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Home AI & Sentiment Analysis

[2406.19226] Simulating Classroom Education with LLM-Empowered Agents

AiNEWS2025 by AiNEWS2025
2024-12-11
in AI & Sentiment Analysis
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[2406.19226] Simulating Classroom Education with LLM-Empowered Agents
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[Submitted on 27 Jun 2024 (v1), last revised 27 Nov 2024 (this version, v2)]
Authors:Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, Linlu Gong, Jinchang Zhou, Zhanxin Hao, Jianxiao Jiang, Jie Cao, Huiqin Liu, Zhiyuan Liu, Lei Hou, Juanzi Li

View a PDF of the paper titled Simulating Classroom Schooling with LLM-Empowered Brokers, by Zheyuan Zhang and 11 different authors

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Summary:Giant language fashions (LLMs) have been utilized throughout varied clever instructional duties to help instructing. Whereas preliminary research have centered on task-specific, unbiased LLM-empowered brokers, the potential of LLMs inside a multi-agent collaborative framework for classroom simulation with actual consumer participation stays unexplored. On this work, we suggest SimClass, a multi-agent classroom simulation instructing framework. We acknowledge consultant class roles and introduce a novel class management mechanism for computerized classroom instructing, and conduct consumer experiments in two real-world programs. Utilizing the Flanders Interactive Evaluation System and Group of Inquiry theoretical frameworks from instructional evaluation, we exhibit that LLMs can simulate a dynamic studying setting for customers with energetic teacher-student and student-student interactions. We additionally observe group behaviors amongst brokers in SimClass, the place brokers collaborate to create enlivening interactions in school rooms to enhance consumer studying course of. We hope this work pioneers the applying of LLM-empowered multi-agent techniques in digital classroom instructing.

Submission historical past

From: Zheyuan Zhang [view email]
[v1]
Thu, 27 Jun 2024 14:51:07 UTC (11,711 KB)
[v2]
Wed, 27 Nov 2024 08:50:24 UTC (1,834 KB)

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#Simulating #Classroom #Schooling #LLMEmpowered #Brokers

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