Competition and public high school performance

Increasing the level of school competition has been suggested as a way to improve school performance. This study examines one of the most extreme examples of such reform using data from New Zealand public high schools. In the 1990s school zoning was abolished in New Zealand and public schools competed for students, not just with private schools, but also with each other. A categorical Data Envelopment Analysis model using data on school resources and student academic performance, stratified using student socio-economic characteristics, is used to calculate efficiency scores for schools. A regression model is then used to analyse differences in these efficiency scores and their relationship to different levels of competition.     

The impact of Chicago’s small high school initiative

This project examines the effects of the introduction of new small high schools on student performance in the Chicago Public School (CPS) district. Specifically, we investigate whether students attending small high schools have better graduation/enrollment rates and achievement than similar students who attend regular CPS high schools. We show that students who choose to attend a small school are more disadvantaged on average, including having prior test scores that are about 0.2 standard deviations lower than their elementary school classmates. To address the selection problem, we use an instrumental variables strategy and compare students who live in the same neighborhoods but differ in their residential proximity to a small school. In this approach, one student is more likely to sign up for a small school than another statistically identical student because the small school is located closer to the student’s house and therefore the “cost” of attending the school is lower. The distance-to-small-school variable has strong predictive power to identify who attends a small school. We find that small schools students are substantially more likely to persist in school and eventually graduate. Nonetheless, there is no positive impact on student achievement as measured by test scores.     

Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students

This paper assesses the differences in educational attainments between students across classes and schools they are grouped by, in the context of Italian educational system. The purpose is to identify a relationship between pupils' reading test scores and students' characteristics, stratifying for classes, schools and geographical areas. The dataset contains detailed information about more than 500,000 students at the first year of junior secondary school in the year 2012/2013. By means of multilevel linear models, it is possible to estimate statistically significant school and class effects, after adjusting for pupil's characteristics, including prior achievement. The results show that school and class effects are very heterogeneous across macro-areas (Northern, Central and Southern Italy), and that there are substantial discrepancies between and within schools; overall, class effects on achievement tend to be larger than school ones.     

Which school attributes matter? The influence of school district performance and demographic composition on property values

Increasing levels of segregation in American schools raises the question: do home buyers pay for test scores or demographic composition? This paper uses Connecticut panel data spanning eleven years from 1994 to 2004 to ascertain the relationship between property values and school district attributes, such as student test scores and the racial and ethnic composition of the student body. Town and census tract fixed effects are included to control for neighborhood unobservables. The effect of changes in school district attributes is also examined over a decade long time frame in order to focus on the effect of long-run changes, which are more likely to be capitalized into prices. The study finds strong evidence that increases in percent Hispanic have a negative effect on housing prices in Connecticut, but mixed evidence concerning the impact of test scores on property values. Student test scores also appear to have increased in importance for explaining housing prices in recent years, while the importance of percent Hispanic has declined. Finally, the study finds that estimates of property tax capitalization increase substantially when the analysis focuses on long run changes.     

Mandatory summer school and student achievement

Using administrative data from a large school district, I exploit the fact that students are mandated to attend summer school based on a discontinuous function of their score on year-end exams to identify the effect of summer school attendance on achievement. I find an average effect of about .12 standard deviations for both math and reading achievement, an effect size on the low end of the range of prior estimates. These averages mask considerable heterogeneity, however, with effect size estimates ranging from just below zero to one-quarter of a standard deviation. The estimates on the upper end of the range presented here suggest that summer school may be a more cost-effective way of raising student achievement scores than class-size reductions.     

Schooling Resources, Educational Institutions and Student Performance: the International Evidence

This paper estimates the effects of family background, resources and institutions on mathematics and science performance using an international database of more than 260,000 students from 39 countries which includes extensive background information at the student, teacher, school and system level. The student-level estimations show that international differences in student performance cannot be attributed to resource differences but are considerably related to institutional differences. Among the many institutions which combine to yield major positive effects on student performance are centralized examinations and control mechanisms, school autonomy in personnel and process decisions, individual teacher influence over teaching methods, limits to teacher unions' influence on curriculum scope, scrutiny of students' achievement and competition from private schools.     

