Jiqun Fan

In the context of AI‐empowered language education, informal digital learning of English has emerged as a key site for fostering young learners ' positive psycho‐emotional development. However, limited attention has been paid to how family factors shape children ' s willingness to communicate with AI. This study investigated how parental investment influences upper‐primary students ' willingness to communicate with AI in an AI‐enhanced informal digital learning of English context, focusing on the mediating roles of AI learning self‐efficacy and learning autonomy. Grounded in Social Cognitive Theory and Self‐Determination Theory, the study surveyed 659 upper‐primary students from eight primary schools. Results revealed a serial mediation pathway: parental investment → self‐efficacy → autonomy → willingness to communicate with AI. These findings extend parental investment research into AI‐enhanced informal digital learning of English contexts and integrate two major motivational frameworks into a unified model of child L2 psycho‐emotional functioning.

This study examines how teacher interpersonal behaviours and AI attributes (responsiveness and anthropomorphism) influence students' willingness to communicate (WTC) with AI through the parallel mediators of classroom enjoyment and AI trust. Using survey data from 557 Chinese undergraduates in AI‐enhanced language classrooms, structural equation modelling revealed that teacher–student interaction predicts communication willingness both directly and indirectly through dual mediators. While responsiveness operates fully through indirect pathways, anthropomorphism exerts both direct and indirect effects. Crucially, classroom enjoyment enhances AI trust, confirming a synergistic affective‐cognitive sequence. Findings demonstrate teachers' irreplaceable role in AI‐enabled classrooms, highlighting human–AI synergy rather than substitution. This dual‐mediation perspective offers valuable insights for integrating AI while preserving essential human elements in education. This study examines how teacher interpersonal behaviours and two key AI attributes—responsiveness (speed/fluency of AI feedback) and anthropomorphism (human‐like cues of AI)—shape students' willingness to communicate with AI (WTCA) through the parallel mediators of classroom enjoyment and AI trust. Survey data from 557 Chinese undergraduates in AI‐enhanced language classrooms were analysed with structural equation modelling. Teacher–student interaction predicted WTCA both directly and indirectly via enjoyment and trust. AI responsiveness operated only through these indirect paths, whereas anthropomorphism exerted additional direct effects. Enjoyment, in turn, enhanced AI trust, confirming an affective‐cognitive synergy. Findings underscore teachers' irreplaceable role in human–AI collaborative learning and offer practical guidance for integrating AI without sacrificing essential human elements.

As an important development in CALL, artificial intelligence (AI)-assisted foreign language teaching not only offers unique advantages in leveled reading, vocabulary, pronunciation, self-assessment, personalized testing, and information retrieval but also effectively enhances learner interaction and emotional regulation in reading. Despite these advancements, research on learner emotional engagement in AI-augmented EFL reading instruction remains limited, and there is a lack of sufficient empirical understanding of the significance of learner interaction. This study constructs a predictive model for emotional engagement among EFL learners in AI-augmented educational contexts, aiming to analyze the impact of learners’ AI literacy and peer interaction on their emotional engagement in reading. The research was conducted among 650 EFL university students in central China. Findings indicate that in AI-augmented EFL learning scenarios, learner AI literacy and peer learning interactions positively influence emotional engagement in reading. Furthermore, learner interest in AI use and reading pleasure play partial mediating and serial mediating roles in this relationship, respectively. This study not only highlights the critical role of AI literacy in AI-assisted EFL reading but also clarifies the significance of interpersonal communication for emotional engagement in AI contexts.

Generative Artificial Intelligence (GenAI) offers robust information generation, swift responsiveness and high personalization for education. However, it remains unclear how these specific technological features translate into improved learning engagement through the mediation of learners' psychological states. Grounded in the Stimulus‐Organism‐Response (S‐O‐R) theory, this study investigates the mediating roles of AI trust and AI learning self‐efficacy in the relationships between GenAI features (responsiveness and personalization) and the learning engagement of English as a Foreign Language (EFL) learners. This study surveyed 697 undergraduate students from four universities in China, all of whom had used GenAI to assist their EFL learning. Using structural equation modelling, the results revealed that: (1) Both responsiveness and personalization significantly enhanced learners' AI trust and self‐efficacy; (2) These psychological states, in turn, positively influenced learning engagement; (3) A critical divergence was observed: responsiveness influenced engagement only indirectly through the full mediation of trust and self‐efficacy, whereas personalization exerted both a direct effect and indirect effects through the same mediators. This study elucidates the distinct psychological pathways through which different AI features affect engagement, providing a more nuanced theoretical account. The findings underscore that for AI tools to foster deep engagement, they must be designed not only to be responsive and personalised but also to proactively build learners' trust and confidence in their AI‐use capabilities.

