@inproceedings{zhang-li-etal-2026-simpbl,
title = "{S}im{PBL}: A Multi-Agent Framework for Project-Based Learning",
author = "Zhang-Li, Daniel and
Lim, Joy Jia Yin and
Liu, Binglin and
Tu, Shangqing and
Yao, Zijun and
Peng, Hao and
Yu, Jifan and
Li, Haoxuan and
Hao, Zhanxin and
He, Ye and
Li, Zekun and
Wang, Jiangyi and
Hou, Lei and
Xu, Bin and
Cong, Xin and
Liu, Zhiyuan and
Liu, Huiqin and
Zhang, Yu and
Li, Juanzi",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.1512/",
pages = "32755--32772",
ISBN = "979-8-89176-390-6",
abstract = "Project-Based Learning (PBL) is an important learning method that promotes understanding and acquiring practical skills through training learners through a project. However, effective PBL often requires sustained orchestration and collaboration, but existing LLM-based learning tools provide partial assistance without explicitly modeling these roles, and overly comprehensive help provided by LLM can reduce learner autonomy. We propose SimPBL, a multi-agent framework with an orchestrator agent that provides adaptive scaffolding from interaction logs and collaborator agents that support project work through boundary-aware collaboration. We conduct comprehensive evaluation to study the effectiveness of SimPBL, where we observe a 14{\%} improvement in learner examination score. Results from extensive studies further highlights the ability of SimPBL to manage learning behavior and improve learning experience. Code and materials are available at https://anonymous.4open.science/r/SimPBL-D5B8."
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<abstract>Project-Based Learning (PBL) is an important learning method that promotes understanding and acquiring practical skills through training learners through a project. However, effective PBL often requires sustained orchestration and collaboration, but existing LLM-based learning tools provide partial assistance without explicitly modeling these roles, and overly comprehensive help provided by LLM can reduce learner autonomy. We propose SimPBL, a multi-agent framework with an orchestrator agent that provides adaptive scaffolding from interaction logs and collaborator agents that support project work through boundary-aware collaboration. We conduct comprehensive evaluation to study the effectiveness of SimPBL, where we observe a 14% improvement in learner examination score. Results from extensive studies further highlights the ability of SimPBL to manage learning behavior and improve learning experience. Code and materials are available at https://anonymous.4open.science/r/SimPBL-D5B8.</abstract>
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%0 Conference Proceedings
%T SimPBL: A Multi-Agent Framework for Project-Based Learning
%A Zhang-Li, Daniel
%A Lim, Joy Jia Yin
%A Liu, Binglin
%A Tu, Shangqing
%A Yao, Zijun
%A Peng, Hao
%A Yu, Jifan
%A Li, Haoxuan
%A Hao, Zhanxin
%A He, Ye
%A Li, Zekun
%A Wang, Jiangyi
%A Hou, Lei
%A Xu, Bin
%A Cong, Xin
%A Liu, Zhiyuan
%A Liu, Huiqin
%A Zhang, Yu
%A Li, Juanzi
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-390-6
%F zhang-li-etal-2026-simpbl
%X Project-Based Learning (PBL) is an important learning method that promotes understanding and acquiring practical skills through training learners through a project. However, effective PBL often requires sustained orchestration and collaboration, but existing LLM-based learning tools provide partial assistance without explicitly modeling these roles, and overly comprehensive help provided by LLM can reduce learner autonomy. We propose SimPBL, a multi-agent framework with an orchestrator agent that provides adaptive scaffolding from interaction logs and collaborator agents that support project work through boundary-aware collaboration. We conduct comprehensive evaluation to study the effectiveness of SimPBL, where we observe a 14% improvement in learner examination score. Results from extensive studies further highlights the ability of SimPBL to manage learning behavior and improve learning experience. Code and materials are available at https://anonymous.4open.science/r/SimPBL-D5B8.
%U https://aclanthology.org/2026.acl-long.1512/
%P 32755-32772
Markdown (Informal)
[SimPBL: A Multi-Agent Framework for Project-Based Learning](https://aclanthology.org/2026.acl-long.1512/) (Zhang-Li et al., ACL 2026)
ACL
- Daniel Zhang-Li, Joy Jia Yin Lim, Binglin Liu, Shangqing Tu, Zijun Yao, Hao Peng, Jifan Yu, Haoxuan Li, Zhanxin Hao, Ye He, Zekun Li, Jiangyi Wang, Lei Hou, Bin Xu, Xin Cong, Zhiyuan Liu, Huiqin Liu, Yu Zhang, and Juanzi Li. 2026. SimPBL: A Multi-Agent Framework for Project-Based Learning. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 32755–32772, San Diego, California, United States. Association for Computational Linguistics.