Design of an Intelligent Home–School Communication Mini-Program Powered by Large Language Models: A Case Study of an AI Teaching Assistant

This study explores the application mechanisms and interaction design innovations of Artificial Intelligence (AI) teaching assistants in home–school communication under the context of large language models. Based on a review of existing research and intelligent communication tools, it addresses challenges such as information fragmentation, heavy teacher workloads, and low feedback efficiency by leveraging the natural language understanding and generation capabilities of large language models. Using the “AI Teaching Assistant” mini-program as a case study, the research analyzes interaction processes, information integration, and intelligent response strategies. The findings indicate that, compared with traditional communication tools, AI teaching assistants based on large language models offer clear advantages in semantic understanding, contextualized feedback, and content generation, effectively reducing teachers’ cognitive and time burdens while improving the efficiency and quality of home–school communication.