Collaborative Research: Deep Insights Anytime, Anywhere (DIA2) - Central Resource for Characterizing the TUES Portfolio through Interactive Knowledge Mining and Visualizations

协作研究:随时随地深入洞察 (DIA2) - 通过交互式知识挖掘和可视化来表征 TUES 产品组合的中心资源

基本信息

  • 批准号:
    1123108
  • 负责人:
  • 金额:
    $ 130.75万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-09-15 至 2017-08-31
  • 项目状态:
    已结题

项目摘要

LEAD INSTITUTION: Purdue UniversityCOLLABORATORS: Arizona State University, Stanford University and Virginia Polytechnic Institute and State UniversityPROJECT DESCRIPTIONThis TUES Central Resource Project is designed to help those engaged in improving STEM education to synthesize knowledge produced through NSF investments through a web-based knowledge mining and interactive visualization platform. The Deep Insights Anytime, Anywhere (DIA2) project allows users (e.g., current and potential principle investigators, NSF/TUES program staff, and administrators at academic institutions) to interactively mine, synthesize, and visualize data at a scale that is not possible with currently available tools. DIA2 is based upon a more narrowly scoped Interactive Knowledge Networks for Engineering Education Research (iKNEER) prototype that targeted the engineering education research community, expanding the functionality by an order of magnitude in scale; integrating newer approaches in data mining and visualization into a fully deployed system. The project has three major goals: (1) Empower the TUES community to leverage TUES investments by understanding the knowledge hidden within its networks; (2) Develop and apply cutting-edge, large-scale knowledge mining and visualization techniques for characterizing the portfolio of TUES and predecessor programs; and (3) Leverage social media optimization and integration to catalyze diffusion of TUES innovations, build a community and sustain the project impact. DIA2 enables users to explore massive amounts of data and make sense of it using a highly intuitive process. The system development approach combines theories of user-centered design, large-scale data mining, community formation, social network analysis, and interactive visualization. The project's evaluation plan includes both formative and summative approaches for documenting, testing, measuring, and sharing community outcomes, internal team working, and system performance.BROADER SIGNIFICANCEDIA2 offers a framework for understanding and characterizing the TUES program along with its predecessor programs. It makes data available to a large community of TUES users and allows them to analyze the portfolio to garner an understanding of how ideas are adopted by others in the community. It allows current and future PIs, NSF program officers and administrators at academic institutions to identify best practices and explore synergistic projects in their environments. Since DIA2 is a knowledge portal, it provides a unique opportunity to showcase work undertaken at underserved and underprivileged institutions in new and novel ways. The project team is employing a methodology that attempts to understand the needs of these communities, in order to better address the DIA2 system design requirements. Ultimately, DIA2 is focused on providing knowledge that will allow the community to increase the impact of NSF STEM investments that improve student learning.
牵头机构:普渡大学合作伙伴:亚利桑那州立大学,斯坦福大学和弗吉尼亚理工学院和州立大学项目简介这个TUES中央资源项目旨在帮助那些从事改善STEM教育的人通过基于网络的知识挖掘和交互式可视化平台综合通过NSF投资产生的知识。Deep Insights Anytime,Anywhere(DIA 2)项目允许用户(例如,当前和潜在的主要研究人员,NSF/TUES计划工作人员和学术机构的管理人员)以交互式方式挖掘,合成和可视化数据,其规模是目前可用工具无法实现的。DIA 2是基于一个范围更窄的交互式知识网络工程教育研究(iKNEER)原型,针对工程教育研究社区,扩大了规模的数量级的功能;集成数据挖掘和可视化到一个全面部署的系统的新方法。该项目有三个主要目标:(1)通过了解其网络中隐藏的知识,使TUES社区能够利用TUES投资;(2)开发和应用尖端的大规模知识挖掘和可视化技术,以表征TUES和前身计划的组合;以及(3)利用社会媒体优化和整合来促进TUES创新的传播,建立社区并维持项目影响。DIA 2使用户能够探索大量的数据,并使用高度直观的过程来理解它。系统开发方法结合了以用户为中心的设计,大规模数据挖掘,社区形成,社会网络分析和交互式可视化的理论。该项目的评估计划包括形成性和总结性的方法,用于记录,测试,测量和共享社区成果,内部团队工作和系统性能。更广泛的意义2提供了一个框架,用于理解和表征TUES计划沿着其前身计划。它为TUES用户的大型社区提供数据,并允许他们分析投资组合,以了解社区中的其他人如何采用想法。它允许当前和未来的PI,NSF项目官员和学术机构的管理人员确定最佳实践并在其环境中探索协同项目。由于DIA 2是一个知识门户网站,它提供了一个独特的机会,以新的和新颖的方式展示在服务不足和贫困机构开展的工作。项目团队正在采用一种方法,试图了解这些社区的需求,以便更好地满足DIA 2系统的设计要求。最终,DIA 2专注于提供知识,使社区能够增加NSF STEM投资的影响,从而改善学生的学习。

