Collaborative Research: Replication of a Community-Engaged Educational Ecosystem Model in Rust Belt Cities

合作研究:在铁锈地带城市复制社区参与的教育生态系统模式

基本信息

  • 批准号:
    2111377
  • 负责人:
  • 金额:
    $ 74.58万
  • 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:
    2021-10-01 至 2022-01-31
  • 项目状态:
    已结题

项目摘要

This project aims to serve the national interest by improving educational environments that contribute to strengthening and diversifying the regional STEM workforce. The challenges of building a STEM workforce in shrinking Rust Belt cities are addressed by replicating and examining an effective STEM learning environment that applies and innovates high impact practices. Rust Belt cities refer to areas of the northern and Midwest United States that were once known for steel production and heavy industry. These cities often have high poverty rates and lower educational attainment in STEM, highlighting the need to bridge the divide of communities that can engage in the knowledge economy. This project aims to build STEM attraction and retention by immersing high school and college students in the STEM knowledge, skill, and capacity needs of deindustrialized cities using project-based learning, community engagement, and community development techniques. The Community-Engaged Educational Ecosystem Model (C-EEEM) was first developed and implemented in South Bend, Indiana in the Center for Civic Innovation at the University of Notre Dame. It produced a sustainable network of educational institutions and community stakeholders in delivering a high impact STEM learning environment. This project will replicate and study the C-EEEM in two other cities, Youngstown, Ohio and Erie, Pennsylvania. The ultimate goal of the project is to establish an interconnected network of STEM education initiatives to benefit the regional workforce.This project seeks to answer questions about the implementation of the C-EEEM in two sites with different community characteristics and types of anchor institutions. The project will also investigate differences in learning and dispositional outcomes in students in these new contexts. Consequently, units of analysis are nested: 1) the learning environment created by the C-EEEM and 2) the individual students. Both levels of examination use structured mixed-methods data collection. For students, the research will explore STEM motivation and persistence in STEM career pathways using theoretical framing derived from Self Determination Theory (SDT), as well as explore and expand on pilot findings regarding place attachment. For the C-EEEM learning environment, researchers will examine the core elements and critical factors specified from the pilot C-EEEM against the development of the new sites, allowing for comparison and assessment of relevance of the C-EEEM specifications in different conditions as well as identification of adaptations for generalizability. Concurrently, researchers will look for differences in student outcomes correlating with model differences. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities.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.
该项目旨在通过改善有助于加强和多样化区域STEM劳动力多样化的教育环境来服务国家利益。通过复制和检查应用和创新高影响力实践的有效的STEM学习环境,解决了在缩小锈腰城市中建立STEM劳动力的挑战。锈带城市是指北部和中西部的地区,这些地区曾经以钢铁生产和重工业而闻名。这些城市通常具有很高的贫困率和较低的STEM教育程度,这强调了弥合可以参与知识经济的社区的鸿沟的必要性。该项目旨在通过将基于项目的学习,社区参与和社区发展技巧的高中生,技能和能力需求沉浸在SEM知识,技能和能力需求中,以建立STEM吸引力和保留率。社区参与的教育生态系统模型(C-EEEM)是在圣母大学公民创新中心的南本德开发和实施的。它建立了一个可持续的教育机构和社区利益相关者网络,以提供高影响力的STEM学习环境。该项目将在俄亥俄州扬斯敦和宾夕法尼亚州伊利的其他两个城市中复制并研究C-EEEM。该项目的最终目标是建立一个相互联系的STEM教育计划网络,以使该地区劳动力受益。本项目旨在回答有关在具有不同社区特征和锚定机构类型的两个站点实施C-EEEM的问题。该项目还将调查这些新背景下学生的学习和性格成果的差异。因此,分析单位是嵌套的:1)C-EEEM创建的学习环境和2)单个学生。两种检查级别的使用结构化混合方法数据收集。对于学生而言,这项研究将使用自我确定理论(SDT)得出的理论框架探索STEM职业道路中的STEM动机和持久性,并探索和扩展有关地点依恋的试点发现。对于C-EEEM学习环境,研究人员将研究试点C-EEEM指定的核心要素和关键因素,以反对新站点的开发,从而可以比较和评估不同条件下C-EEEM规范的相关性,并识别适应性的普遍性。同时,研究人员将寻找与模型差异相关的学生结果的差异。 NSF IUSE:EHR计划支持研发项目,以提高所有学生STEM教育的有效性。通过机构和社区转型的轨道,该计划支持努力在高等教育和学科社区的机构中转变和改善STEM教育的努力。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影响的评估来进行评估的审查标准。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Faisal Aqlan其他文献

