Synergizing AI and collaborative learning: a new approach to Chinese character acquisition in lower elementary education

This study investigated the effectiveness of an AI-enhanced collaborative learning (AICL) framework in supporting Chinese character acquisition among second-grade students. Through a quasi-experimental design, 68 students were assigned to three conditions: AI-enhanced collaborative learning, collaborative learning without AI, and traditional learning. The intervention implemented a six-stage framework integrating AI-powered learning application with structured peer collaboration activities over a one-month period. Writing performance, learning motivation, and student perceptions were assessed through mixed-methods data collection. Results revealed that the AICL group significantly outperformed other groups in overall writing performance. While quantitative analysis showed no significant differences in learning motivation across groups, qualitative findings from student interviews indicated positive engagement with the AI-enhanced collaborative features, despite some technical challenges. The study contributes to ongoing discussions in the learning sciences about how AI can support socially mediated learning. The findings demonstrate that integrating adaptive AI feedback with collaborative learning structures can provide effective support for early literacy development. They also underscore the importance of aligning technical tools with young learners’ developmental needs and ensuring system stability in real-world classroom settings. These insights suggest promising directions for implementing AI-enhanced collaborative approaches in elementary literacy education.