Preparing Highly Qualified Students with Financial Need for Careers in Computing and Cyber-Security through Evidence-Based Educational Practices
通过循证教育实践,为有经济需要的高素质学生做好计算机和网络安全职业的准备
基本信息
- 批准号:1833630
- 负责人:
- 金额:$ 396.94万
- 依托单位:
- 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:2018-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The NSF Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program supports the retention and graduation of high-achieving, low-income students with demonstrated financial need. This S-STEM project is a collaboration between New Mexico State University and New Mexico Tech, in collaboration with four two-year colleges: Dona Ana Community College, Eastern New Mexico University Ruidoso, New Mexico State University Alamogordo, and New Mexico State University Grants. These institutions are Hispanic-Serving Institutions (HSIs) and members of an existing backbone organization, the Computing Alliance of Hispanic Serving Institutions, which focuses on promoting recruitment, training, and career advancement of Hispanic students in computing. Over a five-year period, this S-STEM project will fund 66 scholarships, in three groups of 22 students who are pursuing Associate and Bachelor's degrees in computing-related disciplines. The project will apply practices that the investigators developed over two previous multi-year awards and that have been shown to support the development of students' technical and professional skills in computation. Implementing these practices will guide students along pathways from two-year programs to four-year degrees in computing, and to successful careers and/or graduate studies in computing. The students' professional and technical skills will be enhanced through a structured model that guides development of skills in computer science, research, team work, and communication. These skills will be refined through projects and activities in cybersecurity, a critical computing area with nationwide implications. The skills development activities, coupled with integrated mentoring initiatives, will contribute to the advancement and success of the scholars. The partnering institutions aim to prepare low-income, academically high-achieving students to enter the computing workforce or graduate computing degree programs. To this end, the project will provide the selected scholars with co-curricular activities, grounded in evidence-based pedagogical strategies, to strengthen technical and professional preparation. The strategies build on multi-level mentoring, team work, and active involvement in the scientific community, to build social capital among the scholars, and self-efficacy and confidence in computing. The project will also contribute to advancing the knowledge base about: (1) factors affecting the retention and success of students in computing at HSIs and (2) factors that facilitate the adoption and sustainability of evidence-based reforms that serve low income, highly qualified students in computing. The program will contribute to the training of talented students who can contribute to growing U.S. workforce needs in computing and cybersecurity. The focus on low-income students, and the predominantly Hispanic student population of the partnering institutions, will contribute to building a computing workforce with greater diversity of participants. The program will also contribute to reinforcing the pathways from two-year colleges to four-year academic programs across New Mexico, opening new opportunities for students, and advancing the economic development of the state.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.
NSF 科学、技术、工程和数学奖学金 (S-STEM) 计划支持有经济需求的高成就、低收入学生的保留和毕业。 这个 S-STEM 项目是新墨西哥州立大学和新墨西哥理工学院之间的合作项目,与四所两年制学院合作:多纳安娜社区学院、东新墨西哥大学鲁伊多索分校、新墨西哥州立大学阿拉莫戈多分校和新墨西哥州立大学助学金。 这些机构是西班牙裔服务机构 (HSI) 和现有骨干组织西班牙裔服务机构计算联盟的成员,该联盟专注于促进西班牙裔学生在计算机领域的招聘、培训和职业发展。 该 S-STEM 项目将在五年内为 66 项奖学金提供资助,分三组,每组 22 名正在攻读计算机相关学科副学士学位和学士学位的学生。该项目将应用研究人员在前两个多年奖中开发的实践,这些实践已被证明可以支持学生计算技术和专业技能的发展。实施这些实践将引导学生从两年制课程到四年制计算机学位,以及成功的计算机职业和/或研究生学习。学生的专业和技术技能将通过指导计算机科学、研究、团队合作和沟通技能发展的结构化模型得到提高。这些技能将通过网络安全领域的项目和活动得到完善,网络安全是一个具有全国影响的关键计算领域。技能发展活动,加上综合指导举措,将有助于学者的进步和成功。合作机构旨在帮助低收入、学术成绩优异的学生进入计算机劳动力或研究生计算机学位课程。为此,该项目将为选定的学者提供基于循证教学策略的课外活动,以加强技术和专业准备。这些策略建立在多层次指导、团队合作和积极参与科学界的基础上,以在学者之间建立社会资本,以及对计算的自我效能和信心。该项目还将有助于推进以下方面的知识库:(1) 影响 HSI 计算机专业学生保留和成功的因素;(2) 促进为低收入、高素质计算机专业学生服务的循证改革的采用和可持续性的因素。该计划将有助于培养有才华的学生,他们可以为美国计算和网络安全方面不断增长的劳动力需求做出贡献。对低收入学生以及合作机构中以西班牙裔学生为主的关注,将有助于建立一支参与者更加多元化的计算机队伍。该计划还将有助于加强新墨西哥州从两年制大学到四年制学术课程的衔接,为学生提供新的机会,并促进该州的经济发展。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。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Developing Meaningful Studies of Student Success with Equity in Mind: Considering Context (Experience Report)