Curiosity and anxiety are critical emotional factors influencing language learning; yet, existing studies often overlook their combined effects and the mechanisms through which they shape academic achievements. This study aimed to explore the relationships among language learning curiosity, foreign language anxiety, and academic achievement among junior high school students. A total of 870 students from southeastern China, including 7 selected for semi-structured interviews, participated in the study. Quantitative data were analyzed through SPSS and AMOS with structural equation modeling, while qualitative data were examined using thematic analysis in NVivo to identify profile-based patterns. The findings revealed that students showed relatively high curiosity and moderate anxiety in English language learning. Consistent with our hypotheses, curiosity positively predicted academic achievement, while anxiety had a negative effect. Foreign language anxiety partially mediated the relationship between curiosity and academic performance. Qualitative data supported these findings, showing that curiosity fostered engagement and reduced anxiety in real learning contexts. These findings support the control-value theory of academic emotions and offer theoretical and practical implications for emotional regulation in language education.

The increasing incorporation of artificial intelligence (AI) in English as a foreign language (EFL) instruction has garnered much attention on the importance of technological elements in language instruction. However, while AI in education (AIED) is still in its early development, research on how learners’ AI literacy affects their language learning outcomes is insufficient. Furthermore, studies examining the impact of learners’ emotional states within the context of AIED are remarkably few. This study examines the interplay between AI literacy and EFL learners’ willingness to communicate (WTC), emphasizing the mediating roles of learners’ AI learning self-efficacy and foreign language classroom anxiety. This study utilizes structural equation modeling, analyzing data from 517 university students in China to construct a prediction model for WTC in AI-enhanced EFL contexts. The findings indicate that AI literacy improves self-efficacy in AI learning and diminishes classroom anxiety, both of which are significant mediators in the relationship between AI literacy and willingness to communicate. The study highlights the imperative of integrating AI literacy into EFL instruction to enhance learners’ expressive confidence and mitigate fear. The findings improve understanding of the interplay between AI literacy, psychological factors, and language learning outcomes, offering practical insights for the integration of AI in EFL education.

This study leverages the Stimulus‐Organism‐Response (S‐O‐R) framework to investigate the effects of teacher and technical support (TCHS) on learners' willingness to communicate (WTC) in artificial intelligence (AI)‐enhanced English as a foreign language (EFL) contexts, considering the mediating effects of learners' artificial intelligence literacy (AIL) and foreign language enjoyment (FLE). A quantitative survey encompassing 637 non‐English major university students across four institutions was conducted. Structural equation modelling (SEM) results demonstrated that teacher support (TEAS) exerts a direct influence on learners' WTC, whereas TCHS does not. The study also revealed that AIL and FLE significantly mediate the relationship between teacher and TCHS and learners’ WTC. The findings underscore the pivotal role of cognitive and affective factors, emphasising the substantial impact of TEAS and the value of nurturing learners’ AIL and enjoyment of foreign languages. This research offers strategic implications for educational practitioners and policymakers, advocating for the integration of innovative educational technologies and fostering sustainable growth in artificial intelligence in education.

The academic study of work engagement among pre-service teachers during their practicum has been notably sparse, with even fewer investigations examining the influence of environmental stimuli on their engagement levels and the role of individual psychological and emotional factors throughout the practicum. To address this research gap, the present study, informed by the Stimulus–Organism–Response (SOR) theory, has developed a structural equation model. This model posits teacher support and peer support as stimuli, L2 grit and the foreign language teaching enjoyment as the organism, and the work engagement of pre-service teachers as the behavioral response. A quantitative survey was conducted among 516 preservice EFL teachers to examine the relationships among variables in the model. Findings showed direct predictions of work engagement by teacher support, L2 grit, and FLTE. L2 grit and FLTE sequentially mediated the relationship between teacher and peer support and work engagement. This study identified the factors influencing preservice EFL teachers’ work engagement, contributing to a deeper understanding of their psychological characteristics and emotional experiences during the teaching practicum. Additionally, the study offers practical implications for universities and internship schools to enhance preservice teachers’ work engagement during the practicum.