IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03896378.html
   My bibliography  Save this paper

Évaluer l’action éducative des lycées à travers les indicateurs de valeur ajoutée des lycées : quand le « bruit » s’immisce dans l’administration de la preuve

Author

Listed:
  • Fernando Núñez-Regueiro

    (LaRAC - Laboratoire de Recherche sur les Apprentissages en Contexte - UGA - Université Grenoble Alpes)

  • Pascal Bressoux

    (LaRAC - Laboratoire de Recherche sur les Apprentissages en Contexte - UGA - Université Grenoble Alpes)

Abstract

Chaque année, le ministère de l'Éducation nationale publie des indicateurs de valeur ajoutée des lycées (IVAL) visant à mesurer l'efficacité des actions éducatives. Conçus comme outils de pilotage fiables, ces IVAL jouent un rôle décisionnel important dans le travail des équipes éducatives. Pourtant, les IVAL sont limités par la non-prise en compte d'une erreur d'échantillonnage qui confond l'action des lycées avec du « bruit » statistique (i.e., les effets du hasard). Retraçant l'historique de ces indicateurs-depuis leurs origines dans la recherche sur les effets-établissement, jusqu'à leur diffusion en France-, cette étude montre en quoi cette non-prise en compte de l'erreur d'échantillonnage pose un problème de mesure qui contrarie une évaluation fiable de l'action éducative. Pour pallier cette difficulté, des stratégies d'estimation alternatives sont proposées. La pertinence de cette critique est illustrée à travers l'étude de 112 lycées de l'académie de Grenoble et de leur action éducative sur la réussite au baccalauréat.

Suggested Citation

  • Fernando Núñez-Regueiro & Pascal Bressoux, 2022. "Évaluer l’action éducative des lycées à travers les indicateurs de valeur ajoutée des lycées : quand le « bruit » s’immisce dans l’administration de la preuve," Post-Print hal-03896378, HAL.
    • Handle: RePEc:hal:journl:hal-03896378
    DOI: 10.3917/rfs.632.0257
    Note: View the original document on HAL open archive server: https://hal.science/hal-03896378
    as

    Download full text from publisher

    File URL: https://hal.science/hal-03896378/document
    Download Restriction: no
    File URL: https://libkey.io/10.3917/rfs.632.0257?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mingliang Li, 2007. "Bayesian Proportional Hazard Analysis of the Timing of High School Dropout Decisions," Econometric Reviews, Taylor & Francis Journals, vol. 26(5), pages 529-556.
    2. Cunha, Jesse M. & Miller, Trey, 2014. "Measuring value-added in higher education: Possibilities and limitations in the use of administrative data," Economics of Education Review, Elsevier, vol. 42(C), pages 64-77.
    3. Meyer, Robert H., 1997. "Value-added indicators of school performance: A primer," Economics of Education Review, Elsevier, vol. 16(3), pages 283-301, June.
    4. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    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. Aedin Doris & Donal O'Neill & Olive Sweetman, 2019. "Good Schools or Good Students? The Importance of Selectivity for School Rankings," Economics Department Working Paper Series n293-19.pdf, Department of Economics, National University of Ireland - Maynooth.
    2. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    3. Brasington, D. M., 2003. "The supply of public school quality," Economics of Education Review, Elsevier, vol. 22(4), pages 367-377, August.
    4. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    5. David Brasington & Don Haurin, 2005. "Capitalization of Parent, School, and Peer Group Components of School Quality into House Price," Departmental Working Papers 2005-04, Department of Economics, Louisiana State University.
    6. Temple, Judy A., 1998. "Recent Clinton Urban Education Initiatives and the Role of School Quality in Metropolitan Finance," National Tax Journal, National Tax Association, vol. 51(n. 3), pages 517-29, September.
    7. Arpino, Bruno & Varriale, Roberta, 2009. "Assessing the quality of institutions’ rankings obtained through multilevel linear regression models," MPRA Paper 19873, University Library of Munich, Germany.
    8. Bacalhau, Priscilla & Mattos, Enlinson & Ponczek, Vladimir Pinheiro, 2019. "College quality signaling and individual performance: effects on labor market outcomes after graduation," Textos para discussão 502, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    9. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    10. Magne Mogstad & Joseph P. Romano & Azeem Shaikh & Daniel Wilhelm, 2020. "Inference for Ranks with Applications to Mobility across Neighborhoods and Academic Achievement across Countries," NBER Working Papers 26883, National Bureau of Economic Research, Inc.
    11. Alejandro Arenas Alzate, 2021. "Mejores colegios en Colombia: efecto de las condiciones socioeconómicas sobre el desempeno escolar," Documentos de Trabajo de Valor Público 19829, Universidad EAFIT.
    12. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Rankings and university performance: A conditional multidimensional approach," European Journal of Operational Research, Elsevier, vol. 244(3), pages 918-930.
    13. repec:lan:wpaper:991 is not listed on IDEAS
    14. repec:mpr:mprres:8135 is not listed on IDEAS
    15. Nils Gutacker & Andrew Street, 2015. "Multidimensional performance assessment using dominance criteria," Working Papers 115cherp, Centre for Health Economics, University of York.
    16. Nils Gutacker & Andrew Street, 2018. "Multidimensional performance assessment of public sector organisations using dominance criteria," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 13-27, February.
    17. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    18. Pia Kjær Kristensen & Raquel Perez-Vicente & George Leckie & Søren Paaske Johnsen & Juan Merlo, 2020. "Disentangling the contribution of hospitals and municipalities for understanding patient level differences in one-year mortality risk after hip-fracture: A cross-classified multilevel analysis in Swed," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
    19. Paolo Berta & Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini, 2016. "Multilevel cluster-weighted models for the evaluation of hospitals," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 275-292, December.
    20. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
    21. Henry W. KINNUCAN & Martin D. SMITH & Yuqing ZHENG & Jose R. LLANES, 2012. "The Effects of No Child Left Behind on Student Performance in Alabama’s Rural Schools," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 12(1), pages 5-24.
    22. Horrace, William C. & Rothbart, Michah W. & Yang, Yi, 2022. "Technical efficiency of public middle schools in New York City," Economics of Education Review, Elsevier, vol. 86(C).

    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:hal:journl:hal-03896378. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.