Gender differences in mathematical achievement development: a family psychobiosocial model

• Autores: Mei-Shiu Chiu
• Localización: European journal of psychology of education, ISSN-e 1878-5174, ISSN 0256-2928, Vol. 38, Nº 4, 2023, págs. 1481-1504
• Idioma: inglés
• DOI: 10.1007/s10212-022-00674-1
• Enlaces
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• Resumen

  • This study proposes a family psychobiosocial model on gender differences in cognitive development. Specifically, the aim is to investigate how family biological, socioeconomic, and psychological factors predict child mathematics achievement (MAch) development. The data were obtained from the Millennium Cohort Study. Children’s pattern construction scores collected at ages 5 and 7 years worked as MAch (n = 18,497). The predictors were family data collected when the children were 9 months. The results of path analyses for all students indicate that all three factors in the family psychobiosocial model play some roles in children’s MAch development. Analyses for the female and male students separately reveal that girls’ positive MAch development was significantly predicted by four psychobiosocial factors (fewer mother in-pregnancy alcohol intakes, more family income, higher mother education levels, and more mother cognitive stimulation); boys’ MAch development is predicted by only one factor (higher mother education levels). The results support the psychobiosocial model as a whole. Family psychobiosocial factors, especially social factors, impact children’s cognitive development more for females than for males.

