Building a sustainable national network for developing and disseminating Sports Content for Outreach, Research, and Education in data science

建立一个可持续的国家网络，用于开发和传播体育内容，以促进数据科学的推广、研究和教育

• 批准号: 2142705
• 负责人: Rebecca Nugent
• 金额: $ 110万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2142705&HistoricalAwards=false
• 关键词: Building; sustainable; national; network; developing

This project aims to serve the national interest by exploring approaches to engage and prepare the next generation of data scientists through sports analytics. This collaborative effort will create a national network of academic and sports industry partners to develop modules paired with data, code, example problems. All materials will be housed on the Integrated Statistics Learning Environment (ISLE) platform, which will be freely accessible to students and faculty. Industry partners from over 50 sports teams and leagues will work with educators to create authentic modules that will focus on introducing foundational data science topics via sports applications. Resources will be primarily geared towards undergraduate students and will cover a wide array of men’s and women’s sports including baseball, basketball, hockey, tennis, cricket and much more. The project will also offer professional development opportunities for faculty and work to engage a diverse collection of institutions and students with an additional goal of broadening participation in the data science workforce.This collaboration brings together educators from five institutions (Carnegie Mellon University, Baylor University, St. Lawrence University, University of Pittsburgh and the United States Military Academy) together with sports industry professionals to create authentic curricular materials. Industry partners will lead the development of each module with guidance from a team of expert educators. As a result, educators will better understand skills and approaches used by sports analytics professionals, and will also have access to case studies build from real-world data. Each module will be reviewed and refined to ensure clarity and accessibility for undergraduates at varying educational stages and within multiple disciplines. Modules will showcase multiple steps for working with data: deciding how to collect and wrangle data, building and assessing appropriate models, and communicating the results. Project materials will be hosted on an Integrated Statistics Learning Environment (ISLE) platform, which will provide user data to help the network better understand how the modules are used, identify areas for improvement, and explore engagement across subgroups of students and educators. Evaluation and knowledge generation will focus on exploring three key ideas: 1) incorporating industry partners into the creation of education materials at scale, 2) exploring the directed module structure utilized in the project; and 3) analyzing user data to explore the engagement of students and educators via the ISLE platform. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.

该项目旨在通过探索通过体育分析吸引和培养下一代数据科学家的方法来服务于国家利益。 这项合作将创建一个全国性的学术和体育行业合作伙伴网络，以开发与数据、代码和示例问题配对的模块。 所有材料都将存放在综合统计学习环境（ISLE）平台上，学生和教师可以免费访问该平台。来自50多个运动队和联盟的行业合作伙伴将与教育工作者合作，创建真实的模块，重点是通过体育应用程序介绍基础数据科学主题。资源将主要面向本科生，并将涵盖广泛的男子和女子运动，包括棒球，篮球，曲棍球，网球，板球等等。该项目还将为教师提供专业发展机会，并致力于吸引各种机构和学生，同时扩大数据科学劳动力的参与。（卡内基梅隆大学、贝勒大学、圣劳伦斯大学、匹兹堡大学和美国军事学院）与体育行业的专业人士一起创建真实的课程材料。 行业合作伙伴将在专家教育工作者团队的指导下领导每个模块的开发。因此，教育工作者将更好地了解体育分析专业人员使用的技能和方法，并将获得从真实世界数据构建的案例研究。每个模块都将进行审查和完善，以确保不同教育阶段和多个学科的本科生的清晰度和可访问性。模块将展示使用数据的多个步骤：决定如何收集和整理数据，构建和评估适当的模型，以及传达结果。项目材料将托管在综合统计学习环境平台上，该平台将提供用户数据，以帮助网络更好地了解如何使用这些模块，确定需要改进的领域，并探索学生和教育工作者分组的参与。评估和知识生成将侧重于探索三个关键理念：1）将行业合作伙伴纳入大规模教育材料的创建，2）探索项目中使用的定向模块结构; 3）分析用户数据，以探索学生和教育工作者通过ISLE平台的参与度。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。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。