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ChatGPT-Assisted Information Retrieval: A Comparative Study of User Behavior in Academic Information Retrieval

  • Beijing Normal University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用 (Scopus)

摘要

This study explores the differences in user behavior between ChatGPT-Assisted and traditional information retrieval modes during academic research. By setting up five academic information retrieval tasks with varying cognitive levels remembering, understanding, analyzing, evaluating, and creating and recruiting 20 first-year master's students, the participants were randomly assigned to complete the tasks under one of the retrieval modes. The results indicate that in each task type, the ChatGPT-Assisted mode reduced the number of clicks on the search engine results page, the number of URLs visited, the duration of URL browsing, and the total retrieval time, suggesting that ChatGPT assistance can enhance retrieval efficiency. Further analysis revealed that the assistance effect of ChatGPT was more significant in remembering, understanding, and creating tasks. This study supports the necessity and feasibility of further exploring ChatGPT's application in the field of information retrieval.

源语言英语
主期刊名JCDL 2024 - Proceedings of the 24th ACM/IEEE Joint Conference on Digital Libraries
编辑Jian Wu, Xiao Hu, Terhi Nurmikko-Fuller, Sam Chu, Ruixian Yang, J. Stephen Downie
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798400710933
DOI
出版状态已出版 - 13 3月 2025
已对外发布是
活动24th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2024 - Hong Kong, 中国
期限: 16 12月 2024 → 20 12月 2024

丛书

姓名Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN(印刷版)1552-5996

会议

会议24th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2024
国家/地区中国
市Hong Kong
时期16/12/24 → 20/12/24

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