AI as a digital assistant in a multi-ethnic VET system: Evidence from the VETAssIst project in Serbia - Papp, Zoltán; Kovács, Elvira (Central European Journal of Educational Research, 2025)
Artificial intelligence (AI) is increasingly framed as a lever for teaching efficiency in vocational education and training (VET), yet adoption is mediated by teachers’ linguistic and cultural contexts. This study, conducted within the VETAssIst project, compares AI‑related readiness and needs among VET teachers in Serbia across two cohorts working under the same national framework: Hungarian‑minority teachers in Vojvodina and Serbian‑majority teachers. Using a structured questionnaire, we examine perceived usefulness of AI as a ‘digital assistant’ for lesson planning, assessment, and administrative work, self‑reported digital competence, perceived institutional support, and readiness for integration. The evidence indicates broadly similar baseline competence across cohorts, strong intentions to expand classroom use, and uneven institutional backing. Recurrent requirements include VET‑specific AI tools, clearer school‑level policies, targeted professional development, and language‑accessible resources. We argue that sustainable digital transformation in multi‑ethnic VET systems depends on aligning tool ecosystems and professional learning with the linguistic diversity of the workforce, thereby preventing intra‑system digital divides.