Abstract:

The integration of artificial intelligence into foreign language education has transformed the field by offering personalized, adaptive learning environments. Recent studies suggest that the effective adoption of AI tools depends largely on affective factors such as attitudes toward AI (Chen et al., 2024), AI self-efficacy (Huang et al., 2024; Xie et al., 2025), and AI anxiety (Chen et al., 2024; Parviz & Arthur, 2025). While existing research predominantly focuses on English as a foreign language (EFL), there is a distinct lack of empirical data regarding other foreign languages. This study aims to explore Turkish as a foreign language (TFL) learners’ attitudes toward AI, alongside their AI-related self-efficacy and AI-anxiety levels, and to determine whether the affective variables observed in EFL contexts also apply to learners of Turkish from diverse educational backgrounds. Designed as a cross-sectional study, a total of 143 participants who learn TFL participated in the study. Data were collected using the Artificial Intelligence Attitude Scale (Grassini, 2023), Artificial Intelligence Self‑Efficacy Scale (Wang & Chuang, 2024 ), and the Artificial Intelligence Anxiety Scale (Wang & Wang, 2019). Preliminary analyses indicate that the three affective constructs display distinguishable patterns among learners, offering valuable insights into how AI is perceived within the context of Turkish language learning. Beyond documenting general tendencies, the study also examined the relationships among AI attitudes, AI self-efficacy, and AI anxiety. This investigation contributes to the growing body of literature on AI integration by highlighting the need to consider learners’ emotional and cognitive readiness when designing instructional materials.

Keywords:

AI, foreign language learning, tertiary education, affective factors.