The concept of continuous education as a methodological basis for the artificial intelligence development in the educational system
I. V. Savochkina
Belgorod State Technological University, Belgorod, Russia
Keywords: continuous education, artificial intelligence, prompt engineering, educational policy, education legislation
Abstract
Introduction. The relevance of this study stems from the need for a methodological understanding of the integration of artificial intelligence (AI) technologies into education in response to the global challenges of the 21st century. The aim of this article is to analyze the evolution and legal consolidation of the concept of lifelong education in Russia and to substantiate its role as a systemic foundation for the implementation of AI and industrial engineering. Methodology. The study is based on a retrospective analysis of regulatory documents and scientific literature, as well as a systemic and comparative analysis to identify the relationship between the principles of lifelong education and technological solutions. Discussion. It is shown that the legislatively enshrined principle of continuity, implemented through formal, non-formal, and informal education, generates a methodological demand for personalization, flexibility, and accessibility. Five key contemporary challenges (speed of change, personalization, format integration, accessibility, and goal setting) are identified. AI offers an instrumental response, while industrial engineering serves as an operational mechanism for personalization and a new educational literacy. Conclusion. It is concluded that the concept of lifelong learning is not only a legal principle but also a necessary methodological framework that provides meaning and direction for technological integration. In accordance with the concept of lifelong learning, artificial intelligence ceases to be an accompanying technological attribute, becoming the architectural core of a new model of lifelong learning. AI tools provide the necessary mechanisms for implementing its core principles: adaptability, personalization, integration, and inclusiveness. However, the effectiveness of human interaction with this complex technological environment is determined by mastery of a new tool-industrial engineering. Research prospects include developing industrial engineering didactics and creating pedagogical models where AI serves as the architectural core of a system supporting individual educational trajectories throughout life.
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