Development and validation of the AI-empowered visualization teaching competency scale

This study took primary and secondary school teachers in western China as participants. Grounded in the AI-TPACK framework and integrating visual literacy, data literacy, and relevant learning and development theories, it constructed a five-dimensional theoretical framework for teacher visualization teaching competency under AI empowerment. Drawing on item analysis, exploratory factor analysis, confirmatory factor analysis, reliability testing, measurement invariance testing, and criterion-related validity testing, the study developed and validated the AI-Empowered Teacher Visualization Teaching Competency Scale (AI-VTCS). The results show that AI-VTCS comprises five dimensions-Design and Creation, Awareness and Interpretation, Decision-Making and Collaboration, Ethics and Safety, and Professional Development-with a total of 31 items. The Cronbach's α coefficients of the five subscales ranged from 0.911 to 0.934, and that of the overall scale was 0.967. Both the first-order and second-order five-factor models achieved good fit, and the moderate-to-high correlations among the five dimensions support the hierarchical nature of the construct. Measurement invariance from configural to strict invariance was established across gender, school type (public/private), and teaching stage (primary, middle, and high school). Convergent validity, discriminant validity, and criterion-related validity all met psychometric standards. This study not only fills the theoretical gap in existing teacher competency frameworks regarding AI-empowered visualization teaching, but also provides a reliable and valid standardized measurement instrument for teacher education institutions to assess and precisely enhance teachers' AI visualization teaching competency.