Evaluating the global efficiency of teachers through a multi-criteria approach

Improving the quality of education is one of the main objectives for governments, given that it plays an essential role in providing well-being to the population. In this regard, the efficiency of teachers may be a key issue to improve the students' academic performance and learning achievement. Specifically, in this paper, we analyse the efficiency of teachers from a multi-criteria optimization perspective. The purpose is to detect the most efficient teachers to gain knowledge about the characteristics of their teaching context, which contribute to increase the education performance of the students. To this aim, data from TIMSS and PIRLS 2011 for fourth-grade reading, mathematics and science teachers in Spain have been used. Three synthetic indexes gathering these data are calculated: a weak index allowing full compensation among the variables, a strong index informing about the worst variable value (no compensation scheme) and a synthetic index representing a different degree of compensation of the two formers. These indexes are built using aspiration and reservation levels for each variable. This allows us to include desirable ranges of values to be achieved by the variables in the study of the teachers' efficiency. With this, it is possible to know if the teachers are performing better, within or worse than the desired limits, and to rank the teachers according to their efficiency. The analysis carried out has contributed to have a better understanding of the policies to be followed in order to promote efficiency in teaching.     

Barriers to skill acquisition in Brazil: Public and private school students performance in a public university entrance exam

This paper uses a novel data set to quantify the difference in performance of public and private school students in an entrance test exam of the major public university in Brazilian Northeast (Universidade Federal de Pernambuco – UFPE). Although there are many public universities in Brazil, from our knowledge, there is no study that uses data on entrance test scores at such universities to evaluate the determinants of students’ performance and the barriers for public school students to get in the good universities. The data set has detailed information on individual and school characteristics, and family background. We found that test scores of public school students are on average about 4.2–17% lower than those taken by private school students, depending on the set of controls. This result is robust when we address problems related to attrition, omitted variables (e.g., cognitive ability), and unobservable selectivity. We also show that once students get into the university, those from public schools perform as well as those from private schools. In addition, the proportion of public school students that gets into the university is roughly the same as the proportion of students doing the entrance exam. However, there is a strong barrier for public school students to get into high competitive majors. The fraction of students from public schools that gets into high competitive majors such as law, medicine, and electronic engineering is almost null. Our findings provide quantitative evidence to the common view that the Brazilian elitist high education system is an important channel for inequality persistence.     

A graphically based machine learning approach to predict secondary schools performance in Tunisia

The main purpose of this paper is to identify the key factors that impact schools' academic performance and to explore their relationships through a two-stage analysis based on a sample of Tunisian secondary schools. In the first stage, we use the Directional Distance Function approach (DDF) to deal with undesirable outputs. The DDF is estimated using Data Envelopment Analysis method (DEA). In the second stage we apply machine-learning approaches (regression trees and random forests) to identify and visualize variables that are associated with a high school performance. The data is extracted from the Program for International Student Assessment (PISA) 2012 survey. The first stage analysis shows that almost 22% of Tunisian schools are efficient and that they could improve their students’ educational performance by 15.6% while using the same level of resources. Regression trees findings indicate that the most important factors associated with higher performance are school size, competition, class size, parental pressure and proportion of girls. Only, school location appears with no impact on school efficiency. Random forests algorithm outcomes display that proportion of girls at school and school size have the most powerful impact on the predictive accuracy of our model and hence could more influence school efficiency. The findings disclose also the high non-linearity of the relationships between these key factors and school performance and reveal the importance of modeling their interactions in influencing efficiency scores.     

