Personalized Education

Personalized education aims to tailor learning experiences to individual student needs, boosting engagement and efficiency. Current research heavily utilizes large language models (LLMs), often coupled with techniques like prompt engineering and retrieval-augmented generation (RAG), to create adaptive learning paths, intelligent tutoring systems, and automated assessment tools. This field is actively exploring the challenges of data bias in LLM training and the need to balance personalization with maintaining factual accuracy and fostering intrinsic motivation, with significant implications for improving learning outcomes and educational equity.