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Louisiana's "School Performance Score" (SPS) is the state's primary accountability measure, and it determines whether schools are subject to high-stakes decisions, most notably state takeover. For elementary and middle schools, 90 percent of the SPS is based on testing outcomes. For secondary schools, it is 70 percent (and 30 percent graduation rates).* The SPS is largely calculated using absolute performance measures - specifically, the proportion of students falling into the state's cutpoint-based categories (e.g., advanced, mastery, basic, etc.). This means that it is mostly measuring student performance, rather than school performance. That is, insofar as the SPS only tells you how high students score on the test, rather than how much they have improved, schools serving more advantaged populations will tend to do better (since their students tend to perform well when they entered the school) while those in impoverished neighborhoods will tend to do worse (even those whose students have made the largest testing gains). One rough way to assess this bias is to check the association between SPS and student characteristics, such as poverty.

"This brief describes the prevalence of highest-performing teachers in ten purposely selected districts across seven states. The overall patterns indicate that low-income students have unequal access, on average, to the district's highest-performing teachers at the middle school level but not at the elementary level. However, there is evidence of variation in the distribution of highest-performing teachers within and among the ten districts studied. Some have an under-representation of the highest-performing teachers in high-poverty elementary and middle schools. Others have such under-representation only at the middle school level, and one district has a disproportionate share of the district's highest-performing teachers in its high-poverty elementary schools."

Expanding on the 2009 CREDO National Charter School Study  Multiple Choice: Charter School Performance in 16 States, this report examines the performance of Pennsylvania charter schools for the period 2007 - 2010.  Compared to the educational gains the charter students would have had in their traditional public schools, the analysis shows that students in Pennsylvania charter schools on average make smaller learning gains.  More than one quarter of the charter schools have significantly more positive learning gains than their traditional public school counterparts in reading, but their performance is eclipsed by the nearly half of charter schools that have significantly lower learning gains.  In math, again nearly half of the charter schools studied perform worse than their traditional public school peers and one quarter outperform them.

Redistributing highly effective teachers from low- to high-need schools is an education policy tool that is at the center of several major current policy initiatives. The underlying assumption is that  teacher productivity is portable across different schools settings. Using elementary and secondary school data from North Carolina and Florida, this paper investigates the validity of this assumption. Among teachers who switched between schools with substantially different poverty levels or academic performance levels, we find no change in those teachers' measured effectiveness before and after a school change. This pattern holds regardless of the direction of the school change. We also find that high-performing teachers' value-added dropped and low-performing teachers' value-added gained in the post-move years, primarily as a result of regression to the within-teacher mean and unrelated to school setting changes. Despite such shrinkages, high-performing teachers in the pre-move years still outperformed low-performing teachers after moving to schools with different settings.

Using a statistical technique called value-added modeling, the Teacher Data Reports compare how students are predicted to perform on the state ELA and math tests, based on their prior year's performance, with their actual performance. Teachers whose students do better than predicted are said to have "added value"; those whose students do worse than predicted are "subtracting value." By definition, about half of all teachers will add value, and the other half will not. Carolyn Abbott was, in one respect, a victim of her own success. After a year in her classroom, her seventh-grade students scored at the 98th percentile of New York City students on the 2009 state test. As eighth-graders, they were predicted to score at the 97th percentile on the 2010 state test. However, their actual performance was at the 89th percentile of students across the city. That shortfall-the difference between the 97th percentile and the 89th percentile-placed Abbott near the very bottom of the 1,300 eighth-grade mathematics teachers in New York City. How could this happen? Anderson is an unusual school, as the students are often several years ahead of their nominal grade level. The material covered on the state eighth-grade math exam is taught in the fifth or sixth grade at Anderson. "I don't teach the curriculum they're being tested on," Abbott explained. "It feels like I'm being graded on somebody else's work."

I have been writing critically about states' school rating systems (e.g., Ohio, Florida, Louisiana), and I thought I would find one that is, at least in my (admittedly value-laden) opinion, more defensibly designed. It didn't quite turn out as I had hoped. One big starting point in my assessment is how heavily the systems weight absolute performance (how highly students score) versus growth (how quickly students improve). As I've argued many times, the former (absolute level) is a poor measure of school performance in a high-stakes accountability system. It does not address the fact that some schools, particularly those in more affluent areas, serve  students who, on average, enter the system at a higher-performing level. This amounts to holding schools accountable for outcomes they largely cannot control (see Doug Harris' excellent book for more on this in the teacher context). Thus, to whatever degree testing results can be used to judge actual school effectiveness, growth measures, while themselves highly imperfect, are to be preferred in a high-stakes context. There are a few states that assign more weight to growth than absolute performance (see this prior post on New York City's system). One of them is Colorado's system, which uses the well-known "Colorado Growth Model" (CGM).

