Measuring Teachers' competencies for AI integration: Development and validation of the AI-TPACK in vocational education

Integrating artificial intelligence (AI) into education necessitates teachers acquiring competencies aligned with technological advancements, especially within vocational contexts. This study aimed to adapt and validate a concise self-report instrument, the AI-integrated Technological Pedagogical Content Knowledge (AI-TPACK) scale, grounded in the TPACK framework, to measure vocational teachers' competencies in integrating AI into instructional practices. A total of 460 pre-service and in-service vocational teachers from Indonesia participated. The adapted instrument encompasses seven constructs, including AI Pedagogical Knowledge, AI Content Knowledge, AI Technological Knowledge, and their intersections, culminating in a comprehensive AI-TPACK construct. Confirmatory factor analysis confirmed strong model fit, and convergent and discriminant validity, internal consistency, and composite reliability met acceptable thresholds. Structural equation modeling revealed significant predictive relationships among constructs, while measurement invariance tests supported its suitability across pre-service and in-service teachers. These findings affirm the adapted AI-TPACK scale as a reliable and valid tool for assessing AI-integrated pedagogical competencies specifically within vocational education contexts.