Artificial Intelligence (AI) opens up new perspectives for the transformation of distance learning; however, there is still no clearly structured methodological framework for the development of effective AI-based learning platforms. This study proposes the framework model “learning behavior – AI-oriented scenarios”, which aims to identify key pedagogical and technological factors that contribute to effective learning in a digital environment. Based on an analysis of the scientific literature in educational technologies and the use of AI in teaching, the main characteristics of learning behavior are identified: personalized goal setting, adaptive response to feedback, and autonomous engagement. These characteristics correspond to constructivist and experiential approaches to learning. The study examines how intelligent recommendation systems, adaptive content, and AI-based learning behavior analytics contribute to the development of these characteristics and enhance educational outcomes. As an example, a case study is presented on the development of a prototype AI platform for distance learning, whose effectiveness is supported by survey results demonstrating increased student motivation and engagement. The findings address three key research questions and contribute to the theoretical and methodological foundation for integrating AI into the design of distance education.

Nonlinear single-input single-output (SISO) systems operating under parametric uncertainty often exhibit bifurcations, multistability, and deterministic chaos, which significantly limit the effectiveness of classical linear, adaptive, and switching control methods. This paper proposes a novel synthesis framework for self-organizing control systems based on catastrophe theory, specifically within the class of elliptic catastrophes. Unlike conventional approaches that stabilize a predefined system structure, the proposed method embeds the control law directly into a structurally stable catastrophe model, enabling autonomous bifurcation-driven transitions between stable equilibria. The synthesis procedure is formulated using a Lyapunov vector-function gradient–velocity method, which guarantees aperiodic robust stability under parametric uncertainty. The definiteness of the Lyapunov functions is established using Morse’s lemma, providing a rigorous stability foundation. To support practical implementation, a data-driven parameter tuning mechanism based on self-organizing maps (SOM) is integrated, allowing adaptive adjustment of controller coefficients while preserving Lyapunov stability conditions. Simulation results demonstrate suppression of chaotic regimes, smooth bifurcation-induced transitions between stable operating modes, and improved transient performance compared to benchmark adaptive control schemes. The proposed framework provides a structurally robust alternative for controlling nonlinear systems in uncertain and dynamically changing environments.

This article presents a comparative analysis of the capabilities of the Creo Parametric graphics system in comparison with other popular software products. Special attention is paid to the specifics of working with assemblies in the full-featured NX CAD system, as well as the process of creating a three-dimensional model of a part in SolidWorks. The application areas of graphics systems such as NX and CATIA are also considered. The principle of building a 3D model in the T-FLEX CAD system is investigated. In addition, the possibilities, approaches, and principles of operation of applications of the Creo Parametric graphics system are analyzed. To improve the performance and quality of work in graphics systems, it is recommended to use each of them in those areas of industry where they demonstrate clear advantages. In the engineering industry, the use of the Creo Parametric CAD system is especially advantageous, as it allows you to combine two approaches — parametric and direct modeling. Furthermore, it is convenient to work with small applications and supports the import of formats from computer-aided design (CAD) systems from other manufacturers.

Research on this topic is relevant due to the increasing need for practical skills that enhance the competitiveness of graduates, the development of technology and the need to solve real problems. The purpose of the work is to evaluate the effectiveness of a practice-oriented approach to teaching Python programming in universities in order to optimize curricula and increase students’ readiness to meet the requirements of modern industry. Among the applied methods, analytical, experimental, comparative, modeling, classification, statistical and others can be distinguished. The study noted a significant improvement in academic performance, an increase in interest in the subject and the development of practical skills, which confirms the importance of a practice-oriented approach in university education. The results of the work indicate a significant improvement in the quality of education, high student satisfaction, increased interest in the subject and increased practical skills, which together emphasizes the success and effectiveness of this educational approach. The work focuses not only on improving the educational process, but also on its positive impact on students’ readiness for a career in the field of programming. The results of the study also emphasize the importance of courses based on practical training in Python programming for the formation of both technical skills and the ability to creatively solve problems. Improving student academic performance and satisfaction confirms the effectiveness and prospects of this approach. Thus, the study provides an in-depth analysis of practical benefits and successful outcomes, supporting the implementation of practice-oriented learning in curricula. The practical value of the work lies in the development and implementation of an effective educational approach based on practical training in Python programming, which provides students with real software development skills, increases their competitiveness in the labor market and contributes to successful adaptation in the information technology industry. Keywords: curricula, innovations in education, modern technologies, assessment of educational results, integration of knowledge.

Currently, special attention is being focused on to the application of a practice-oriented approach in the educational process. The article examines the organization of a practice-oriented approach in the study of SMART technologies in educational institutions. In the context of rapid technological progress and digitalization of the economy, the training of specialists with not only theoretical knowledge, but also practical skills in working with modern SMART technologies is of particular importance. The main attention is paid to the methods of introducing SMART technologies into the educational process, their impact on the motivation and academic performance of students, as well as on the development of key competencies needed in the modern world. Examples of successful application of these technologies in an educational institution are given and the results of their use are analyzed. As a result of this study, the following conclusions can be drawn that the practice-oriented approach contributes to the application of solving practical problems, as well as develops the professional experience of future computer science teachers in the organization of modeling practice-oriented tasks. Keywords: Project-oriented approach, SMART technologies, higher education institution, project work, practical assignmen

The article is devoted to substantiating the relevance of training future computer science teachers to use artificial intelligence technologies for analyzing and visualizing educational data in schools. The current state of development of artificial intelligence as an applied industry and as an educational trend in the context of digital transformation of education is analyzed. It has been established that in contemporary conditions, the issues of introducing artificial intelligence technologies into the educational process of general education institutions and higher pedagogical educational institutions are of particular importance as a necessary element of training future teachers. Possible ways of integrating artificial intelligence into school education are considered, and key areas of training for future computer science teachers capable of effectively using AI to analyze and visualize educational data in their professional activities are identified. The research findings demonstrated the necessity of introducing innovative methodological approaches, elective courses, and interdisciplinary projects aimed at enhancing the professional competence of future teachers. The authors emphasize that improving the model of training computer science teachers in the context of educational digitalization is one of the key factors in ensuring high-quality, modern, and competitive school education. In addition, the article identifies the scientific and methodological foundations for applying artificial intelligence tools in pedagogical practice.