Academic anxiety is a negative emotional state experienced by learners of Chinese as a foreign language (CFL) during their Chinese language learning process. To explore the mediating mechanisms of positive and negative emotions and academic self-efficacy between teacher support and academic anxiety, a questionnaire survey was conducted among 1047 CFL learners, and a structural equation model was established to test the mediating effects. The study found that teacher support helps alleviate academic anxiety among CFL learners; teacher support exerts a certain inhibitory effect on learners’ academic anxiety. However, teacher support does not directly reduce academic anxiety but indirectly influences it through the independent mediating roles of self-efficacy and academic emotions, as well as through the chain mediating effect of both. Based on these findings, the paper provides recommendations for maintaining positive emotions, enhancing self-efficacy, implementing tailored teacher support, and constructing comprehensive motivational mechanisms for CFL learners.

Generative artificial intelligence represented by ChatGPT is triggering profound changes in Chinese writing instruction. Based on self-determination theory, this study uses questionnaires and open-ended feedback to examine the effect of introducing the generative AI chatbot ChatGPT into teacher-led Chinese L2 writing courses on learners’ engagement. The participants were 83 Chinese L2 learners, divided into an intervention group and a control group. Learners in the intervention group participated in writing workshops combined with ChatGPT feedback. Results show: (1) Learners using ChatGPT showed improvements in behavioral, emotional, and cognitive engagement in writing; (2) ChatGPT feedback significantly enhanced learners’ behavioral and cognitive engagement, while improvements in emotional engagement were limited; (3) There is a certain association between increased engagement and improved writing performance, indicating that generative AI technology has potential to promote learner participation and improve task completion in writing. The study suggests that effective application of generative AI in Chinese writing instruction should be based on learner individual differences and specific writing task requirements, combined with scientific instructional design to achieve more efficient learner engagement and higher writing quality.

Many learners of Chinese can complete classroom tasks and demonstrate formal knowledge, yet remain reluctant to use Chinese when communication becomes socially visible. This study examined how learning motivation is associated with L2 willingness to communicate (WTC) among international students enrolled in blended Chinese as a second language (CSL) programs. Drawing on the L2 WTC framework, control-value theory, and self-efficacy theory, the study specified a theory-informed indirect-association model in which academic emotions and academic self-efficacy link motivation with communicative readiness. Survey data were collected from 956 international students in Chinese-language programs at eight universities in China. Measures covered learning motivation, positive academic emotions, negative academic emotions, academic self-efficacy, and L2 WTC. Confirmatory factor analysis and structural equation modeling with 5,000 bootstrap resamples were used to evaluate the measurement structure and the proposed indirect pathways. The structural model fitted the data well, χ ² /df = 2.84, CFI = 0.96, TLI = 0.95, RMSEA = 0.044, and SRMR = 0.038. Learning motivation was directly associated with L2 WTC ( β = 0.21, p < 0.001), and the total indirect association through emotions and self-efficacy ( β = 0.34) was larger than the direct component. Positive emotions, lower negative emotions, and self-efficacy each accounted for part of the motivation-WTC association. Because the study used cross-sectional data, these pathways are interpreted as theoretically ordered associations rather than causal effects. The findings refine motivation-centered accounts of WTC by showing that motivation is linked with communicative readiness partly through emotionally supportive and capability-enhancing psychological conditions in blended CSL learning.

Based on competency theory, evaluate and study international Chinese language teachers at different stages of development, establish predictive models of international Chinese language teachers at different stages of development, and analyze their competency characteristics. To establish predictive models of international Chinese language teachers at different development stages based on artificial intelligence-related technologies. First, the research data obtained from the questionnaire survey method are clustered and analyzed by machine learning. Second, models suitable for categorizing international Chinese teachers at different stages of development were selected to explore the competency factors of international Chinese teachers at different stages of development.