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    DEA and Education

    On this page, we have provided all the information about DEA and Education that may be interesting and useful to users. This page contains the following sections:

    1. Background

    2. Key papers

    3. New interesting papers

    4. Related subject

    5. Statistics

    6. References







    Education is the application that attracts the most attention in the early days of DEA development. Frontier efficiency measurement techniques have been applied to many different types of education institutions. These include primary and secondary schools (Bessent 1982; Deller and Rudnicki 1993; Chalos and Cherian 1995), universities (Athanassopoulos and Shale 1997), university departments (Sinuany-Stern 1994; Johnes and Johnes 1993; Beasley 1990; Madden 1997) and training and enterprise councils (Cubbin and Zamani 1996). The primary frontier technique employed in assaying the efficiency of education programs has been the data envelopment analysis or DEA approach (Charnes, Cooper and Rhodes, 1981; Diamond and Medewitz 1990; Ray 1991; Thanassoulis and Dunstan 1994).
    Perhaps the best-known and earliest work in the area of measuring education production was conducted by Bessent (1982). Employing the well-known Charnes, Cooper and Rhodes (1978) constant returns-to-scale DEA model, they examined the productive efficiency of Houston’s 241 school districts. Bessent was one of the first studies to point out some advantages of DEA over previously used techniques. These included the incorporation of multiple outputs, the fact that a parametric functional form does not have to be specified for the production function, and the ability to identify sources of inefficiency for individual schools. In addition, Bessent enshrined the use of standardised test scores as the measure of educational attainment, incorporated issues relating to local, state and federal funding, and proxied the quality of teaching inputs with teaching experience, training and qualifications. Finally, Bessent cogently listed the major problems found in educational efficiency studies:
    (1) obtaining data to specify adequate input measures, (2) obtaining data to specify outputs that were not limited to cognitive test results, and (3) difficulties in communicating the results of a complex quantitative process to those affected by the results.
    Generally, there are two major streams of literature in the DEA and education. The one of them studies the efficiency of higher education. This stream includes Bessent (1983), Sinuanystern (1994), Arcelus and Coleman (1997), Johnes (2006) and Johnes and Yu (2008). The other stream examines that of basic education, including Ray (1991), Kirjavainen and Loikkanen (1998), and Bradley (2001). For measuring the efficiency of education, different authors apply different specifications of DEA model. Diversity of the applied models primarily is determined by various input-output combinations. Worthington (2008) has investigated an empirical survey of frontier efficiency measurement techniques in education and has presented various inputs and outputs in the primary education studies.


    This section introduces key papers in the DEA and Education. These papers have had a significant impact on the DEA and its application in Education sector.
    Evaluating program and managerial efficiency: An application of data envelopment analysis to Program Follow Through
    Authors: Charnes, A., Cooper, W.W., and Rhodes, E.
    Journal: Management Science
    Published: 1981

    Abstract: A model for measuring the efficiency of Decision Making Units (=DMU's) is presented, along with related methods of implementation and interpretation. The term DMU is intended to emphasize an orientation toward managed entities in the public and/or not-for-profit sectors. The proposed approach is applicable to the multiple outputs and designated inputs which are common for such DMU's. A priori weights, or imputations of a market-price-value character are not required. A mathematical programming model applied to observational data provides a new way of obtaining empirical estimates of extrernal relations—such as the production functions and/or efficient production possibility surfaces that are a cornerstone of modern economics. The resulting extremal relations are used to envelop the observations in order to obtain the efficiency measures that form a focus of the present paper. An illustrative application utilizes data from Program Follow Through (=PFT). A large scale social experiment in public school education, it was designed to test the advantages of PFT relative to designated NFT (=Non-Follow Through) counterparts in various parts of the U.S. It is possible that the resulting observations are contaminated with inefficiencies due to the way DMU's were managed en route to assessing whether PFT (as a program) is superior to its NFT alternative. A further mathematical programming development is therefore undertaken to distinguish between “management efficiency” and “program efficiency.” This is done via procedures referred to as Data Envelopment Analysis (=DEA) in which one first obtains boundaries or envelopes from the data for PFT and NFT, respectively. These boundaries provide a basis for estimating the relative efficiency of the DMU's operating under these programs. These DMU's are then adjusted up to their program boundaries, after which a new inter-program envelope is obtained for evaluating the PFT and NFT programs with the estimated managerial inefficiencies eliminated. The claimed superiority of PFT fails to be validated in this illustrative application. Our DEA approach, however, suggests the additional possibility of new approaches obtained from PFT-NFT combinations which may be superior to either of them alone. Validating such possibilities cannot be done only by statistical or other modelings. It requires recourse to field studies, including audits (e.g., of a U.S. General Accounting Office variety) and therefore ways in which the results of a DEA approach may be used to guide such further studies (or audits) are also indicated.


