Parental Expectations and Student Performance in Secondary School Mathematics Education
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Parental Expectations and Student Performance in Secondary School Mathematics Education

Authors: Daya Weerasinghe

Abstract:

Parental expectations often differ to that of their children and the influence and involvement of parents, at home, may affect the student performance in the classroom. This paper presents results from a survey of Asian and European background secondary school mathematics students (N=128) in Melbourne, Australia. Student responses to survey questions were analysed using confirmatory factor analysis, followed by t-tests and ANOVA. The aim of the analysis was to identify similarities and differences in parental expectations in relation to ethnicity, gender, and the year level of the students. The notable findings from the analysis showed no significant difference (at 0.05 level) in parental expectations and student performance, in relation to ethnicity or gender. Conversely, there was a significant difference in both parental expectations and student performance between year 7 and year 12 students. Further, whilst there was a significant difference in parental expectations between year 7 and year 11 students, the students’ performances were not significantly different. The results suggest further research may be needed to understand the parental expectations and student performance between the lower and upper secondary school mathematics students.

Keywords: Ethnic background, gender, parental expectations, student performance, year level.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1110964

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References:


[1] F. K. S. Leung, (2012). “What can and should we learn from international studies of mathematics achievement?” In J. Dindyal, L. P. Cheng, and S. F. Ng, (Eds.), 35th Annual Conference of the Mathematics Education Research Group of Australasia, 34-60. Adelaide: Mathematics Education Research Group of Australasia.
[2] S. Thomson, K. Hillman, N. Werner, M. Schmidt, S. Buckley, and A. Munene, (2012). „Highlights from TIMSS & PIRLS 2011 from Australia’s perspective,” Melbourne, Australia: ACER.
[3] J. Dandy, and T. Nettelbeck, (2002). “A cross-cultural study of parents’ academic standards and educational aspirations for their children,” Educational Psychology: An International Journal of Experimental and Educational Psychology, 22(5), 621-627.
[4] X. Fan, (2001). “Parental involvement and students' academic achievement: A growth modeling analysis,” The Journal of Experimental Education, 70(1), 27-61.
[5] S. Hong, and H. Ho (2005). Direct and indirect longitudinal effects of parental involvement on student achievement: Second-order latent growth modelling across ethnic groups. Journal of Educational Psychology, 97(1), 32-42. doi: 10.1037/0032-0663.97.1.32.
[6] G. Hornby, and R. Lafaele, (2011). “Barriers to parental involvement in education: an explanatory model,” Educational Review, 63(1), 37-52. doi: 10.1080/00131911.2010.488049.
[7] K. V. Hoover-Dempsey, and H. M. Sandler, (1997). “Why do parents become involved in their children's education?” Review of Educational Research, 67(1), 3-42. doi: 10.3102/00346543067001003.
[8] X. Ma, (1999). “Dropping out of advanced mathematics: The effects of parental involvement” Teachers College Record, 101(1), 60-81.
[9] J. Cai, J. C. Moyer, and N. Wang, (1997). “Parental roles in students' learning of mathematics: An exploratory study,” Chicago: American Educational Research Association.
[10] Z. Cao, A. Bishop, and H. Forgasz, (2007). “Perceived parental influence on mathematics learning: A comparison among students in China and Australia,” Educational Studies in Mathematics, 64(1), 85-106.
[11] S. Phillipson, and S. N. Phillipson, (2007). “Academic expectations, belief of ability, and involvement by parents as predictors of child achievement: A cross‐cultural comparison,” International Journal of Experimental and Educational Psychology, 27(3), 329-348. doi: 10.1080/01443410601104130.
[12] J Pallant, (2013). “SPSS survival manual” (5th ed.). Australia: Allen & Unwin.
[13] B. G. Tabachnick, and L. S. Fidell, (2013). “Using multivariate statistics” (6th ed.). Boston: Pearson Education.
[14] J. W. Thacker, M. W. Fields, and L. E. Tetrick, (1989). “The factor structure of union commitment: An application of Confirmatory Factor Analysis,” Journal of Applied Psychology, 74(2), 228-232.
[15] D. Hooper, J. Coughlan, and M. Mullen (2008). “Structural equation modelling: Guidelines for determining model fit,” Electronic journal of business research methods, 6(1), 53-60.
[16] L. Hu, and P. M. Bentler, (1999) “Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives,” Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
[17] J. Miles, and M. Shevlin, (1998), “Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis,” Personality and Individual Differences, 25, 85-90.
[18] B. M. Byrne, (1998), “Structural Equation Modeling with LISREL, PRELIS and SIMPLIS: Basic Concepts, Applications and Programming,” Mahwah, New Jersey: Lawrence Erlbaum Associates.
[19] X. Fan, B. Thompson, and L. Wang, (1999), “Effects of Sample Size, Estimation Methods, and Model Specification on Structural Equation Modeling Fit Indexes,” Structural Equation Modeling, 6 (1), 56-83.
[20] P. Allen, and K. Bennett, (2012). “SPSS practical guide version 20.0” (1st ed.) Cengage Learning Australia Pty Limited.
[21] J. W. Cohen, (1988). “Statistical power analysis for the behavioural sciences,” (2nd ed.) Hillsdale, NJ: Lawrence Erlbaum Associates.