Which factors are associated to fourth grade children’s academic performance?
Article Sidebar
Main Article Content
Abstract
In this paper it is analyzed which factors are associated with the academic performance of fourth grade children, considering variables of the boy or girl, theirschoolenvironment and their family context. The analyzed participants correspond to 25245 fourth level Primary Education students, evaluated by the “Evaluación General de Diagnóstico” in Spain at 2009. The statistical analysis was Multiple Correspondence Analysis. The main results obtained allow us to conclude that there is an association between high performance and non-repetition in school, the taste (quite a lot) for attending school, the language in which the students took the test (assessment in Spanish) and ownership of the school (private). High academic performance is also associated with a parents’ high educational level. In terms of factors associated with an academic performance considered medium, there is a taste for attending school (very happy), the language in which they carried out the evaluations (Valencian and Catalan), the ownership of the school (public) and the family’s educational level (ESO/EGB). Finally, the factors associated with low values of academic performance are identified with little taste for attending school (not at all), repetition of at least one year of primary school,conducting tests in Basque and single-parent homes. No associations between academic performance and the sex of the scholar were detected.
Downloads
Article Details
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
References
Alejandre Casanova, X. (2014). Rendimiento académico, entorno social y titularidad dellas escuelas de educación primaria de la ciudad de Barcelona. Trabajo Final de Máster oficial en Política Social, Treball i Benestar, Universitat Autònoma de Barcelona, 2013 – 2014.
Barca Enríquez, E.y Barca Lozano, A. (2019). rendimiento académico en niñosadoptados: interacción e influencia de variables escolares y conductuales. International Journal of Developmental and Educational Psychology INFAD Revista de Psicología, Nº1 - Monográfico 2, 2019. ISSN: 0214-9877. pp:241-252.
Benzecri, J.P. (1992). Correspondence Analysis Handbook. New York. Marcel Dekker. Greenacre, M. (1993). Correspondence Analysis in Practice. London: Academic Press.
Greenacre, M. (2009). Power transformations in correspondence analysis. Computational Statistics & Data Analysis. Vol. 53, No. 8.
Greenacre, M. and Blasius, J. (2006). Multiple Correspondence Analysis and Related Methods. London: Chapman & Hall/CRC.
Instituto de Evaluación (España). (2010). Evaluación general de diagnóstico 2009. Instituto de Evaluación.
Kassambara A.l y Mundt F.. (2019). factoextra: Extract and Visualize the Results of Mu ltivariate Data Analyses. R package version 1.0.6. https://CRAN.R-project.org/package=factoextr.
Le, S., Josse J., y Husson F.. (2008). FactoMineR: An R Package for Multivariate Anal ysis. Journal of Statistical Software, 25(1), 1-18. 10.18637/jss.v025.i01
Martínez, C., Rúa, A., Redondo, R., Fabra, ME., Núñez, A., y Martín, MJ. (2010). Influencia del nivel educativo de los padres en el rendimiento académico de los estudian tes de ADE. Un enfoque de género. AEDE, 5, 1273-94.
Montes, J. F. C., Castro, B. E. P., & González, M. G. M. (2007). Niveles de estrés y ren dimiento académico en estudiantes de la carrera de Psicología del Centro Universitario d e Los Altos. Revista de Educación y Desarrollo, 77-82.
Navarro, R. E. (2003). El rendimiento académico: concepto, investigación y desarrollo. REICE Revista Electrónica Iberoamericana sobre Calidad, Eficacia y Cambio en Educación, 1(2), 1-15.
RCore Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Santamaría Villar, B. y Valdés Muñoz, M.. (2017). Rendimiento del alumnado de educa ción secundaria obligatoria: influencia delas habilidades sociales yla inteligencia emocional. International Journal of Developmental and Educational Psychology. INFAD Revi sta de Psicología, Nº1 - Monográfico 1, 2017. ISSN: 0214-9877. pp:57-66.
Siegenthaler Hierro, R., Abellán Roselló, L., Badenes-Gasset Presentación, A., y Mercader Ruiz, J. (2019). Motivación temprana haciaelaprendizajeyrendimiento lector: estudio longitudinal. Journal of Developmental and Educational Psychology INFAD Revista de Psicología, Nº1 - Monográfico 2, 2019. ISSN: 0214-9877. pp:381-390
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.
Wickham, H., Romain François, Lionel Henry and Kirill Müller (2019). dplyr: A Gram mar of Data Manipulation. R package version 0.8.1. https://CRAN.R-project.org/packag e=dplyr