Integrating Research and Practice: Reimagining Youth Community Science through Make-and-Take Data Sensing Kits

整合研究与实践：通过自制数据传感套件重新构想青年社区科学

• 批准号: 2314089
• 负责人: Paulo Blikstein
• 金额: $ 163.87万
• 依托单位: Teachers College, Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2314089&HistoricalAwards=false
• 关键词: Integrating; Research; Practice; Reimagining; Youth

In dozens of ways, youths' lives are shaped by data. Yet, youth seldom have the opportunity to pull back the curtain on data science to experience how data are collected, prepared, analyzed, and presented into the final, neatly packaged statistics and figures they see every day. This lack of first-hand data science experience not only limits youths' data science skills - key to their educational and career pathways - but also limits their skills as civically engaged decision-makers capable of critically analyzing data-based claims. This project investigates how youth can use low-cost sensors to collect data from their communities and engage in data science practices to explore and tell stories about community-relevant phenomena (e.g., climate change, urban segregation, public transportation, pollution). These museum-based camps are week-long, immersive experiences that focus on question formulation, data collection, analysis, visualization, and interpretation. The informal camp setting offers a mix of both high-contact instructional time (i.e., working with other students and facilitators during the day) and independent exploration time (i.e., taking the hardware home each afternoon and evening) through which youth can both learn new skills and apply them in their homes and communities. In this collaborative project, a university research lab and children's science museum work together to design, implement, study, and revise a week-long data science camp for middle school age students, data science learning assessment items and a facilitator training curriculum. Camps will be implemented during Winter, Spring, and Summer school breaks over a two year period. The project will investigate two primary questions: What data science knowledge and practices do learners gain in the course of designing, carrying out and interpreting a scientific data collection effort relevant to their community? And what ways can museums serve as springboards and touchstones for broader informal STEM learning experiences that expand into learners' homes and communities? Potential contributions include learning theory and design heuristics for informal STEM education programming that positions STEM inquiry and learning within participants' broader communities and sparks youth's recognition of the relevance of a data-oriented approach to understanding their day-to-day environments, spaces, and lives. As camp programming includes four diverse informal data contexts of increasing independence and complexity - (1) guided explorations; (2) 1-day projects; (3) multi-day projects; and (4) longitudinal, at-home, extension projects for a subset of participants (who take the hardware home) - anticipated contributions include comparisons of the varied settings in which informal data science learning occurs. The project uses a mixed-methods research approach that includes: 1) quantitative analyses of paired pre- and post-camp assessments to identify shifts in data science practices and perspectives; 2) qualitative thematic analyses of pre-, post-camp, and delayed interviews triangulated with interaction analysis of in-camp observations; and 3), and log file analyses identifying patterns in learners' data gathering behavior. Additionally, longitudinal analyses of assessment and interview data over the 2.5-year project timeframe will gauge the efficacy of camp curriculum and assessment revisions over the 6 implementations. The project centers equity and belonging in two primary ways: curriculum development efforts focus on inclusive and equitable informal science learning and a focus on Latine populations who are often underserved in STEM education.This project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants.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.

以数十种方式，年轻人的生活是由数据塑造的。然而，青年很少有机会撤回数据科学的窗帘，以体验如何收集，准备，分析和呈现数据到他们每天看到的最终包装的最终包装的统计数据和数字。缺乏第一手数据科学经验不仅限制了年轻人的数据科学技能，这是他们的教育和职业途径的关键 - 而且还将他们的技能限制为能够认真分析基于数据的主张的公民参与决策者。该项目调查了年轻人如何使用低成本传感器从其社区收集数据，并从事数据科学实践，以探索和讲述有关社区相关现象的故事（例如，气候变化，城市隔离，公共交通，污染，污染）。这些基于博物馆的营地是为期一周的沉浸式体验，专注于问题制定，数据收集，分析，可视化和解释。非正式的训练营提供了高接触教学时间（即白天与其他学生和促进者一起工作）和独立探索时间（即每天下午和晚上将硬件回家带回家）的混合在一起，而青年都可以学习新技能并将其应用于他们的家庭和社区。在这个合作项目中，大学研究实验室和儿童科学博物馆共同设计，实施，研究和修改了为期一周的中学时代学生的数据科学训练营，数据科学学习评估项目以及促进者培训课程。在冬季，春季和暑期学校休息两年期间，营地将在两年内实施。该项目将研究两个主要问题：学习者在设计，进行和解释与社区相关的科学数据收集工作的过程中会获得哪些数据科学知识和实践？博物馆可以用哪些方式充当弹簧板和触摸石，以扩大扩展到学习者的家园和社区的更广泛的非正式STEM学习经验？潜在的贡献包括对非正式STEM教育计划的学习理论和设计启发式方法，该计划的立场在参与者的更广泛的社区中进行了探究和学习，并激发了青年人认识到以数据为导向的方法来理解其日常环境，空间和生活的相关性。由于营地编程包括增加独立性和复杂性的四种非正式数据背景 - （1）指导探索； （2）1天项目； （3）多日项目； （4）为一部分参与者（将硬件带回家）的纵向，在家扩展项目 - 包括对发生非正式数据科学学习的各种环境的比较。该项目使用混合方法研究方法，其中包括：1）对训练前和训练后评估的定量分析来确定数据科学实践和观点的转变； 2）通过对训练营内观察的相互作用分析，对训练后，训练后和延迟访谈的定性主题分析；和3），并记录文件分析，识别学习者数据收集行为中的模式。此外，对2。5年项目时间表的评估和访谈数据的纵向分析将衡量CAMP课程和评估修订对6种实施的功效。项目中心公平性和属于两种主要方式：课程开发工作的重点是包容性和公平的非正式科学学习，并专注于经常在STEM教育中服务不足的拉丁人群。该项目是由前进的非正式STEM学习计划（AISL）计划资助的，该计划旨在促进对知识环境的设计和开发的新方法，并促进基于循证的方法和循证理解信息的设计和发展。这包括提供多种途径，以扩大对STEM学习经验的访问和参与，推进对非正式环境中STEM学习的创新研究和评估，并发展参与者对更深入的学习的理解。该奖项反映了NSF的法定任务，并认为通过使用该基金会的知识分子和更广泛的影响来评估Criteria Criteria的评估。