Private versus public high schools in Spain: disentangling managerial and programme efficiencies

The purpose of this paper is to compare the efficiency of a set of Spanish public and private high schools using data envelopment analysis (hereafter DEA). In view of the usual difficulties of obtaining reliable budget figures on private schools, we have used a restrictive efficiency notion which focuses on the relation between the academic results obtained by each school and the socio-economic background and academic profile of its pupils. In this study, special emphasis is placed upon decomposing the overall inefficiencies of each school into managerial (due to individual performance) and programme (due to structural differences between management models) components. Our results reveal that although, in general, private schools obtain better academic results than public schools in absolute terms, this is not the consequence of comparatively more effective management but rather of having pupils with a more favourable background for the educational process.     

A comparison of public and private schools in Spain using robust nonparametric frontier methods

This paper uses an innovative approach to evaluate educational performance of Spanish students in PISA 2009. Our purpose is to decompose their overall inefficiency between different components with a special focus on studying the differences between public and state subsidized private schools. We use a technique inspired by the non-parametric free disposal hull and the application of robust order-\(m\) models, which allow us to mitigate the influence of outliers and the curse of dimensionality. Subsequently, we adopt a metafrontier framework to assess each student relative to the own group best practice frontier (students in the same school) and to different frontiers constructed from the best practices of different types of schools. The results show that state-subsidised private schools outperform public schools, although the differences between them are significantly reduced once we control for the type of students enrolled in both type of centres.     

Efficiency and equity in private and public education: A nonparametric comparison

We present a nonparametric approach for (1) efficiency and (2) equity evaluation in education. Firstly, we use a nonparametric (Data Envelopment Analysis) model that is specially tailored to assess educational efficiency at the pupil level. The model accounts for the fact that typically minimal prior structure is available for the behavior (objectives and feasibility set) under evaluation. It allows for uncertainty in the data, while it corrects for exogenous ‘environmental’ characteristics that are specific to each pupil. Secondly, we propose two multidimensional stochastic dominance criteria as naturally complementary aggregation criteria for comparing the performance of different school types (private and public schools). While the first criterion only accounts for efficiency, the second criterion also takes equity into consideration. The model is applied for comparing private (but publicly funded) and public primary schools in Flanders. Our application finds that no school type robustly dominates another type when controlling for the school environment and taking equity into account. More generally, it demonstrates the usefulness of our nonparametric approach, which includes environmental and equity considerations, for obtaining ‘fair’ performance comparisons in the public sector context.     

Measuring the relative efficiency of quality management practices in Turkish public and private universities

Using data envelopment analysis (DEA) in conjunction with stochastic frontier analysis (SFA), the aim of this study was to measure the relative efficiency of quality management (QM) practices in Turkish public and private universities. Based on the extant literature, a set of nine critical QM factors and seven performance indicators for Turkish universities were identified as input and output variables, respectively. SFA confirmed the existence of significant relationships between QM factors and performance indicators. DEA findings indicated that private universities with higher levels of QM efficiency on stakeholder-focus indicators achieved better performance in terms of fulfilling the expectations of their stakeholders. In contrast, public universities were more successful in managing QM practices for a superior teaching and research performance. Finally, after eliminating the managerial discrepancies, no significant structural efficiency difference was found between these two groups of universities through stakeholder-focus model, though some significant variation was noted in both factor-efficiency and total-efficiency models. As for total-efficiency model, we may infer that the structural differences found in favour of public universities for factor-efficiencies are counterbalanced by private universities which tend to focus more on their stakeholders in managing QM applications.     

Single-sex Classes: Female Physics Students State Their Case

Since the passage of Title IX in 1972, gender equity has been addressed through means that reflect inclusion and integration by gender. Recent Supreme Court decisions such as the one deeming the Virginia Military Institute's admission policies to be unlawfully discriminatory against women suggest a reinforced and perhaps narrowed interpretation of appropriate means for attaining gender equity in public schools. This case and others also suggest that publicly funded single-sex programs may be in jeopardy. This study examines data collected from a girls-only physics class in a public coeducational high school. Interview and observation data from this class, as well as from a coeducational physics class taught by the same teacher, illustrate that the girls in the single-sex class made substantial gains in both academic achievement and in perceptions of themselves as competent learners of science.     