Teacher quality and dropout outcomes in a large,urban school district

Recent research shows that variation in teacher quality has large effects on student performance. However, this research is based entirely on student test scores. Focusing on high-school math teachers, this paper evaluates teacher quality in terms of another educational outcome of great interest—graduation. I use a unique instrumental variables approach to identify teacher effects and find that differences in teacher quality have large effects on graduation outcomes. Because teacher effects on graduation outcomes will be more pronounced for students who are on the graduation margin, the results imply an avenue through which high-quality teachers are more productive with disadvantaged students.     

Discrimination in the market for public school teachers

We seek to provide an answer to the question, ‘How much is required to induce white teachers to teach in black schools?’ using cross section data from the Coleman Report for 1965. The conceptual framework underlying estimation is a model of the spatial distribution of teachers based on the theory of equal advantage. School characteristics, including student racial composition, intelligence of students, student motivational indicators and neighborhood hazards are found to be important sources of real wage variation in the teachers' market. The estimates imply that a minimum increment of $300 (and probably more) was required for average white teachers to accept average black teachers' school characteristics in 1965.     

Is the gender gap in school performance affected by the sex of the teacher?

Girls outperform boys in school. We investigate whether the gender performance gap can be attributed to the fact that the teacher profession is female dominated, that is, is there a causal effect on student outcomes from having a same-sex teacher? Using data on upper-secondary school students and their teachers from the municipality of Stockholm, Sweden, we find that the gender performance differential is larger in subjects where the share of female teachers is higher. We argue, however, that this effect can not be interpreted as causal, mainly due to teacher selection into different subjects and non-random student-teacher matching. Exploring the fact that teacher turnover and student mobility give rise to variation in teacher's gender within student and subject, we estimate the effect on student outcomes of changing to a teacher of the same sex. We find no strong support for our initial hypothesis that a same-sex teacher improves student outcomes.     

Identification and estimation of bounds on school performance measures: a nonparametric analysis of a mixture model with verification

This paper identifies and nonparametrically estimates sharp bounds on school performance measures based on test scores that may not be valid for all students. A mixture model with verification is developed to handle this problem. This is a mixture model for data that can be partitioned into two sets, one of which (the so‐called verified set) is more likely to be from the distribution of interest than the other. An administrative classification of each student as English proficient or limited English proficient determines these sets. An analysis of performance measures for some California public schools reveals how verification information and plausible monotonicity restrictions can bound the range of disagreement about school performance based on observed scores. Copyright © 2006 John Wiley & Sons, Ltd.     

Teacher quality and dropout outcomes in a large, urban school district

Recent research shows that variation in teacher quality has large effects on student performance. However, this research is based entirely on student test scores. Focusing on high-school math teachers, this paper evaluates teacher quality in terms of another educational outcome of great interest—graduation. I use a unique instrumental variables approach to identify teacher effects and find that differences in teacher quality have large effects on graduation outcomes. Because teacher effects on graduation outcomes will be more pronounced for students who are on the graduation margin, the results imply an avenue through which high-quality teachers are more productive with disadvantaged students.     

Teacher Quality and Student Achievement: Evidence from a Sample of Dutch Twins

This paper examines the causal link that runs from classroom quality to student achievement using data on twin pairs who entered the same school but were allocated to different classrooms in an exogenous way. In particular, we apply twin fixed‐effects estimation to assess the effect of teacher quality on student test scores from second through eighth grade of primary education, arguing that a change in teacher quality is probably the most important classroom intervention within a twin context. In a series of estimations using measurable teacher characteristics, we find that (a) the test performance of all students improves with teacher experience; (b) teacher experience also matters for student performance after the initial years in the profession; (c) the teacher experience effect is most prominent in earlier grades; (d) the teacher experience effects are robust to the inclusion of other classroom quality measures, such as peer group composition and class size; and (e) an increase in teacher experience also matters for career stages with less labor market mobility, which suggests positive returns to on‐the‐job learning of teachers. Copyright © 2016 John Wiley & Sons, Ltd.     

