Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

Understand

Personalized learning represents a promising educational strategy within intelligent educational systems, aiming to enhance learners' practice efficiency.

• However, the discrepancy between offline metrics and online performance significantly impedes their progress.
• To address this challenge, we introduce Agent4Edu, a novel personalized learning simulator leveraging recent advancements in human intelligence through large language models (LLMs).
• Agent4Edu features LLM-powered generative agents equipped with learner profile, memory, and action modules tailored to personalized learning algorithms.