Transforming EFL students' engagement: How AI-enhanced environments bridge emotional health challenges like depression and anxiety

Abstract

This study investigates the impact of AI-enhanced environments on EFL students' emotional health and engagement, with a particular focus on challenges related to depression and anxiety. The research finds a significant relationship between AI-integrated learning environments and students' emotional well-being, which in turn influences their levels of engagement. While AI systems provide personalized learning experiences and immediate feedback that can alleviate some emotional distress, they also have the potential to evoke negative emotions such as anxiety and frustration, particularly when students feel overwhelmed or unsupported. These emotional fluctuations directly affect student engagement, leading to difficulties in participation, motivation, and focus. Data from 673 university participants in North China were analyzed using SPSS (version 27) and AMOS (version 24) to apply various statistical methods, including correlation, regression, and structural equation modeling (SEM). The results suggest that emotional health, particularly in terms of depression and anxiety, plays a pivotal role in student engagement in AI-enhanced environments. Students experiencing emotional distress tend to struggle with engagement, which adversely impacts academic performance. Conversely, those with better emotional health demonstrate improved engagement, highlighting the importance of addressing emotional well-being in AI-supported learning settings. This study provides valuable insights into the complex relationship between emotional health and student engagement, offering implications for the design of more supportive and effective AI-based educational experiences.