IDEAS home Printed from https://ideas.repec.org/p/ind/igiwpp/2025-008.html
   My bibliography  Save this paper

When low scores don't tell the full story: A Composite indicator of student achievement

Author

Listed:
  • Japneet Kaur

    (Indira Gandhi Institute of Development Research)

Abstract

This paper introduces a new composite indicator of student achievement, grounded in an axiomatic framework. Unlike conventional measures that assign equal weight to all subjects, our index applies student and subject specific weights, placing greater emphasis on areas where a student performs well. This allows for a more individualized assessment, recognizing strengths in non-core subjects like music, sports, or social sciences. Using test score data from 44,173 students studying in 117 private English medium schools in rural North India, we compare our indices with the traditional average score index. The results show that a substantial proportion of students initially ranked in the bottom quartile move up significantly under our metric, highlighting overlooked talent. The proposed indices CS1 and CS2 markedly increase mean scores from 0.696 (under the original index CS0) to 0.838 and nearly 1.0, respectively, while sharply reducing standard deviations from 1.88 to 0.129 and 0.017.

Suggested Citation

  • Japneet Kaur, 2025. "When low scores don't tell the full story: A Composite indicator of student achievement," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2025-008, Indira Gandhi Institute of Development Research, Mumbai, India.
  • Handle: RePEc:ind:igiwpp:2025-008
    as

    Download full text from publisher

    File URL: http://www.igidr.ac.in/pdf/publication/WP-2025-008.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abdul Razaq Ahmad & Ahmad Ali Seman & Mohd Mahzan Awang & Fadzilah Sulaiman, 2015. "Application of Multiple Intelligence Theory to Increase Student Motivation in Learning History," Asian Culture and History, Canadian Center of Science and Education, vol. 7(1), pages 210-210, March.
    2. Glenn Ellison & Ashley Swanson, 2023. "Dynamics of the Gender Gap in High Math Achievement," Journal of Human Resources, University of Wisconsin Press, vol. 58(5), pages 1679-1711.
    3. Verbunt, Pim & Rogge, Nicky, 2018. "Geometric composite indicators with compromise Benefit-of-the-Doubt weights," European Journal of Operational Research, Elsevier, vol. 264(1), pages 388-401.
    4. Gülşah Batdal Karaduman & Halime Cihan, 2018. "The Effect of Multiple Intelligence Theory on Students’ Academic Success in The Subject of Geometric Shapes in Elementary School," International Journal of Higher Education, Sciedu Press, vol. 7(2), pages 227-227, April.
    5. M. M. Segovia-González & I. Contreras, 2023. "A Composite Indicator to Compare the Performance of Male and Female Students in Educational Systems," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 165(1), pages 181-212, January.
    6. Shorrocks, A F, 1978. "The Measurement of Mobility," Econometrica, Econometric Society, vol. 46(5), pages 1013-1024, September.
    7. Camanho, Ana S. & Stumbriene, Dovile & Barbosa, Flávia & Jakaitiene, Audrone, 2023. "The assessment of performance trends and convergence in education and training systems of European countries," European Journal of Operational Research, Elsevier, vol. 305(1), pages 356-372.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. D’Inverno, Giovanna & Polo, Cristina & Sicilia, Gabriela & Simancas, Rosa, 2025. "International differences in educational equity: An assessment using the Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 99(C).
    2. Gulati, Rachita & Charles, Vincent & Kumar, Sunil, 2024. "School education development index: A meta-frontier range directional measure benefit-of-the-doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    3. Mergoni, Anna & Emrouznejad, Ali & De Witte, Kristof, 2025. "Fifty years of Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 326(3), pages 389-412.
    4. Stumbrienė, Dovilė & Ruiz, José L. & Sirvent, Inmaculada, 2025. "Towards gender equality in education: Different strategies to improve subnational performance of European countries using data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 98(C).
    5. Laetitia Comminges & Arnak Dalalyan, 2012. "Minimax Testing of a Composite null Hypothesis Defined via a Quadratic Functional in the Model of regression," Working Papers 2012-19, Center for Research in Economics and Statistics.
    6. Jørn Rattsø & Hildegunn E. Stokke, 2011. "Accumulation of education and regional income growth: Limited human capital effects in Norway," Working Paper Series 11211, Department of Economics, Norwegian University of Science and Technology.
    7. Duro, Juan Antonio, 2013. "International mobility in carbon dioxide emissions," Energy Policy, Elsevier, vol. 55(C), pages 208-216.
    8. Jolakoski, Petar & Pal, Arnab & Sandev, Trifce & Kocarev, Ljupco & Metzler, Ralf & Stojkoski, Viktor, 2023. "A first passage under resetting approach to income dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    9. Satya R. Chakravarty & Nachiketa Chattopadhyay & Nora Lustig & Rodrigo Aranda, 2020. "Measuring Directional Mobility: The Bartholomew and Prais-Bibby Indices Reconsidered," Research on Economic Inequality, in: Inequality, Redistribution and Mobility, volume 28, pages 75-96, Emerald Group Publishing Limited.
    10. Irene Brunetti & Davide fiaschi & Lisa Gianmoena, 2013. "An Index of Growth Rate Volatility: Methodology and an Application to European Regions," Discussion Papers 2013/169, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    11. David Cantarero & Marta Pascual, 2005. "Regional Differences In Health In Spain - An Empirical Analysis," ERSA conference papers ersa05p551, European Regional Science Association.
    12. David Aristei & Cristiano Perugini, 2022. "Credit and income mobility in Russia," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(3), pages 639-669, September.
    13. Danny Quah, 1996. "Twin Peaks: Growth and Convergence in Models of Distribution Dynamics," CEP Discussion Papers dp0280, Centre for Economic Performance, LSE.
    14. Fiaschi, Davide & Lavezzi, Andrea Mario, 2007. "Nonlinear economic growth: Some theory and cross-country evidence," Journal of Development Economics, Elsevier, vol. 84(1), pages 271-290, September.
    15. Sanghamitra Bandyopadhyay, 2016. "The Vulnerable Are Not (Necessarily) the Poor," Research on Economic Inequality, in: Inequality after the 20th Century: Papers from the Sixth ECINEQ Meeting, volume 24, pages 29-57, Emerald Group Publishing Limited.
    16. Burhan Can Karahasan, 2020. "Can neighbor regions shape club convergence? Spatial Markov chain analysis for Turkey," Letters in Spatial and Resource Sciences, Springer, vol. 13(2), pages 117-131, August.
    17. Lidia Ceriani & Sergio Olivieri & Marco Ranzani, 2023. "Housing, imputed rent, and household welfare," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 21(1), pages 131-168, March.
    18. Aleksandra Urbaniec, 2012. "Life cycle income and consumption patterns in transition," EcoMod2012 4457, EcoMod.
    19. Sanghamitra Bandyopadhyay & Gaston Yalonetzky, 2016. "An individual-based approach to measurement of multiple-period mobility for nominal and ordinal variables," Working Papers 65, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    20. Claudia Curi & Paolo Guarda & Valentin Zelenyuk, 2011. "Changes in bank specialisation: comparing foreign subsidiaries and branches in Luxembourg," BCL working papers 67, Central Bank of Luxembourg.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • P36 - Political Economy and Comparative Economic Systems - - Socialist Institutions and Their Transitions - - - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ind:igiwpp:2025-008. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Shamprasad M. Pujar (email available below). General contact details of provider: https://edirc.repec.org/data/igidrin.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.