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Measuring and managing educational performance

  • Review Paper
  • Published:
Journal of the Operational Research Society

Abstract

Performance measures have come to play a central role in the management of the education sector. This paper identifies a number of desirable properties for educational performance measures, whose breach is likely to result in sub-optimal patterns of educational outcomes and resource management. Recent trends in the study of mathematics in schools give particular cause for concern. The paper examines several outstanding issues that require further attention if performance evaluation techniques are to provide reliable measures of school effectiveness.

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References

  • HM Treasury (2002). 2002 Spending Review Public Service Agreements. HM Treasury: London.

  • HM Treasury (2002). 2002 Spending Review. HM Treasury: London.

  • Office for Standards in Education (1995). The OFSTED Handbook — Guidance on the Inspection of Secondary Schools. TSO: London.

  • Gillborn D and Youdell D (1999). Rationing Education: Policy, Practice, Reform and Equity. Open UP: Buckingham.

    Google Scholar 

  • Department for Education and Skills (2002). Education and Skills: Delivering Results. DfES: London.

  • Mayston DJ (1992). School Performance Indicators and Performance Related Pay. Assistant Masters and Mistresses Association: London.

    Google Scholar 

  • Department for Education and Skills (2002). School and College (Post 16) Performance Tables 2001. DfES: London.

  • Department for Education and Skills (2003). Secondary School Performance Tables 2002. DfES: London.

  • Assessment and Qualifications Alliance (2002). GCE Interboard Statistics — Advanced Level 1990–2002. AQA: Guildford.

  • Roberts G (2002). Set for Success: The Supply of People with Science, Technology, Engineering and Mathematics Skills. HM Treasury: London.

    Google Scholar 

  • Department for Education and Employment (1998). Fair Funding. DfEE: London.

  • Arrow KJ (1973). Higher education as a filter. J Public Econ 2: 193–216.

    Article  Google Scholar 

  • Todd K . (2000). An Historical Study of the Correlation Between GCE Advanced Level Grades and the Subsequent Academic Performance of Well-Qualified Students in a University Engineering Department. University of York: York.

    Google Scholar 

  • Thomson A (2002). GCSEs are route to HE expansion. Times Higher Ed Sup, 22 February.

  • Jesson D, Mayston DJ and Smith PC (1987). Performance assessment in the education sector: educational and economic perspectives. Oxford Rev Educ 13: 249–266.

    Article  Google Scholar 

  • Mayston DJ and Jesson D (1988). Developing models of educational accountability. Oxford Rev Educ 14: 321–340.

    Article  Google Scholar 

  • Jesson D (2002). Value Added and the Benefits of Specialism. Technology College Trust: London.

    Google Scholar 

  • Jesson D and Gray J (1991). Slants on slopes: using multi-level models to investigate differential school effectiveness and its impact on pupils' examination results. School Effectiveness School Improvement 2: 230–247.

    Article  Google Scholar 

  • Atkinson AB (1970). The measurement of inequality. J Econ Theory 2: 244–263.

    Article  Google Scholar 

  • Becker G (1985). Human Capital. Chicago University Press: Chicago.

    Google Scholar 

  • Cohn E and Addison J . (1998). The economic returns to lifelong learning. Education Econ 6: 309–346.

    Article  Google Scholar 

  • Belfield C (2000). Economic Principles for Education. Edward Elgar: Cheltenham.

    Google Scholar 

  • Mayston DJ and Smith P (1990). Analysing the need to spend on education. J Opl Res Soc 41: 125–131.

    Article  Google Scholar 

  • Mayston DJ (1996). Educational attainment and resource use: mystery or econometric misspecification? Education Econ 4: 127–142.

    Article  Google Scholar 

  • Johnston J . (1984). Econometric Methods, 3rd edn. McGraw-Hill: London.

    Google Scholar 

  • Mayston DJ (2000). The demand for education and the production of local public goods. Discussion Papers in Economics, 2000/50. University of York: York.

    Google Scholar 

  • Hanushek E (1986). The economics of schooling: production and efficiency in public schools. J Econ Lit 24: 1141–1177.

    Google Scholar 

  • Mayston DJ (2002). Tackling the Endogeneity Problem when Estimating the Relationship Between School Spending and Pupil Outcomes. DfES Research Report RR328. DfES: London.

    Google Scholar 

  • Aigner D, Lovell AK and Schmidt P (1977). Formulation and estimation of stochastic frontier production function models. J Econometrics 6: 21–37.

    Article  Google Scholar 

  • Smith DJ and Tomlinson S (1989). The School Effect. Policy Studies Institute: London.

    Google Scholar 

  • Mayston DJ and Jesson D (1999). Linking Educational Resourcing with Enhanced Educational Outcomes. DfEE Research Report RR179. DfEE: London.

    Google Scholar 

  • Goldstein H (1995). Multilevel Statistical Models, 2nd edn. Arnold: London.

