This study aims to develop and implement a multidimensional vector modeling approach to comprehensively analyze the methodological competence of prospective mathematics teachers. The analysis focuses on five core dimensions: cognitive, social, operational, research, and methodological. The participants comprised 25 master’s students in Mathematics Education with a minimum of one year of teaching experience. Data were collected through self-perception questionnaires and classroom performance observation sheets, and subsequently represented as five-component vectors. The calculated vector modulus was 3.66, indicating that the overall methodological competence is at a developing level. Findings reveal that the cognitive and operational dimensions dominate competence achievements, whereas the social and research dimensions require further reinforcement. Vector modeling allows for simultaneous representation of inter-component competencies, providing a precise depiction of ability distribution and inter-dimensional variation. These results offer an empirical basis for teacher education institutions to design adaptive professional development programs and extend the literature on multidimensional teacher competence assessment in mathematics education. Thus, this approach not only enhances conceptual understanding of the structure of methodological competence but also provides an objective and strategic diagnostic tool for targeted teacher training interventions.
Copyrights © 2026