课题基金 / 基金详情

Scientific Computation for Interdisciplinary Data Analysis and Technological Application

Scientific Computation for Interdisciplinary Data Analysis and Technological Application
跨学科数据分析与技术应用的科学计算
批准号:
9851642
负责人:
Keith Clay
金额:
$6.41万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-09-15 至 2000-08-31

项目摘要

项目成果

Keith Clay的其他基金

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中文摘要
翻译
绿河社区学院的教职员工正在创建一个新的项目,要求在地质学、物理学和化学的所有课程中进行现实的计算机化数据分析。该计划要求所有学生使用来自工业和他们自己的实验室的数据参与科学计算,在一个新的中央计算机实验室和与该中心电子连接的实验室进行。取消数据分析和计算局限于实验室阶段,使整个课程成为活跃的科学课程。大多数理科学生通过传统课本中的家庭作业来培养解决有限问题的能力,但当面对真实数据分析中的问题时,即使是有天赋的学生也经常不知所措。职业学生和非理科专业的学生更不可能接触到科学数据的真实世界,或者将计算机用作文字处理器以外的任何东西。企业认为,对计算机技能的需求是工作场所最大的问题之一,教育研究发现,有必要直接接触具有真实数据和应用程序的调查科学。一个协调的计算机化数据分析程序可以满足这两种需求。这个项目让所有自然科学专业的学生参与到日常的科学数据分析中来。计算机被用作科学探索的自然组成部分。能力较差的学生利用同伴辅导来提高他们的计算机技能。所有学生从实验或工业合作者那里收集数据,并在中心计算机实验室协作分析数据。跨学科课程将计算机、物理和化学、地质和环境以及其他科学与科学以外的学科结合在一起。这个项目的学生可以加强他们的计算机技能,他们的科学素养,他们的合作学习技能,以及他们对科学的相关性和相互关联性的欣赏。职业生和非理科专业的学生与未来的科学家和工程师一样受益。我们对科学教育的理解可能会带来远远超出这所学院界限的好处。
英文摘要
The faculty of Green River Community College are creating a new program requiring realistic computerized data analysis in all courses in geology, physics, and chemistry. The program requires all students to participate in scientific computing using data from industry and their own labs, to be done in a new central computer laboratory and in laboratories electronically connected to the center. The confinement of data analysis and computation to lab period will be eliminated, making entire courses into active science courses. Most science students develop problem solving skills for a limited range of problems modeled by homework assignments from traditional texts, but when presented with problems in real data analysis even talented students are often at a loss. Vocational students and non-science majors are even less likely to gain exposure to the real world of scientific data or to use a computer as anything other than a word processor. Businesses have identified the need for computer skills as one of the greatest problems in the workplace and education research has identified a need for direct exposure to investigative science with real data and applications. A coordinated program of computerized data analysis meets both needs. This project involves all physical science students in the daily analysis of scientific data. Computers are used as natural components of scientific exploration. Less able students utilize peer tutors to boost their computer skills. All students collect data from experiments or industrial collaborators and analyze data cooperatively in the central computer laboratory. Interdisciplinary courses blend computers, physics, and chemistry, geology and the environment, and other sciences with subjects outside of the sciences as well. Students in this program can strengthen their computer skills, their scientific literacy, their cooperative study skills, and their appreciation for the relevance and interconnectedness of science. Vocational students and non-science majors benefit along with future scientists and engineers. Gains in our understanding of science education could have benefits well beyond the boundaries of this college.
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DISSERTATION RESEARCH: The role of phyllosphere microbiomes in plant species coexistence and plant-pathogen interactions
  • 批准号:
    1701816
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.01万
  • 财政年份:
    2017
  • 负责人:
    Keith Clay
  • 依托单位:
Dissertation Research: Assembly, maintenance, and function of the plant-endophyte symbiosis
  • 批准号:
    1601135
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.96万
  • 财政年份:
    2016
  • 负责人:
    Keith Clay
  • 依托单位:
OPUS: Synthesizing Defensive Symbiosis from a Microbial Perspective
  • 批准号:
    1354078
  • 项目类别:
    Standard Grant
  • 资助金额:
    $14.53万
  • 财政年份:
    2014
  • 负责人:
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  • 依托单位:
Doctoral Dissertation Research: Assessing geographic patterns of negative density dependence in temperate tree species.
  • 批准号:
    1110533
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.34万
  • 财政年份:
    2011
  • 负责人:
    Keith Clay
  • 依托单位:
国内基金
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  • 批准号:
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  • 资助金额:
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  • 依托单位:
基于g-computation控制纵向数据未测混杂因素的因果推断模型构建及应用研究
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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