The development of a model for student achievement

This article describes the results of work being conducted on the development of a model for student achievement. Steps employed in the reduction of the large number of variables into a fewer number of indices and the utilization of these indices in regression analyses are described. Some of the more salient findings are that both school achievement and school resources (including such things as the number of pupils per teacher, the teacher's view of his working conditions and the school's special staff and services) are highly related to the socio-economic status and racial-ethnic composition of the student body. The influence of the schools is bound up with the kinds of students that they get initially. Consequently, when the schools are equated for the kinds of students that they get they tend also to be equated for the influence that they have on these students. The schools play an important role in promoting student achievement and the extent of this involvement appears to be greater for higher socio-economic status and white students than for lower socio-economic status and non-white students.     

Does school matter for educational achievement? a two-way nested-error components analysis

School effectiveness is a much-debated question both at an analytical level and as a policy issue. In this paper we used a two-way nested-error components educational production function model to evaluate the relative importance of latent class and school variables in explaining student school achievement. The analysis is carried out with a sample of Montreal francophone public elementary school students. As for the observable variables, the empirical results suggest that the latent class and school variables are negligible with respect to the latent personal and socioeconomic variables. Related policy issues are discussed in the conclusion.     

Charter school closure and student achievement: Evidence from Ohio

The closure of low-performing schools is an essential feature of the charter school model. Our regression discontinuity analysis uses an exogenous source of variation in school closure—an Ohio law that requires charter schools to close if they fail to meet a specific performance standard—to estimate the causal effect of closure on student achievement. The results indicate that closing low-performing charter schools eventually yields achievement gains of around 0.2–0.3 standard deviations in reading and math for students attending these schools at the time they were identified for closure. The study also employs mandatory closure as an instrument for estimating the impact of exiting low-quality charter schools, thus providing plausible lower-bound estimates of charter school effectiveness. These results complement the more common lottery-based estimates of charter school effects, which likely serve as upper-bound estimates due to their focus on oversubscribed schools often located in cities with high-performing charter sectors. We discuss the implications for research and policy.     

The efficiency of schools in developing countries,analysed through PISA 2012 data

This paper analyses the efficiency of more than 6800 schools in 28 developing countries, by means of a two-stage Data Envelopment Analysis and using data from OECD PISA 2012. The results reveal that the average efficiency of schools is around 70%, meaning that achievement scores can be raised by 30% by employing a more effective use of available resources. Substantial heterogeneity exists both between and within countries; in general, efficiency scores are higher when comparing schools only with those in the same country. Among factors associated with schools' efficiency, the most important are the characteristics of student population (for instance, motivation, truancy, etc.). Therefore, some practices related to accountability, teachers’ involvement and professional development, and extracurricular activities are also positively associated with higher levels of efficiency.     

Measuring efficiency in education: The influence of imprecision and variability in data on DEA estimates

Many studies devoted to efficiency performance evaluation in the education sector are based on measures of central tendency at school level as, for example, the average values of students belonging to the same school. Although this is a common and accepted way of summarizing data from the original observations (students), it is not less true that this approach neglects the existing dispersion of data, which may become a serious problem if variability across schools is high. Additionally, imprecision may arise when experts on each evaluated subject select the battery of questions, with different levels of difficulty, which will be the base for the final questionnaires completed by students. This paper uses data from US students and schools participating in PISA (Programme for International Student Assessment) 2015 to illustrate that schools' efficiency measures based on aggregate data and imprecision may reflect an inaccurate picture of their performance if they are compared to measures estimated accounting for broader information provided by all students of the same school. In order to operationalize our approach, we resort to Fuzzy Data Envelopment Analysis. This methodology allows us to deal with the notion of fuzziness in some variables such as the socio-economic status of students or test scores. Our results indicate that the estimated measures of performance obtained with the fuzzy DEA approach are highly correlated with those calculated with traditional DEA models. However, we find some relevant divergences in the identification of efficient units when we account for data dispersion and vagueness.