AI literacy and attitudes among teacher candidates in a comparative study of Kazakhstan and Türkiye

The purpose of this study was to examine differences and relationships among computer self-efficacy, artificial intelligence (AI) literacy, and attitudes toward AI among teacher candidates in Türkiye and Kazakhstan. A quantitative comparative-correlational survey design was employed. The sample consisted of 246 teacher candidates from Türkiye and 234 teacher candidates from Kazakhstan, selected through convenience sampling with predefined inclusion criteria, including voluntary participation and sufficient English proficiency to complete the scales. Data were collected through a personal information form, the Computer Self-Efficacy Scale, the Artificial Intelligence Literacy Scale, and the General Attitudes toward Artificial Intelligence Scale. Independent samples t-tests, one-way ANOVA, and multiple regression analyses were conducted. The results showed that Turkish teacher candidates reported significantly higher computer self-efficacy than Kazakh teacher candidates. No significant country-based difference was found in AI literacy or positive attitudes toward AI; however, Kazakh teacher candidates reported significantly higher negative attitudes toward AI. Gender-based analyses showed no significant differences in the Kazakhstan sample, whereas in the Türkiye sample male teacher candidates reported higher computer self-efficacy and female teacher candidates reported higher negative attitudes toward AI. Grade level was not significantly associated with computer self-efficacy or AI literacy in either country. In the Türkiye sample, negative attitudes toward AI differed significantly by grade level, while the difference in positive attitudes was borderline and should be interpreted cautiously. Regression analyses showed that computer self-efficacy and AI literacy significantly predicted positive attitudes toward AI in the Kazakhstan sample, explaining 54% of the variance. In the Türkiye sample, AI literacy was the only significant predictor, and the model explained 23% of the variance. These findings suggest that AI literacy may be an important factor associated with teacher candidates’ attitudes toward AI, although the cross-sectional and self-report design limits causal interpretation.