Аннотация
Teachers’ socio-emotional competencies are increasingly recognized as essential for professional well-being, adaptive teaching, and effective participation in digitally transforming educational systems. However, valid and culturally appropriate instruments for assessing these competencies among teachers remain limited, particularly in multilingual and underrepresented educational contexts. This study aimed to adapt the Behavioral, Emotional, and Social Skills Inventory (BESSI) for teachers in Kazakhstan and to examine its preliminary psychometric properties and socio-emotional competency profiles. The instrument was translated and culturally adapted into Kazakh and Russian using a TRAPD-based (Translation, Review, Adjudication, Pretesting, and Documentation) procedure involving translation, review, adjudication, pretesting, and documentation. Data were collected from 1458 school teachers across Kazakhstan representing different subject areas and language groups. After data-quality screening, the final analytic sample included 918 valid observations. Reliability analyses demonstrated excellent total-scale internal consistency (Cronbach’s α = 0.92; McDonald’s ω = 0.94), while domain-level reliability ranged from moderate to acceptable (α = 0.60–0.76; ω = 0.73–0.81). Exploratory factor analysis suggested an empirical eight-factor structure rather than a direct replication of the original BESSI framework, indicating that socio-emotional competencies may be organized differently in teacher populations. Model-based clustering identified four exploratory teacher profiles reflecting different configurations of self-management, emotional regulation, interpersonal, and innovation-related competencies. The profiles differed not only in overall competency levels but also in specific patterns of strengths and developmental needs. The findings provide preliminary evidence supporting the use of the adapted BESSI as a promising research and diagnostic instrument for assessing teachers’ socio-emotional competencies in Kazakhstan. At the same time, the results indicate the need for further confirmatory validation, measurement invariance testing, and external validity evidence before broader application.