Academic Resilience in Mathematics and ScienceEurope TIMSS-2019 Data

  1. Francisco Javier García-Crespo 1
  2. Javier Suárez-Álvarez 2
  3. Rubén Fernández-Alonso 3
  4. José Muñiz 4
  1. 1 Universidad Complutense de Madrid
    info

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

  2. 2 University of Massachusetts Amherst
    info

    University of Massachusetts Amherst

    Amherst Center, Estados Unidos

    ROR https://ror.org/0072zz521

  3. 3 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

  4. 4 Universidad Nebrija
    info

    Universidad Nebrija

    Madrid, España

    ROR https://ror.org/03tzyrt94

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Revista:
Psicothema

ISSN: 0214-9915,  1886-144X

Año de publicación: 2022

Volumen: 34

Número: 2

Páginas: 217-225

Tipo: Artículo

DOI: 10.7334/PSICOTHEMA2021.486 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Psicothema

Resumen

Antecedentes: el alumnado académicamente resiliente es aquel que obtiene un alto rendimiento partiendo de una situación socioeconómica desaventajada. Esta investigación pretende identificar los factores personales, escolares y nacionales que están asociados a la resiliencia académica en la Unión Europea (UE). Método: la muestra fue de 96.556 estudiantes de 4º grado de 21 países de la UE participantes en TIMSS-2019. Para el conjunto de la muestra se ajustaron dos modelos de regresión logística multinivel de tres niveles. Resultados: la UE tiene un promedio de 25,67% de alumnado resiliente en matemáticas y 24,16% en ciencias. La confianza de los estudiantes y haber realizado tareas lingüísticas previas a la escuela son las variables con mayor poder predictivo después de tener en cuenta el género y los antecedentes inmigrantes de los estudiantes. Los países europeos analizados compensan en buena medida la situación doblemente desaventajada del alumnado inmigrante. Aquellos países que poseen un mayor porcentaje de alumnado con bajo rendimiento tienen menos estudiantes resilientes. Conclusiones: las políticas educativas de los estados miembros de la UE son capaces de compensar en gran medida las situaciones desfavorecidas de partida. Fundamentalmente aquellas de carácter social como el apoyo al alumnado inmigrante, a la familia o las instituciones educativas.

