Abstract
Parents are their children’s most influential educators, and their joint activities can influence these children’s early learning. Past studies with small, non-representative samples do not show a consistent link between early numeracy activities at home and children’s mathematics achievement. Specifically, whether or how early numeracy activity at home (ENAH) enhances mathematics learning in upper primary school remains an open question. This study tests this link, its precursors (home resources for learning, gender), and its possible mechanisms (including early numeracy skills, mathematics interest, and mathematics self-efficacy) on a representative sample of 3,600 Hong Kong fourth-grade children, with a multilevel path analysis. The results showed that ENAH was linked to both early numeracy and fourth-grade mathematics achievement, and did not support the substitution hypothesis (that other factors such as school lessons substitute for ENAH). The results also support two ENAH mechanisms. Children’s early numeracy and mathematics self-efficacy both partially mediated the link between ENAH and children’s later mathematics achievement. After including these explanatory variables in the model, ENAH still retained a significant direct link to fourth-grade mathematics achievement, suggesting that ENAH also operates through one or more other mechanisms. Lastly, boys and children in families with more home resources for learning were more likely than other children to participate in ENAH.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aunio, P., & Niemivirta, M. (2010). Predicting children’s mathematical performance in grade one by early numeracy. Learning and Individual Differences, 20(5), 427–435. https://doi.org/10.1016/j.lindif.2010.06.003
Baker, D. P., Goesling, B., & LeTendre, G. K. (2002). Socioeconomic status, school quality, and national economic development: A cross-national analysis of the “Heyneman-Loxley Effect” on mathematics and science achievement. Comparative Education Review, 46(3), 291–312. https://doi.org/10.1086/341159
Bandura, A. (1997). Developmental analysis of self-efficacy. Self-efficacy: The exercise of control, 162–211.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.
Byrnes, J. P., & Miller, D. C. (2007). The relative importance of predictors of math and science achievement: An opportunity-propensity analysis. Contemporary Educational Psychology, 32(4), 599–629. https://doi.org/10.1016/j.cedpsych.2006.09.002
Byrnes, J. P., & Wasik, B. A. (2009). Factors predictive of mathematics achievement in kindergarten, first and third grades: An opportunity-propensity analysis. Contemporary Educational Psychology, 34(2), 167–183. https://doi.org/10.1016/j.cedpsych.2009.01.002
Castro, M., Expósito-casas, E., López-martín, E., & Lizasoain, L. (2015). Parental involvement on student academic achievement: A meta-analysis. Educational Research Review, 14, 33–46. https://doi.org/10.1016/j.edurev.2015.01.002
Chiu, M. M. (2007). Families, economies, cultures, and science achievement in 41 countries: Country-, school-, and student-level analyses. Journal of Family Psychology, 21(3), 510–519. https://doi.org/10.1037/0893-3200.21.3.510
Chiu, M. M. (2010). Effects of inequality, family and school on mathematics achievement: Country and student differences. Social Forces, 88(4), 1645–1676. https://doi.org/10.1353/sof.2010.0019
Chiu, M. M., & Chow, B. W. Y. (2015). Classmate characteristics and student achievement in 33 countries: Classmates’ past achievement, family socioeconomic status, educational resources and attitudes toward reading. Journal of Educational Psychology, 107(1), 152–169. https://doi.org/10.1037/a0036897
Chiu, M. M., & Khoo, L. (2005). Effects of resources, inequality, and privilege bias on achievement: Country, school, and student level analyses. American Educational Research Journal, 42(4), 575–603. https://doi.org/10.3102/00028312042004575
Chiu, M. M., & Zeng, X. (2008). Family and motivation effects on mathematics achievement: Analyses of students in 41 countries. Learning and Instruction, 18(4), 321–336. https://doi.org/10.1016/j.learninstruc.2007.06.003
