AIGC is increasingly integrated into university English learning, creating new opportunities and challenges for students' learning experiences. This study examined the dynamic relations among social support, digital stress, digital resilience and learning engagement in AIGC-mediated English learning. Five-wave longitudinal data were collected from 428 Chinese university students across one academic semester. A random-intercept cross-lagged panel model (RI-CLPM) separated stable between-person differences from within-person fluctuations and estimated directional lagged associations, while panel network analysis extended the structural description by estimating temporal, contemporaneous and between-person conditional associations. The RI-CLPM results showed that digital stress negatively predicted later digital resilience and learning engagement, whereas social support positively predicted later digital resilience and showed mostly positive direct effects on subsequent engagement. Digital resilience further predicted later learning engagement and significantly mediated the negative lagged association between digital stress and engagement, although the corresponding indirect pathway from social support to engagement was not supported. The panel network results showed that digital stress occupied a central position in the contemporaneous network, while digital resilience was the central hub at the between-person level. These findings suggest that adaptation to AIGC-mediated English learning is not a simple linear process, but a dynamic system in which digital stress acts as a risk factor and digital resilience functions as a key adaptive mechanism. The study highlights the need to reduce unnecessary digital stress while strengthening students’ capacity to use AIGC tools critically and sustainably.
Background Informal digital learning of English (IDLE) has attracted growing attention in computer-assisted language learning (CALL) research due to its potential to support learners’ affective and motivational development beyond formal instruction. Given the rapid expansion of this research area, this systematic review synthesized empirical evidence on the relationships between IDLE engagement and Positive Psychology (PP)-related learner variables. Methods The Web of Science Core Collection and Scopus were searched on 31 January 2025 for empirical studies published from 2015 onwards. Following PRISMA 2020 guidelines, 45 studies met the inclusion criteria. Each was coded for publication and participant characteristics, the direction of reported associations between IDLE and PP-related constructs, research design, and methodological quality. Results The findings revealed a sharp increase in IDLE research in recent years, with 71% of the included studies published between 2022 and 2024. Most studies were conducted in Asian contexts (76%) and focused on university-level learners (62%). Because many studies examined more than one construct, the 45 studies yielded 86 study–construct entries. Of these, 59 (68.6%) reported positive associations between IDLE and constructs such as enjoyment, confidence, grit, and motivation; 11 (12.8%) reported negative associations with negatively valenced states (anxiety, boredom, and burnout); and 16 (18.6%) reported non-significant or mixed findings. All studies examining enjoyment reported positive associations, and most studies examining foreign language anxiety reported negative associations. Most studies (36 of 45) were rated as high in methodological quality, and the same pattern emerged when only these studies were considered. However, the literature was dominated by cross-sectional designs, limiting causal interpretation. Conclusions Despite these limitations, the review suggested that IDLE may provide a meaningful technology-mediated learning context that is associated with learners’ affective engagement and motivational regulation. Future CALL research should adopt longitudinal and experimental approaches, examine diverse learner populations, and explore how specific digital affordances shape PP-related outcomes.
This study investigates the psychological mechanisms through which artificial intelligence (AI) literacy relates to L2 learners’ willingness to write (WTW). It proposes a serial mediation model wherein L2 writing self-efficacy (WSE) and L2 writing anxiety (WA) sequentially mediate this relationship. Grounded in social cognitive theory and control-value theory, the research employed a sequential explanatory mixed-methods design with 303 Chinese EFL learners. Quantitative results from structural equation modeling indicate that: (1) L2 WSE fully mediates the relationship between AI literacy and L2 WTW; (2) AI literacy is indirectly linked to L2 WTW through a sequential pathway: by first positively predicting L2 WSE, which in turn negatively predicts L2 WA; and (3) the direct effects of AI literacy on L2 WA and L2 WTW are non-significant.To explain these quantitative pathways, qualitative interviews with 16 participants further elucidated how AI tool usage corresponds to higher L2 WSE through strategic partnership, reduced startup burden, and task scaffolding support. Furthermore, the qualitative narratives revealed that while AI usage can initially be associated with anxiety (e.g., fear of exposure, tool-related frustration), the heightened L2 WSE linked to AI literacy effectively serves as a protective factor against these affective barriers. The study concludes that AI literacy positively correlates with L2 WTW through a fully indirect mechanism, in which heightened L2 WSE serves as a vital prerequisite for lowering L2 WA. These findings contribute to theory by integrating two major psychological frameworks and offer practical implications for leveraging AI to cultivate more willing L2 writers.