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 }}

Krishna Madhavan其他文献

AC 2011-1873: UNDERSTANDING THE ENGINEERING EDUCATION RE-SEARCH PROBLEM SPACE USING INTERACTIVE KNOWLEDGE NET-WORKS
AC 2011-1873:使用交互式知识网络了解工程教育研究问题空间
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Krishna Madhavan;Hanjun Xian;B. Jesiek;P. Wankat
  • 通讯作者:
    P. Wankat
Erratum to: A fibrin/hyaluronic acid hydrogel for the delivery of mesenchymal stem cells and potential for articular cartilage repair
  • DOI:
    10.1186/1754-1611-8-27
  • 发表时间:
    2014-11-28
  • 期刊:
  • 影响因子:
    6.500
  • 作者:
    Timothy N Snyder;Krishna Madhavan;Miranda Intrator;Ryan C Dregalla;Daewon Park
  • 通讯作者:
    Daewon Park

Krishna Madhavan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('Krishna Madhavan', 18)}}的其他基金

EAGER: BIGDATA: SMART Data - Academic Success Made Affordable, Rapid, and Timely through Integrated Data Analytics
EAGER:大数据:智能数据 - 通过集成数据分析,经济、快速、及时地取得学术成功
  • 批准号:
    1552288
  • 财政年份:
    2015
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research (EAGER): Data Ecosystem for Catalyzing Transformative Research in Engineering Education
协作研究(EAGER):促进工程教育变革性研究的数据生态系统
  • 批准号:
    1306377
  • 财政年份:
    2014
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
CAREER: Advancing engineering education through learner-centric, adaptive cyber-tools and cyber-environments
职业:通过以学习者为中心的自适应网络工具和网络环境推进工程教育
  • 批准号:
    0956819
  • 财政年份:
    2009
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: Interactive Knowledge Networks for Engineering Education Research (iKNEER)
合作研究:工程教育研究交互式知识网络(iKNEER)
  • 批准号:
    0935090
  • 财政年份:
    2009
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: Interactive Knowledge Networks for Engineering Education Research (iKNEER)
合作研究:工程教育研究交互式知识网络(iKNEER)
  • 批准号:
    0957015
  • 财政年份:
    2009
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
CAREER: Advancing engineering education through learner-centric, adaptive cyber-tools and cyber-environments
职业:通过以学习者为中心的自适应网络工具和网络环境推进工程教育
  • 批准号:
    0747795
  • 财政年份:
    2008
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
RE@L: Research Environments Associated with Learning through Social Networks
RE@L:与社交网络学习相关的研究环境
  • 批准号:
    0726023
  • 财政年份:
    2007
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Geophysical and geochemical investigation of links between the deep and shallow volatile cycles of the Earth
合作研究:地球深层和浅层挥发性循环之间联系的地球物理和地球化学调查
  • 批准号:
    2333102
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Continuing Grant
Collaborative Research: Resolving the LGM ventilation age conundrum: New radiocarbon records from high sedimentation rate sites in the deep western Pacific
合作研究:解决LGM通风年龄难题:西太平洋深部高沉降率地点的新放射性碳记录
  • 批准号:
    2341426
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Continuing Grant
Collaborative Research: Resolving the LGM ventilation age conundrum: New radiocarbon records from high sedimentation rate sites in the deep western Pacific
合作研究:解决LGM通风年龄难题:西太平洋深部高沉降率地点的新放射性碳记录
  • 批准号:
    2341424
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Continuing Grant
Collaborative Research: OAC Core: CropDL - Scheduling and Checkpoint/Restart Support for Deep Learning Applications on HPC Clusters
合作研究:OAC 核心:CropDL - HPC 集群上深度学习应用的调度和检查点/重启支持
  • 批准号:
    2403088
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: OAC Core: CropDL - Scheduling and Checkpoint/Restart Support for Deep Learning Applications on HPC Clusters
合作研究:OAC 核心:CropDL - HPC 集群上深度学习应用的调度和检查点/重启支持
  • 批准号:
    2403090
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: Resolving the LGM ventilation age conundrum: New radiocarbon records from high sedimentation rate sites in the deep western Pacific
合作研究:解决LGM通风年龄难题:西太平洋深部高沉降率地点的新放射性碳记录
  • 批准号:
    2341425
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Continuing Grant
Collaborative Research: OAC Core: CropDL - Scheduling and Checkpoint/Restart Support for Deep Learning Applications on HPC Clusters
合作研究:OAC 核心:CropDL - HPC 集群上深度学习应用的调度和检查点/重启支持
  • 批准号:
    2403089
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: Geophysical and geochemical investigation of links between the deep and shallow volatile cycles of the Earth
合作研究:地球深层和浅层挥发性循环之间联系的地球物理和地球化学调查
  • 批准号:
    2333101
  • 财政年份:
    2024
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: FET: Medium:Compact and Energy-Efficient Compute-in-Memory Accelerator for Deep Learning Leveraging Ferroelectric Vertical NAND Memory
合作研究:FET:中型:紧凑且节能的内存计算加速器,用于利用铁电垂直 NAND 内存进行深度学习
  • 批准号:
    2312886
  • 财政年份:
    2023
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
Collaborative Research: RI: Medium: Principles for Optimization, Generalization, and Transferability via Deep Neural Collapse
合作研究:RI:中:通过深度神经崩溃实现优化、泛化和可迁移性的原理
  • 批准号:
    2312841
  • 财政年份:
    2023
  • 资助金额:
    $ 130.75万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了