Agent4EDU: Advancing AI for Education with Agentic Workflows

The vigorous development of artificial intelligence (AI) represented by large language models (LLMs) has rapidly promoted the updating and development of educational technology. Agentic workflows (AWs) built based on LLMs can realize complex tasks in the field of education, which allows the emergence of swarm intelligence (SI) through multi-agent collaboration[1]. This study introduces the Agent4EDU (agent for education) framework, which outlines 4 application models in education from the two dimensions of degree of agency and degree of interaction, including human-AI collaboration, AI assistant, instruction execution, and general type. The proposed Agent4EDU framework discusses the paradigm of educational applications of AI agents and promotes the development of the field of AI for education.