Exploring the Potential Barrier Factors of AI Chatbot Usage Among Teacher Trainees: From the Perspective of Innovation Resistance Theory
Liu Yonggang, Hapini Awang, Nur Suhaili Mansor
Abstract
With the development of Artificial Intelligence (AI) technology, more and more AI chatbots (e.g., ChatGPT and DeepSeek) are beginning to affect work and lifestyles. Although AI chatbots have brought many opportunities to education and teacher trainees, they have also caused many problems and resistance among some teacher trainees. However, previous studies have focused more on the influence of positive acceptance factors induced by AI chatbots and less on the negative barrier model induced by AI chatbots. Therefore, this study starts from the negative barrier factors induced by AI chatbots and builds an influencing barrier model of AI chatbot resistance guided by Innovation Resistance Theory (IRT) and appropriately draws on Cultural Dimension Theory (CDT), Unified Theory of Acceptance and Use of Technology (UTAUT), and practical characteristics. The questionnaires mainly adopt convenience sampling and snowball sampling methods, and the data are empirically analyzed. The results show that Uncertainty Avoidance, the Social Influence Barrier, and Technology Anxiety have a significant and direct influence on teacher trainees’ resistance to AI chatbots. Meanwhile, Uncertainty Avoidance, the Social Influence Barrier, and Technology Anxiety play significant mediating roles in the impact of the Usage Barrier (UB), Image Barrier (IB), Value Barrier (VB), Risk Barrier (RB), and Tradition Barrier (TB) on resistance behaviors, revealing the complex path through which cognition-emotion-society factors jointly shape technology resistance behaviors. Therefore, this study not only contributes to enriching the theoretical results of combining Innovation Resistance Theory with AI chatbots and adding new research paths (e.g., the mediating role of Uncertainty Avoidance) but also provides a practical guide for the dissemination of AI chatbots among teacher trainees and future technological talents in a sustainable future.