ANALYSIS OF THE MAIN METHODOLOGICAL APPROACHES TO FORMING MATHEMATICL COMPETENCE IN SECONARY AND HIGH SCHOOL STUDENTS

The article substantiates the author's perspective on the importance of methodological approaches to the development of mathematical competence, based on an analysis of studies by Ukrainian and foreign researchers that examine methodological approaches to the organization of the educational process in general. Mathematical competence is characterized as one of the key skills necessary in the modern world, encompassing the ability to apply mathematical knowledge, understand concepts, and solve problems using Mathematics. Human competence is defined as structured sets of knowledge, skills, abilities, and relationships which enable individuals to identify and solve problems arising in a specific field of activity regardless of the context. To analyze the process of forming mathematical competence in middle and high school students, which is based on collaborative educational and creative activities, the author identifies the following theoretical and methodological approaches: personality-oriented, activity-based, systemic, integrative, competency-based, neurocognitive, and neuromodeling. The study focuses on the detailed analysis of these approaches and highlights specific principles that elaborate on them: personality-oriented (principles: individualization of learning, development of independence and responsibility, support for personal growth, attention to individual needs), activity-based (principles: active student participation, practical orientation, problem-based learning, independent problem-solving), systemic (principles: integrity, structuring, multiplicity, systemic nature), integrative (principles: integration of mathematical disciplines, connection with other subjects, practical application, holistic learning), competency-based (principles: activity orientation, development of critical thinking, interactivity and collaboration, individualization of learning, competency-based assessment), neurocognitive (principles: scientific evidence, adaptive learning, gamified metacognition, analytical learning outcomes), neuromodeling (principles: individualization of learning, adaptability, use of modern technologies, stimulation of cognitive activity, development of critical thinking).