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大数据应用于教育决策的可行性与潜在问题研究 被引量:24

Research on the Feasibility and Potential Problems of Big Data Applied to Education Decision-making
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摘要 通过对大数据特征的考察,结合教育决策过程本质及需求,研究发现:(1)大数据应用于教育决策具有一定的可行性,大数据可以为教育决策提供科学的证据支持。(2)大数据应用于教育决策时会遇到一些潜在的问题,如大数据自身的异质性、价值密度低的特性会影响教育决策的科学性。决策主体的数据能力瓶颈和价值偏好会制约决策的有效性。规范缺位增加了大数据应用于教育决策的风险性。(3)为推动大数据科学化应用于教育决策,需要完善大数据各类标准建设,夯实各类大数据仓库基底。培养大数据整合与分析人才,为决策主体提取有效证据信息。逐步建立大数据应用规范,规避应用过程中的负向影响。推进大数据相关理论研究,提升大数据转化为决策依据的能力。 Based on the investigation of the characteristics of big data, combined with the essence and requirements of education decision-making, the study finds that(1) big data applied in education decision-making have certain feasibility and big data can provide scientific evidence for education decision-making.(2) Some potential problems when big data is applied to education decision-making affect the scientific nature of education decision-making, such as the heterogeneity and low value density of big data.The bottleneck and the value preference of the decision-making subject would restrict the validity of the decision.And Specification absence increases the risk of applying big data to education decisionmaking.(3)In order to promote the scientific application of big data in education decision-making,it is necessary to perfect the standard construction of various big data and consolidate the warehouse base of various big data.Talents of integration and analysis of big data should be cultivated to extract valid evidence information for decision-making subject.Application specification of big data should be gradually established to avoid the negative impact in the process of application.And relevant theoretical research of big data should be promoted to enhance the ability to transform big data into decision-making base.
作者 刘金松 LIU Jinsong(Department of Education/Education Macro Economic Policy Institute, East China Normal University, Shanghai 20006)
出处 《电化教育研究》 CSSCI 北大核心 2017年第11期38-42,74,共6页 E-education Research
关键词 大数据 教育决策 逻辑 规范 风险 Big Data Education Decision-making Logic Specification Risk
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  • 1[英]托马斯·克伦普.数字人类学[M].郑元者译.北京:中央编译出版社,2007.
  • 2[德]乌尔里希·贝克著 何博闻译.风险社会[M].南京:译林出版社,2004..
  • 3[英]安东尼·吉登斯著 田禾译.现代性的后果[M].南京:译林出版社,2000..
  • 4涂子沛.大数据[M].桂林:广西师范大学出版社.2012.
  • 5黄荷.今日谈:大数据时代降临[J].半月谈,2012,(17).
  • 6Siemens,GlstInternational Conferenceon Learning Analyticsand Knowledge 2011 [EB/OL].<https ://tekri.athabascau.ca/ analytics/about.〉.
  • 7Johnson,L.,Adams,S.,andCummins,M.(2012).TheNMCHorizon Report: 2012 Higher EducationEdition.Austin,Texas:TheNewMediaConsortium.
  • 8Baepler,P.& Murdoch, C. J.(2010). Academic Analytics andData Mining in Higher Education. International Journal forthe Scholarship of Teaching and Learning, 4(2). 170-178.
  • 9Chen.E.,Heritage,M.&Lee,J.Identifying and MonitoringStudents, Learning Needs With Technology[J].Journal of Education for Students Placed at Risk,2010(3):309-332.
  • 10Romero& Ventura. Educational Data Mining;A Survey from1995 to 2005[J]. Expert Systems with Applications.2007,(33):125-146.

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