Deci, E. L., Koestner, R., & Ryan, R. M. (2001). Extrinsic rewards and intrinsic motivation in education: Reconsidered once again. Review of Educational Research, 71(1), 1–27. https://doi.org/10.3102/00346543071001001
Dufur, M. J., Parcel, T. L., & Troutman, K. P. (2013). Does capital at home matter more than capital at school? Social capital effects on academic achievement. Research in Social Stratification and Mobility, 31(1), 1–21. https://doi.org/10.1016/j.rssm.2012.08.002
Fan, W., & Williams, C. M. (2010). The effects of parental involvement on students’ academic self-efficacy, engagement and intrinsic motivation. Educational Psychology, 30(1), 53–74. https://doi.org/10.1080/01443410903353302
Fast, L. A., Lewis, J. L., Bryant, M. J., Bocian, K. A., Cardullo, R. A., Rettig, M., & Hammond, K. A. (2010). Does math self-efficacy mediate the effect of the perceived classroom environment on standardized math test performance? Journal of Educational Psychology, 102(3), 729–740. https://doi.org/10.1037/a0018863
Flore, P. C., & Wicherts, J. M. (2015). Does stereotype threat influence performance of girls in stereotyped domains? A meta-analysis. Journal of School Psychology, 53(1), 25–44. https://doi.org/10.1016/j.jsp.2014.10.002
Ganley, C. M., & Lubienski, S. T. (2016). Mathematics confidence, interest, and performance: Examining gender patterns and reciprocal relations. Learning and Individual Differences, 47, 182–193. https://doi.org/10.1016/j.lindif.2016.01.002
Gottfried, A. E., Marcoulides, G. A., Gottfried, A. W., & Oliver, P. H. (2009). A latent curve model of parental motivational practices and developmental decline in math and science academic intrinsic motivation. Journal of Educational Psychology, 101(3), 729–739. https://doi.org/10.1037/a0015084
Gunderson, E. A., Ramirez, G., Levine, S. C., & Beilock, S. L. (2012). The role of parents and teachers in the development of gender-related math attitudes. Sex Roles, 66(3–4), 153–166. https://doi.org/10.1007/s11199-011-9996-2
Halpern, D. F. (2012). Sex differences in cognitive abilities (4th ed.). New York, NY: Taylor & Francis.
Hidi, S., Berndorff, D., & Ainley, M. (2002). Children’s argument writing, interest and self- efficacy: An intervention study. Learning and Instruction, 12(4), 429–446. https://doi.org/10.1016/S0959-4752(01)00009-3
Hill, C. J., Bloom, H. S., Black, A. R., & Lipsey, M. W. (2008). Empirical benchmarks for interpreting effect sizes in research. Child Development Perspectives, 2(3), 172–177. https://doi.org/10.1111/j.1750-8606.2008.00061.x
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
Huang, Q., Zhang, X., Liu, Y., Yang, W., & Song, Z. (2017). The contribution of parent–child numeracy activities to young Chinese children’s mathematical ability. British Journal of Educational Psychology, 87(3), 328–344. https://doi.org/10.1111/bjep.12152
Kennedy, P. (2008). A guide to econometrics (6th ed.). New York, NY: Wiley-Blackwell.
Kleemans, T., Peeters, M., Segers, E., & Verhoeven, L. (2012). Child and home predictors of early numeracy skills in kindergarten. Early Childhood Research Quarterly, 27(3), 471–477. https://doi.org/10.1016/j.ecresq.2011.12.004
Konstantopoulos, S. (2008). Methodological studies: The power of the test for treatment effects in three-level block randomized designs. Journal of Research on Educational Effectiveness, 1(4), 265–288. https://doi.org/10.1080/19345740802328216
Lefevre, J.-A., Polyzoi, E., Skwarchuk, S.-L., Fast, L., & Sowinski, C. (2010). Do home numeracy and literacy practices of Greek and Canadian parents predict the numeracy skills of kindergarten children? International Journal of Early Years Education, 18(1), 55–70. https://doi.org/10.1080/09669761003693926
Lefevre, J.-A., Skwarchuk, S.-L., Smith-Chant, B. L., & Bisanz, J. (2009). Home numeracy experiences and children’s math performance in the early school years. Canadian Journal of Behavioural Science, 41(2), 55–66. https://doi.org/10.1037/a0014532
Ma, X., Shen, J., Krenn, H. Y., Hu, S., & Yuan, J. (2015). A meta-analysis of the relationship between learning outcomes and parental involvement during early childhood education and early elementary education. Educational Psychology Review, 28(4), 771–801. https://doi.org/10.1007/s10648-015-9351-1
Mankiw, N. G. (2014). Principles of macroeconomics (7th ed.). Nashville, TN: Southwestern Publishing.
