AISL: Innovations in Development: Community-Driven Projects That Adapt Technology for Environmental Learning in Nature Preserves
AISL:发展创新:社区驱动的项目,采用自然保护区环境学习技术
基本信息
- 批准号:1423212
- 负责人:
- 金额:$ 88.87万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-04-01 至 2021-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
While low-income and minority communities suffer disproportionately from poor environmental conditions, members of these communities tend to be under-represented in participatory scientific projects and informal science learning opportunities. There are many benefits to community-driven STEM projects, both for individuals' experiential learning and for the betterment of communities. Expanding participation also contributes to a more complete understanding of complex environmental problems, including STEM content and skills. This project engages members of racially and economically diverse communities in identifying and carrying out environmental projects that are meaningful to their lives, and adapts technology known as NatureNet to assist them. NatureNet, which encompasses a cell phone app, a multi-user, touch-based tabletop display and a web-based community, was developed with prior NSF support. Core participants involved in programs of the Anacostia Watershed Society in Washington, D.C., and Maryland, and the Reedy Creek Nature Preserve in Charlotte, NC, will work with naturalists, educators, and technology specialists to ask scientific questions and form hypotheses related to urban waterway restoration and preservation of native species. They will then collect and analyze data using NatureNet, requesting changes to the technology to customize it as needed for their projects. Casual visitors to the nature centers will be able to interact with the environmental projects via the tabletop, and those who live farther away will be able to participate more peripherally via the online community. This study 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.The research project, led by researchers from the University of Maryland, College Park, with collaborators from the University of North Carolina, Charlotte, and the University of Colorado, Boulder, will provide answers to two questions: 1) How do community-driven informal environmental learning projects impact participants, including their motivation to actively participate in science issues via technology and their disposition toward nature preserves and scientific inquiry, and 2) What are the key factors (e.g., demographic composition of participants, geographical location) that influence the development of community-driven environmental projects? Researchers will gather extensive qualitative and quantitative data to understand how community projects are selected and carried out, how participants approach technology use and adaptation, and how informal learning and engagement on STEM-related issues can be fostered over a period of several months and through iterative project cycles. Data will be collected through motivation questionnaires; focus groups; interviews; tabletop, mobile, and website interaction logs; field notes from participatory design and reflection sessions; and project journals kept by nature preserve staff. Through extensive research, iterative design, and evaluation efforts, researchers will develop an innovative model for community-driven environmental projects that will deepen informal science education by demonstrating how members of diverse communities connect environmental knowledge and scientific inquiry skills to the practices, values, and goals of their communities, and how technology can be used to facilitate such connections.
虽然低收入和少数族裔社区尤其受到恶劣环境条件的影响,但这些社区成员在参与性科学项目和非正式科学学习机会中的代表性往往不足。社区驱动的 STEM 项目有很多好处,无论是对于个人的体验式学习还是对于社区的改善。扩大参与还有助于更全面地了解复杂的环境问题,包括 STEM 内容和技能。该项目让种族和经济多元化社区的成员参与识别和实施对他们的生活有意义的环境项目,并采用 NatureNet 技术来帮助他们。 NatureNet 包含一个手机应用程序、一个多用户、基于触摸的桌面显示器和一个基于网络的社区,是在 NSF 先前的支持下开发的。参与华盛顿特区和马里兰州阿纳科斯蒂亚流域协会以及北卡罗来纳州夏洛特芦苇溪自然保护区项目的核心参与者将与自然学家、教育工作者和技术专家合作,提出与城市水道相关的科学问题并形成假设恢复和保护本土物种。然后,他们将使用 NatureNet 收集和分析数据,请求更改技术以根据项目需要进行定制。自然中心的休闲游客将能够通过桌面与环境项目互动,而那些住得更远的人将能够通过在线社区更外围地参与。这项研究由推进非正式 STEM 学习 (AISL) 计划资助,该计划旨在推进非正式环境中 STEM 学习设计和开发的新方法和基于证据的理解。这包括提供多种途径来扩大 STEM 学习体验的获取和参与,推进非正式环境中 STEM 学习的创新研究和评估,以及加深参与者对更深层次学习的理解。该研究项目由马里兰大学的研究人员领导,College Park 与北卡罗来纳大学夏洛特分校和科罗拉多大学博尔德分校的合作者将回答两个问题:1)社区驱动的非正式环境学习项目如何影响参与者,包括他们积极参与的动机通过技术及其技术解决科学问题对自然保护区和科学探究的倾向,以及 2) 影响社区驱动的环境项目发展的关键因素(例如参与者的人口构成、地理位置)是什么?研究人员将收集广泛的定性和定量数据,以了解如何选择和实施社区项目、参与者如何处理技术使用和适应,以及如何在几个月的时间内通过迭代促进 STEM 相关问题的非正式学习和参与项目周期。将通过动机问卷收集数据;焦点小组;采访;桌面、移动和网站交互日志;参与式设计和反思会议的现场记录;以及自然保护区工作人员保存的项目日志。通过广泛的研究、迭代设计和评估工作,研究人员将为社区驱动的环境项目开发一个创新模型,通过展示不同社区的成员如何将环境知识和科学探究技能与实践、价值观和环境联系起来,深化非正式科学教育。他们社区的目标,以及如何利用技术来促进这种联系。
