Thinking with Data: A Cross-Disciplinary Approach

用数据思考：跨学科方法

• 批准号: 0628122
• 负责人: Dale Cook
• 金额: $ 97.93万
• 依托单位: Kent State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0628122&HistoricalAwards=false
• 关键词: Thinking; Data; Cross; Disciplinary; Approach

This project is developing a data literacy curriculum for 7th grade students which will be composed of four two-week units to be taught in social studies, mathematics, science and English courses. The curriculum will utilize data on water use and quality in Ohio, chosen because other communities will have comparable data to modify the curriculum to meet their needs. Central to the curriculum will be the issue of fairness and how data are used to make societal decisions. The curriculum will be pilot tested and field tested in three middle schools in Ohio.Research will be conducted on the efficacy of an instructional model called Preparation for Future Learning (PFL). The underlying tenant of this model is that learning is enhanced if students become familiar with a problem and its context before a solution is developed. In this case, the social studies unit will be the preparation for the learning that will occur in mathematics and science.

该项目正在为七年级学生开发数据素养课程，该课程将由四个为期两周的单元组成，教授社会研究、数学、科学和英语课程。 该课程将利用俄亥俄州用水和水质的数据，之所以选择这些数据是因为其他社区将拥有可比较的数据来修改课程以满足他们的需求。 课程的核心将是公平问题以及如何使用数据做出社会决策。 该课程将在俄亥俄州的三所中学进行试点测试和实地测试。将对名为“未来学习准备”（PFL）的教学模式的有效性进行研究。 该模型的基本原理是，如果学生在开发解决方案之前熟悉问题及其背景，那么学习就会得到加强。 在这种情况下，社会研究单元将为数学和科学的学习做好准备。