Psychological determinants of GenAI adoption for foreign language education: An extended UTAUT2 model and sentiment analysis approach

Huan Wang^*Tian Liu^*

• Northeastern University, Shenyang, China

The use of Generative Artificial Intelligence (GenAI) in foreign language education is also a paradigm shift; however, psychological factors that affect its adoption are not well understood. While established models such as the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) describe technology adoption in general, they often fail to capture the unique emotional and cognitive reactions triggered by AI. This paper thus presents an important construct to explain the special emotional and cognitive reactions triggered by the learning of human-AI collaboration: AI anxiety. Structural equation modeling (SEM) was used to analyze survey data (N = 632), and sentiment analysis was used for online reviews. The results indicate that Performance Expectancy, Effort Expectancy, and Social Influence positively affect Behavioral Intention. On the other hand, AI Anxiety and Habit significantly negatively affect Behavioral Intention. Sentiment analysis supported these findings, demonstrating positive public sentiment and anxiety and complexity associated with adopting decision-making. The research shows that integrating GenAI into learning is not a functional interaction but a complex psychological interaction. The implications of this research are important for people developing technologically sophisticated yet psychologically attuned AI tools.