项目成果
期刊论文数量(0)
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会议论文数量(0)
专利数量(0)
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Mary Lou Maher其他文献
Enabling Investigation of Impacts of Inclusive Collaborative Active Learning Practices on Intersectional Groups of Students in Computing Education
调查包容性协作主动学习实践对计算机教育中交叉学生群体的影响
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Sri Yash Tadimalla;Celine Latulipe;Mary Lou Maher;Marlon Mejias;Jamie Payton;A. Rorrer;John Fiore;G. Kwatny;Andrew Rosen - 通讯作者:
Andrew Rosen
Exploring AI-based Computational Models of Novelty to Encourage Curiosity in Student Learning
探索基于人工智能的新颖计算模型,以激发学生学习的好奇心
- DOI:
10.1007/s42979-024-02837-x - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Maryam Mohseni;Mary Lou Maher;Kazjon Grace;Safat Siddiqui;Nadia Najjar - 通讯作者:
Nadia Najjar
Risks and benefits of mass screening for colorectal neoplasia with the stool guaiac test
通过粪便愈创木脂试验大规模筛查结直肠肿瘤的风险和益处
- DOI:
- 发表时间:
1983 - 期刊:
- 影响因子:0
- 作者:
D. Winchester;Joanne Sylvester;Mary Lou Maher - 通讯作者:
Mary Lou Maher
Implications of Identity in AI: Creators, Creations, and Consequences
人工智能中身份的含义:创造者、创造和后果
- DOI:
10.1609/aaaiss.v3i1.31268 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Sri Yash Tadimalla;Mary Lou Maher - 通讯作者:
Mary Lou Maher
An Exploratory Study on the Impact of AI tools on the Student Experience in Programming Courses: an Intersectional Analysis Approach
人工智能工具对学生编程课程体验影响的探索性研究:交叉分析方法
- DOI:
10.1109/fie58773.2023.10343037 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Mary Lou Maher;Sri Yash Tadimalla;Dhruv Dhamani - 通讯作者:
Dhruv Dhamani
Mary Lou Maher的其他文献
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{{ truncateString('Mary Lou Maher', 18)}}的其他基金
Conference: NSF Workshop: Expanding Capacity and Diversity in AI Education
会议:NSF 研讨会:扩大人工智能教育的能力和多样性
- 批准号:
2330257 - 财政年份:2023
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
Examining the Effects of Course Climate, Active Learning, and Intersectional Identities on Undergraduate Student Success in Computing
检查课程气氛、主动学习和交叉身份对本科生计算机成功的影响
- 批准号:
2111376 - 财政年份:2021
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
I-Corps: Digital Platform for Informal Learning Experiences to Encourage Curiosity in STEM Career Paths
I-Corps:提供非正式学习体验的数字平台,鼓励对 STEM 职业道路的好奇心
- 批准号:
2031900 - 财政年份:2020
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
Collaborative Research: Developing a Systemic, Scalable Model to Broaden Participation in Middle School Computer Science
合作研究:开发系统的、可扩展的模型以扩大中学计算机科学的参与
- 批准号:
1837240 - 财政年份:2018
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
EAGER: An Interactive Learning Analytics Framework based on a Student Sequence Model for understanding students, retention, and time to graduation
EAGER:基于学生序列模型的交互式学习分析框架,用于了解学生、保留率和毕业时间
- 批准号:
1820862 - 财政年份:2018
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
RI: Small: CompCog: Pique: A Cognitive Model of Curiosity for Personalizing Sequences of Learning Resources
RI:小:CompCog:Pique:用于个性化学习资源序列的好奇心认知模型
- 批准号:
1618810 - 财政年份:2016
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
IUSE/PFE:RED: The Connected Learner: Design Patterns for Transforming Computing and Informatics Education
IUSE/PFE:RED:互联学习者:变革计算和信息学教育的设计模式
- 批准号:
1519160 - 财政年份:2015
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
EAGER: Collaborative Research: A Computational Model for Evaluating the Quality of Citizen Science Contributions
EAGER:协作研究:评估公民科学贡献质量的计算模型
- 批准号:
1451079 - 财政年份:2014
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
VOSS: Crowdsourcing interaction design for citizen science virtual organizations
VOSS:公民科学虚拟组织的众包交互设计
- 批准号:
1221513 - 财政年份:2012
- 资助金额:
$ 88.87万 - 项目类别:
Standard Grant
HCC: Small: Designing Tangible Computing for Creativity
HCC:小型:为创造力设计有形计算
- 批准号:
1218160 - 财政年份:2012
- 资助金额:
$ 88.87万 - 项目类别:
Continuing Grant
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