A deterministic linear optimization model for allocating schools to zones

This paper presents a deterministic linear optimization model to support decisions on optimal allocation of schools to zones, its characterization and assignment of students, maximizing the social benefits of school owners and students. Students are assumed to show a multi-attribute behaviour, considering as important not only location, as is usual in the literature, but also quality of education and infrastructure, school costs and other attributes. There is heterogeneity of supply and demand. Students are classified by place of residence and socio-economic characteristics. Schools can be private, subsidized or free municipal ones. The model developed is applied to data of one of the municipalities of Santiago. The results obtained under different scenarios tend to confirm the expected demand's behaviour. This model could be used to guide decisions of both school owners or municipalities as well as students towards an equilibrium closer to a social optimum.     

Chapter 12 New uses of DEA and statistical regressions for efficiency evaluation and estimation — with an illustrative application to public secondary schools in Texas

This paper examines new combinations of Data Envelopment Analysis (DEA) and statistical approaches that can be used to evaluate efficiency within a multiple-input multiple-output framework. Using data on five outputs and eight inputs for 638 public secondary schools in Texas, unsatisfactory results are obtained initially from both Ordinary Least Squares (OLS) and Stochastic Frontier (SF) regressions run separately using one output variable at-a-time. Canonical correlation analysis is then used to aggregate the multiple outputs into a single aggregate output, after which separate regressions are estimated for the subsets of schools identified as efficient and inefficient by DEA. Satisfactory results are finally obtained by a joint use of DEA and statistical regressions in the following manner. DEA is first used to identify the subset of DEA-efficient schools. The entire collection of schools is then comprehended in a single regression with dummy variables used to distinguish between DEA-efficient and DEA-inefficient schools. The input coefficients are positive for the efficient schools and negative and statistically significant for the inefficient schools. These results are consistent with what might be expected from economic theory and are informative for educational policy uses. They also extend the treatments of production functions usually found in the econometrics literature to obtain one regression relation that can be used to evaluate both efficient and inefficient behavior.     

Analysis of complementary methodologies for the estimation of school value added

This paper analyses the value added (VA) of a sample of Portuguese schools using two methodologies: data envelopment analysis (DEA) and the methodology used presently by the UK Department for Children, Schools and Families (DCSF). The VA estimates obtained by the two methods are substantially different. This reflects their different focus: DEA emphasizes on best-observed performance, whereas the DCSF method reveals average performance. The main advantage of the methodology used by the DCSF is its simplicity, although it confounds pupil effects with school effects in the estimation of school VA. In contrast, the DEA methodology can differentiate these effects, but the complexity may prevent its use in a systematic way. This paper shows that the two methods provide complementary information regarding the VA of schools, and their joint use can improve the understanding of the relative effectiveness of schools regarding the progress that pupils make between educational stages.     

Guiding Schools to Improved Performance Using Data Envelopment Analysis: An Illustration with Data from a Local Education Authority

The educational process is characterized by multiple outcomes such as the achievement of academic results of various standards and non-academic achievements. This paper shows how data envelopment analysis (DEA) can be used to guide secondary schools to improved performance through role-model identification and target setting in a way that recognizes the multi-outcome nature of the education process and reflects the relative desirability of improving individual outcomes. The approach presented in the paper draws from a DEA-based assessment of the schools of a local education authority carried out by the authors. Data from that assessment are used to illustrate the approach presented in the paper.     

Decomposing school and school-type efficiency

This paper puts forward a Data Envelopment Analysis (DEA) approach to decomposing a pupil’s under-attainment at school. Under-attainment is attributed to the pupil, the school and the type of funding regime under which the school operates. A pupil-level analysis is used firstly on a within school and secondly on a between school basis, grouping schools by type such as state-funded, independent and so on. Overall measures of each pupil’s efficiency are thus disentangled into pupil, school and school-type efficiencies. This approach provides schools with a set of efficiency measures, each one conveying different information.     

