Collaborative Research: An Equity-Focused Approach to Integrating Physical Activity and CS Education for K-8 Learners

合作研究：一种以公平为中心的方法，将 K-8 学习者的体育活动和计算机科学教育结合起来

• 批准号: 2031498
• 负责人: Christine Julien
• 金额: $ 25.5万
• 依托单位: University of Texas at Austin
• 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 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2031498&HistoricalAwards=false
• 关键词: Collaborative; Research; Equity; Focused; Approach

This project brings instruction in computing and data science to an elementary school with a predominantly Hispanic population through Project SMART, a digital educational game that uses students’ in-school physical activity to motivate student learning. Students record their physical activity during the school day, whether in physical education class, at recess, or at other teacher-provided opportunities for physical activity. An elementary school class plays collaboratively; the physical activity of all the students in the class is converted to a distance traveled along an extended virtual journey. The learning modules are defined by teachers and directly connected to the core curriculum. Key to the approach is that the computational learning activities provided introduce data collection, analysis, and prediction questions using the students’ own physical activity data. As such, the project explores research questions that are advancing the field's understanding about how to engage students in computer science. It also is investigating whether students are more engaged in, motivated by, and successful at computational thinking learning objectives if these objectives relate to data that is relevant to them: their physical activity, their interests, their environment, and, importantly, their own collected data.This project expands and strengthens the Project SMART researcher-practitioner partnership (RPP), engaging researchers and teachers in collaborative efforts to identify strategies for computer science and computational thinking instruction that engages an elementary student population and addresses instructional challenges. These challenges include pressures to adhere to state standards that make it difficult to integrate additional content, a lack of at-home internet infrastructure that limits out-of-school student engagement, and teachers' lack of experience with and confidence in computer science content knowledge. Conjectures that orient the research plan explicate a premise that contextualizing computer science within the students' own physical activity during the regular school day as an integrated core subject lesson will help to address these challenges. In addition to advancing the field's understanding of a contextualized approach to data science instruction, this project also creates shareable learning modules that present data science learning activities that use the students' own physical activity to enable data modeling and prediction; guide students in hardware-software co-design to create wearable physical activity monitors that can improve data collection; and enable students to write code that extends the functions available in the game. 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.

该项目通过Project SMART为一所以西班牙裔人口为主的小学带来了计算和数据科学方面的教学，Project SMART是一种数字教育游戏，使用学生的校内体育活动来激励学生学习。学生记录他们在校期间的体育活动，无论是在体育课上，课间休息，还是在教师提供的其他体育活动机会。一个小学班级在一起合作玩;班上所有学生的身体活动都被转换成沿着一段延长的虚拟旅程所走过的距离。学习模块由教师定义，并与核心课程直接相关。该方法的关键在于，所提供的计算学习活动使用学生自己的身体活动数据引入数据收集、分析和预测问题。因此，该项目探讨了正在推进该领域对如何让学生参与计算机科学的理解的研究问题。它还调查了学生是否更积极地参与，动机和成功地实现计算思维学习目标，如果这些目标与与他们相关的数据有关：他们的身体活动，他们的兴趣，他们的环境，而且，重要的是，他们自己收集的数据。这个项目扩大和加强项目SMART研究人员-实践者伙伴关系（RPP），让研究人员和教师共同努力，确定计算机科学和计算思维教学的策略，以吸引小学生群体并解决教学挑战。这些挑战包括遵守国家标准的压力，这使得难以整合额外的内容，缺乏家庭互联网基础设施，限制了校外学生的参与，以及教师缺乏计算机科学内容知识的经验和信心。定位研究计划的猜想阐明了一个前提，即在学生自己的身体活动中，将计算机科学作为一门综合的核心学科课程，将有助于应对这些挑战。除了推进该领域对数据科学教学的情境化方法的理解外，该项目还创建了可共享的学习模块，这些模块展示了使用学生自己的身体活动来进行数据建模和预测的数据科学学习活动;指导学生进行硬件-软件协同设计，以创建可以改善数据收集的可穿戴身体活动监视器;并使学生能够编写扩展游戏中可用功能的代码。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。

项目成果

Integrating Computer Science and Physical Education in Elementary Schools with Data Science Learning Modules Using Wearable Microcontrollers

使用可穿戴微控制器将小学计算机科学和体育与数据科学学习模块相结合

• DOI: 10.1109/mass56207.2022.00105
• 发表时间: 2022
• 期刊: 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS
• 作者: Jeong, Hyun;Payton, Jamie;Julien, Christine;Castelli, Darla
• 通讯作者: Castelli, Darla

Linking Learning Fundamental Reinforcement Learning Concepts with Being Physically Active

将学习基本强化学习概念与身体活动联系起来

• DOI: 10.1145/3545947.3576316
• 发表时间: 2022
• 期刊: ACM
• 作者: Annaluru, Ramakrishna Sai;Julien, Christine;Payton, Jamie
• 通讯作者: Payton, Jamie

Project moveSMART: When Physical Education Meets Computational Thinking in Elementary Classrooms

moveSMART 项目：当小学课堂中体育遇到计算思维

• DOI: 10.1109/mc.2022.3167600
• 发表时间: 2022
• 期刊: Computer
• 影响因子: 2.2
• 作者: Fritz, Connor;Bray, Dylan;Lee, Grace;Julien, Christine;Burson, Sheri;Castelli, Darla;Ramsey, Carol;Payton, Jamie
• 通讯作者: Payton, Jamie

Expanding Elementary School Computer Science Education with an Introduction to Machine Learning Through Rhythmic Studies

通过节奏研究介绍机器学习，扩大小学计算机科学教育

• DOI: 10.1145/3565287.3617623
• 发表时间: 2023
• 期刊: ACM
• 作者: Hunter, Holly;Payton, Jamie;Julien, Christine
• 通讯作者: Julien, Christine