Digital Skills of the Population and Modernization of University Education

The purpose of the study is to identify priority areas for the modernization of university education in the field of digital skills development based on a comparison of international approaches to measuring digital competencies, data of official Rosstat statistics for 2025, and modern online learning models. Special attention is paid to identifying the gap between normative models of digital competencies and actual practices of their use by the population, as well as finding effective educational mechanisms to bridge this gap.
Methods of research. The methodological basis of the study includes the analysis and comparison of international frameworks for digital competencies (DigComp 2.2, ITU Digital Skills Toolkit, PIAAC), which make it possible to structure digital skills by levels, as well as official statistical data from the Federal State Statistics Service (Rosstat) for 2022–2025, reflecting the prevalence of various types of online activities among the population aged 15 years and older. Additionally, a systematic review of modern online education models as an environment for developing applied digital competencies was conducted. The study employs methods of comparative analysis, systematization, generalization, and interpretation of empirical data.
Results. The structure of the population’s digital skills is found to be markedly heterogeneous: despite the widespread adoption of basic communication and information practices (calls, video calls – 80.5%; file sharing via messaging – 75.9%), more complex and professionally significant competencies remain poorly represented (use of neural networks – 6.4%; programming – 1.5%). A steady increase has been recorded in the use of cloud technologies (from 16.5% in 2022 to 20.5% in 2025) and information verification skills (from 12.3% to 15.0%). It is shown that international models of digital competencies cover a wide range of skills, including data processing, digital content and artificial intelligence technologies; however, the actual level of these skills among the population lags significantly behind. It is argued that online education, characterized by high adaptability, a modular structure, project-based orientation, and a close connection with practical labor market needs, serves as an effective environment for developing in-demand digital skills and can be considered a reference model for updating university curricula.
Conclusion. The study concludes that systemic modernization of university education is necessary, considering the identified imbalances in the structure of the population’s digital skills. Key priorities include integrating universal modules on generative artificial intelligence (prompt engineering, generation of analytical materials, automation of routine tasks), developing cloud-related competencies (collaborative work, data processing in digital environments, the use of BI systems), and implementing project-based learning methods. Mechanisms for improving the assessment of educational outcomes are proposed, including the use of digital portfolios and the recognition of online learning outcomes through crediting the results of mastering individual disciplines and the recognition of learning outcomes, as well as a phased roadmap has been developed for integrating digital modules into bachelor’s degree programs.

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