STEM TRansfer Students Opportunity for Nurtured Growth (STRONG)

STEM 转学生提供培育成长的机会(强)

基本信息

项目摘要

With funding from the National Science Foundation's Scholarships in Science, Technology, Engineering and Mathematics (S-STEM) program, the STEM TRansfer Students Opportunity for Nurtured Growth (STRONG) is providing support to low-income students with demonstrated financial need and academic promise to succeed in STEM disciplines at the University of Central Florida (UCF). This S-STEM Track 2 project is funding up to 36 scholarships over 5 years for transfer students who are pursuing bachelor's degrees in STEM. Compared to first time in college (FTIC) students who begin their academic careers at a four-year institution, transfer students generally find the path to obtaining a bachelor's degree more challenging, and they are significantly less likely to graduate than their FTIC counterparts. Finding ways to improve the educational experiences of these students is an urgent national priority. The aim of UCF's STRONG project is to substantially increase retention, graduation rates, and career success of STEM transfer students. This goal is achieved in part by giving each student a role in various STEM activities within a community of high-achieving scholars, who are majoring in similar fields. Providing financial support, mentorship, and opportunities for academic engagement outside the classroom promises to reduce the obstacles students face, keep them interested in their field of study, and motivate them to excel academically. A thorough study of how the program affects its participants will maximize the impact of the intervention and informs future efforts to improve the educational experiences of STEM transfer students.The UCF STRONG project consists of three components, which are all essential for reaching the program goal of increasing retention, graduation rates, and career success of STEM transfers. The first component is to design, implement, and improve a high-accuracy prediction model for identifying high-risk STEM transfers. Using known information about transfers, along with statistical analysis and machine learning, it will establish a means of predicting which students are least likely to complete a STEM degree, thereby helping UCF to know which students will benefit most from STRONG. The second component is to increase retention of transfers in STEM fields. STRONG scholars will be selected from financially needy incoming transfers who have been predicted to be unlikely to graduate, with the purpose of retaining them through graduation due to their participation in STRONG. This outcome is an expected result of increased student success through stimulation of academic integration and a cultivation of proficiency in their chosen fields. More specifically, each student is given a role within a community of like-minded students from closely related fields; they also meet regularly with mentors and participate in STEM activities that promote their success. The third component is to learn how the interventions influence STEM transfer students' ability to become active participants in their own learning. The project team will study the effects of the intervention on metacognition, motivation, and behavior, which are the three pillars of Self-Regulated Learning and are essential for student success.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.
借助国家科学基金会在科学,技术,工程和数学(S-STEM)计划方面的奖学金,STEM转移学生的培育学生机会(Strong)为具有经济需求和学术上的诺言提供支持的低收入学生提供支持,并在中央佛罗里达大学(UCF)的STEM学科中取得成功。这个S-STEM 2项目将为在STEM中攻读学士学位的转学学生提供5年的最高36个奖学金。与在四年制机构开始学术职业的大学(FTIC)学生相比,转学学生通常会发现获得学士学位更具挑战性的途径,而毕业的可能性要比FTIC同行少得多。寻找改善这些学生的教育经历的方法是紧急的国家优先事项。 UCF强大的项目的目的是大大提高STEM转移学生的保留率,毕业率和职业成功。 该目标的部分是通过在高成就学者社区内的各种STEM活动中发挥作用,这些目标是在类似领域主修的。 在课堂外提供财政支持,指导和学术参与的机会,有望减少学生面临的障碍,使他们对自己的学习领域感兴趣,并激励他们在学术上表现出色。 对该计划如何影响其参与者的详尽研究将最大程度地提高干预措施的影响,并告知未来的努力,以改善STEM转移学生的教育经验。UCF强大的项目由三个组成部分组成,这对于提高保留率,毕业率和STEM转移的职业成功的计划目标都是至关重要的。第一个组成部分是设计,实施和改进用于识别高风险茎转移的高准确性预测模型。使用有关转移的已知信息,以及统计分析和机器学习,它将建立一种预测哪些学生最不可能完成STEM学位的方法,从而帮助UCF知道哪些学生将从Strong中受益最大。第二个组成部分是增加茎场中转移的保留率。强大的学者将是从经济需要的传入转移中选出的,这些转会被预计不太可能毕业,目的是通过毕业,因为他们参与了强者。该结果是通过刺激学术融合和在所选领域培养熟练程度来增加学生成功的预期结果。 更具体地说,每个学生都在来自密切相关领域的志趣相投的学生社区中发挥作用。他们还定期与导师会面,并参加促进成功的STEM活动。 第三个组成部分是学习干预措施如何影响STEM转移学生成为自己学习的积极参与者的能力。项目团队将研究干预对元认知,动机和行为的影响,这是自我调节学习的三个支柱,对于学生的成功至关重要。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估的。

