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
基本信息
- 批准号:2314089
- 负责人:
- 金额:$ 163.87万
- 依托单位:
- 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:
- 关键词:
项目摘要
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.
在许多方面,年轻人的生活都是由数据塑造的。然而,年轻人很少有机会拉开数据科学的帷幕,体验如何收集、准备、分析数据,并将其呈现为他们每天看到的最终、包装整齐的统计数据和数字。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-这是他们教育和职业道路的关键-而且限制了他们作为公民参与决策者的技能,能够批判性地分析基于数据的主张。该项目研究青年如何使用低成本传感器从社区收集数据,并参与数据科学实践,以探索和讲述与社区相关的现象(例如,气候变化、城市隔离、公共交通、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。非正式的营地设置提供了高接触教学时间(即,白天与其他学生和辅导员一起工作)和独立探索时间(即,每天下午和晚上把硬件带回家),通过这些活动,青年人既可以学习新技能,又可以将其应用于家庭和社区。在这个合作项目中,一所大学的研究实验室和儿童科学博物馆共同设计,实施,研究和修改为期一周的中学生数据科学营,数据科学学习评估项目和促进者培训课程。夏令营将在为期两年的冬季、春季和夏季学校放假期间实施。该项目将调查两个主要问题:学习者在设计、执行和解释与其社区相关的科学数据收集工作的过程中获得了哪些数据科学知识和实践?博物馆可以通过哪些方式作为跳板和试金石,让更广泛的非正式STEM学习体验扩展到学习者的家庭和社区?潜在的贡献包括非正式STEM教育规划的学习理论和设计方法,将STEM调查和学习定位在参与者更广泛的社区中,并激发青年对以数据为导向的方法的相关性的认识,以了解他们的日常环境,空间和生活。由于营地规划包括四种不同的非正式数据环境,其独立性和复杂性越来越高-(1)引导探索;(2)1天项目;(3)多日项目;(4)针对一部分参与者(将硬件带回家)的纵向,在家,扩展项目-预期的贡献包括比较非正式数据科学学习发生的各种环境。该项目采用混合方法研究方法,包括:1)对训练营前和训练营后的成对评估进行定量分析,以确定数据科学实践和观点的转变; 2)对训练营前、训练营后和延迟访谈进行定性主题分析,并与训练营内观察的交互分析进行三角分析; 3)和日志文件分析,以确定学习者数据收集行为的模式。此外,在2.5年的项目时间框架内对评估和访谈数据进行的纵向分析将衡量6次实施中营地课程和评估修订的有效性。该项目以两种主要方式为中心:课程开发工作侧重于包容性和公平的非正式科学学习,并关注在STEM教育中往往服务不足的拉丁裔人口。该项目由推进非正式STEM学习(AISL)计划资助,该计划旨在推进非正式环境中STEM学习的设计和发展的新方法和基于证据的理解。这包括提供多种途径,以扩大获得和参与STEM学习经验,推进创新研究和评估的STEM学习在非正式环境中,并发展的理解,更深层次的学习参与者。该奖项反映了NSF的法定使命,并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响力审查标准的支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Paulo Blikstein其他文献
Design Guidelines and Empirical Case Study for Scaling Authentic Inquiry-based Science Learning via Open Online Courses and Interactive Biology Cloud Labs
通过开放在线课程和交互式生物学云实验室扩展真实探究式科学学习的设计指南和实证案例研究
- DOI:
10.1007/s40593-017-0150-3 - 发表时间:
2018 - 期刊:
- 影响因子:4.9
- 作者:
Zahid Hossain;Engin Bumbacher;Alison Brauneis;Monica Diaz;Andrew J. Saltarelli;Paulo Blikstein;Ingmar H. Riedel - 通讯作者:
Ingmar H. Riedel
Using video analysis and learning analytics to understand programming trajectories in data science activities with Scratch
使用视频分析和学习分析来了解 Scratch 数据科学活动中的编程轨迹
- DOI:
10.1145/3501712.3529742 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Cassia Fernandez;João Adriano Freitas;R. Lopes;Paulo Blikstein - 通讯作者:
Paulo Blikstein
Using Multimodal Learning Analytics to Study Learning Mechanisms
使用多模态学习分析来研究学习机制
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
M. Worsley;Paulo Blikstein - 通讯作者:
Paulo Blikstein
Leveraging multimodal learning analytics to differentiate student learning strategies
利用多模式学习分析来区分学生的学习策略
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
M. Worsley;Paulo Blikstein - 通讯作者:
Paulo Blikstein
Inside out: teaching empathy and social-emotional skills
由内而外:教授同理心和社交情感技能
- DOI:
10.1145/3202185.3213525 - 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Dana Kralicek;Swati Shelar;Lisa von Rabenau;Paulo Blikstein - 通讯作者:
Paulo Blikstein
Paulo Blikstein的其他文献
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{{ truncateString('Paulo Blikstein', 18)}}的其他基金
Collaborative Research: Seeing Science: Using Computer Vision to Explore the Scientific Principles Behind Everyday Objects
协作研究:看到科学:利用计算机视觉探索日常物体背后的科学原理
- 批准号:
2202579 - 财政年份:2022
- 资助金额:
$ 163.87万 - 项目类别:
Standard Grant
From Access to Sustainability: Investigating Ways to Foster Sustainable Use of Computational Modeling in K-12 Science Classrooms
从可及性到可持续性:研究在 K-12 科学课堂中促进计算模型可持续使用的方法
- 批准号:
2010413 - 财政年份:2020
- 资助金额:
$ 163.87万 - 项目类别:
Standard Grant
NRI: Liquid Handling Robots - A New Paradigm for STEM Education
NRI:液体处理机器人——STEM 教育的新范式
- 批准号:
2032359 - 财政年份:2019
- 资助金额:
$ 163.87万 - 项目类别:
Standard Grant
NRI: Liquid Handling Robots - A New Paradigm for STEM Education
NRI:液体处理机器人——STEM 教育的新范式
- 批准号:
1638070 - 财政年份:2016
- 资助金额:
$ 163.87万 - 项目类别:
Standard Grant
EAGER: Infusing Learning Sciences Research into Digital Fabrication and Making in Education
EAGER:将学习科学研究融入教育中的数字制造和制作
- 批准号:
1349163 - 财政年份:2013
- 资助金额:
$ 163.87万 - 项目类别:
Standard Grant
CAREER: Bifocal Modeling: A New Famework for the Learning of Advanced STEM Content in High-school
职业:双焦点建模:高中高级 STEM 内容学习的新名作
- 批准号:
1055130 - 财政年份:2011
- 资助金额:
$ 163.87万 - 项目类别:
Continuing Grant
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