"No one knows who I am," exclaimed a senior in a high-poverty, predominantly minority and low-performing high school in the Austin area. She explained, "I have been at this school four years and had four principals and six algebra I teachers." Elsewhere in Texas, the first school to be closed by the state for low performance was Johnston High School, which was led by 13 principals in the 11 years preceding closure. The school also had a teacher turnover rate greater than 25 percent for almost all of the years and greater than 30 percent for 7 of the years. While the above examples are rather extreme cases, they do underscore two interconnected issues - teacher and principal turnover - that often plague low-performing schools and, in the case of principal turnover, afflict a wide range of schools regardless of performance or school demographics. In recent years, those seeking to improve schooling through efforts to increase teacher effectiveness and build teacher capacity have quickly realized that such efforts rely heavily on principal capacity and stability.

Have you ever wondered how your state's educational performance compares to the performance of other states? Now with the new State of the States in Education document released yesterday by the Department of Education, you can see a snapshot of how educational performance varies substantially across states.

State assessments are increasingly used as outcome measures for education evaluations and pretest scores are generally used as control variables in these evaluations. The correlation between the pretest and outcome (posttest) measures is a factor in determining, among other things, the statistical power of a study. This report examines the variability in pretest-posttest correlation coefficients for state assessment data on samples of low-performing, average-performing, and proficient students to determine how sample characteristics (e.g., achievement level) affect pretest-posttest correlation coefficients. As an application, this report illustrates how statistical power is affected by variations in pretest-posttest correlation coefficients across groups with different sample characteristics. Achievement data from four states and two large districts are examined. The results confirm that pretest-posttest correlation coefficients are smaller for samples of low performers than for samples representing the full range of performers, thus, resulting in lower statistical power for impact studies than would be the case if the study sample included a more representative group of students.

A recent report found that California charter schools' performance is "U-shaped"-meaning there are relatively large numbers of charters clumped among the state's highest and lowest performers. But what would it take to remove a substantial number of charters from the ranks of the stragglers? The second annual "Portrait of the Movement," report from the California Charter Schools Association concludes that if the state were to adopt higher standards for charter renewal, it could eliminate the overrepresentation of charters from the bottom rung, and do it in seven years. As it now stands, about 19 percent of charters in the state, or 150 out of 789, ranked within the bottom 10 percent of performance in California. Just 9 percent of non-charters fell in that category.

More than half the states have now been excused from important conditions of the No Child Left Behind education law. They've been allowed to create new measures of how much students have improved and how well they are prepared for college or careers, and to assess teacher performance on that basis. Teachers will be evaluated in part on how well their students perform on standardized tests. One study, though, found that some state plans could weaken accountability. How can we measure achievement of students, teachers and schools in a way that is fair and accurate, and doesn't provide incentives for obsessive testing, and cheating? Contributors include: Leonie Haimson, Pedro Noguera, Michael Petrilli, Marcus Winters, Rishawn Biddle, Julia Fox, Kevin Carey, Patrick Bassett, and Sandra Stotsky

Increased spending and decreased student performance have been attributed in part to teachers' unions and to the collective bargaining agreements (CBAs) they negotiate with school boards. However, only recently have researchers begun to examine impacts of specific aspects of CBAs on student and district outcomes. This article uses a unique measure of contract restrictiveness generated through the use of a partial independence item response model to examine the relationships between CBA strength and district spending on multiple areas and district-level student performance in California. I find that districts with more restrictive contracts have higher spending overall, but that this spending appears not to be driven by greater compensation for teachers but by greater expenditures on administrators' compensation and instruction-related spending. Although districts with stronger CBAs spend more overall and on these categories, they spend less on books and supplies and on school board-related expenditures. In addition, I find that contract restrictiveness is associated with lower average student performance, although not with decreased achievement growth.