• Referencias bibliográficas
  • Chiu, M. -S. (2016). Using demographics to predict mathematics achievement development and academic ability and job income expectations. Open...
  • Chiu, M. -S. (2018). Effects of early numeracy activities on mathematics achievement and affect: Parental value and child gender conditions...
  • Chiu, M. -S. (2020). Exploring models for increasing the effects of school information and communication technology use on learning outcomes...
  • Chiu, M. -S. (2022). Transcend socioeconomic status constraints to mathematics and science achievement by collaborative problem-solving: The...
  • Baye, A., & Monseur, C. (2016). Gender differences in variability and extreme scores in an international context. Large-Scale Assessments...
  • Bodovski, K., & Youn, M. J. (2010). Love, discipline and elementary school achievement: The role of family emotional climate. Social Science...
  • Bollen, K. A., & Long, J. S. (1993). Testing structural equation models. Sage.
  • Booth-LaForce, C., & Oxford, M. L. (2008). Trajectories of social withdrawal from grades 1 to 6: Prediction from early parenting, attachment,...
  • Bronfenbrenner, U. (1986). Ecology of the family as a context for human development: Research perspectives. Developmental Psychology, 22,...
  • Bronfenbrenner, U. (1994). Ecological models of human development. International Encyclopedia of Education, 3(2), 37–43.
  • Bronfenbrenner, U., & Ceci, S. J. (1994). Nature-nurture reconceptualized in developmental perspective: A bioecological model. Psychological...
  • Castelao, C. F., & Kröner-Herwig, B. (2013). Different trajectories of depressive symptoms in children and adolescents: Predictors and...
  • Chen, P. P. (2003). Exploring the accuracy and predictability of the self-efficacy beliefs of seventh-grade mathematics students. Learning...
  • Chen, H., Chen, M. F., Chang, T. S., Lee, Y. S., & Chen, H. P. (2010). Gender reality on multi-domains of school-age children in Taiwan:...
  • Dickerson, A., & Popli, G. K. (2016). Persistent poverty and children’s cognitive development: Evidence from the UK Millennium Cohort...
  • Duchesne, S., & Ratelle, C. (2010). Parental behaviors and adolescents’ achievement goals at the beginning of middle school: Emotional...
  • Duncan, G. J., Morris, P. A., & Rodrigues, C. (2011). Does money really matter? Estimating impacts of family income on young children’s...
  • Else-Quest, N. M., Hyde, J. S., & Linn, M. C. (2010). Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological...
  • Evans, J., Melotti, R., Heron, J., Ramchandani, P., Wiles, N., Murray, L., & Stein, A. (2012). The timing of maternal depressive symptoms...
  • Filho, E. (2020). Shared zones of optimal functioning: A framework to capture peak performance, momentum, psycho–bio–social synchrony, and...
  • Flak, A. L., Su, S., Bertrand, J., Denny, C. H., Kesmodel, U. S., & Cogswell, M. E. (2014). The association of mild, moderate, and binge...
  • Frazier, L. D. (2020). The past, present, and future of the biopsychosocial model: A review of the biopsychosocial model of health and disease:...
  • Gray, H., Lyth, A., McKenna, C., Stothard, S., Tymms, P., & Copping, L. T. (2019). Sex differences in variability across nations in reading,...
  • Guiso, L., Monte, F., Sapienza, P., & Zingales, L. (2008). Culture, gender, and mathematics. Science, 320, 1164–1165. https:// doi. org/...
  • Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson...
  • Halpern, D. F., Wai, J., & Saw, A. (2005). A psychobiosocial model: Why females are sometimes greater than and sometimes less than males...
  • Hansen, K. (Ed.). (2014). Millennium cohort study: A guide to the datasets (8th ed.). UK: Centre for Longitudinal Studies.
  • Howard, M. C. (2016). A review of exploratory factor analysis decisions and overview of current practices: What we are doing and how can we...
  • Hyde, J. S. (2005). The gender similarities hypothesis. American Psychologist, 60, 581–592. https:// doi. org/ 10. 1037/ 0003- 066X. 60.6....
  • Hyde, J. S. (2014). Gender similarities and differences. Annual Review of Psychology, 65, 373–398. https:// doi. org/ 10. 1146/ annur ev-...
  • Hyde, J. S., & Mertz, J. E. (2009). Gender, culture, and mathematics performance. Proceedings of the National Academy of Sciences, 106,...
  • Jones, E. M., & Ketende, S. C. (2010). Millennium cohort study: User guide to analyzing MCS data using SPSS. London, UK: Centre for Longitudinal...
  • Kelly, Y., Iacovou, M., Quigley, M. A., Gray, R., Wolke, D., Kelly, J., & Sacker, A. (2013). Light drinking versus abstinence in pregnancy–behavioral...
  • Leavitt, C. E., Siedel, A. J., Yorgason, J. B., Millett, M. A., & Olsen, J. (2021). Little things mean a lot: Using the biopsychosocial...
  • Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness lead to success? Psychological...
  • Martin, A. J., Liem, G. A., Mok, M., & Xu, J. (2012). Problem solving and immigrant student mathematics and science achievement: Multination...
  • McCarthy, B., Koman, C. A., & Cohn, D. (2018). A psychobiosocial model for assessment, treatment, and relapse prevention for female sexual...
  • McCulloch, A., & Joshi, H. E. (2001). Neighborhood and family influences on the cognitive ability of children in the British National...
  • Morin, A. J., Rodriguez, D., Fallu, J. S., Maïano, C., & Janosz, M. (2012). Academic achievement and smoking initiation in adolescence:...
  • Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS advanced 2015 international results in advanced mathematics and physics....
  • Nykjaer, C., Alwan, N. A., Greenwood, D. C., Simpson, N. A., Hay, A. W., White, K. L., & Cade, J. E. (2014). Maternal alcohol intake prior...
  • Organization for Economic Co-operation and Development. (2014). PISA 2012 results: What students know and can do – student performance in...
  • Oxford, M. L., & Lee, J. O. (2011). The effect of family processes on school achievement as moderated by socioeconomic context. Journal...
  • Pargulski, J. R., & Reynolds, M. R. (2017). Sex differences in achievement: Distributions matter. Personality and Individual Differences,...
  • Raykov, T., Lee, C. L., Marcoulides, G. A., & Chang, C. (2013). A commentary on the relationship between model fit and saturated path...
  • Raykov, T., Marcoulides, G. A., & Akaeze, H. O. (2017). Comparing between- and within-group variances in a two-level study: A latent variable...
  • Rees, G. (2018). The association of childhood factors with children’s subjective well-being and emotional and behavioral difficulties at 11...
  • Simmons, B. L., Gooty, J., Nelson, D. L., & Little, L. M. (2009). Secure attachment: Implications for hope, trust, burnout, and performance....
  • Slominski, L., Sameroff, A., Rosenblum, K., & Kasser, T. (2011). Longitudinal predictors of adult socioeconomic attainment: The roles...
  • Su, Y., Doerr, H. S., Johnson, W., Shi, J., & Spinath, F. M. (2015). The role of parental control in predicting school achievement independent...
  • Taylor, R. (1990). Interpretation of the correlation coefficient: A basic review. Journal of Diagnostic Medical Sonography, 6, 35–39. https://...
  • Watson, J. C. (2017). Establishing evidence for internal structure using exploratory factor analysis. Measurement and Evaluation in Counseling...
  • West, K. K., Mathews, B. L., & Kerns, K. A. (2013). Mother–child attachment and cognitive performance in middle childhood: An examination...
  • Willis, J. O., Elliott, C. D., & Dumont, R. (2008). Essentials of Das-ii assessment. John Wiley & Sons.
  • Ximénez, C., Maydeu-Olivares, A., Shi, D., & Revuelta, J. (2022). Assessing cutoff values of SEM fit indices: Advantages of the unbiased...