| 文献数据库用户心智模型演进驱动因素结构测量研究 |
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| 引用本文： | 韩正彪,韩正芝.文献数据库用户心智模型演进驱动因素结构测量研究[J].图书情报工作,2017,61(15):111-119. |
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| 作者姓名： | 韩正彪 韩正芝 |
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| 作者单位： | 1. 南京农业大学信息科学技术学院领域知识关联研究中心 南京 210095;
2. 北方自动化控制研究所 太原 030051 |
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| 基金项目： | 本文系国家社科青年基金资助项目"人机交互环境下文献数据库用户心智模型演进机理研究"（项目编号：14CTQ023）研究成果之一。 |
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| 摘 要： | 目的/意义]对文献数据库用户心智模型演进的驱动因素结构进行测量。方法/过程]研究采用问卷调查法收集483份关于文献数据库用户对其心智模型演进驱动因素认知的问卷,采用二阶验证性因素分析方法对收集到的数据进行分析。结果/结论]研究发现文献数据库用户心智模型的驱动因素有文献数据库界面引导与提示、自我摸索、与同学交流、文献数据库信息服务产品、搜索引擎学习迁移、简单信息检索任务、复杂信息检索任务、信息检索课程、请教老师、图书馆信息检索培训和购物网站学习迁移。这些因素对用户心智模型演进的重要性依次升高。此外,由于用户心智模型构成维度的复合性,每种驱动因素对文献数据库内容认知、信息检索方法认知、信息检索结果筛选的影响都存在差异。研究结果可为文献数据库的界面优化设计和用户信息素养培训提供指导建议。
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| 关 键 词： | 文献数据库 信息检索 心智模型 演进 用户 |
| 收稿时间： | 2017-05-09 |
A Study on Measuring the Driving Factor Structure of Academic Database Users' Mental Model Evolution |
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| Han Zhengbiao,Han Zhengzhi.A Study on Measuring the Driving Factor Structure of Academic Database Users' Mental Model Evolution[J].Library and Information Service,2017,61(15):111-119. |
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| Authors: | Han Zhengbiao Han Zhengzhi |
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| Institution: | 1. Research Center for Correlation of Domain Knowledge, College of Information Science and Technology, Nanjing Agriculture University, Nanjing 210095;
2. North Automatic Control Institute of China, Taiyuan 030051 |
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| Abstract: | Purpose/significance] The purpose of this study is to measure the driving factor structure of academic database users' mental model evolution. Method/process] The collected surveys from academic database users were analyzed by the second-order confirmatory factor analysis model. Result/conclusion] The results show that driving factors include interface guide and cues, self-learning, communication with students, information service product academic databases, learning transfer of search engines, simple information retrieval task, complexity information retrieval task, information retrieval course, consulting teachers, information retrieval training of library and learning transfer of shopping websites. The importance of these driving factors increases in turn. As the mental model is complex, each driving factor has a different influence on users' cognition of academic database contents, information retrieval methods and selecting information retrieval results. The results can provide guidance for the optimized design of the academic database interface and information literacy training. |
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| Keywords: | academic database information retrieval mental model evolution user |
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