The impact of artificial intelligence and virtual teachers on students' learning stress and anxiety: A social psychological analysis

This study explores the impact of Artificial Intelligence (AI) and virtual teachers on students' learning stress and anxiety, applying the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The research investigates key factors influencing students' perceptions and usage of AI-driven learning tools, including Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Behavioral Intention (BI), and Use Behavior (UB). Data were collected from 100 students, revealing generally positive attitudes towards AI tools. The results show that AI's potential to reduce learning stress and improve academic performance (PE) significantly influences students' intention to use these tools in the future (BI). Ease of use (EE) and social support (SI) were also found to positively affect behavioral intention, while facilitating conditions (FC), such as access to necessary resources and technical support, played a crucial role in determining the actual use of AI tools. The study highlights that students are more likely to adopt AI-based educational systems when they perceive them as useful, easy to use, and adequately supported. These findings suggest that fostering positive perceptions, ensuring sufficient resources, and leveraging social influence can significantly enhance the adoption of AI tools, ultimately reducing learning stress and anxiety.