Work

Agent4EDU: Advancing AI for Education with Agentic Workflows

Year: 2024

Type: conference-paper

Abstract: 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. 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.

DOI: 10.1145/3722237.3722268

Authors: Ling Dai, Yuan-Hao Jiang, Yuanyuan Chen, Zinuo Guo, Tian-Yi Liu, Xiaobao Shao

Institutions: Nanyang Technological University, National Institute of Education, East China Normal University, Shanghai Jiao Tong University, Jiangsu University of Science and Technology

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Funders: East China Normal University, Research and Innovation Foundation

OpenAlex ID: W4409965221

FWCI: 3.925

Cites: 29

Cited by: 10

Related to: 10