Collaborative Research: Exploring the Mathematics of Biological Ecosystems with Data Science

合作研究：用数据科学探索生物生态系统的数学

• 批准号: 2031459
• 负责人: Andee Rubin
• 金额: $ 29.99万
• 依托单位: TERC Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2031459&HistoricalAwards=false
• 关键词: Collaborative; Research; Exploring; Mathematics; Biological

Using software tools to explore, analyze, visualize, and explain data is increasingly common. However, the development of data science skills and practices are still not common in much of K-12 education. This project will create and study "data excursions," structured activities that develop high school students' competencies with data practices and modeling within existing, phenomenon-based science curriculum. Integrating the Common Online Data Analysis Platform (CODAP), a free web-based data analysis and modeling tool designed for students in grades 6 – 14, the data excursions will allow students to interact with existing datasets drawn from primary research. Students will learn to aggregate and represent data to explain biological phenomena such as the spread of antibiotic-resistant bacteria and population changes in the Serengeti plains.The project will use design-based research to investigate how working with real datasets, creating computational representations and using them to reason about ecosystem phenomena can support students' development of data science literacy. Transfer tasks, classroom observations, student interviews, and short exit surveys will be used to identify what aspects of the interventions lead to desired learning outcomes. The researchers will also develop professional learning opportunities for teachers to help them create relevant and coherent materials for students from nondominant communities. This project is funded by the CS for All: Research and RPPs program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

使用软件工具来探索，分析，可视化和解释数据越来越普遍。然而，数据科学技能和实践的发展在K-12教育中仍然不常见。该项目将创建和研究“数据游览”，结构化的活动，发展高中学生的能力与数据实践和建模在现有的，基于现象的科学课程。整合通用在线数据分析平台（CODAP），一个免费的基于网络的数据分析和建模工具，专为6 - 14年级的学生设计，数据游览将允许学生与现有的数据集从主要研究得出互动。学生将学习如何聚合和表示数据，以解释生物学现象，如抗药性细菌的传播和塞伦盖蒂平原的人口变化。该项目将使用基于设计的研究来研究如何使用真实的数据集，创建计算表示并使用它们来推理生态系统现象，以支持学生的数据科学素养的发展。转移任务，课堂观察，学生访谈和简短的退出调查将被用来确定哪些方面的干预措施导致理想的学习成果。研究人员还将为教师开发专业学习机会，帮助他们为来自非主导社区的学生创造相关和连贯的材料。该项目由CS for All：Research and RPPs计划资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。