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Collaborative Learning in Cloud-based Virtual Computer Labs

Collaborative Learning in Cloud-based Virtual Computer Labs
基于云的虚拟计算机实验室中的协作学习
批准号:
1712384
负责人:
Xiaolin Hu
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-15 至 2021-07-31

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中文摘要
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英文摘要
Computer labs in which students work through assignments using specialized software and/or hardware play a critical role in computing education and in STEM education in general. Traditionally these computer labs have been carried out in computer centers on campus due to the need for specialized software and/or dedicated hardware. Collaborative labs help students to: (1) learn through experience, (2) leverage the perceptions of their learning partners, and (3) form their own opinions through social constructivism. The evidence to date is that collaborative labs consistently demonstrate positive effects on student achievement, self-esteem, and attitude toward learning. Advances in cloud computing and virtualization technologies enable students to complete labs on virtualized resources remotely through the Internet. However, while virtual computer labs provide anywhere, anytime, on-demand access to specialized software and hardware, the virtual workspaces to which students are assigned lack support for sharing, causing the collaborative aspect of learning to be lost. This project serves the national interest in producing a highly-qualified STEM workforce by developing and evaluating an environment that supports collaborative learning in cloud-based virtual computer labs.The goal of this project is to integrate three models of virtual collaboration into a collaborative lab software tool: shared remote collaboration, virtual study rooms, and a virtual tutoring center. The environment will allow students to reserve virtual computers labs with multiple participants and will support remote real-time collaboration among the participants during a lab. The learning environment will be evaluated in computer science and other STEM discipline courses, and a virtual tutoring center for evaluation will be developed. The collaborative lab environment has the potential to significantly enhance students' collaborative learning in cloud-based virtual computer labs and benefit a wide range of universities and colleges that use virtual computer labs in education. It is expected to support collaborative learning in many STEM disciplines using virtual computer labs, benefitting traditional undergraduates as well as returning adult and distance learning students in both formal and informal settings. The collaborative lab software tool will be distributed as an open source project with all materials, designs, and source code available on a public web site for wide dissemination.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Support Remote Collaboration in Virtual Computer Labs
支持虚拟计算机实验室中的远程协作
DOI: --
发表时间: 2019
期刊: 2019
影响因子: --
作者: [Xiaolin Hu, Hai Le]
通讯作者: Xiaolin Hu, Hai Le
Online Tutoring Through a Cloud-Based Virtual Tutoring Center
通过基于云的虚拟辅导中心进行在线辅导
DOI: 10.1007/978-3-030-59635-4_20
发表时间: 2020
期刊: Cloud Computing – CLOUD 2020. CLOUD 2020. Lecture Notes in Computer Science
影响因子: --
作者: [Hu, X., Tabdil, S.D., Achhe, M., Pan, Y., Bourgeois, A.G.]
通讯作者: Bourgeois, A.G.
Collaborative Learning in Cloud-based Virtual Computer Labs
基于云的虚拟计算机实验室中的协作学习
DOI: 10.1109/fie.2018.8659018
发表时间: 2018
期刊: 2018 IEEE Frontiers in Education Conference (FIE
影响因子: --
作者: [Hu, Xiaolin, Le, Hai, Bourgeois, Anu G., Pan, Yi]
通讯作者: Pan, Yi
Collaborative Research: Planning: FIRE-PLAN:High-Spatiotemporal-Resolution Sensing and Digital Twin to Advance Wildland Fire Science
SCC-IRG Track 1: Smart and Safe Prescribed Burning for Rangeland and Wildland Urban Interface Communities
SCC-PG: Smart and Safe Prescribed Burning for Rangeland and Farmland Communities
Collaborative Research: Portable, Modular, Modern Technology Infused Courseware for Broader Embedded System Education
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Understanding structural evolution of galaxies with machine learning
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  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位:
煤矿安全人机混合群智感知任务的约束动态多目标Q-learning进化分配
  • 批准号:
    --
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30万元
  • 批准年份:
    2022
  • 负责人:
    吉建娇
  • 依托单位:
基于领弹失效考量的智能弹药编队短时在线Q-learning协同控制机理
  • 批准号:
    62003314
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    沈剑
  • 依托单位: