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构建院校智能体系:院校研究发展的新趋势 被引量：18

Developing an institutional intelligence system:a new trend of institutional research
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摘要 院校智能是院校研究与商业智能相结合的产物,是当今信息时代院校研究不可或缺的组成部分。院校智能体系的使用有利于提高院校数据收集整合效率、管理信息知识产出效率以及研究成果推广应用效率,并最终强化院校研究对大学政策制定的支撑作用。本文从院校研究的发展和商业智能的功能两个方面对院校智能的含义和价值进行了阐述,并对院校智能体系的基本框架进行了介绍。 Institutional intelligence is a result of integrating business intelligence techniques into institutional research. It is an indispensable component of institutional research in this information era, which plays a significant role in improving efficiency and effectiveness of collecting and integrating data, exploring unknown information and knowledge, disseminating results, and, thus, eventually enhancing higher education decision making. This study describes the concept and significance of institutional intelligence from the perspective of the development of institutional research and the functions of business intelligence, and also introduces a fundamental framework of institutional intelligence system.
作者 常桐善
机构地区 美国加利福尼亚州大学校长办公室院校研究处
出处 《高等教育研究》 CSSCI 北大核心 2009年第10期49-54,共6页 Journal of Higher Education
关键词 院校研究 商业智能 院校智能 大学管理 institutional research business intelligence institutional intelligence higher education administration
分类号 G640 [文化科学—高等教育学]
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参考文献12

  • 1赵炬明.管理咨询与院校研究[J].高等工程教育研究,2007,55(2):53-62. 被引量：21
  • 2KUSTER J, ROUSE C. A business intelligence primer for higher education: Applying BI in higher education [EB/OL]. BeyeNETWORK. 2009, http:// www. b-eye-network, com/channels/5085/view/9704/ , 2009-09-21.
  • 3WELLS D. Institutional intelligence: Applying business intelligence principles to higher education [EB/OL]. Campus Technology. 2007, http://campustechnology, com/ articles/ 2007 /04 / insti tutionalintelligence, aspx, 2009-09-21.
  • 4PETERSON M. Institutional research and management in the U. S. and Europe: Some EAIR - AIR comparisons[A]. Roddy Begg. The Dialogue between Higher Education Research and Practice[C]. New York: Kluwer Academic Publishers, 2003. 31-44.
  • 5程星 周川.院校研究与美国高校管理[M].长沙:湖南人民出版社,2003..
  • 6LUHN H P. A business intelligence system [J]. IBM Journal, 1958, 314-319.
  • 7HOWSON C. Successful Business Intelligence: Secrets to Making BI a Killer App[M]. New York: Mc Graw Hill, 2003.
  • 8CAMP R. The Search for Industry Best Practices That Lead 2 Superior Performance[M]. Productivity Press, 1989.
  • 9常桐善.数据挖掘技术在美国院校研究中的应用[J].复旦教育论坛,2009,7(2):72-79. 被引量：47
  • 10POWER D, POWER JD. Decision Support Systems: Concepts and Resources for Managers [M].. Westport, Conn. , Quorum Books. 2002.1-19.

二级参考文献35

  • 1谢邦昌.数据挖掘Clementine应用实物[M].北京:机械工业出版社,2008.
  • 2Applying Data Mining Techniques Using SAS Enterprise Miner[M].Cary,USA:The SAS Institute,2005.
  • 3Michael J.A.Berry &Gordon S.Linoff.Data Mining Techniques for Marking,Sales,and Customer Relationship Management[M].Indianapolis,USA:Wiley Publishing,2004.
  • 4Lin Chang.Applying Data Mining to Predict College Admissions Yield:A Case Study[G]//Jing Luan &Chun-Mei Zhao.Data Mining in Action:Case Studies of Enrollment Management:New Directions for Institutional Research.San Francisco,USA:Jossey-Bass,2006.
  • 5Jing Luan.Data Mining and Its Applications in Higher Education[G] //Andreea M Serban and Jing Luan (eds.),Knowledge Management:Building a Competitive Advantage in Higher Education:New Directions for Institutional Research.San Francisco,USA:JosseyBass,2002.
  • 6Chris Dede &Jody Clarke.Data Mining as an Emerging Means of Assessing Student Learning[C].Presented at EDUCAUSE Annual Conference,2007.
  • 7National Survey of Student Engagement.Experience That Matters:Enhancing Student Learning and Success[R].2007.
  • 8Steven Brint,John Aubrey Douglass,Richard Flacks,Gregg Thomson,& Steve Chatman.A New Generation:Ethnicity,Socioeconomic Status,Immigration and the Undergraduate Experience at the University of California[R].Center for Studies in Higher Education.Berkeley:The University of California Berkeley,2007.
  • 9Chong Ho Yu,Angel Jannaseh-Pennell,Samuel DidGangi,Chang Kim,&Sandra Andrew.A Data Visualization and Data Mining Approach to Response and Non-Response Analysis in Survey Research[J].Practical Assessment,Research &Evaluation.2007,12(19).
  • 10Tom Bohannon.Data Mining Concepts,Myths,and Case studies[C].Presentation.Annual Forum of Association for Institutional Research,2006.

共引文献85

同被引文献181

引证文献18

二级引证文献213

高等教育研究
2009年 第10期

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