    Google Scholar 

  • Charnes A, Cooper WW and Rhodes E (1978). A Data Envelopment Approach to Evaluation of the Program Follow Through Experiements in US Public School Education. Management Science Research Report 432. Carnegie-Mellon University: Pittsburgh.

    Google Scholar 

  • Bessent A, Bessent W, Kennington J and Reagan B (1982). An application of mathematical programming to assess productivity in the Houston independent school district. Mngt Sci 28: 1355–1367.

    Article  Google Scholar 

  • Desai A and Schinnar AP (1990). Technical issues in measuring scholastic improvement due to compensatory education programs. Socio-Economic Plann Sci 24: 143–153.

    Article  Google Scholar 

  • McCarty TA and Yaisawarng S (1993). Technical efficiency in New Jersey school districts. In: Fried HO, Lovell CAK and Shelton S (eds). The Measurement of Productive Efficiency. Oxford University Press: Oxford, pp 271–287.

    Google Scholar 

  • Worthington A (2001). An empirical survey of frontier efficiency measurement techniques in education. Education Econ 9: 245–268.

    Article  Google Scholar 

  • Charnes A and Cooper WW (1985). Preface to topics in data envelopment analysis. Ann Opns Res 2: 59–94.

    Article  Google Scholar 

  • Orme C and Smith P (1996). The potential for endogeneity bias in data envelopment analysis. J Opl Res Soc 47: 73–83.

    Article  Google Scholar 

  • Gravelle H and Rees R (1992). Microeconomics, 2nd edn. Longman: Harlow.

    Google Scholar 

  • Varian H (1992). Microeconomic Analysis, 3rd edn. Norton: New York.

    Google Scholar 

  • Shephard RW (1970). Theory of Cost and Production Functions. Princeton University Press: Princeton, NJ.

    Google Scholar 

  • Charnes A, Cooper WW and Rhodes E (1978). Measuring the efficiency of decision making units. Eur J Opl Res 2: 429–444.

    Article  Google Scholar 

  • Cooper WW, Seiford L and Tone K (2000). Data Envelopment Analysis. Kluwer: Boston.

    Google Scholar 

  • Berndt ER (1991). The Practice of Econometrics. Addison-Wesley: New York.

    Google Scholar 

  • Chambers RG (1988). Applied Production Analysis. Cambridge University Press: Cambridge.

    Google Scholar 

  • Banker RD, Charnes A and Cooper WW (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Mngt Sci 30: 1078–1092.

    Article  Google Scholar 

  • Henderson JM and Quandt RE (1980). Microeconomic Theory. McGraw-Hill: New York.

    Google Scholar 

  • Department for Education and Employment (2000). Setting Targets. DfEE: London.

  • Deprins D, Simar L and Tulkens H (1984). Measuring labor-efficiency in post offices. In: Marchand M, Pestieau P and Tulkens H (eds). The Performance of Public Enterprises: Concepts and Measurement. Elsevier: Amsterdam, pp 243–267.

    Google Scholar 

  • Farrell MJ (1957). The measurement of productive efficiency. J Roy Stat Soc 120: 11–282.

    Google Scholar 

  • Cooper WW, Park KS and Pastor JT (1999). RAM: a range adjusted measure of inefficiency for use with additive models and relations to other models and measures in DEA. J Productivity Analy 11: 5–42.

    Article  Google Scholar 

  • Mayston DJ (1996). Capital and labour markets for health. In: Culyer AJ and Wagstaff A (eds). Reforming Health Care Systems. Edward Elgar: Cheltenham, pp 104–133.

    Google Scholar 

  • Fare R and Grosskopf S (1996). Intertemporal Production Frontiers: With Dynamic DEA. Kluwer: Boston.

    Book  Google Scholar 

  • Pedraja-Chaparro F, Salinas-Jimenez P and Smith P (1997). On the role of weight restrictions in data envelopment analysis. J Productivity Anal 8: 215–230.

    Article  Google Scholar 

  • Mayston DJ (1985). Non-profit performance indicators in the public sector. Financial Accountability Mngt 1: 51–74.

    Article  Google Scholar 

  • Mittag H-J and Rinne H (1993). Statistical Methods of Quality Assurance. Chapman & Hall: London.

    Google Scholar 

  • Quality Assurance Agency (2000). Subject Review Handbook. QAA: Gloucester.

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Authors and Affiliations

  1. University of York, York, UK

    D J Mayston

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  1. D J Mayston
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Correspondence to D J Mayston.

Additional information

2The author is Professor of Public Sector Economics, Finance and Accountancy, and Director of the Centre for Performance Evaluation and Resource Management, at the University of York.

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Mayston, D. Measuring and managing educational performance. J Oper Res Soc 54, 679–691 (2003). https://doi.org/10.1057/palgrave.jors.2601576

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  • DOI: https://doi.org/10.1057/palgrave.jors.2601576

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