The Relationship Between Supra-Professional Competencies and Socio-Demographic Parameters of Students

   This article is dedicated to examining the interrelationship of supra-professional competencies among students of higher educational institutions, as well as their correlation with sample parameters. The methodological foundation of the study is based on a competence-based approach; supra-professional competencies are regarded as key skills essential for successful adaptation and effective performance across various professional fields. The research was conducted using the assessment results of competencies among students from Russian higher education institutions in the 2022–2023 academic year (n = 76,269). Reliable and valid methodologies developed by specialists from the Assessment and Methodology Department of the Autonomous Non-Profit Organization “Russia – the Country of Opportunities” were employed as tools. A correlational analysis of the relationships between competencies and a comparative analysis based on gender, course of study, educational standards, and regions were performed. It was found that most competencies demonstrate a significant positive correlation, with the exception of the competency “Following Rules and Procedures”, which is negatively correlated with the others. Students in medical specialties exhibited higher results across most competencies compared to students in other fi elds. Female students displayed stronger competencies related to social interaction, while male students showed greater proficiency in competencies pertaining to individual work. Students from capital universities achieved higher results across all competencies, except for “Following Rules and Procedures”. Among students participating in the 2023 season, scores for many competencies were higher than those of participants from the 2022 season (both considering and not considering the course). The findings clarify the characteristics of the relationship between employer-demanded competencies and socio-demographic attributes within a large dataset of student samples. This article will be of interest to employers across various sectors of the economy, as well as to the leadership of higher education institutions for developing eff ective educational policies.

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