Teachers’ self-efficacy beliefs regarding artificial intelligence competencies: Turkish adaptation and psychometric validation of the TAICS scale

This study aimed to adapt the Teachers’ Artificial Intelligence Competence Self-Efficacy Scale (TAICS), developed by Chiu et al. (2025), into Turkish and to examine its psychometric properties within the Turkish educational context. The study was designed as a methodological scale adaptation and psychometric validation study. The adaptation process included forward translation, translation review, back-translation, linguistic refinement, expert evaluation, pilot testing, and main validation analyses. Five separate study groups, consisting of field experts, language experts, pre-service English language teachers, pilot participants, and teachers from different school levels and subject areas, contributed to the process. The main validation sample comprised 449 teachers. Confirmatory factor analysis supported the original six-factor structure of the scale, consisting of AI Knowledge, AI Pedagogy, AI Assessment, AI Ethics, Human-Centred Education, and Professional Engagement. The second-order CFA findings further indicated that these dimensions could be represented under a higher-order construct of teachers’ self-efficacy beliefs regarding AI competencies. Reliability analyses showed that Cronbach’s alpha, McDonald’s omega, and composite reliability coefficients were satisfactory for both the subscales and the total score. Convergent validity was supported, whereas discriminant validity findings indicated substantial empirical overlap among some theoretically related dimensions. Measurement invariance analyses further supported the comparability of the scale across gender. Overall, the Turkish version of the TAICS Scale provides psychometric evidence supporting its use for assessing teachers’ self-efficacy beliefs regarding AI competencies in Türkiye.