Digital competences are widely regarded as a key prerequisite for educational success, labour market participation, and social inclusion (Fraillon, 2025; Hoe, 2025). International large-scale assessments (ILSAs) such as the International Computer and Information Literacy Study (ICILS) play a central role in producing policy-relevant knowledge on these competences and in shaping educational discourse. International evidence from ICILS shows substantial cross-national variation in students’ digital competences, which—similar to traditional competence domains—is closely associated with socioeconomic background (Fraillon, 2025). However, less is known about how institutional features of education systems structure inequalities in digital competences, and how such inequalities emerge within data-driven, internationally comparative research contexts. In particular, early between-school tracking constitutes a core institutional design feature that systematically differentiates learning environments at an early stage, yet its role in shaping digital competence inequalities has received little empirical attention. This paper addresses this gap by examining early tracking as a structural moderator of socioeconomic inequalities in digital competences. We ask: (1) To what extent does the association between socioeconomic status (SES) and digital competences vary across countries? (2) Does early tracking affect average levels of digital competences? (3) Does early tracking moderate the relationship between SES and digital competences? Theoretically, the paper brings together insights from the digital divide literature, which conceptualises inequalities in digital access, use, and competences as socially structured (Dijk, 2020), and theories of educational inequality that emphasise the role of cultural and economic capital in shaping learning opportunities (Bourdieu, 1983). Early tracking is understood as an institutional mechanism that allocates students to differentiated learning environments (Terrin & Triventi, 2023), thereby structuring access to pedagogical resources, digital infrastructures, and forms of knowledge valued within education systems. Empirically, the analyses draw on pooled data from ICILS 2013, 2018, and 2023, covering 44 education systems, including 12 characterised by early tracking. Digital competences are measured using the Computer and Information Literacy (CIL) and Computational Thinking (CT) scales. Multilevel regression models with students nested in schools and countries are estimated, including cross-level interactions between SES and early tracking. Preliminary results based on ICILS 2023 indicate strong socioeconomic gradients in digital competences across systems. While early tracking shows no significant effect on average competence levels, inequalities by SES are significantly steeper in early-tracking systems. These findings suggest that early tracking primarily structures the distribution—rather than the overall level—of digital competences.

Bourdieu, P. (1983). Ökonomisches Kapital, kulturelles Kapital, soziales Kapital. In R. Kreckel (Ed.), Soziale Ungleichheiten (pp. 183–198). Schwartz. Dijk, J. van. (2020). The digital divide. Polity. Fraillon, J. (2025). ICILS 2023 International Report: An International Perspective on Digital Literacy. International Association for the Evaluation of Educational Achievement (IEA). https://www.iea.nl/sites/default/files/2025-03/ICILS_2023_International_Report.pdf Hoe, S. L. (2025). Digital transformation and the future of work: Closing the digital skills gap. Development and Learning in Organizations: An International Journal, 39(3), 14–17. https://doi.org/10.1108/DLO-06-2024-0167 Terrin, É., & Triventi, M. (2023). The Effect of School Tracking on Student Achievement and Inequality: A Meta-Analysis. Review of Educational Research, 93(2), 236–274. https://doi.org/10.3102/00346543221100850