Scientific and Methodological Support for the Natural Science Education Cluster: From Visual Regulators to an Intelligent Support System

Introduction. The digital transformation of modern education is highlighting the need to create intelligent systems, where the development of learners' trajectories based on principles of continuity and continuity is particularly important in the context of natural science education clusters (ENO Cluster). The aim of this study is to analyze the cluster's scientific and methodological support and develop an intelligent system architecture based on the integration of static visual didactic guidelines. Materials and Methods. The study is based on a systemic and structural-functional approach. The study was conducted at the M. Akmulla Bashkir State Pedagogical University, involving methodologists, science teachers, and students involved in cluster projects. The theoretical basis was an analysis of the university's existing arsenal of visual didactic tools, including the logical-semantic models and metamodels "PROFI" and "TECHNO." Requirements development and conceptual validation were conducted through expert assessments and focus groups involving specialists in the field of digitalization of education and natural science teaching methods. KEYWORDS Results. Using a systemic and structural-functional approach, we analyzed the scientific and methodological support for the natural science education cluster and developed the architecture of an intelligent support system that integrates static visual didactic guidelines (logical-semantic models, the PROFI and TECHNO metamodels) with an algorithm for the situational selection of teaching and learning materials. An empirical study showed that the system's implementation resulted in statistically significant positive changes. Teachers' self-assessment of methodological competence increased from 2.8 to 4.1 on a 5-point scale (p < 0.001), the proportion of lessons with effective use of visual aids increased from 15% to 68% (p < 0.001), and students' readiness to design a lesson increased from 41.6 to 67.3 points (p < 0.001). The results confirm that the proposed model facilitates the adaptation of content to individual tasks, ensures the continuity of educational trajectories, and creates the basis for a dynamic, personalized environment within the cluster model of natural science education. Conclusion. The research results have practical implications for the development of digital educational environments, personalization of learning, and the effective integration of visual didactic tools into the educational process. The article is intended for researchers in the fields of pedagogy, digitalization of education, and natural science teaching methods.