项目成果

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会议论文数量(0)
专利数量(0)

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Mubarak Shah其他文献

CodaMal: Contrastive Domain Adaptation for Malaria Detection in Low-Cost Microscopes
CodaMal:低成本显微镜中疟疾检测的对比域适应
  • DOI:
    10.48550/arxiv.2402.10478
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    I. Dave;Tristan de Blegiers;Chen Chen;Mubarak Shah
  • 通讯作者:
    Mubarak Shah
Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images
Lung-CADex:胸部 CT 图像中肺结节的全自动零样本检测和分类
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Furqan Shaukat;Syed Muhammad Anwar;Abhijeet Parida;Van Lam;M. Linguraru;Mubarak Shah
  • 通讯作者:
    Mubarak Shah
SRI-Sarnoff AURORA System at TRECVID 2013 Multimedia Event Detection and Recounting
SRI-Sarnoff AURORA 系统参加 TRECVID 2013 多媒体事件检测和重算
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jingen Liu;Hui Cheng;O. Javed;Qian Yu;Ishani Chakraborty;Weiyu Zhang;Ajay Divakaran;H. Sawhney;James Allan;R. Manmatha;John Foley;Mubarak Shah;Afshin Dehghan;Michael Witbrock;Jon Curtis;Gerald Friedland
  • 通讯作者:
    Gerald Friedland
Supervised Learning via Conditional Sampling with Energy-Based Models
通过条件采样和基于能量的模型进行监督学习
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Dr Katherine Abreu;Dr Mitchell Hill;Mubarak Shah
  • 通讯作者:
    Mubarak Shah
Machine Vision and Applications Understanding Human Behavior from Motion Imagery
机器视觉和应用从运动图像理解人类行为
  • DOI:
  • 发表时间:
    2003
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Mubarak Shah
  • 通讯作者:
    Mubarak Shah

Mubarak Shah的其他文献

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{{ truncateString('Mubarak Shah', 18)}}的其他基金

REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
  • 批准号:
    2349386
  • 财政年份:
    2024
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
Scholarships, Academic, and Social Supports to Provide Low-Income Transfers Students Opportunities for Nurtured Growth in AI
奖学金、学术和社会支持为低收入转学生提供促进人工智能发展的机会
  • 批准号:
    2321986
  • 财政年份:
    2024
  • 资助金额:
    $ 100万
  • 项目类别:
    Continuing Grant
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
  • 批准号:
    2050731
  • 财政年份:
    2021
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
CRI: II-New: Cognitive Mechanisms and Computational Modeling of Gaze Control During Scene Free Viewing, Visual Search, and Daily Tasks
CRI:II-新:场景自由观看、视觉搜索和日常任务期间注视控制的认知机制和计算模型
  • 批准号:
    1823276
  • 财政年份:
    2018
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
  • 批准号:
    1757858
  • 财政年份:
    2018
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
BIGDATA: IA: Distributed Semi-Supervised Training of Deep Models and Its Applications in Video Understanding
BIGDATA:IA:深度模型的分布式半监督训练及其在视频理解中的应用
  • 批准号:
    1741431
  • 财政年份:
    2017
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
RET Site: Research Experiences for Teachers in Computer Vision and Bio-Medical Imaging
RET 网站:计算机视觉和生物医学成像教师的研究经验
  • 批准号:
    1542439
  • 财政年份:
    2016
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
REU Site: NSF Research Experience for Undergraduates in Computer Vision
REU 网站:NSF 计算机视觉本科生研究经验
  • 批准号:
    1461121
  • 财政年份:
    2015
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
REU Site: Research Experience for Undergraduates in Computer Vision
REU 网站:计算机视觉本科生的研究经验
  • 批准号:
    1156990
  • 财政年份:
    2012
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant
Students Actualizing Talent at Education?s Subsequent Stages (STATESS)
学生在教育后续阶段实现才能(STATESS)
  • 批准号:
    0966249
  • 财政年份:
    2010
  • 资助金额:
    $ 100万
  • 项目类别:
    Standard Grant

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通过制定目标和实践经验建立研究独立性(BRIDGE)计划
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