Intersectional effects of Socioeconomic status, phase and gender on Mathematics achievement

ABSTRACT

I explored the effect of socio-economic status (SES) on mathematics achievement by gender at grades 5 in 2012 and 10 in 2017. Secondary Italian data (30,868 pupils in primary and 38,091 in secondary school) were analysed via the Rasch model to estimate students’ ability in mathematics and then via a three-level regression (students nested into classroom and schools) to estimate SES effect (calculated at individual, classroom and school level) on ability. Data analysis showed positive correlation between SES and ability, and a significant mediating role of gender, in secondary more strongly than in primary school, and a greater effect of classroom and school rather than individual SES on students attending secondary school. In particular, at grade 10, individual SES effect tends to disappear when classroom and school SES are accounted for, suggesting that adolescents are much more prone to the effect of context variables than younger pupils are.

KEYWORDS:

• Socio-economic status (SES)
• mathematics
• gender
• pseudo-longitudinal

Acknowledgments

I would like to thank the European Commission that supported this work through the grant award H2020-MSCA-IF-2015/782479. In addition, I would like to thank INVALSI for the data sets allowing the analyses presented in this paper. Nevertheless, the views expressed in this work are attributable exclusively to the author and, thereby, in citing the work, it is not appropriate to attribute the arguments expressed herein to the European Commission, to INVALSI or its Management.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. After primary and lower intermediate school, students can enrol three different types of secondary school: (1) LICEI; (2) TECNICI; and (3) PROFESSIONALI. LICEI is a broad category, including very different training courses with a very different importance assigned to mathematics. No additional information is available about this and thus this analysis cannot account for these differences. TECNICI and PROFESSIONALI, instead, offer a more technical training. Although each type of school allows enrolment at university, TECNICI and PROFESSIONALI offer specific training to get a job in sectors where a degree is not required, whereas LICEI offer a broader education, usually preparatory for university enrolment.

2. Similar (but a bit stronger) effect can be disclosed for boys. A second multilevel model with girl (rather than boy) as reference category for the variable “gender” has been estimated. Gender coefficient in this second model is equal to 35.412, i.e. more than ¾ of SD. Results have been shown in appendix at the end of the paper. Asymmetric variations of gender coefficients estimated in these two regression models are due to the presence of interaction terms.

3. Different results can be disclosed in primary school at the top SES level (i.e. level 7). Nevertheless, the percentage of school with SES at level 7 is very low and thus some more information (not available in the secondary data analysed here), about these particular cases, is needed to understand this result in-depth. The use of secondary data implies some advantages in terms of replicability but also some shortcuts in results interpretability as discussed in the final section.

Additional information

Funding

This work was supported by the Marie Curie Individual Fellowship [H2020-MSCA-IF-2016/782479].

Notes on contributors

Clelia Cascella

Clelia Cascella, Ph.D. in Methodology of Social Sciences and Ph.D. in Economics, is a Marie Curie research fellow at the University of Manchester (United Kingdom) and researcher in Social Statistics and Psychometrics at the Italian National Institute for the Evaluation of Educational System. She works with IRT modelling and multivariate Statistics to study the effect of personal and contextual variables on students' achievement, with a particular attention to learning Mathematics.