Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866914330295926784 |
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| author | Yao, Bingsheng Chen, Jiaju Chen, Chaoran Wang, April Li, Toby Jia-jun Wang, Dakuo |
| author_facet | Yao, Bingsheng Chen, Jiaju Chen, Chaoran Wang, April Li, Toby Jia-jun Wang, Dakuo |
| contents | Intelligent systems have traditionally been designed as tools rather than collaborators, often lacking critical characteristics that collaboration partnerships require. Recent advances in large language model (LLM) agents open new opportunities for human-LLM-agent collaboration by enabling natural communication and various social and cognitive behaviors. Yet it remains unclear whether principles of computer-mediated collaboration established in HCI and CSCW persist, change, or fail when humans collaborate with LLM agents. To support systematic investigations of these questions, we introduce an open and configurable research platform for HCI researchers. The platform's modular design allows seamless adaptation of classic CSCW experiments and manipulation of theory-grounded interaction controls. We demonstrate the platform's research efficacy and usability through three case studies: (1) two Shape Factory experiments for resource negotiation with 16 participants, (2) one Hidden Profile experiment for information pooling with 16 participants, and (3) a participatory cognitive walkthrough with five HCI researchers to refine workflows of researcher interface for experiment setup and analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_18008 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration Yao, Bingsheng Chen, Jiaju Chen, Chaoran Wang, April Li, Toby Jia-jun Wang, Dakuo Human-Computer Interaction Artificial Intelligence Computation and Language Intelligent systems have traditionally been designed as tools rather than collaborators, often lacking critical characteristics that collaboration partnerships require. Recent advances in large language model (LLM) agents open new opportunities for human-LLM-agent collaboration by enabling natural communication and various social and cognitive behaviors. Yet it remains unclear whether principles of computer-mediated collaboration established in HCI and CSCW persist, change, or fail when humans collaborate with LLM agents. To support systematic investigations of these questions, we introduce an open and configurable research platform for HCI researchers. The platform's modular design allows seamless adaptation of classic CSCW experiments and manipulation of theory-grounded interaction controls. We demonstrate the platform's research efficacy and usability through three case studies: (1) two Shape Factory experiments for resource negotiation with 16 participants, (2) one Hidden Profile experiment for information pooling with 16 participants, and (3) a participatory cognitive walkthrough with five HCI researchers to refine workflows of researcher interface for experiment setup and analysis. |
| title | Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2509.18008 |