"School closings, the threat of which hang over Chicago public schools, and which have been a central feature of Bloomberg educational policies in New York, are perhaps the most controversial features of the Obama administration's "Race to the Top" initiative. The idea of closing low-performing schools, designated as such entirely on the basis of student test scores, removing half of their teaching staff and all of their administrators, and replacing them with a new (typically charter) school in the same building, is one which has tremendous appeal among business leaders and almost none among educators. Advocates see this policy as a way of removing ineffective teachers, adding competition to what had been a stagnant sphere of public service, and putting pressure on teachers in high-poverty areas to demand and get high performance from their students, once again based on performance on standardized tests. For a "data driven" initiative, school closings have produced surprisingly little data to support their implementation."

There is a dearth of research that supports paying teachers beyond their base salaries to improve student achievement, but there is a broad body of research that indicates that pay for performance might actually do damage as teachers feel a threat to their livelihoods because of this narrow method of measuring their efficacy. Pay for performance has been documented as compromising the good will and cooperation among teachers since it creates competition for a small amount of money, which can result in an "I'm out for myself only" attitude. Such a tone can hurt the necessary collaboration and communication found to nurture student achievement and success.

Although most new teacher evaluations are still in various phases of pre-implementation, it's safe to say that classroom observations and/or value-added (VA) scores will be the most heavily-weighted components toward teachers' final scores, depending on whether teachers are in tested grades and subjects. One gets the general sense that many - perhaps most - teachers strongly prefer the former (observations, especially peer observations) over the latter (VA). One of the most common arguments against VA is that the scores are error-prone and unstable over time - i.e., that they are unreliable. And it's true that the scores fluctuate between years (also see here), with much of this instability due to measurement error, rather than "real" performance changes. On a related note, different model specifications and different tests can yield very different results for the same teacher/class. These findings are very important, and often too casually dismissed by VA supporters, but the issue of reliability is, to varying degrees, endemic to all performance measurement. Actually, many of the standard reliability-based criticisms of value-added could also be leveled against observations. Since we cannot observe "true" teacher performance, it's tough to say which is "better" or "worse," despite the certainty with which both "sides" often present their respective cases. And, the fact that both entail some level of measurement error doesn't by itself speak to whether they should be part of evaluations.*

Now fast-forward to the latest plan to measure teacher and principal effectiveness. New York has joined with other states around the country to impose a system of measurement that on first blush appears to be long overdue. Known as the Annual Professional Performance Review (APPR), the system of evaluation is a multifaceted approach to review all aspects of educator performance and includes the use of student test scores as a factor in rating performance. There is no doubt that education stands to improve in order to meet the demands of a highly competitive society, however there are many unforeseen consequences of this ill-conceived system.

Faced with mounting policy pressures from federal and state accountability programs, school leaders are reallocating curricula, time, even diet in an attempt to boost student achievement. To explore whether they are using test score data to reallocate their teacher resources as well, I designed a cross-case, cross-sectional study and explored principals' reported staffing practices in one higher performing and one lower performing elementary school in each of five Florida school districts. Findings show that school leaders are "staffing to the test" by hiring, moving, and developing teachers in an effort to increase their schools' overall performance. The paper discusses the implications of evidence-based staffing for policy, practice and future research.

We first must specify just what it is we intend to evaluate: performance? effectiveness? something else? It is critical that we answer this question clearly, because performance and effectiveness are different criteria determined by different variables, which suggests the potential for different interventions to improve them.

Gov. Chris Christie said Wednesday his administration has developed a new system for reviewing and rating school performance for the state's annual schools report card. The state's nearly 600 school districts will be classified in to one of three categories; "focus schools," the worst, followed by "priority schools," and the best will be called "reward" schools. It's unclear whether the best performing schools would receive any additional perks for achieving "reward" status.

K12 Inc. enrolls more public school students than any other private education management organization in the U.S. Much has been written about K12 Inc. (referred to in this report simply as "K12") by financial analysts and investigative journalists because it is a large, publicly traded company and is the dominant player in the operation and expansion of full-time virtual schools. This report provides a new perspective on the nation's largest virtual school provider through a systematic review and analysis of student characteristics, school finance, and school performance of K12-operated schools. Using federal and state data, this report provides a description of the students served by K12 and the public revenues received and spent by the company at the school level. Further, the report presents evidence from a range of school performance measures and strives to understand and explain the overall weak performance of these virtual schools.