Probability and Statistics for Secondary Schools--A ComputerLearning Environment and Curriculum

中学概率与数理统计--计算机学习环境与课程

• 批准号: 9400091
• 负责人: William Finzer
• 金额: $ 29.83万
• 依托单位: Key Curriculum Press
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-10-01 至 1996-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9400091&HistoricalAwards=false
• 关键词: Probability; Statistics; Secondary; Schools; ComputerLearning

9400091 Finzer This project aims to develop a computer learning environment and curriculum materials for use in teaching data analysis and statistics at the high school level. The proposed curriculum materials will be usable in a semester-long course, as substantial units within other mathematics and science courses, and as skill-focused components of other courses. This project will bring learning experiences to secondary school classrooms that intimately involve students with concepts and technologies they need to become informed and productive participants in the information age. The software, provisionally named StochasticsLab, is a conceptually unified platform for data gathering and exploration, simulation, and statistical analysis. The innovative design supports the latest understanding about how children learn stochastic ideas, including the importance of user-constructed measures, the problems and potentials associated with categorical variables, and the need to feed simulation data into data analysis tools. It is based from the ground up on net- worked collaboration, access to large datasets, and visual explanation of how things work. While the software is expected to enhance existing courses, the curriculum materials will require the presence of computers and software. In this project, the software is the major innovation. ***

9400091 芬策 该项目旨在开发计算机学习环境和课程材料，用于高中数据分析和统计教学。 拟议的课程材料将在一个学期的课程中使用，作为其他数学和科学课程的实质性单元，并作为其他课程的技能为重点的组成部分。 该项目将把学习经验带到中学课堂，使学生密切参与，掌握他们成为信息时代知情和富有成效的参与者所需的概念和技术。 该软件暂时命名为StochasticsLab，是一个概念上统一的数据收集和探索，模拟和统计分析平台。 创新的设计支持对儿童如何学习随机想法的最新理解，包括用户构建的措施的重要性，与分类变量相关的问题和潜力，以及将模拟数据输入数据分析工具的必要性。 它是基于从底层开始的网络协作，访问大型数据集，以及对事物如何工作的可视化解释。虽然预计该软件将加强现有课程，但课程材料将需要计算机和软件。 在这个项目中，软件是主要的创新。 ***