This study aimed to adapt the Artificial Intelligence Self-Efficacy Scale developed by Wang and Chuang (2024) into Turkish and evaluate its validity and reliability. The study was conducted with two independent samples: a group of 291 university students participated in the exploratory factor analysis (EFA), while a separate group of 374 participants was involved in the confirmatory factor analysis (CFA). The 22-item scale, along with demographic questions and one item on AI usage, was administered online. Cronbach’s alpha was used to assess reliability, and correlations with AI usage were examined to evaluate criterion validity. EFA revealed a four-factor structure: assistance, anthropomorphic interaction, comfort with AI, and technological skill, with factor loadings ranging from 0.43 to 0.85. The total variance explained by the factors ranged from 41.23% to 67.47% across the sub-dimensions. A weak negative correlation was found between AI self-efficacy and AI usage levels. The Cronbach’s alpha coefficient was 0.958 for the overall scale, indicating high internal consistency. CFA results confirmed that the Turkish version of the scale is a valid and reliable instrument for measuring AI self-efficacy.
Baltacı et al. (Tue,) studied this question.