Popa et al. (2026) — Bucharest University of Economic Studies. arXiv preprint.
Post-COVID ICT Career Aspirations uses PISA 2018 and 2022 country-level data to investigate whether students entering the generative AI era have adequate educational foundations. Using a mixed-methods approach including Variational Autoencoders for latent representation learning, the study finds that ICT career aspirations have increased globally but unevenly. Digital skills are the strongest and most consistent predictor of ICT aspirations, while teacher support plays a complementary role and student autonomy shows only weak, context-dependent effects. The findings challenge simplistic narratives about ai-literacy — rising interest in ICT careers does not automatically mean students have the foundational skills to succeed in AI-driven labor markets. This connects to digital-literacy-illusion findings about student overconfidence, and to teacher-ai-adoption-confidence research on the complementary role of teacher support. The multidimensional nature of educational readiness aligns with teacher-ai-competency frameworks, and the uneven global distribution of digital skills raises equity concerns previously documented in ai-education-global-capacity.
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