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◆ IEEE Signal Processing Magazine2025-11-01· Realm

Large Language Models for Education: <i>A survey and outlook</i>

Shen Wang, T. Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, Qingsong Wen

原始摘要(英文原文)· Original abstract
The advent of large language models (LLMs) has ushered in a new era of possibilities in the realm of education. This survey article summarizes recent progress in the application of LLMs in educational settings from multiple perspectives, including student and teacher assistance, adaptive learning, and commercial tools. Additionally, it systematically reviews technological advancements in each area, compiles related datasets and benchmarks, and identifies the risks and challenges associated with deploying LLMs in education. Furthermore, the article outlines future research opportunities, highlighting promising directions. This article aims to provide a comprehensive technological overview for educators, researchers, and policy makers to harness the power of LLMs, revolutionize educational practices, and foster a more effective personalized learning environment.
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Large Language Models for Education: <i>A survey and outlook</i> — 科研速览 Science Skim