图书情报知识 ›› 2020, Vol. 0 ›› Issue (4): 32-42.doi: 10.13366/j.dik.2020.04.032

• “不同环境和情境下的信息行为研究” 专号征文 • 上一篇    下一篇

面向任务终止的认知停止规则应用及影响因素

黄崑,陈佳琦,乔佳荣,李蕾,王凯飞   

  • 出版日期:2020-07-10 发布日期:2020-08-10

A Study on Application and Influencing Factors of Cognitive Stopping Rules When Digital Library Users Terminate InformationSearch Task

  • Online:2020-07-10 Published:2020-08-10

摘要: [目的/意义]探索数字图书馆用户在停止搜索任务时认知停止规则的使用情况及影响因素。[研究设计/方法]采取实验室研究设计,随机招募35位被试完成5项不同认知复杂度的任务。在检索前收集被试的基本人口学特征、先验检索经验;使用屏幕录制软件记录被试的检索过程;在任务停止检索后收集用户对认知停止规则的使用程度和检索体验。[结论/发现] 用户会综合使用多个认知停止规则来决定搜索任务的终止,其中“信息量阈值”规则使用最多;任务属性和用户的先验经验一定程度影响认知停止规则的使用;“头脑清单”“信息量阈值”和“单一标准”规则使用程度越高,用户的检索体验越好;此外,部分认知停止规则的使用与用户检索行为存在显著相关。[创新/价值]从认知停止规则使用角度提出提升用户检索效果和体验的检索系统优化建议。

关键词: 检索停止, 认知停止规则, 数字图书馆, 信息行为

Abstract: [Purpose/Significance]The purpose of this paper is to explore the use and influencing factors of cognitive stopping rules when users stop their searching in digital libraries.[Design/Methodology]This study adopted laboratory research design, and randomly recruited 35 participants to execute 5 tasks with different cognitive complexity. Their basic demographic characteristics and prior retrieval experience were gathered before their retrieval; their retrieval process was recorded with screen recording software; and their use of cognitive stopping rules and their retrieval experience were collected after the tasks were terminated.[Findings/Conclusion]The experimental results show that users would use multiple cognitive stopping rules to decide whether or not to terminate their searching, while the "Mental List" is mostly used; task characteristics and users’ prior retrieval experience also play an important role in their use of cognitive stopping rules; the higher usage frequency of "Mental List","Magnitude Threshold" and "Single Criterion",the better the users’ retrieval experience; in addition, the use of some cognitive stopping rules is also significantly associated with users’ retrieval behavior.[Originality/Value]From the perspective of cognitive stopping rules use, suggestions of retrieval system optimization have been proposed for improving the effects and experience of users’ retrieval.

Key words: Searching termination, Cognitive stopping rules, Digital library, Information behavior