Psychological determinants of GenAI adoption for foreign language education: an extended UTAUT2 model and sentiment analysis approach
Huan Wang, Tian Liu

TL;DR
This study explores how psychological factors like AI anxiety influence the adoption of GenAI in foreign language education.
Contribution
The paper introduces AI anxiety as a novel construct in the UTAUT2 model to explain emotional and cognitive reactions to AI in education.
Findings
Performance Expectancy, Effort Expectancy, and Social Influence positively affect Behavioral Intention.
AI Anxiety and Habit significantly negatively affect Behavioral Intention.
Sentiment analysis revealed positive public sentiment alongside anxiety and complexity in AI adoption.
Abstract
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…
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Taxonomy
TopicsAI in Service Interactions · Artificial Intelligence in Healthcare and Education · Educational Games and Gamification
