LA CONSTRUCCIÓN DE HECHOS NUMÉRICOS BÁSICOS: INCIDENCIA DEL SEXO, CURSO Y NIVEL SOCIOECONÓMICO DEL ALUMNO

Alexa von Hagen; Ariel Cuadro; Valeria Giloca

doi:10.22235/cp.v11i2.1348

Authors

Alexa von Hagen IDEALAB PhD Program. University of Potsdam. Germany Macquarie University. Australia
Ariel Cuadro Facultad de Psicología, Universidad Católica del Uruguay
Valeria Giloca Facultad de Psicología, Universidad Católica del Uruguay

DOI:

https://doi.org/10.22235/cp.v11i2.1348

Keywords:

math computation, math facts, sex, socioeconomic status

Abstract

Worldwide students from low socioeconomic status (SES) have been shown to present an academic disadvantage with respect to their mathematical abilities. In order to approach this problem, details of the characteristics in different school levels, students of different sex and different mathematical subskills are needed. To our knowledge, few studies have explored the interaction of these factors in the same sample of participants. Therefore, we aim to analyse the influence of SES and sex on the addition, subtraction and multiplication math facts (MF) skills of a sample of 619 primary school students from year 2 to 6. Besides confirming the socioeconomic disadvantage in all school years and in students of both sexes, our results reveal a higher performance of boys over girls only in medium to higher SES and in multiplication MF. Future research is needed to investigate this unexpected result.

Downloads

Download data is not yet available.

References

Agirdag, O., Van Houtte, M., & Van Avermaet, P. (2012). Why does the ethnic and socio-economic composition of schools influence math achievement? The role of sense of futility and futility culture. European Sociological Review, 28(3), 366-378.doi: 10.1093/esr/jcq070

Blums, A., Belsky, J., Grimm, K., & Chen, Z. (2016). Building Links Between Early Socioeconomic Status, Cognitive Ability, and Math and Science Achievement. Journal of Cognition and Development, 18(1), 16-40. doi: 10.1080/15248372.2016.1228652.

Bradley, R. H., & Corwyn, R. F. (2016). Home Life and the Development of Competence in Mathematics: Implications of Research with the HOME Inventory. In B. Blevins-Knabe, A.M.B. Austin (eds.), Early Childhood Mathematics Skill Development in the Home Environment (pp. 29-49). Zurich: Springer International Publishing. doi: 10.1007/978-3-319-43974-7_3.

Cervini, R. (2002). Desigualdades Socioculturales en el Aprendizaje de Matemática y Lengua de la Educación Secundaria en Argentina: Un modelo de tres niveles. Revista Electrónica de Investigación y Evaluación Educativa, 8(2), p.135-158.

Crane, J. (1996). Effects of home environment, SES, and maternal test scores on mathematics achievement. The Journal of Educational Research, 89(5), 305-314. doi: 10.1080/00220671.1996.9941332.

Cuadro, A., & Balbi, A. (2012). Las diferencias socioeconómicas y la lectura: claves para analizar los resultados de las evaluaciones PISA. Neuropsicología Latinoamericana, 4(1), 57-64.

Cuadro, A., & Piquet, A. (2010). Evaluación del lenguaje de niños de diferentes niveles socioeconómicos. The Quarterly Journal of Experimental Psychology, 51(2), 305-320.

Cuadro, A., Barg, G., Navarrete, I., & Suero, M. (2008). Evaluación de las competencias cognitivas y sociales de ninos que han estado en situación de calle. Ciencias Psicológicas II(2), 143-152.

da Rosa Piccolo, L., Arteche, A. X., Fonseca, R. P., Grassi-Oliveira, R., & Salles, J. F. (2016). Influence of family socioeconomic status on IQ, language, memory and executive functions of Brazilian children.Psicologia: Reflexão e Crítica, 29(1), 1. doi: 10.1186/s41155-016-0016-x.

Else-Quest, N. M., Hyde, J. S., &Linn, M. C. (2010). Cross-national patterns of gender differences in mathematics: a meta-analysis. Psychological bulletin, 136(1), 103-127. doi: 10.1037/a0018053.

Friso-van den Bos, I., van der Ven, S. H., Kroesbergen, E. H., & van Luit, J. E. (2013). Working memory and mathematics in primary school children: A meta-analysis. Educational research review, 10, 29-44. doi: 10.1016/j.edurev.2013.05.003

Guo, J., Marsh, H. W., Parker, P. D., Morin, A. J., & Yeung, A. S. (2015). Expectancy-value in mathematics, gender and socioeconomic background as predictors of achievement and aspirations: A multi-cohort study. Learning and Individual Differences, 37, 161-168. doi: 10.1016/j.lindif.2015.01.008.

