Exploring Sophisticated Data Mining Analytics as a Strategy for Diagnostic Assessment of Rich Student Datastreams

探索复杂的数据挖掘分析作为丰富学生数据流诊断评估的策略

• 批准号: 0639783
• 负责人: Christopher Dede
• 金额: --
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-15 至 2008-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0639783&HistoricalAwards=false
• 关键词: Exploring; Sophisticated; Data; Mining; Analytics

This is a SGER for the development of analytic tools used for data mining in commercial applications (from SAS) to be applied to educational data. The tools will be tested on three sets of data: data streams from Multi-User Virtual Environments; data streams from Intelligent Tutoring Systems; and data streams from Educational Games. This SGER will investigate whether the data mining and analysis tools can help answer educational research questions about the effectiveness of these educational systems for whom and under what conditions. The intellectual merit of this research arises from the development of a set of analytic tools that can be used to answer research questions arising from learning technology systems. The broader impact lies in the development of an analytic infrastructure that can be used by other researchers working in the design and analysis of learning technology systems.

这是一个SGER，用于开发用于商业应用程序（来自SAS）的数据挖掘的分析工具，以应用于教育数据。这些工具将在三组数据上进行测试：来自多用户虚拟环境的数据流；来自智能辅导系统的数据流；以及来自Educational Games的数据流。该SGER将调查数据挖掘和分析工具是否可以帮助回答有关这些教育系统在什么条件下对谁有效的教育研究问题。本研究的智力价值源于一套分析工具的发展，这些工具可用于回答学习技术系统产生的研究问题。更广泛的影响在于分析基础设施的发展，可供其他从事学习技术系统设计和分析的研究人员使用。