考虑到背景(经验报告),对学生成功开展有意义的研究,同时牢记公平:
- DOI:10.18260/1-2--34432
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Hug, Sarah;Chi, Wendy
- 通讯作者:Chi, Wendy
Shifting Identity Trajectories within a Scholarship Program: Local Community Practices that Shape Computing Careers
在奖学金计划中改变身份轨迹:塑造计算机职业的当地社区实践
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Hug, Sarah
- 通讯作者:Hug, Sarah
Building Computational Thinking in K12 Outreach to Serve Latinas: Impact of Moving Summer Programming Online
在 K12 外展中建立计算思维以服务拉丁裔:将夏季编程转移到网上的影响
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Hug, Sarah;McKay, Mark
- 通讯作者:McKay, Mark
Students' Complex Perspectives on Diversity—A Mixed Methods Pilot Study
学生对多样性的复杂观点——混合方法试点研究
- DOI:
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Hug, Sarah;Chi, Wendy
- 通讯作者:Chi, Wendy
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Huiping Cao其他文献
Beef Production in the Southwestern United States: Strategies Toward Sustainability
美国西南部的牛肉生产:可持续发展战略
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:4.7
- 作者:
S. Spiegal;A. Cibils;B. Bestelmeyer;J. Steiner;R. Estell;D. Archer;B. Auvermann;S. Bestelmeyer;L. Boucheron;Huiping Cao;A. Cox;D. Devlin;G. Duff;Kristy K. Ehlers;E. Elias;C. Gifford;A. González;J. Holland;J. Jennings;A. Marshall;D. McCracken;M. McIntosh;Rhonda L. Miller;Mark Musumba;R. Paulin;S. Place;M. Redd;C. Rotz;C. Tolle;A. Waterhouse - 通讯作者:
A. Waterhouse
External Factors Affecting Determination of Mineral Filler Contact Angle with Capillary Rise Method
影响毛细管上升法测定矿物填料接触角的外部因素
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:3.2
- 作者:
Lingyun kONG;Tong Li;Huiping Cao;Yuzhen Zhang - 通讯作者:
Yuzhen Zhang
YOLOv8-BS: An integrated method for identifying stationary and moving behaviors of cattle with a newly developed dataset
YOLOv8-BS:一种利用新开发的数据集识别牛的静止和移动行为的综合方法
- DOI:
10.1016/j.atech.2025.101153 - 发表时间:
2025-12-01 - 期刊:
- 影响因子:5.700
- 作者:
Md Ishtiaq Ahmed;Huiping Cao;Andrés Ricardo Perea;Mehmet Emin Bakir;Huiying Chen;Santiago A. Utsumi - 通讯作者:
Santiago A. Utsumi
Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets
- DOI:
10.1016/j.jappgeo.2024.105493 - 发表时间:
2024-10-01 - 期刊:
- 影响因子:
- 作者:
Ahsan Jamil;Dale F. Rucker;Dan Lu;Scott C. Brooks;Alexandre M. Tartakovsky;Huiping Cao;Kenneth C. Carroll - 通讯作者:
Kenneth C. Carroll
Integrating LoRaWAN sensor networks and machine learning models to classify beef cattle behavior on arid rangelands of the southwestern United States
将 LoRaWAN 传感器网络与机器学习模型相集成,以对美国西南部干旱草原上的肉牛行为进行分类
- DOI:
10.1016/j.atech.2025.101002 - 发表时间:
2025-08-01 - 期刊:
- 影响因子:5.700
- 作者:
Andres Perea;Sajidur Rahman;Huiying Chen;Andrew Cox;Shelemia Nyamuryekung’e;Mehmet Bakir;Huiping Cao;Richard Estell;Brandon Bestelmeyer;Andres F. Cibils;Santiago A. Utsumi - 通讯作者:
Santiago A. Utsumi
Huiping Cao的其他文献
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{{ truncateString('Huiping Cao', 18)}}的其他基金
Travel: III: Student Travel Support for 2023 ACM International Conference on Web Search and Data Mining (WSDM)
差旅:III:2023 年 ACM 网络搜索和数据挖掘国际会议 (WSDM) 学生差旅支持
- 批准号:
2245056 - 财政年份:2023
- 资助金额:
$ 396.94万 - 项目类别:
Standard Grant
Travel: III: Student Travel Support for 2022 ACM International Conference on Web Search and Data Mining (WSDM)
差旅:III:2022 年 ACM 网络搜索和数据挖掘国际会议 (WSDM) 学生差旅支持
- 批准号:
2154473 - 财政年份:2022
- 资助金额:
$ 396.94万 - 项目类别:
Standard Grant
REU Site: BIGDatA - Big Data Analytics for Cyber-physical Systems
REU 网站:BIGDatA - 网络物理系统的大数据分析
- 批准号:
1950121 - 财政年份:2020
- 资助金额:
$ 396.94万 - 项目类别:
Standard Grant
BIGDATA: Collaborative Research: F: Discovering Context-Sensitive Impact in Complex Systems
BIGDATA:协作研究:F:发现复杂系统中的上下文敏感影响
- 批准号:
1633330 - 财政年份:2016
- 资助金额:
$ 396.94万 - 项目类别:
Standard Grant
REU Site: BIGDatA - Big Data Analytics for Cyber-Physical Systems
REU 网站:BIGDatA - 网络物理系统的大数据分析
- 批准号:
1559723 - 财政年份:2016
- 资助金额:
$ 396.94万 - 项目类别:
Standard Grant
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