Exploring STEM Impact and Engagement in Student-Led and Purpose-Driven Projects

探索学生主导和目标驱动项目中的 STEM 影响和参与度

• 批准号: 1759299
• 负责人: Luo Cassie Xu
• 金额: $ 29.5万
• 依托单位: Columbia University
• 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
• 起止时间: 2018-09-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1759299&HistoricalAwards=false
• 关键词: Exploring; STEM; Impact; Engagement; Student

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.

该项目将推进学生和教师创新技术体验 (ITEST) 计划的工作，通过提高学生在数据科学领域的技能和兴趣，更好地理解和推广提高学生在科学、技术、工程或数学 (STEM) 领域追求职业的动力和能力的实践。 我们生活在一个数据驱动的时代，STEM 领域及其他领域对数据及其相关技能的需求量很大。许多学生，特别是来自 STEM 专业中代表性不足的群体的学生，很少有机会以将他们的生活经历与科学实践联系起来的方式接触数据。该项目旨在通过授权年轻人使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。通过让年轻人能够确定对个人有意义的项目，并将他们纳入由教育工作者、数据科学家、行业专业人士和社区团体组成的协作团队中，他们的共同目标是解决当地社区的问题，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解决引人注目的社区挑战的项目的领导者，培训他们熟悉用于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主要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见解，并研究如何更好地利用共同设计和共享的数据驱动体验来扩大参与并使 STEM 劳动力多样化。这个为期两年的合作研究项目将解决 通过让高中生参加课后俱乐部，该俱乐部利用数据来识别当地社区面临的重大挑战，并设计潜在的解决方案来解决该问题，从而解决 STEM 领域缺乏多样性的问题。该项目将利用建构主义设计范式和基于项目的服务学习研究，研究如何构建 STEM 实践来为社区做出贡献和改善社区，从而提高学生对 STEM 领域的兴趣并将身份转变为 STEM 领域。该项目不是创建一个假定社区问题的一刀切的活动，而是旨在开发和研究设计框架，以创建对个人有意义且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具有相似人口统计数据的广泛社区中。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。第二年，将在两个地点与八所合作学校部署试点。研究活动将包括评估学生对数据科学核心概念和实践的学习情况、学生与当地社区的个人联系以及学生的 STEM 兴趣和身份。该项目将加深拉蒙特-多尔蒂地球观测站、师范学院、纽约市教育部教学部门、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价值和更广泛的影响审查标准进行评估，被认为值得支持。