The possibilities of personalizing the adapted training of future specialists in the context of digital transformation

Abstract

This article examines the theoretical and methodological foundations of the transition from traditional mass education models to personalized learning within the context of economic digital transformation and evolving labor market demands. The relevance of this research is driven by the necessity to adapt vocational education systems to new employer expectations, which increasingly prioritize practical competencies, adaptability, and readiness for lifelong learning over formal academic credentials. The aim of the study is to substantiate the potential for personalizing the adaptive training of future professionals through digital technologies. The paper presents a comparative analysis of mass instruction, differentiated learning, and personalized education models across key parameters, including educational objectives, the instructor’s role, assessment methodologies, technological infrastructure, and associated risks. Key contradictions between the technological capabilities of digitalization and contemporary pedagogical practice are identified, highlighting challenges such as the digital divide, inadequate methodological training of faculty, scarcity of high-quality digital content, and the risks of algorithmic bias.