Collaborative Research: HDR DSC: Data Science Training and Practices: Preparing a Diverse Workforce via Academic and Industrial Partnership

合作研究:HDR DSC:数据科学培训和实践:通过学术和工业合作培养多元化的劳动力

基本信息

  • 批准号:
    2123380
  • 负责人:
  • 金额:
    $ 60.65万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-01 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

A significant number of modern scientific studies rely upon processing and analyzing a large amount of data for information extraction, scientific discovery, and decision making. This motivates the need for training a new generation of data scientists with interdisciplinary skills and a deep understanding of appropriate and applicable data analysis methods, as well as the ability to communicate the outcomes of the scientific inquiry. Historically, a considerable number of students graduating from traditional programs in statistics, mathematics, and computer science are not prepared to handle the emerging challenges of data-intensive problems. To address this issue, this project aims to develop a cross-disciplinary curricular, research, and career preparation program in data science. Moreover, it will create a paradigm for taking data science training from academia into real-world applications through close partnership with industry, government, and non-profit organizations. This project will have a broad societal impact by creating a diverse community of learners, equipped with the required skills to join the workforce. Through engaging students selected from a pool of highly diverse populations in STEM areas, this project, California Data Experience Transformation (CADET), will facilitate data science training via curriculum development, hands-on experiences, and close interactions with both academic and non-academic organizations. The CADET project gives rise to the creation of an integrative, dialectical, and interactive ecosystem between the University of California at Irvine, California State University at Fullerton, and Cypress College. These institutions represent the three tiers of higher learning in California, namely, University of California, spearheading research and discovery; California State University, combining research and pedagogy; and Community College, offering two-year preparatory programs. The primary components of the CADET project include generating data science opportunities for underrepresented STEM majors, developing and implementing modern data science curricula at the three participating institutes and disseminating them to other institutions, and finally creating a gateway to diverse career opportunities through mentoring and direct involvement in real-world projects. More than 120 CADET scholars will participate in a host of activities including a summer bootcamp, team science training, weekly seminars, and a collaborative research project, all of which will lead to presentations at symposiums and conferences. Ultimately, through implementing new curricula and student and faculty training, the CADET project will establish a data science culture across STEM disciplines that extends beyond the lifetime of this award.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.
大量现代科学研究依赖于处理和分析大量数据来提取信息、科学发现和决策。这就需要培训新一代数据科学家,使其具备跨学科技能、对适当和适用的数据分析方法有深刻的理解,以及传达科学探究结果的能力。从历史上看,相当多从统计、数学和计算机科学传统课程毕业的学生没有准备好应对数据密集型问题的新挑战。为了解决这个问题,该项目旨在开发数据科学领域的跨学科课程、研究和职业准备计划。此外,它将创建一个范例,通过与行业、政府和非营利组织的密切合作,将数据科学培训从学术界带入现实世界的应用。该项目将通过创建一个多元化的学习者社区来产生广泛的社会影响,这些学习者具备加入劳动力所需的技能。通过吸引从 STEM 领域高度多样化的人群中选出的学生,加州数据体验转型 (CADET) 项目将通过课程开发、实践经验以及与学术和非学术界的密切互动来促进数据科学培训组织。 CADET 项目在加州大学欧文分校、加州州立大学富勒顿分校和赛普拉斯学院之间创建了一个综合的、辩证的、互动的生态系统。这些机构代表了加州的三级高等教育机构,即加州大学,引领研究和发现;加州州立大学,将研究与教学相结合;和社区学院,提供两年的预科课程。 CADET 项目的主要组成部分包括为代表性不足的 STEM 专业创造数据科学机会,在三个参与机构开发和实施现代数据科学课程并将其传播到其他机构,最后通过指导和直接参与创建通往多样化职业机会的门户在现实世界的项目中。超过 120 名 CADET 学者将参加一系列活动,包括夏季训练营、团队科学培训、每周研讨会和合作研究项目,所有这些活动都将在研讨会和会议上进行演讲。最终,通过实施新课程以及学生和教师培训,CADET 项目将在 STEM 学科中建立一种数据科学文化,这种文化将超越该奖项的有效期。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。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Orthogonal array composite designs for drug combination experiments with applications for tuberculosis
  • DOI:
    10.1002/sim.9423
  • 发表时间:
    2022-05-06
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Luna,Jose;Jaynes,Jessica;Wong,Weng Kee
  • 通讯作者:
    Wong,Weng Kee
An Urgent Plea for More Graduate Programs in Statistics Education
迫切呼吁开设更多统计教育研究生课程
  • DOI:
    10.5642/jhummath.202201.32
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0.3
  • 作者:
    Drew, David;Behseta, Sam;Ichinose, Cherie
  • 通讯作者:
    Ichinose, Cherie
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  • 批准号:
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  • 财政年份:
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  • 资助金额:
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  • 批准号:
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