    An application of mathematical programming to assess productivity in the Houston independent school district
    Authors: Bessent, A., Bessent, W., Kennington, J & Reagan, B.
    Journal: Management Science
    Published: 1982
    Abstract: A school may be viewed as an enterprise in which the professional staff provide the operating conditions for converting quantifiable resources or inputs into pupil learning (outputs). The resources are determined by budgets, teacher assignments, and student assignments while learning is determined by various outputs scored according to standardized tests such as the Iowa Test of Basic Skills. Following the work of Charnes, Cooper, and Rhodes (Charnes, A., W. W. Cooper, E. Rhodes. 1981. Evaluating program and managerial efficiency: an application of data envelopment analysis to program follow through. Management Sci.27 (6) 668–697.), we use a ratio definition of efficiency that takes account of all outputs and inputs without requiring a priori specification of weights. Instead a series of mathematical programs are applied to determine “virtual multipliers” from actual data. The multipliers produce values that can be regarded as the “most favorable weights” for each school being evaluated. If the resulting optimum virtual multipliers for a given school yield an efficiency ratio of one, then that school is said to be efficient. If the ratio is less than one then that school is said to be inefficient relative to the other schools in the analysis. The ratio is also accorded operational significance—it is not merely an index number—so that the resulting values and the associated virtual multipliers make it possible to locate where improvements may be made along with their relative magnitudes. This analysis was applied to 167 elementary schools in the Houston Independent School District. Of these schools, 78 were found to be inefficiently utilizing their resources as compared to the 89 efficient schools. Based on this pilot study, an Educational Productivity Council has been formed at the University of Texas at Austin to provide an annual analysis for all of its member schools. At present 285 Texas schools in 22 districts are scheduled for participation in the annual analysis as described in this investigation.


    Evaluation of educational-program proposals by means of DEA
    Authors: Bessent A.M., Bessent E.W., Charnes A, Cooper W.W., Thorogood N.C.
    Journal: Educational Administration Quarterly
    Published: 1983
    Abstract: A new application of DEA (Data Envelopment Analysis) is examined for evaluating the efficiency of occupational-technical programs in a comprehensive community college. This includes extensions of DEA for use in evaluating new programs that might be introduced along with possible combinations of old programs. Emphasis is placed on the relative efficiency aspects of DEA so that consequences for the efficiency ofprograms other than those being considered can be taken into account. Uses by the director of San Antonio College are described and placed in a context of the other elements that entered into her decisions. In conclusion, possible further improvements in DEA are discussed along with the kinds of research needed to achieve them.




    Comparing university departments
    Author: Beasley, J. E.
    Journal: OMEGA Journal of Management Science
    Published: 1990
    Abstract: In this paper we present a quantitative model for comparing university departments concerned with the same discipline. This model is based upon ideas drawn from data envelopment analysis. Computational results are given for chemistry and physics departments in the United Kingdom.









    Academic departments efficiency via DEA
    Authors: Sinuanystern Z, Mehrez A, Barboy A.
    Journal: Computers & Operations Research
    Published: 1994
    Abstract: This paper presents a case study where academic departments at Ben-Gurion University were evaluated via the Data Envelopment Analysis using the CCR model. Extensive post analyses were performed in several directions. First various sets of data were used to identify efficient and inefficient departments. New efficiency measures am suggested in relation to the reference set included in the analyses of academic departments. We measured the efficiency of departments to other departments within the same school. We applied cluster analyses to divide the departments into several sets; and the discriminant analysis to test the match of the efficiency/inefficiency division of the CCR ratio. We further tested organizational changes where an inefficient department was closed and joins other departments. Finally we compared the CCR model to the pure economic approach-the cost per student ratio.



    Assessing the comparative efficiency of higher education institutions in the UK by mean of data envelopment analysis
    Authors: Athanassopoulos, A.D. and Shale, E.
    Journal: Education Economics
    Published: 1997
    Abstract: In this paper, we examine the comparative efficiency of higher education institutions in the UK. The governmental initiatives of the last decade within this sector have given emphasis to issues of accountability, value for money and cost control. The reporting of various statistics regarding the universities' activities only fully achieves its potential value if it is used to define comprehensive concepts of performance and goal achievements informed by the institutions' missions. In that spirit, we propose concepts of cost and outcome efficiency in order to gain further insights into the universities' operations. Data envelopment analysis and its recent advances were used to assess the two types of efficiency. The application of the methodology to 45 universities in the UK revealed a subset of six institutions that showed satisfactory performance across alternative efficiency tests.



