Binglin Liu
2026
SimPBL: A Multi-Agent Framework for Project-Based Learning
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 | Juanzi Li
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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 | Juanzi Li
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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.