Manolitsis, G., Georgiou, G. K., & Tziraki, N. (2013). Examining the effects of home literacy and numeracy environment on early reading and math acquisition. Early Childhood Research Quarterly, 28(4), 692–703. https://doi.org/10.1016/j.ecresq.2013.05.004
Martin, M. O., Mullis, I. V. S., & Hooper, M. (2016). Methods and procedures in TIMSS 2015. Lynch School of Education, Boston College: TIMSS & PIRLS International Study Center.
Masters, G. N., & Wright, B. D. (1993). The partial credit model. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of polytomous item response theory models (pp. 101–121). New York: Springer. https://doi.org/10.4324/9780203861264.ch5
Missall, K., Hojnoski, R. L., Caskie, G. I. L., & Repasky, P. (2015). Home numeracy environments of preschoolers: Examining relations among mathematical activities, parent mathematical beliefs, and early mathematical skills. Early Education and Development, 26(3), 356–376. https://doi.org/10.1080/10409289.2015.968243
Mok, M. M. C., Zhu, J., & Law, C. L. K. (2017). Cross-lagged cross-subject bidirectional predictions among achievements in mathematics, English language and Chinese language of school children. Educational Psychology, 37(10), 1259–1280. https://doi.org/10.1080/01443410.2017.1334875
Moon, U. J., & Hofferth, S. L. (2016). Parental involvement, child effort, and the development of immigrant boys’ and girls’ reading and mathematics skills: A latent difference score growth model. Learning and Individual Differences, 47, 136–144. https://doi.org/10.1016/j.lindif.2016.01.001
Mullis, I. V. S., & Martin, M. O. (2013). TIMSS 2015 Assessment Frameworks. International Association for the Evaluation of Educational Achievement (IEA). TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College.
Muthén, B. O., & Satorra, A. (1995). Complex sample data in Structural Equation Modeling. Sociological Methodology, 25(1995), 267–316. https://doi.org/10.2307/271070
Muthén, L. K., & Muthén, B. O. (2018). Mplus user’s guide (8th ed.). Los Angeles, CA: Muthén & Muthén.
Niklas, F., Cohrssen, C., & Tayler, C. (2016). Parents supporting learning: A non-intensive intervention supporting literacy and numeracy in the home learning environment. International Journal of Early Years Education, 9760(April), 1–22. https://doi.org/10.1080/09669760.2016.1155147
Purpura, D. J., Reid, E. E., Eiland, M. D., & Baroody, A. J. (2015). Using a brief preschool early numeracy skills screener to identify young children with mathematics difficulties. School Psychology Review, 44(1), 41–59. https://doi.org/10.17105/SPR44-1.41-59
Sandberg, J. F., & Hofferth, S. L. (2001). Changes in children’s time with parents: United States, 1981-1997. Demography, 38(3), 423–436.
Schunk, D. H., & Pajares, F. (2009). Self-efficacy theory. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motivation at school (pp. 35–53). New York, NY: Routledge.
Sirin, S. R., & Rogers-Sirin, L. (2005). Components of school engagement among African American adolescents. Applied Developmental Science, 9(1), 5–13. https://doi.org/10.1207/s1532480xads0901_2
Skwarchuk, S. L., Sowinski, C., & LeFevre, J. A. (2014). Formal and informal home learning activities in relation to children’s early numeracy and literacy skills: The development of a home numeracy model. Journal of Experimental Child Psychology, 121(1), 63–84. https://doi.org/10.1016/j.jecp.2013.11.006
Steiger, J. H., & Lind, J. C. (1989). Statistically based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society, Iowa City, IA.
Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10. https://doi.org/10.1007/BF02291170
Funding
The work was fully supported by the grants from the Central Reserve Allocation Committee and the Faculty of Education and Human Development of The Education University of Hong Kong (Project No. 03A28) on the project titled “Big data for school improvement: Identifying and analyzing multiple sources to support schools as learning communities.”
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no competing interests.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Zhu, J., Chiu, M.M. Early home numeracy activities and later mathematics achievement: early numeracy, interest, and self-efficacy as mediators. Educ Stud Math 102, 173–191 (2019). https://doi.org/10.1007/s10649-019-09906-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10649-019-09906-6