Applying Product Manufacturing Techniques to Teach Data Analytics in Industrial Engineering: A Project Based Learning Experience
应用产品制造技术教授工业工程中的数据分析:基于项目的学习体验
Optimal Cholera Vaccine Allocation Policies in Developing Countries: A Case Study
发展中国家霍乱疫苗的最佳分配政策:案例研究
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    A. G. Qasem;Abdulrahman Shamsan;Faisal Aqlan
  • 通讯作者:
    Faisal Aqlan
A risk-based optimization framework for integrated supply chains using genetic algorithm and artificial neural networks
使用遗传算法和人工神经网络的基于风险的集成供应链优化框架
AN APPROXIMATION TO THE INVERSE OF LEFT-SIDED TRUNCATED GAUSSIAN CUMULATIVE NORMAL DENSITY FUNCTION USING POLYA’S MODEL TO GENERATE RANDOM VARIATES FOR SIMULATION APPLICATIONS
左端截断高斯累积正态密度函数的反函数的近似,利用Polya模型生成随机变量用于仿真应用
  • DOI:
    10.5937/jaes0-35413
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Hamasha;Abdulaziz Ahmed;Haneen Ali;S. Hamasha;Faisal Aqlan
  • 通讯作者:
    Faisal Aqlan
Sensor-Based Virtual Reality for Clinical Decision Support in the Assessment of Mental Disorders
基于传感器的虚拟现实用于精神障碍评估中的临床决策支持
  • DOI:
    10.1109/cog47356.2020.9231896
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bryant Niederriter;Alice Rong;Faisal Aqlan;Hui Yang
  • 通讯作者:
    Hui Yang

Faisal Aqlan的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Faisal Aqlan', 18)}}的其他基金

REU Site in Advanced Manufacturing and Supply Chain
REU 先进制造和供应链基地
  • 批准号:
    2244119
  • 财政年份:
    2023
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
Collaborative Research: An Extended Reality Factory Innovation for Adaptive Problem-solving and Personalized Learning in Manufacturing Engineering
协作研究:制造工程中自适应问题解决和个性化学习的扩展现实工厂创新
  • 批准号:
    2302833
  • 财政年份:
    2023
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
Integrating Undergraduate Learning in Engineering and Business to Improve Manufacturing Education
将工程和商业本科学习相结合以改善制造教育
  • 批准号:
    2211066
  • 财政年份:
    2022
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
Research Initiation: Advanced Modeling of Metacognitive Problem Solving and Group Effectiveness in Collaborative Engineering Teams
研究启动:协作工程团队中元认知问题解决和团队有效性的高级建模
  • 批准号:
    2208680
  • 财政年份:
    2021
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
RET Site in Manufacturing Simulation and Automation
制造仿真和自动化中的 RET 站点
  • 批准号:
    2055384
  • 财政年份:
    2021
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
RET Site in Manufacturing Simulation and Automation
制造仿真和自动化中的 RET 站点
  • 批准号:
    2204719
  • 财政年份:
    2021
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
GOALI: Stochastic Optimization Framework for Energy-Smart Re/Manufacturing Systems
GOALI:能源智能再造/制造系统的随机优化框架
  • 批准号:
    2038325
  • 财政年份:
    2021
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
RET Site in Manufacturing Simulation and Automation
制造仿真和自动化中的 RET 站点
  • 批准号:
    2204601
  • 财政年份:
    2021
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
Collaborative Research: Replication of a Community-Engaged Educational Ecosystem Model in Rust Belt Cities
合作研究:在铁锈地带城市复制社区参与的教育生态系统模式
  • 批准号:
    2152282
  • 财政年份:
    2021
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Continuing Grant
Integrating Undergraduate Learning in Engineering and Business to Improve Manufacturing Education
将工程和商业本科学习相结合以改善制造教育
  • 批准号:
    2021303
  • 财政年份:
    2020
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant

相似国自然基金

锰通过转录和转录后调控抑制HBV复制的作用及机制研究
  • 批准号:
    82360390
  • 批准年份:
    2023
  • 资助金额:
    32 万元
  • 项目类别:
    地区科学基金项目
石斑鱼Rab11对虹彩病毒SGIV感染复制的调控机制研究
  • 批准号:
    42306100
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
Sin3复合体通过液-液相分离调控DNA复制的机制研究
  • 批准号:
    32300562
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
肠道病毒下调去整合素金属蛋白酶15促进病毒复制膜形成的机制研究
  • 批准号:
    82302502
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
FBXO9蛋白调控HIV-1 Tat稳定性的机制及其在病毒复制和潜伏中的作用研究
  • 批准号:
    82372239
  • 批准年份:
    2023
  • 资助金额:
    49 万元
  • 项目类别:
    面上项目

相似海外基金

Mentoring Psychology Research Experiences through Replication with the Collaborative Replication and Education Project
通过协作复制和教育项目的复制来指导心理学研究经验
  • 批准号:
    2312491
  • 财政年份:
    2023
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
Defining the role of persistent DNA bridges in tumor-intrinsic immune activation in hereditary breast and ovarian cancer
确定持久性 DNA 桥在遗传性乳腺癌和卵巢癌肿瘤内在免疫激活中的作用
  • 批准号:
    10606942
  • 财政年份:
    2023
  • 资助金额:
    $ 74.58万
  • 项目类别:
Collaborative Research: CNS Core: Small: Resource-efficient, Strongly Consistent Replication for the Cloud
合作研究:CNS 核心:小型:资源高效、强一致性的云复制
  • 批准号:
    2149389
  • 财政年份:
    2022
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
Virus-host interactions regulating innate signaling for human cytomegalovirus latency
病毒-宿​​主相互作用调节人类巨细胞病毒潜伏期的先天信号
  • 批准号:
    10464446
  • 财政年份:
    2022
  • 资助金额:
    $ 74.58万
  • 项目类别:
Collaborative Research: CNS Core: Small: Resource-efficient, Strongly Consistent Replication for the Cloud
合作研究:CNS 核心:小型:资源高效、强一致性的云复制
  • 批准号:
    2149443
  • 财政年份:
    2022
  • 资助金额:
    $ 74.58万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了