AI Insight
This study of 269 Chinese university students in AI-enhanced English courses found that AI literacy significantly predicts foreign language classroom engagement, with foreign language enjoyment serving as a mediating mechanism between the two. Using structural equation modeling and latent profile analysis, researchers identified two distinct learner groups: a high-enjoyment group showing significantly greater engagement and a low-enjoyment group with weaker participation in AI-assisted learning activities. The results demonstrate that emotional factors play a crucial role in how effectively students engage with AI-integrated language learning environments.
Why it matters
These findings suggest that improving students' AI literacy alone may not be sufficient for effective AI-enhanced language learning; fostering positive emotional experiences is equally important. The identification of distinct learner profiles based on enjoyment levels can help educators design more targeted interventions and emotionally responsive AI-supported learning environments that account for individual differences in affective engagement.
Understand the Science
PurposeLearner engagement is central to effective EFL learning, yet limited research has examined how AI literacy contributes to students’ engagement in AI-enhanced language classrooms. Drawing on the growing recognition of emotion in technology-mediated learning, this study investigates whether foreign language enjoyment (FLE) functions as an affective mechanism through which AI literacy influences foreign language classroom engagement (FCE).DesignThe study was conducted with 269 undergraduate students enrolled in AI-enhanced English courses at a Chinese university. This study integrated two complementary methodological approaches. First, structural equation modeling (SEM) was employed to explore the mediating role of FLE in the relationship between AI literacy (AIL) and classroom engagement. Second, latent profile analysis (LPA) was utilized to categorize students into homogeneous subgroups based on their FLE levels.FindingsSEM results showed that AI literacy significantly predicted foreign language enjoyment, which in turn positively predicted classroom engagement. The findings supported the mediating role of FLE in the relationship between AI literacy and classroom engagement. LPA identified two distinct learner profiles: a High-FLE group and a Low-FLE group. Learners in the High-FLE profile reported significantly higher levels of positive affect and classroom engagement, whereas those in the Low-FLE profile demonstrated lower enjoyment and weaker participation in AI-assisted learning activities.ValueThis study advances research on AI-enhanced language learning by conceptualizing foreign language enjoyment as a key affective pathway linking AI literacy to classroom engagement. It reveals both the emotional mechanisms and learner heterogeneity underlying engagement in AI-integrated EFL classrooms. The findings offer pedagogical insights for designing emotionally responsive and pedagogically innovative AI-supported language learning environments.