Educational equity refers to the provision of equal educational opportunities for all students, regardless of student characteristics such as gender, ethnicity and socioeconomic status (SES). Equity and equality are central goals in most education systems. For several decades, the impact of home conditions on educational outcomes has been well documented. (e.g. Boudon, 1974; Bourdieu & Wacquant, 1992; Coleman, 1968; Jonsson, 1967). While educational equity is often analyzed at the system level, subject-specific equity has received less attention (see e.g. Kraehe et al., 2016 for an exception). However, gender-based inequality in core subjects, such as mathematics (TIMSS 2023) and reading (PIRLS 2021), is well documented.

The significance of the home environment has been represented as an index of SES for many years (Chapin, 1928). According to the American Psychological Association (APA), SES “(e)ncompasses not only income but also educational attainment, occupational prestige, and subjective perceptions of social status and social class” (American Psychological Association, 2025). There is no consensus on how to operationalize the concept (Broer et al., 2019), although the elements stated in the APA-definition seem to be common in operationalization.

Since PISA 2003 introduced the Economic, Social and Cultural Status (ESCS) measure, a form of a SES-measure has become a standard metric in ILSA studies, facilitating evaluations of educational equity. However, these analyses have mostly focused on student attainment as a general outcome, and not on the relative effects of SES in relation to different subjects.

TIMSS 2023 introduced a new SES measure for grade 4, designed to more accurately reflect the theoretical construct. Analyses of the correlation between this new SES measure and student achievement in mathematics and science indicate that in a large proportion of countries, SES is more strongly correlated with science achievement than with mathematics achievement (Kjeldsen et al., 2024). This difference is statistically significant in at least four countries, including Denmark.

This study further explores these subject-specific differences through two approaches.. The first is an empirical investigation of possible explanatory variables such as the number of weekly lessons in the two subjects in different countries, which might relate to students’ outcomes and explain differences in what students have learned both inside and outside the classroom.

The second track is more theoretical, investigating – with point of departure in the Danish case – how subject specific competencies varies between science and mathematics as described in the curriculum. Differences may stem from the home’s ability to influence student development. Core science competencies appear more related to reflection and societal perspectives, whereas mathematics competencies are more focused on modeling and abstraction (Møller, 2024).

This ongoing study aims to contribute to the literature on SES and student achievement.

Data for the presentation is from the TIMSS 2023 4th grade international database, supplemented with PIRLS 2021. The first part of the presentation is based on a dataset consisting of country-level correlation coefficients for each subject and their subdomains’ correlation with SES, enriched with information on country-level variables, such as the number of hours taught in each subject. The number of instructional hours is particularly relevant, as it serves as an indicator of students’ school-related exposure to each subject. This dataset will be analyzed with regression analyses, where the difference in correlation coefficient between science and mathematics is the dependent variable, and country-level variables are independent variables. Additionally, findings from PIRLS 2021 on fourth-grade students' reading attainment and its relationship to SES will be considered. These analyses will help determine whether the difference can be attributed to students' learning opportunities in the classroom, measured by, for example, the number of hours taught. The second part will be addressed through a qualitative analysis of the learning objectives for each subject presented in the Danish curriculum “Fælles Mål” [Common Objectives]. This analysis will mainly rely on existing analyses (e.g. Binau et al., 2021; Møller, 2024; Rasmussen et al., 2019) and will include systematic review of the specific competencies required in science and mathematics and interpret these competencies in relation to existing knowledge on the relationship between student achievement and SES. The Danish case is particularly interesting, as a core objective of the science curriculum is to “develop thoughts, language, and concepts about nature and technology that have value in daily life” (Common Objectives in Science) and to foster an understanding of human-nature interactions. Additionally, it emphasizes 'responsibility towards the environment as a basis for commitment and action in relation to sustainable development' (Common Objectives in Science). These objectives strongly connect science education to students' daily lives and the world around them — an emphasis that is far less pronounced in the mathematics curriculum.

The project is still ongoing, but preliminary analyses indicate that the content and cognitive domains within the TIMSS Science scale correlate differently with students’ SES. This suggests that it is within specific elements of science that students seem to benefit from their socioeconomic background. For example, the biology content domain appears to drive the stronger correlation between science achievement and SES. Similarly, the relatively new environmental awareness scale, which significantly overlaps with biology in its item composition, exhibits the same pattern. In the cognitive domains, knowledge and applying are more strongly correlated with SES within science than within mathematics. These preliminary findings have important implications for educational policy and practices. They highlight the need to consider subject-specific differences when developing strategies to promote educational equity. In particular, strengthening instruction in the science domains most affected by SES may be necessary to ensure equitable learning opportunities for all students, regardless of socioeconomic background.

American Psychological Association. (2025). socioeconomic status (SES) https://dictionary.apa.org/socioeconomic-status Binau, C., Dolin, J., Elmose, S., Nielsen, J., & Schmidt, J. (2021). Kompetenceorienteret undervisning i naturfagene. MONA - Matematik- og Naturfagsdidaktik, 21(3). https://tidsskrift.dk/mona/article/view/128341 Boudon, R. (1974). Education, opportunity, and social inequality : changing prospects in western society. Wiley. Bourdieu, P., & Wacquant, L. J. D. (1992). An Invitation to Reflexive Sociology. University of Chicago Press. Broer, M., Bai, Y., & Fonseca, F. (2019). Socioeconomic Inequality and Educational Outcomes: Evidence from Twenty Years of TIMSS (Vol. 5). Springer. https://doi.org/10.1007/978-3-030-11991-1 Chapin, F. S. (1928). A quantitative scale for rating the home and social environment of middle class families in an urban community: a first approximation to the measurement of socio-economic status. Journal of Educational Psychology, 19(2), 99-111. https://doi.org/https://doi.org/10.1037/h0074500 Coleman, J. (1968). The Concept of Equality of Educational Opportunity. Harvard Educational Review, 38(1), 7. https://doi.org/10.17763/haer.38.1.m3770776577415m2 Jonsson, G. (1967). Delinquent boys, their parents and grandparents. Acta Psychiatrica Scandinavica, 42(s195), 1-256. Kjeldsen, C. C., Kristensen, R. M., Christensen, J. H., & Gonzales, C. d. V. (2024). Matematik og natur/teknologi i 4. klasse: Resultater af TIMSS-undersøgelsen 2023. Aarhus University Press. https://doi.org/10.2307/jj.22992825 Kraehe, A. M., Acuff, J. B., & Travis, S. (2016). Equity, the Arts, and Urban Education: A Review. The Urban Review, 48(2), 220-244. https://doi.org/10.1007/s11256-016-0352-2 Møller, M. (2024). Kompetenceorienteret STEM-undervisning [Ph.d. dissertation]. DPU, Aarhus Universitet. Rasmussen, J., Rasch-Christensen, A., Molbæk, M., Kristensen, R. M., Reimer, D., & Smith, E. (2019). Undervisning med Fælles Mål i dansk og matematik: Et overvejende kvalitativt mixed methods studie (2. runde) (87-7684-560-5). A. U. V. U. C. DPU. http://edu.au.dk/fileadmin/edu/Udgivelser/E-boeger/Ebog_-_Undervisning_med_Faelles_Maal_i_dansk_og_matematik_-_2019.pdf