A Study of Student Investigations in Data-Sharing Projects

数据共享项目中的学生调查研究

• 批准号: 9725228
• 负责人: Clifford Konold
• 金额: $ 38.61万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-10-01 至 2000-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9725228&HistoricalAwards=false
• 关键词: Study; Student; Investigations; Data; Sharing

9725228KonoldThe investigation will study a number of the projects that NSF is funding which students collect, share, and analyze real-world data in the course of conducting scientific investigations. IN these projects to date, the data gathering and sharing activities have gone more smoothly than the data ansalysis, in which many students and teachers have struggled. Such difficulties pose a serious barrier to fostering authentic mathematics and science learning and to enabling shared inquiry among students and scientists. This research will study the nature of the data analysis problems to provide a specific information that can help current projects better support data analysis skills, and a research base that can inform the development of future data analysis projects, materials, software, and teacher development efforts. The study will focus on issues such as data authenticity, tractability, and accessibility to students and teachers. Major products will include (1) analyses of individual projects' data sets, including and assessment of the extent to which interesting and interpretable findings can be reached and suggestions on how to make this data more accessible to students, and (2) a technical report that summarizes major findings, includes representative case studies that highlight both the problems and possibilities of students analyzing real world scientific data and makes recommendations about the design of data sharing and analysis projects, including ancillary materials and tools.

9725228 Konold该调查将研究NSF资助的一些项目，这些项目是学生在进行科学调查的过程中收集，共享和分析真实世界的数据。到目前为止，在这些项目中，数据收集和共享活动比数据分析进行得更顺利，许多学生和教师都在努力。 这些困难对培养真正的数学和科学学习以及使学生和科学家能够共同探究构成了严重障碍。 本研究将研究数据分析问题的性质，以提供具体的信息，可以帮助当前的项目更好地支持数据分析技能，并为未来的数据分析项目，材料，软件和教师发展工作的发展提供信息。 这项研究将侧重于数据的真实性、易处理性以及学生和教师的可访问性等问题。 主要成果将包括：（1）分析各个项目的数据集，包括评估在多大程度上可以得出有趣和可解释的结论，并就如何使学生更容易获得这些数据提出建议;（2）总结主要结论的技术报告，包括有代表性的案例研究，突出了学生分析真实的世界科学数据的问题和可能性，并提出了建议，设计数据共享和分析项目，包括辅助材料和工具。