中学教师组织支持感对工作压力的预测作用研究

在中、高考指挥棒的引导下,目前中学教师群体的工作压力达到了前所未有的高度,而教师对组织支持的感知影响着教师对工作压力的认识.通过对2187名中学教师进行问卷调查,运用SPSS和AMOS软件对数据进行分析,分析中学教师组织支持感工作压力所在水平,目前组织支持感水平处于中等状态,且教师对组织支持感的认识比较一致.中学教师工作压力总体比较高,但不同的教师群体工作压力不同.并对组织支持感预测工作压力模型进行检验.发现组织支持感与工作压力呈负相关初/高中在0.001水平上差异显著,而性别、公/民办和教龄在0.05水平上差异显著.     

Predictors of Science Fair Participation Using the Theory of Planned Behavior

The purpose of this study was to use The Theory of Planned Behavior (TPB) to examine factors that predict junior high and secondary students' attitude toward participating in a district science fair competition (attitude toward behavior), beliefs about who would approve or disapprove of participation in a science fair (subjective norm), and perceptions of control about participating in the science fair (perceived behavioral control). Factors used to predict these included gender, type of school (public or private), grade level, GPA, participation in a gifted class, participation in a research course, requirement to complete a science fair project, and level of anxiety about completing a science fair project. Three hundred three participants completed a standard TPB questionnaire and the State-Trait Anxiety Indicator. Multiple regression models revealed that subjective norm and participation in a gifted class were predictors of attitude toward the behavior. Attitude toward the behavior, the science fair project counting toward a grade in science class, the parent's level of education, and the science fair entry being required predicted subjective norm. A discriminant function analysis found that type of school (public or private), parents' level of education, participation in a research program at school, grade level, and trait anxiety were the strongest predictors of perceived behavioral control. It was concluded that science fair entry appears to be involuntary, in conflict with NSTA's Position Statement on Science Fairs. Typically junior high students (whose parents have a higher level of education) attending private schools are required to enter science fairs, and the entry counts toward a grade in science class.     

Elective course planning

Efficient planning increasingly becomes an indispensable tool for management of both companies and public organizations. This is also the case for high school management in Denmark, because the growing individual freedom of the students to choose courses makes planning much more complex. Due to reforms, elective courses are today an important part of the curriculum, and elective courses are a good way to make high school education more attractive for the students. In this article, the problem of planning the elective courses is modeled using integer programming and three different solution approaches are suggested, including a Branch-and-Price framework using partial Dantzig-Wolfe decomposition. Explicit Constraint Branching is used to enhance the solution process, both on the original IP model and in the Branch-and-Price algorithm. To the best of our knowledge, no exact algorithm for the Elective Course Planning Problem has been described in the literature before. The proposed algorithms are tested on data sets from 98 of the 150 high schools in Denmark. The tests show that for the majority of the problems, the optimal solution can be obtained within the one hour time bound. Furthermore the suggested algorithms achieve better results than the currently applied meta-heuristic.     

Assigning mathematics instruction time in secondary schools: what are the influential factors?

Similar to countries such as the Netherlands and the United Kingdom, secondary schools in Ireland can decide how to allocate instruction time between curriculum subjects. Although there are national guidelines available from the Department of Education and Skills (DES), the majority of schools make their own decisions about how much time they allocate to different subjects. This results in variations between the amounts of time allocated to teaching mathematics in different schools and between different year and class groups within the same school. Decisions regarding time allocation are generally taken by the school management. This means that the ethos of the school and the individual opinions of school management can determine the amount of mathematics that students experience throughout their second level education. The aim of this study is to evaluate the most influential factors that management considers when assigning instruction time in Irish secondary schools. For the purpose of this research, seven possible factors were identified and 400 deputy principals from a stratified sample of secondary schools around Ireland were asked to select their top three. Timetabling constraints, the availability of mathematics teachers and the perceived importance of the subject were found to be the most influential factors.     