Referencias bibliográficas

  • Agasisti, T., & Longobardi, S. (2017). Equality of educational opportunities, schools’. Social Indicators Research, 134(3), 917-953. https://doi. org/10.1007/s11205-016-1464-5
  • Agasisti, T., Avvisati, F., Borgonovi, F., & Longobardi, S. (2018). Academic resilience. What schools and countries do to help disadvantaged students succeed in PISA. Education Working Papers, nº 167, OECD Publishing, Paris. www.oecd-ilibrary.org/docserver/e22490ac-en.pdf
  • Agasisti, T., Soncin, M., & Valenti, R. (2016). School factors helping disadvantaged students to succeed: Empirical evidence from four Italian cities. Policy Studies, 37(2), 147-177. https://doi.org/10.1080/ 01442872.2015.1127341
  • Avvisati, F (2020). Measuring socio-economic status in PISA: A review and suggested improvements. Large-scale Assessments in Education, 8. https://doi.org/10.1186/s40536-020-00086-x
  • Caprara, G. V., Barbaranelli, C., Borgogni L, L., & Steca, P. (2003). Efficacy beliefs as determinants of teachers’ job satisfaction. Journal of Educational Psychology, 95(4), 821-832.
  • Clavel, J. G., García-Crespo, F. J., & Sanz San Miguel, L. (2021). Rising above their circumstances: What makes some disadvantaged East and South-East Asian students perform far better in science than their background predicts? Asia Pacific Journal of Education. https://doi.org /10.1080/02188791.2021.1886905
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge. https://doi.org/10.4324/9780203774441
  • Cordero, J. M., & Mateos-Romero, L. (2021). Exploring factors related with resilience in primary education: Evidence from European countries. Studies In Educational Evaluation, 70(1), 101045. https:// doi.org/10.1016/j.stueduc.2021.101045
  • Coronado Hijón, A., & Paneque Folch, M. (2016). Resiliencia al fracaso escolar y desventaja sociocultural: un reto para la orientación y la tutoría [Resilience to school failure and socio-cultural disadvantage: A challence for guidance and tutoring]. Trauma, contexto y exclusión. Promocionando la resiliencia. Grupo Editorial Universitario GEU.
  • De la Cruz, F. (2008). Modelos multinivel [Multi-level models]. Epidemiol, 12(3), 1-8. http://sisbib.unmsm.edu.pe/bvrevistas/epidemiologia/v12_ n3/pdf/a02v12n3.pdf
  • Delpit, L. (1996). The politics of teaching literate discourse. New Press. Edwards, M. S., & Ashkanasy, N. M. (2018). Emotions and failure in academic life: Normalising the experience and building resilience. Journal of Management & Organization, 24(2), 167-188. https://doi. org/10.1017/jmo.2018.20
  • Edwards, M. S., & Ashkanasy, N. M. (2018). Emotions and failure in academic life: Normalising the experience and building resilience. Journal of Management & Organization, 24(2), 167-188. https://doi. org/10.1017/jmo.2018.20
  • Erberber, E., Stephens, M., Mamedova, S., Ferguson, S., & Kroeger, T. (2015). Socioeconomically disadvantaged students who are academically successful: Examining academic resilience crossnationally. IEA’S Policy Brief Series, 5. http://www.iea.nl/policy_briefs.html
  • European Comission (2020). Education and Training Monitor 2020. https:// op.europa.eu/webpub/eac/education-and-training-monitor-2020/en/ chapters/foreword.html#targets
  • Fernández-Alonso, R., & Muñiz, J. (2011). Diseños de cuadernillos para la evaluación de las competencias básicas [Booklet designs for the evaluation of basic skills]. Aula Abierta, 39(2), 3-34.
  • Fernández-Alonso, R., Suárez-Álvarez, J., & Muñiz, J. (2012). Imputación de datos perdidos en las evaluaciones diagnósticas educativas [Imputation methods for missing data in educational diagnostic evaluation]. Psicothema, 24(1), 167-175. http://www.psicothema.com/psicothema.asp?id=3995
  • Fishbein, B., Foy, P., & Yin, L. (2021). TIMSS 2019 User Guide for the International Database. Boston College, TIMSS & PIRLS International Study Center. https://timssandpirls.bc.edu/timss2019/internationaldatabase/
  • Gabrielli, G., Longobardi, S., & Strozza, S. (2021). The academic resilience of native and immigrant-origin students in selected European countries. Journal of Ethnic and Migration Studies, 1-22. https://doi.org/10.1080 /1369183X.2021.1935657
  • García-Crespo, F. J., Fernández-Alonso, R., & Muñiz, J. (2019). Resilient and low performer students: Personal and family determinants in European countries. Psicothema, 31(4), 363-375. https://doi. org/10.7334/psicothema2019.245
  • García-Crespo, F. J., Fernández-Alonso, R., & Muñiz, J. (2021). Academic resilience in European countries: The role of teachers, families, and student profiles. PLoS ONE, 16(7).
  • García-Crespo, F. J., Galián, B., Fernández-Alonso, R., & Muñiz, J. (2019). Educational resilience in reading comprehension: Deteminant factors in PIRLS-Europe. Revista de Educación, 384, 65-89. https://doi. org/10.4438/1988-592X-RE-2019-384-413
  • Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/ hierarchical models. Cambridge University Press.
  • Heckman, J. J., & Rubinstein, Y. (2001). The importance of noncognitive skills: Lessons from the GED testing program. The American Economic Review, 91(2), 145-149.
  • Iñiguez-Berrozpe, T., & Marcaletti, F. (2018). Modelos lineales multinivel en SPSS y su aplicación en investigación educativa [Linear multilevel models in SPSS and its application in educational research]. REIRE Revista d’Innovació i Recerca en Educació, 11(1), 26-40. https://doi. org/10.1344/reire2018.11.118984
  • Jacob, B. A. (2002). Where the boys aren’t: Non-cognitive skills, returns to school and the gender gap in higher education. Economics of Education Review, 21, 589-598.
