CHOIR: A Chatbot-mediated Organizational Memory Leveraging Communication in University Research Labs
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866911412669906944 |
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| author | Lee, Sangwook Abbas, Adnan Chen, Yan Kim, Young-Ho Lee, Sang Won |
| author_facet | Lee, Sangwook Abbas, Adnan Chen, Yan Kim, Young-Ho Lee, Sang Won |
| contents | University research labs often rely on chat-based platforms for communication and project management, where valuable knowledge surfaces but is easily lost in message streams. Documentation can preserve knowledge, but it requires ongoing maintenance and is challenging to navigate. Drawing on formative interviews that revealed organizational memory challenges in labs, we designed CHOIR, an LLM-based chatbot that supports organizational memory through four key functions: document-grounded Q\&A, Q\&A sharing for follow-up discussion, knowledge extraction from conversations, and AI-assisted document updates. We deployed CHOIR in four research labs for one month (n=21), where the lab members asked 107 questions and lab directors updated documents 38 times in the organizational memory. Our findings reveal a privacy-awareness tension: questions were asked privately, limiting directors' visibility into documentation gaps. Students often avoided contribution due to challenges in generalizing personal experiences into universal documentation. We contribute design implications for privacy-preserving awareness and supporting context-specific knowledge documentation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_20512 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | CHOIR: A Chatbot-mediated Organizational Memory Leveraging Communication in University Research Labs Lee, Sangwook Abbas, Adnan Chen, Yan Kim, Young-Ho Lee, Sang Won Human-Computer Interaction Artificial Intelligence H.5.3 University research labs often rely on chat-based platforms for communication and project management, where valuable knowledge surfaces but is easily lost in message streams. Documentation can preserve knowledge, but it requires ongoing maintenance and is challenging to navigate. Drawing on formative interviews that revealed organizational memory challenges in labs, we designed CHOIR, an LLM-based chatbot that supports organizational memory through four key functions: document-grounded Q\&A, Q\&A sharing for follow-up discussion, knowledge extraction from conversations, and AI-assisted document updates. We deployed CHOIR in four research labs for one month (n=21), where the lab members asked 107 questions and lab directors updated documents 38 times in the organizational memory. Our findings reveal a privacy-awareness tension: questions were asked privately, limiting directors' visibility into documentation gaps. Students often avoided contribution due to challenges in generalizing personal experiences into universal documentation. We contribute design implications for privacy-preserving awareness and supporting context-specific knowledge documentation. |
| title | CHOIR: A Chatbot-mediated Organizational Memory Leveraging Communication in University Research Labs |
| topic | Human-Computer Interaction Artificial Intelligence H.5.3 |
| url | https://arxiv.org/abs/2509.20512 |