Enhancing the inclusion of non-discretionary inputs in DEA

The aim of this paper is to provide an alternative approach for estimating efficiency when a set of decision-making units uses non-discretionary inputs in the productive process. To test the influence of these variables, our proposal uses a multi-stage approach based on Tobit regressions. In order to avoid potential bias, a bootstrap procedure is used to estimate these regressions. This methodology allows enhancing other models previously proposed to introduce non-controllable inputs in data envelopment analysis (DEA) overcoming, thus, some of their main shortcomings. We illustrate our framework with an empirical application on Spanish high schools where non-controllable factors play a major role to explain educational achievements.     

Performance assessment of secondary schools: the snapshot of a country taken by DEA

This paper describes a performance assessment of Portuguese secondary schools using data envelopment analysis (DEA). The assessment adopts a perspective where schools are viewed as promoting students achievement given their characteristics in terms of academic abilities and socio-economic background. Our sample comprised all secondary schools in Portugal with both basic and secondary education levels. Two types of DEA analysis are performed: one using an output-oriented model that restricts output (exam scores) weights to be linked to the number of students that have done that exam in the school, and the other using a model that restricts factor weights to be equal for all schools. In this model the weight restrictions are linked to the total number of exams done nationally. The first model is well suited for identifying worst performing schools and to assess schools that may specialize in certain subjects, whereas the latter is best suited for improving discrimination between best performing schools when pursuing the identification of benchmarks, as well as to construct performance rankings.     

The Hurricane Katrina Effect on Mathematics Achievement in Mississippi

Hurricane Katrina caused severe physical damage to the Gulf Coast states of Louisiana, Mississippi, and Alabama. Homes and businesses were destroyed. Natural habitats were annihilated, and many Americans were displaced for days, weeks, and even years. This study investigated the within‐subject effects and contrasts of poverty, rurality, and location within a Katrina distance impact zone on mathematics achievement in fifth‐grade, eighth‐grade, and Algebra I schools in Mississippi during the 2004–2007 school years. Through an analysis of publicly available school data, all school groups were found to have been impacted by Katrina, but the nonpoor/nonrural Algebra I schools within a 90‐mile radius of Katrina's point of landfall were affected the greatest. Interesting patterns in eighth‐grade mathematics achievement results were additionally found. Rural schools were impacted to a greater extent than their nonrural counterparts. Several findings in this study were startling and counterintuitive, but this initial analysis into the impact of Katrina on mathematics achievement in Mississippi illustrated that catastrophic natural disasters like Hurricane Katrina can cause more than just physical damage.     

Strategic groups based on marginal rates: An application to the Spanish banking industry

This paper uses Data Envelopment Analysis (DEA) to identify strategic groups (SGs) in the Spanish banking industry. The concept of SG relies on the fact that firms grouped together value inputs and outputs in the same way. As such, they take identical direction when, due to external influences, changes are required. Weights obtained from DEA are extremely useful in the valuation of inputs and outputs. Specifically, by comparing DEA weights pair-wise, i.e. quantifying the variables’ marginal rates (MR), we can obtain a very good representation of the existent trade-off and the relative importance of the two variables.The paper uses MRs obtained through DEA models and, simultaneously, proposes feasible ways to overcome two usual problems with DEA virtual weights, namely: (1) the multiplicity of weights for efficient DMUs; and (2) the inexistence of dual variables for inefficient DMUs.From the empirical point of view, once the MRs are determined, the second stage is to perform Cluster Analysis. We apply Cluster Analysis in two ways: (1) on the basis of the MRs; and (2) following the traditional application by running Cluster Analysis with the original variables. The results obtained show the advantages of using MRs instead of the standard application of Cluster Analysis.Summing up, the concept of SG is reinforced if we use refined methods to determine the existence of SGs. The results of the application of DEA models to observe the presence of SG in the Spanish banking industry offer interesting views on it.     

Privacy-preserving horizontally partitioned linear programs

We propose a simple privacy-preserving reformulation of a linear program whose equality constraint matrix is partitioned into groups of rows. Each group of matrix rows and its corresponding right hand side vector are owned by a distinct private entity that is unwilling to share or make public its row group or right hand side vector. By multiplying each privately held constraint group by an appropriately generated and privately held random matrix, the original linear program is transformed into an equivalent one that does not reveal any of the privately held data or make it public. The solution vector of the transformed secure linear program is publicly generated and is available to all entities.