  • Klassen, R., Wilson, E., Siu, A. F. Y., Hannok, W., Wong, M. W., Wongsri, N., Sonthisap, P., Pibulchol, C., Buranachaitavee, Y., & Jansem, A. (2013). Preservice teachers’ work stress, self-efficacy, and occupational commitment in four countries. European Journal of Psychology, 28(4), 1289-1309. https://doi.org/10.1007/s10212-012-0166-x
  • Lera, M. J., León-Peréz, J. M., & Ruiz-Zorrilla, P. (2021). Adaptation of the Teacher Efficacy Scale to Measure Effective Teachers’ Educational Practices Through Students’ Ratings: A Multilevel Approach. Psicothema, 33(3), 509-517. https://doi.org/10.7334/ psicothema2020.262
  • López-Zambrano, J., Lara Torralbo, J. A., & Romero, C. (2021). Early prediction of student learning performance through data mining: A systematic review. Psicothema, 33(3), 456-465. https://doi.org/10.7334/ psicothema2021.62
  • Martin, M. O., von Davier, M., & Mullis, I. V. (2020). Methods and Procedures: TIMSS 2019 Technical Report. Boston College, TIMSS & PIRLS International Study Center. https://timssandpirls.bc.edu/ timss2019/methods
  • Martín-Lagos, M. D. (2018). Education and inequality: A meta-synthesis after the 50th anniversary of Coleman’s report. Revista de Educación, 380, 186-209. https://doi.org/10.4438/1988-592X-RE-2017-380-377
  • Mullis, I. V., & Martin, M. O. (2017). TIMSS 2019 Assessment Frameworks. Boston College, TIMSS & PIRLS International Study Center. https:// timssandpirls.bc.edu/timss2019/frameworks/
  • Mullis, I. V., Martin, M. O., Foy, P., Kelly, D., & Fishbein, B. (2020). TIMSS 2019 International Results in Mathematics and Science. Boston College, TIMSS & PIRLS International Study. https://timssandpirls. bc.edu/timss2019/international-results/
  • Mullis, I., Martin, M., Foy, P., & Hooper, M. (2017). PIRLS 2016 International Results in Reading. Boston College, TIMSS & PIRLS International Study Center. http://timssandpirls.bc.edu/pirls2016/ international-results/
  • Noftle, E., & R. Robins (2007). Personality predictors of academic outcomes: Big five correlates of GPA and SAT scores. Journal of Personality and Social Psychology, 93(1,) 116-130. https://doi. org/10.1037/0022-3514.93.1.116
  • OECD (2010). PISA 2009 results: Overcoming social background equity in learning opportunities. OECD Publishing, Paris. https://doi. org/10.1787/9789264091504-en
  • OECD (2011a). Does participant in pre-primary education translate into better learning outcomes at school? PISA in Focus nº 1. OECD-ilibrary. http://cort.as/-M3Ms
  • OECD (2011b). How do some students overcome their socio-economic background? PISA in Focus, nº 5. https://www.oecd-ilibrary.org/ education/how-do-some-students-overcome-their-socio-economicbackground_5k9h362p77tf-en
  • OECD (2016). PISA 2015 results: Policies and practices for successful schools (Vol. 2). OECD Publishing, Paris. https://doi. org/10.1787/9789264267510-en
  • OECD (2018). The resilience of students with an immigrant background: Factors that shape well-being, OECD Reviews of migrant education. OECD Publishing, Paris. https://doi.org/10.1787/9789264292093-en
  • OECD (2021a). 21st-Century Readers: Developing Literacy Skills in a Digital World. OECD Publishing, Paris. https://doi.org/10.1787/a83d84cb-en
  • OECD (2021b). Beyond Academic Learning: First Results from the Survey of Social and Emotional Skills. OECD Publishing, Paris. https://doi. org/10.1787/92a11084-en
  • Rutkowski, L., González, E., Joncas, M., & von Davier, M. (2010). International largescale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142-151.
  • Sandoval-Hernández, A., & Białowolski, P. (2016). Factors and conditions promoting academic resilience: A TIMSS based analysis of five Asian education systems. Asia Pacific Education Review, 17, 511-520. https:// doi.org/10.1007/s12564-016-9447-4
  • Santos, M. A., Ferraces, M. J., Godas, A., & Lorenzo, M. M. (2018). Do cooperative learning and family involvement improve variables linked to academic performance? Psicothema, 30(2), 212-217. https://doi. org/10.7334/psicothema2017.311
  • Servicio de Evaluación Educativa (2017). Éxito contra todo pronóstico: el alumnado académicamente resiliente [Success against all odds: Academically resilient students]. Informe Evaluación, 12, 1-8.
  • Snijders, T. A., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling. Sage.
  • Suárez-Alvarez, J., Fernández-Alonso, R., Kyllonen, P.C., De Fruyt, F., Fonseca-Pedrero, E., & Muñiz, J. (2020). Editorial: Bridging the gap between research and policy in fostering social and emotional skills. Frontiers in Psychology, 11, 426. https://doi.org/10.3389/fpsyg.2020.00426
  • Suárez-Álvarez, J. R., Fernández-Alonso, J. Muñiz (2014). Self-concept, motivation, expectations, and socioeconomic level as predictors of academic performance in mathematics. Learning and Individual Differences, 30, 118-123. https://doi.org/10.1016/j.lindif.2013.10.019
  • Tschannen-Moran, M., & Hoy, A. W. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17(7), 783-805. https://doi.org/10.1016/S0742-051X(01)00036-1
  • UNESCO (2021). UNESCO and Sustainable Development Goals. https:// en.unesco.org/sustainabledevelopmentgoals
  • Waxman, H. C., Gray, J. P., & Padrón, Y. N. (2003). Review of research on educational resilience. Center for Research on Education, Diversity & Excellence, University of California.
  • Waxman, H. C., Huang, S. L., & Padron, Y. N. (1997). Motivation and learning environment differences between resilient and nonresilient latino middle school students. Hispanic Journal of Behavioral Sciences, 19(2), 137-155. https://doi.org/10.1177/07399863970192003
  • Yeung, W. J., & Li, H. (2021). Educational resilience among asian children in challenging family environment. Social Indicators Research, 153, 675-685. https://doi.org/10.1007/s11205-019-02143-7
Fuente de los datos: Dialnet