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Analysis of the Well-Being Levels of Students in Spain and Finland through Interval Multiobjective Linear Programming

Author

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  • Sandra González-Gallardo

    (Department of Applied Economics (Mathematics), University of Málaga, Calle Ejido 6, 29071 Málaga, Spain
    These authors contributed equally to this work.)

  • Ana B. Ruiz

    (Department of Applied Economics (Mathematics), University of Málaga, Calle Ejido 6, 29071 Málaga, Spain
    These authors contributed equally to this work.)

  • Mariano Luque

    (Department of Applied Economics (Mathematics), University of Málaga, Calle Ejido 6, 29071 Málaga, Spain
    These authors contributed equally to this work.)

Abstract

To study the reasons of the low academic performance of students in Spain, authorities must consider emotional dimensions, such as well-being, which directly affect their learning achievement. Furthermore, it would be interesting to compare Spanish students with students from Finland, which stand out in international rankings. We analyze how to promote students’ well-being in Spain as a mechanism to enhance their academic achievement. Using data from PISA 2018, four indicators are used to measure well-being according to variables describing the students’ context. By means of econometric techniques, interval multiobjective linear programming problems are formulated for Spain and Finland and solved through a new methodological scheme proposed in this paper, assuring the generation of possibly and necessarily efficient solutions in interval multiobjective linear programming. The purpose is to determine which aspects would allow the best possible well-being to be reached. We found several differences between the students achieving optimal compromise levels in each country, and we analyzed how the improvement of one indicator might affect the remaining aspects of well-being. Spanish students can further enhance their well-being compared to Finnish students. Furthermore, the lowest improvement rate is associated with the bullying index, especially in Finland, highlighting the need to promote anti-bullying measures.

Suggested Citation

  • Sandra González-Gallardo & Ana B. Ruiz & Mariano Luque, 2021. "Analysis of the Well-Being Levels of Students in Spain and Finland through Interval Multiobjective Linear Programming," Mathematics, MDPI, vol. 9(14), pages 1-27, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:14:p:1628-:d:591830
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Boris Pérez-Cañedo & José Luis Verdegay & Eduardo René Concepción-Morales & Alejandro Rosete, 2020. "Lexicographic Methods for Fuzzy Linear Programming," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    3. Gabriel R. Bitran, 1980. "Linear Multiple Objective Problems with Interval Coefficients," Management Science, INFORMS, vol. 26(7), pages 694-706, July.
    4. Henriques, C.O. & Luque, M. & Marcenaro-Gutierrez, O.D. & Lopez-Agudo, L.A., 2019. "A multiobjective interval programming model to explore the trade-offs among different aspects of job satisfaction under different scenarios," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 35-46.
    5. Luque, M. & Marcenaro-Gutiérrez, O.D. & López-Agudo, L.A., 2015. "On the potential balance among compulsory education outcomes through econometric and multiobjective programming analysis," European Journal of Operational Research, Elsevier, vol. 241(2), pages 527-540.
    6. Robert J. Barro, 2001. "Human Capital and Growth," American Economic Review, American Economic Association, vol. 91(2), pages 12-17, May.
    7. Henriques, C.O. & Inuiguchi, M. & Luque, M. & Figueira, J.R., 2020. "New conditions for testing necessarily/possibly efficiency of non-degenerate basic solutions based on the tolerance approach," European Journal of Operational Research, Elsevier, vol. 283(1), pages 341-355.
    8. Inuiguchi, Masahiro & Kume, Yasufumi, 1991. "Goal programming problems with interval coefficients and target intervals," European Journal of Operational Research, Elsevier, vol. 52(3), pages 345-360, June.
    9. Oliveira, Carla & Antunes, Carlos Henggeler, 2007. "Multiple objective linear programming models with interval coefficients - an illustrated overview," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1434-1463, September.
    10. J W Chinneck & K Ramadan, 2000. "Linear programming with interval coefficients," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(2), pages 209-220, February.
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    Cited by:

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    3. María Luisa Nolé & David Soler & Juan Luis Higuera-Trujillo & Carmen Llinares, 2022. "Optimization of the Cognitive Processes in a Virtual Classroom: A Multi-objective Integer Linear Programming Approach," Mathematics, MDPI, vol. 10(7), pages 1-20, April.

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