Work

Educational content generation using multi-LLM agents

Year: 2024

Type: article

Abstract: This paper presents a framework for generating educational content using a multi-agent architecture powered by Large Language Models (LLMs). Leveraging the Crew AI framework, the system coordinates multiple autonomous agents, each with specific roles, to produce cohesive educational materials. The agents work collaboratively to generate, detail, direct, and refine content aimed at children under 13, ensuring the inclusion of moral lessons and engaging narratives. This approach enhances the efficiency and effectiveness of content creation, providing a scalable solution for educational material generation.

Source: International Robotics & Automation Journal

DOI: 10.15406/iratj.2024.10.00288

Authors: Ishmam Ahmed Solaiman, Tanzila Sultana Maria, Mariofanna Milanova

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W4402324036

FWCI: 1.517

Cites: 2

Cited by: 4

Related to: 10