SGER: Exploratory Study of Data Mining Techniques Applied to Educational Research Data

SGER：数据挖掘技术应用于教育研究数据的探索性研究

• 批准号: 0607635
• 负责人: Tasha Inniss
• 金额: --
• 依托单位: Spelman College
• 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: 2006-02-01 至 2008-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0607635&HistoricalAwards=false
• 关键词: SGER; Exploratory; Study; Data; Mining

This SGER proposal seeks to apply emerging research on data mining to the analysis of educational video text. The proposal will review in depth existing literatures from both the mathematics research community and the education research community. An advisory team of leading mathematics educators and statisticians will review the work. One of the expected outcomes of the proposal is reduce the amount of time education researchers must spend in analyzing the video by using these advanced technologies. The study will also explore whether these techniques can provide different insights into video text data. The proposal will contribute to further collaboration between mathematics researchers and education researchers.

该SGER提案旨在将数据挖掘的新兴研究应用于教育视频文本的分析。该提案将深入审查现有的文献从数学研究界和教育研究界。一个由顶尖数学教育家和统计学家组成的咨询小组将审查这项工作。该提案的预期结果之一是通过使用这些先进技术，减少教育研究人员必须花费在分析视频上的时间。研究还将探讨这些技术是否可以为视频文本数据提供不同的见解。该提案将有助于数学研究者和教育研究者之间的进一步合作。