    Efficiency differences of Finnish senior secondary schools: an application of DEA and Tobit analysis
    Authors: Kirjavainen T., Loikkanen H.A.
    Journal: Economics of Education Review
    Published: 1998
    Abstract: We studied efficiency differences among Finnish senior secondary schools by Data Envelopment Analysis (DEA). Four model variants were used. Average efficiencies in the most extensive models
    were 82-84 per cent. When parents’ educational level was treated as an additional input, average efficiency increased to 91 per cent. The efficiency rankings of schools changed to some extent when simplest quantitative inputs and outputs were augmented by measures of teacher quality and national matriculation examination results. As a second stage after DEA analysis, we explained the degree of inefficiency (l00-efficiency score) by a statistical Tobit model. Schools with small classes and heterogenous student bodies were inefficient whereas school size did not affect efficiency. Surprisingly, private schools were inefficient relative to public schools. When parents’ educational level was only included in the Tobit model, it affected efficiency positively. [JEL 1211 0 1998 Elsevier Science Ltd. All rights reserved.


    The effect of competition on the efficiency of secondary schools in England
    Authors: Bradley S, Johnes G, Millington J.
    Journal: European Journal of Operational Research
    Published: 2001
    Abstract: In this paper we calculate the technical efficiencies, based upon multiple outputs – school exam performance and attendance rates – of all secondary schools in England over the period 1993–1998. We then estimate models to examine the determinants of efficiency in a particular year, and the determinants of the change in efficiency over the period. Our results suggest that the greater the degree of competition between schools the more efficient they are. The strength of this effect has also increased over time which is consistent with the evolution of the quasi-market in secondary education. Competition is also found to be an important determinant of the change in efficiency over time. There is, however, some evidence of conditional convergence between schools.



    The using of the DEA technique in the Education sector is increasing over time. This section introduces new articles that present a new method or significant results in this area.








    Evaluation of Performance Based Appraisal System in Higher Education Sector using DEA and AHP
    Authors: Dr. Neeta Saxena, Dr. Neha Jain
    Journal: International Journal on Recent and Innovation Trends in Computing and Communication
    Published: 2018
    Abstract: There is a broad interest in the study of schemes for the measurement of the efficiency of the higher education sector, which generates demand but at the same time is controversial because of the complexity of the problem. Performance evaluation in Higher Education institutions is one of the essential activities in teaching and learning procedure. This problem is associated with the highly combinatorial characteristics that occur when facing the selection of the proper combination of the attributes, namely inputs and outputs. This study proposes an integrated approach to measure performance based appraisal system (PBAS) in higher educational institutions combining Analytic Hierarchy Process (AHP) with Data Envelopment Analysis (DEA).The AHP allows consideration of the varying importance of each criterion of teaching performance, while DEA enables to the comparison of teachers on teaching as perceived by students with a view to identifying the scope for improvement by each teacher.

    A Research Framework for Data Envelopment Analysis with Upper Bound on Output to Measure Efficiency Performance of Higher Learning Institution in Aceh Province
    Authors: D. Abdullah, Tulus, S. Suwilo, S. Efendi, M. Zarlis, H. Mawengkang
    Journal: International Journal on Advanced Science, Engineering and Information Technology
    Published: 2018
    Abstract: The higher education system in Indonesia can be considered not only as an important source of developing knowledge in the country but also could create favourable living conditions for the country. Therefore, it is not surprising that enrollments in higher education continue to expand. Data envelopment analysis (DEA) is a method to evaluate the technical efficiency of production units which have multiple input and output. The higher learning institution considered in this paper is Min Aceh province of Indonesia. This research framework of this research is DEA, with the bounded output. Accordingly, we present some important differences in efficiency performance of higher education institute. Finally, we will discuss the effort from these departments to become efficient.

    Performance of private higher education institutions in Vietnam: evidence using DEA-based bootstrap directional distance approach with quasi-fixed inputs
    Authors: Renato A. Villano and Carolyn-Dung T. T. Tran
    Journal: Applied Economics
    Published: 2018
    Abstract: Vietnam’s higher education has witnessed substantial improvements since the implementation of the Doi Moi (renovation) policy. One of the significant developments is the promotion of establishment and enhancement of the role of private institutions in national education systems. However, the quest to improve the overall performance of the private higher education institutions remains a big challenge for many stakeholders. We assess the performance of Vietnamese private universities using a data envelopment analysis–based bootstrap directional distance approach with quasi-fixed inputs. The results show that there was a large variation in the efficiency levels of private universities within and between academic years and between metropolitan and other private universities. Our empirical findings provide more insights for educational leaders and policy makers on the performance of private higher education institutions and the implications of privatization of the national higher education system.




    In this section, we list a series of selected descriptive statistics involving the numbers and distributions of papers, journals and keywords of DEA and Education related articles during the years 1983 to 2018.

    1. Statistics involving publications by year



    2. Statistics involving publications by journal



    3. Statistics involving keywords used
    The following table lists the most popular keywords by number of publications.



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