Exploring STEM Impact and Engagement in Student-Led and Purpose-Driven Projects
Exploring STEM Impact and Engagement in Student-Led and Purpose-Driven Projects
批准号:
1759224
负责人:
Nathan Holbert
金额:
$10.3万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2021-06-30
中文摘要
该项目将推动学生和教师创新技术体验(ITEST)计划的努力,以更好地了解和促进实践,通过提高学生在数据科学领域的技能和兴趣,提高学生在科学、技术、工程或数学(STEM)领域追求职业生涯的动机和能力。我们生活在一个数据驱动的时代,STEM领域和其他领域对数据及其相关技能的需求很高。许多学生,特别是那些来自STEM专业中代表性不足的群体的学生,几乎没有机会以一种将他们的生活经验与科学实践联系起来的方式接触数据。该项目旨在通过赋予年轻人能力,利用开源数据构建解决方案来应对对个人有意义的社区挑战,从而解决这一问题。通过让年轻人能够识别对个人有意义的项目,并将他们固定在一个由教育工作者、数据科学家、行业专业人士和社区团体组成的协作团队中,他们都有解决当地社区问题的共同目标,该项目支持学生看到STEM实践符合他们的个人身份和价值观。通过将学生定位为设计应对引人注目的社区挑战的项目的领导者,培训他们熟悉面向解决方案的学习的数据科学工具,并扩大他们的声音以与关键利益相关者分享他们的解决方案,该项目提供了对有助于学生学习的因素和经验的重要洞察,并研究了如何更好地利用共同设计和共享的数据驱动的经验来扩大参与和使STEM工作人员多样化。这个为期两年的合作研究项目将通过邀请高中生年龄的学习者参加课外俱乐部来解决STEM领域缺乏多样性的问题,该俱乐部使用数据来确定引人注目的本地社区挑战并设计潜在的解决方案来解决该问题。利用建构主义设计范式和基于项目的服务学习研究,该项目将调查制定STEM实践以促进和改善一个人的社区如何提高学生对STEM领域的兴趣并将身份认同转移到STEM领域。该项目不是创建一刀切的活动来假设社区问题,而是旨在开发和研究设计框架,以创建对个人有意义的、以学习者为中心的体验和活动,这些体验和活动可以部署在人口统计相似的广泛社区中。该项目的第一年将致力于发展教育和行业合作伙伴网络以及试点活动设计和评估。在第二年,将在两个地点与八所伙伴学校部署一项试点。研究活动将包括评估学生对数据科学核心概念和实践的了解,学生与当地社区的个人联系,以及学生对STEM的兴趣和认同。该项目将深化拉蒙特-多尔蒂地球天文台、师范学院、纽约市教育部教学处、社区组织、学校教育工作者和相关行业合作伙伴之间的合作。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase student motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM) through advancing student skills and interest in the area of data science. We live in a data-driven age where data and the skills associated with it are in high demand in STEM fields and beyond. Many students, particularly those from groups under-represented in STEM professions, are given few opportunities to engage with data in a way that connects their lived experiences to scientific practices. This project aims to address this by empowering youth to construct solutions to personally meaningful community challenges using open-source data. By putting youth in a position to identify personally meaningful projects, and anchoring them in a collaborative team of educators, data scientists, industry professionals, and community groups all with the shared aim of solving a problem in their local community, the project supports students in seeing see STEM practices as aligning with their personal identity and values. By positioning students as leads in designing projects that address compelling community challenges, training them to become familiar with data science tools for solutions-oriented learning, and amplifying their voice to share their solutions with key stakeholders, this project provides important insight into the factors and experiences that contribute to student learning and examines how to better use co-designed and shared data-driven experiences to broaden participation and diversify STEM workforces.This two-year collaborative research project will address the lack of diversity in STEM fields by engaging high school aged learners in an after-school club that uses data to identify a compelling local community challenge and to design a potential solution to address the problem. Leveraging the constructionist design paradigm and research on project-based service learning, the project will investigate how framing STEM practices to contribute to and improve one's community might increase student interest in and shift identity towards STEM fields. Rather than create a one-size-fits-all activity that assumes a community problem, the project aims to develop and study design frameworks for creating personally meaningful and learner-centric experiences and activities that can be deployed in a broad range of communities with similar demographics. Year 1 of the project will be devoted to the development of a network of education and industry partners and pilot activity design and evaluation. In year 2, a pilot will be deployed at two locations with eight partnering schools. Research activities will include the evaluation of student learning about the core concepts and practices of data science, students' personal connections with local communities, and students' STEM interests and identities. The project will deepen collaborations between Lamont-Doherty Earth Observatory, Teachers College, the New York City Department of Education's Division on Teaching and Learning, community organizations, school educators, and relevant industry partners.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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Make with Data: Challenging and contextualizing open-source data with personal and local knowledge
用数据创造:利用个人和本地知识挑战开源数据并将其置于情境中
DOI:
--
发表时间:
2021
期刊:
Proceedings of the 15th International Conference of the Learning Sciences—ICLS 2021
影响因子:
--
作者:
[Holbert, N., Xu, C.]
通讯作者:
Xu, C.
A Technological Framework for Fostering Collaboration by Linking Novice Makers with Mentors and Peers
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批准号:2048852
-
项目类别:Standard Grant
-
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-
财政年份:2021
-
负责人:Nathan Holbert
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依托单位:
Formative Assessments for Computer Science in NYC
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批准号:1742011
-
项目类别:Standard Grant
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资助金额:$140.2万
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财政年份:2017
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负责人:Nathan Holbert
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批准号:1645700
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项目类别:Standard Grant
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资助金额:$6.71万
-
财政年份:2016
-
负责人:Nathan Holbert
-
依托单位:
国内基金
海外基金
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