This study investigated the application of an artificial intelligence (AI) coach for second language (L2) learning in a primary school involving 327 participants. In line with Community of Inquiry, learners were expected to perceive social, cognitive, and teaching presences when interacting with the AI coach, which was considered a humanized agent. To examine how learners’ perceived AI presences were related to their language learning, this study drew on AI usage data, actual learning outcomes, and attitudinal data. Results from hierarchical regression analyses suggest that cognitive presence and learners’ affection for AI’s appearance were significant predictors of L2 enjoyment, which also positively predicted learning outcomes. The score of English shadowing (representing the quality of AI usage) positively predicted learning outcomes. Contrary to intuition, teaching presence was found to negatively predict learning outcomes. Based on cluster analysis and subsequent MANOVA results, this study indicates that the learners perceiving higher social and cognitive presences via interacting with AI and showing greater affection for AI’s appearance tended to use the AI coach more frequently, demonstrate higher L2 enjoyment, and achieve higher learning outcomes. The present study contributes to the limited but increasing knowledge of human-AI interaction in educational settings and carries implications for future efforts on the use of AI for L2 learning.

To investigate the phenomenon of technostress among university teachers in higher education, a multidimensional person-environment misfit framework of technostress was proposed and validated by 343 teachers from universities in China. The findings indicate that person-organization (P-O) misfit, person-technology (P-T) misfit, and person-people (P-P) misfit largely captured how university teachers interact with multiple dimensions of the higher education environment in an imbalanced way that causes technostress. P-O misfit predicted P-T misfit and P-P misfit. Relationships between multidimensional technostress and job performance were investigated. It was found that university requirements related to the use of ICT and the suitability of ICT for university teachers’ work were critical factors affecting their job performance. In addition, a comparison was made among university teachers from different grade levels, revealing that university management related to ICT use tended to affect university teachers of higher-grade levels more than those of lower-grade levels in generating technostress.