Jordan, N. C., Kaplan, D., Locuniak, M. N., & Ramineni, C. (2007). Predicting firstgrade math achievement from developmental number sense trajectories. Learning Disabilities Research & Practice, 22(1), 36-46. doi: 10.1111/j.1540-5826.2007.00229.x

Jordan, N. C., Kaplan, D., Nabors Oláh, L., & Locuniak, M. N. (2006). Number sense growth in kindergarten: A longitudinal investigation of children at risk for mathematics difficulties. Child development, 77(1), 153-175.doi: 10.1111/j.1467-8624.2006.00862.x

Lizasoain, L., Joaristi, L., Lukas, J. F., & Santiago, K. (2007). Efectos Contextuales del Nivel Socioeconómico sobre el Rendimiento Académico en la Educación Secundaria Obligatoria en la Comunidad Autónoma Vasca (España). Estudio Diferencial del Nivel Socioeconómico Familiar y del Centro Escolar. Education Policy Analysis Archives, 15(8), 1-35.

Llambí, C., & Piñeyro, L. (2012). Índice de Nivel Socioeconómico (INSE). Montevideo: Cámara de Empresas de Investigación Social y de Mercado del Uruguay (CEISMU). Disponible en http://www.gruporadar.com.uy/01/wp-content/uploads/2012/04/Informe-Nuevo-INSE-2011.pdf

Lundberg, I., Larsman, P., & Strid, A. (2012). Development of phonological awareness during the preschool year: The influence of gender and socio-economic status. Reading and writing, 25(2), 305-320. doi: 10.1007/s11145-010-9269-4.

Mella, O., & Ortiz, I. (1999). Rendimiento escolar. Influencias diferenciales de factores externos e internos. Revista latinoamericana de estudios educativos, 29(1), 69-92.

Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS 2015 International Results in Mathematics. Retrieved from Boston College, TIMSS & PIRLS International Study Center website: http://timssandpirls.bc.edu/timss2015/international-results/

Niklas, F., & Schneider, W. (2013). Home literacy environment and the beginning of reading and spelling. Contemporary Educational Psychology, 38(1), 40-50. doi: 10.1016/j.cedpsych.2012.10.001.

Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., ...& Kesebir, S. (2009). National differences in gender–science stereotypes predict national sex differences in science and math achievement. Proceedings of the National Academy of Sciences, 106(26), 10593-10597.

Organización de las NacionesUnidas para la Educación, la Ciencia y la Cultura (UNESCO) (2016).Informe de resultados terce – tercer studio regional comparative y explicativo – Logros de aprendizaje – Laboratorio Latinoamericano de evaluación de la calidad de la educación – Julio 2015. Recuperado de: http://unesdoc.unesco.org/images/0024/002435/243532S.pdf

Organización para la Cooperación y el Desarrollo Económicos (OECD) (2016).PISA 2015 Resultados Clave. Recuperado de: https://www.oecd.org/pisa/pisa-2015-results-in-focus-ESP.pdf

Palardy, G. J. (2008). Differential school effects among low, middle, and high social class composition schools: A multiple group, multilevel latent growth curve analysis. School Effectiveness and School Improvement, 19(1), 21-49. doi: 10.1080/09243450801936845

Passolunghi, M. C., &Mammarella, I. C. (2012).Selective spatial working memory impairment in a group of children with mathematics learning disabilities and poor problem-solving skills. Journal of learning disabilities, 45(4), 341-350.

Scheiber, C., Reynolds, M. R., Hajovsky, D. B., & Kaufman, A. S. (2015). Gender differences in achievement in a large, nationally representative sample of children and adolescents. Psychology in the Schools, 52(4), 335-348. doi: 10.1002/pits.21827

Singer, V., Cuadro, A., Costa, D., & von Hagen, A. (2014).Evaluación de la eficacia de cálculo matemático: Manual Técnico del Test de Eficacia de Cálculo Matemático (TECA). Montevideo: Grupo Magro Ediciones.

Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of educational research, 75(3), 417-453.

Universidad Católica del Uruguay (UCU) (sin publicar). Base de datos de colegios privados en Montevideo. Montevideo: Universidad Católica del Uruguay (UCU).

Van de Weijer-Bergsma, E., Kroesbergen, E. H., & Van Luit, J. E. (2015). Verbal and visual-spatial working memory and mathematical ability in different domains throughout primary school.Memory & cognition, 43(3), 367-378. doi: 10.3758/s13421-014-0480-4

Vukovic, R. K., &Lesaux, N. K. (2013). The relationship between linguistic skills and arithmetic knowledge.Learning and Individual Differences, 23, 87-91. doi: 10.1016/j.lindif.2012.10.007

Wei, W., Lu, H., Zhao, H., Chen, C., Dong, Q., & Zhou, X. (2012). Gender differences in children’s arithmetic performance are accounted for by gender differences in language abilities. Psychological science, 23(3), 320-330. doi: 10.1177/0956797611427168.

Yarbrough, J. L., Cannon, L., Bergman, S., Kidder-Ashley, P., &McCane-Bowling, S. (2016). Let the Data Speak Gender Differences in Math Curriculum–Based Measurement. Journal of Psychoeducational Assessment. doi: 10.1177/0734282916649122.

Zhou, X., Chen, C., Dong, Q., Zhang, H., Zhou, R., Zhao, H., & Guo, Y. (2006).Event-related potentials of single-digit addition, subtraction, and multiplication.Neuropsychologia, 44(12), 2500-2507. doi: 10.1016/j.neuropsychologia.2006.04.003