavior for females, but negative effects on males (Jeffrey R. Kling and Jeffrey B. Liebman, 2004). Similarly, Michael Anderson (2005) reanalyzed data from three randomized trials of early childhood education and found that all of the long-term benefits accrued to girls and not to boys. We use data from a public school choice program, with school assignment by lottery, to estimate the impacts on academic outcomes by race and gender of attending a first-choice school. Our data come from the CharlotteMecklenburg school district (CMS) in North Carolina, which introduced district-wide public school choice in the fall of 2002 after a racebased busing plan was terminated by the courts. The data include students’ choices, lottery numbers, school assignments, demographics, and academic achievement for the years surrounding implementation of school choice. We compare outcomes for those making similar choices, whose school assignment was determined solely by lottery number. Overall, there was no gain in academic achievement for those winning the lottery. White females did experience significant improvements in test scores when randomized into their first choice school, however. White females were also more likely to choose academically focused magnets and, among those who won the lottery, reported significant increases in time spent on homework. Our evidence suggests that school choice programs may have heterogeneous treatment effects by gender, which are related to differences in the factors driving parental choices.

During the past decade, states have constructed elaborate systems for rating the performance of individual schools based on student test scores and then have released this information in the form of school “report cards.” The federal No Child Left Behind Act of 2001 will accelerate that movement by requiring states to test all students in grades three through eight, publicly report each school’s student test performance, and sanction schools when they fail to achieve specific standards. Earlier research has documented the cross-sectional relationship between housing values and student test scores at neighborhood schools. 1 Given the magnitude of the relationship between test scores and housing prices in the cross section, one might expect the release of school report cards to have important effects on housing values and, indirectly, to provide incentives for schools to improve performance. However, there are also reasons to believe that the housing market would downplay the information in school report cards. In particular, school test scores are noisy measures of school performance and may provide homeowners with little new information about which schools are the best ones. 2

In recent years, most states have constructed elaborate accountability systems using school-level test scores. However, because the median elementary school contains only 69 children per grade level, such measures are quite imprecise. We evaluate the implications for school accountability systems. For instance, rewards or sanctions for schools with scores at either extreme primarily affect small schools and provide weak incentives to large ones. Nevertheless, we conclude that accountability systems may be worthwhile. Even in states with aggressive financial incentives, the marginal reward to schools for raising student performance is a small fraction of the potential labor market value for students.

In a widely cited study, Chetty, Friedman, and Rockoff (2014a; hereafter CFR) evaluate the degree of bias in teacher value-added estimates using a novel "teacher switching" research design with data from New York City. They conclude that there is little to no bias in their estimates. Using the same model with data from North Carolina, Rothstein (2014) argued that the CFR research design is invalid, given a relationship between student baseline test scores and teachers' value-added. In this paper, we replicated the CFR analysis using data from the Los Angeles Unified School District and similarly found that teacher value-added estimates were valid predictors of student achievement. We also demonstrate that Rothstein's test does not invalidate the CFR design and instead reflects a mechanical relationship, given that teacher value-added scores from prior years and baseline test scores can be based on the same data. In addition, we explore the (1) predictive validity of value-added estimates drawn from the same, similar, and different schools, (2) an alternative way of estimating differences in access to effective teaching by taking teacher experience into account, and (3) the implications of alternative ways of imputing value-added when it cannot be estimated directly.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

In a widely cited study, Chetty, Friedman, and Rockoff (2014a; hereafter CFR) evaluate the degree of bias in teacher value-added estimates using a novel "teacher switching" research design with data from New York City. They conclude that there is little to no bias in their estimates. Using the same model with data from North Carolina, Rothstein (2014) argued that the CFR research design is invalid, given a relationship between student baseline test scores and teachers' value-added. In this paper, we replicated the CFR analysis using data from the Los Angeles Unified School District and similarly found that teacher value-added estimates were valid predictors of student achievement. We also demonstrate that Rothstein's test does not invalidate the CFR design and instead reflects a mechanical relationship, given that teacher value-added scores from prior years and baseline test scores can be based on the same data. In addition, we explore the (1) predictive validity of value-added estimates drawn from the same, similar, and different schools, (2) an alternative way of estimating differences in access to effective teaching by taking teacher experience into account, and (3) the implications of alternative ways of imputing value-added when it cannot be estimated directly.

The brightness of a laser-generated guide star is determined not only by the power of the laser, but also by the spectral and temporal properties of the laser. We show that a guide star laser pulsed at the Larmor frequency of the sodium atoms enhances guide star brightness by up to 2X, compared to an optimized cw laser at the same average power. We describe a frequency-addition source of optical radiation that can provide such pulsed light, while providing any desired spectral shape.

Herrnstein and Murray assume that test score gaps between blacks and whites attending the same schools or in the same jobs must result from the application of different selection criteria to blacks and whites. To the contrary, we show that race-blind screening processes normally will produce large gaps between the test scores of blacks and whites.

A closer look at the Taxpayer Relief Act of 1997 suggests the following: first, that the package will do little to encourage college enrollment, since low-income youth on the margin of college entry can expect little from the nonrefundable credits; second, because the package has no impact on the marginal cost of tuition above $5,000, it is unlikely to lead to sizable increases in college expenditures by families already spending more than $5,000; third, because the marginal tuition subsidy is between 50-100 percent for institutions charging less than $2,000, state governments will be tempted to capture a share of the federal subsidies by tailoring their own tuition and financial aid policies; fourth, the package does little to encourage parental saving since many families will benefit more from the Hope Scholarship credit than from the Education IRAs. Ironically, by partially relieving the burden of college expenses for families and by granting larger subsidies for borrowing than parental saving, the package may actually discourage parental saving.

Objects to educational tax incentives (in the form adopted in the 97 tax act) as not well targeted and ineffective in reducing the cost to families of future tuition increases. Recommends greater reliance on income-contingent loan forgiveness as an alternative way to help families pay for college.

It is argued that the net effect of any restriction of abortion access on birth rates is an empirical question. This study examines the impact of access to abortion on county teenage birth rates. Birth rates are expected to decrease by 1% among White adolescents aged 15-19 years for a 25-mile increase in the distance to the nearest abortion provider particularly among in-wedlock births. Data are obtained from 1973-88 National Natality Local Area Summary files for counties in the US and four other national sources. Data did not provide useful information on the empirical relationship between access and birth rate for densely populated urban areas. Cross-sectional findings that had omitted variable bias indicate that an increase of 25 miles in distance to a provider was associated with an additional 1.4 births per 1000 White teenage women or a 3% increase in the average teen birth rate of 45/1000 White teenagers. The findings from a county fixed-effects model that controlled for omitted variable bias indicate that an increase of 25 miles was associated with a reduction in teen births of 0.5/1000 or about 1% of the mean birth rate. Both Medicaid restrictions and parental consent laws were negative and significant and more negative in poor and more isolated counties. The state-year effects models did not change findings on distance and Medicaid restriction effects. The effects of changes in timing of laws suggests that laws followed preexisting trends. Changes in distance to provider were primarily in the first 2 years following the change. Out-of-wedlock births were unaffected by changes in distance to providers. The out-of-wedlock teen birth rate increased with a complete ban on abortions. Fewer wanted births were associated with small restrictions. Findings imply that closing of clinics during 1977-88 had an impact on teen birth rates of under one-tenth of 1%. The 20% increase in teen births was unexplained.