Scaffolded Computing Projects for the Social Good

为社会公益服务的脚手架计算项目

基本信息

  • 批准号:
    2315323
  • 负责人:
  • 金额:
    $ 11.19万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-06-15 至 2026-05-31
  • 项目状态:
    未结题

项目摘要

This project aims to serve the national interest by increasing service-learning opportunities in computing programs. To meet the increasing demand for well-qualified computing professionals, computing graduates must be ready to apply their knowledge and skills in a real-world environment. The goal of this project is to develop a service-learning framework that will help instructors embed externally sourced projects supporting the social good into existing software engineering or similar courses. This work will also support competency-based learning by offering students an opportunity to solve real-world problems in an authentic environment using current industrial practices and tools coupled with strong mentoring by support volunteer professionals and near peers. By enabling competency-based learning, this project will help address the skills gap, both technical and professional, so that computing students graduate with both the appropriate knowledge, and the ability to apply their knowledge in a practical setting. This project will produce the Scaffolded Projects for the Social Good (SPSG) framework, a low adoption threshold framework to help computing programs incorporate service-learning projects in their courses. The SPSG framework will incorporate studio-based learning concepts, agile principles, and the lessons learned from the Humanitarian Free and Open-Source Software (HFOSS) initiative. SPSG will provide instructors with a customizable set of curricular materials aimed at streamlining the software project workflow and offering ample mechanisms for formative and summative assessment of student learning. SPSG will help students make meaningful contributions to the missions of non-profit and community organizations while providing concrete examples regarding the impact of computing on society. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.
该项目旨在通过增加计算机程序中的服务学习机会来服务于国家利益。为了满足对合格的计算机专业人员日益增长的需求,计算机专业毕业生必须准备好在现实世界中应用他们的知识和技能。这个项目的目标是开发一个服务学习框架,帮助教师将支持社会公益的外部项目嵌入到现有的软件工程或类似的课程中。这项工作还将支持基于能力的学习,为学生提供一个机会,利用当前的工业实践和工具,在一个真实的环境中解决现实世界的问题,再加上支持志愿者专业人员和附近同龄人的强大指导。通过实现基于能力的学习,该项目将有助于解决技术和专业方面的技能差距,从而使计算机专业的学生在毕业时既掌握了适当的知识,又有能力将其知识应用于实际环境。该项目将产生社会公益脚手架项目(SPSG)框架,这是一个低采用门槛的框架,可帮助计算项目在其课程中纳入服务学习项目。SPSG框架将结合基于工作室的学习概念、敏捷原则以及从人道主义自由和开源软件(HFOSS)计划中吸取的经验教训。SPSG将为教师提供一套可定制的课程材料,旨在简化软件项目的工作流程,并为学生学习的形成性和总结性评估提供充足的机制。SPSG将帮助学生为非营利组织和社区组织的使命做出有意义的贡献,同时提供有关计算对社会影响的具体例子。NSF IUSE: EDU项目支持研究和开发项目,以提高所有学生STEM教育的有效性。通过其参与学生学习轨道,该计划支持有前途的实践和工具的创建,探索和实施。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。

项目成果

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Nathan Sommer其他文献

Developing a Machine Learning Approach to Controlling Musical Synthesizer Parameters in Real-Time Live Performance
开发一种机器学习方法来控制实时现场表演中的音乐合成器参数
Sensitivity of Northern Hemisphere Cyclone Detection and Tracking Results to Fine Spatial and Temporal Resolution using ERA5
使用 ERA5 北半球气旋探测和跟踪结果对精细空间和时间分辨率的敏感性
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    A. Crawford;E. Schreiber;Nathan Sommer;M. Serreze;J. Stroeve;D. Barber
  • 通讯作者:
    D. Barber

Nathan Sommer的其他文献

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    Standard Grant
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