Collaborative Research: Pacific Alliance for Low-Income Inclusion in Statistics & Data Science
Collaborative Research: Pacific Alliance for Low-Income Inclusion in Statistics & Data Science
批准号:
2221337
负责人:
Daniel Gillen
金额:
$65.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-10-01 至 2028-09-30
中文摘要
该项目将通过支持加州大学圣巴巴拉分校、加州大学欧文分校、华盛顿大学、加州州立大学东湾分校、加州州立大学蒙特利湾分校、圣地亚哥州立大学、加州大学圣巴巴拉分校、加州州立大学欧文分校、加州州立大学圣巴巴拉分校、加州州立大学欧文分校、加州州立大学圣巴巴拉分校、加州州立大学欧文分校、加州州立大学圣巴巴拉分校、加州州立大学欧文分校、加州州立大学圣巴巴拉分校、加州州立大学欧文分校、加州州立大学欧文分校、加州州立大学欧文分校、加州州立大学欧文分校、加州州立大学圣迭戈分校、以及位于圣路易斯奥比斯波的加州州立理工大学。在统计与数据科学领域,数据革命催生了许多高薪职业道路,并造成了严重的劳动力短缺。许多利润丰厚、数据丰富的职业都需要研究生学位,这对低收入家庭的学生来说可能是一个重大障碍。该项目将为大约115名有才华的低收入本科生提供奖学金支持,学习统计和数据科学,并为其中至少65人提供两年研究生学习的持续奖学金支持。学者们将受益于教师和同伴指导,一个涵盖所有七所参与学校的年度会议,以及申请和准备研究生院的支持,包括研究生前的夏季训练营。额外的学术支持包括一个小组指导阅读计划,共享课程,在学者群体中建立社区,以及本科生研究机会。该项目的总体目标是提高有经济需求的低收入、高成就本科生的STEM学位完成率。其他项目目标和目的包括:(a)提供一个基于队列的项目,通过长达3年的奖学金为学生提供经济支持;(b)为学者提供学术和课外经验,以促进他们在统计和数据科学领域的就业;(c)提供干预措施以增强学者的社区文化资本。项目研究将使用调查和访谈来研究三个主要主题:(a)对抗空间和其他类型的社区如何发展和支持学者朝着他们的目标前进;(b)学者的社区文化财富是如何形成的,又是如何被形成的抗衡空间和社区所塑造的;(c)学生的低收入地位和其他身份如何影响关键的抗衡空间和社区,并影响学者的选择和结果。项目评估将对项目的各个方面提供形成性和总结性反馈,以支持实现目标的有效进展。该项目由美国国家科学基金会的科学、技术、工程和数学奖学金项目资助,旨在增加有经济需求的低收入学术天才学生在STEM领域获得学位的人数。它还旨在改善未来STEM工作者的教育,并为低收入学生提供有关学业成功、留校、转学、毕业和学术/职业道路的知识。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值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 contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at the University of California - Santa Barbara, the University of California - Irvine, the University of Washington, California State University, East Bay, California State University, Monterey Bay, San Diego State University, and California Polytechnic State University, San Luis Obispo. The Data Revolution is generating numerous well-paid career paths, and creating a significant workforce shortage, in Statistics & Data Science. Graduate degrees are needed for many lucrative, data-rich careers, which can represent a significant barrier for low-income students. This project will provide scholarship support to approximately 115 talented, low-income undergraduate students studying statistics and data science and provide continued scholarship support for at least 65 of them over two years of graduate studies. Scholars will benefit from faculty and peer mentoring, an annual meeting that spans all seven participating schools, and support for applying to and preparing for graduate school, including a pre-grad summer bootcamp. Additional academic supports include a small-group directed reading program, shared coursework to build community within scholar cohorts, and undergraduate research opportunities.The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. Additional project goals and aims include: (a) to offer a cohort-based program that supports students financially via scholarships lasting up to 3 years; (b) provide scholars with academic and co-curricular experiences designed to facilitate placement into careers in statistics and data science; and (c) offer interventions to enhance scholars’ community cultural capital. Project research will use surveys and interviews to study three main themes: (a) how counterspaces and other kinds of community develop and support scholars’ progress towards their goals; (b) how scholars’ community cultural wealth shapes and is shaped by the counterspaces and communities that develop; and (c) how students’ low-income status and other identities impact key counterspaces and communities and influence scholars’ choices and outcomes. Project evaluation will provide formative and summative feedback on all aspects of the project to support efficient progress towards goals. This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.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.
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