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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

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中文摘要
翻译
绿河社区学院的教师正在创建一个新项目,要求在地质学、物理学和化学的所有课程中进行真实的计算机数据分析。该计划要求所有学生参与科学计算,使用来自行业和自己实验室的数据,在新的中央计算机实验室和与中心电子连接的实验室中完成。取消数据分析和计算在实验期间的限制,使整个课程成为活跃的科学课程。大多数理科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常常不知所措。职校学生和非理工科专业的学生更不可能接触到真实世界的科学数据,也不太可能把电脑当作文字处理器以外的东西来使用。企业已经认识到对计算机技能的需求是工作场所最大的问题之一,教育研究已经认识到需要直接接触具有真实数据和应用的调查科学。计算机数据分析的协调程序满足这两种需要。这个项目要求所有物理科学专业的学生每天分析科学数据。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导师来提高他们的计算机技能。所有学生在中央计算机实验室收集实验或工业合作者的数据并合作分析数据。跨学科课程将计算机、物理、化学、地质和环境以及其他科学与科学以外的学科相结合。这个项目的学生可以加强他们的计算机技能,科学素养,合作学习技能,以及对科学的相关性和相互关联性的认识。高职学生和非理工科学生以及未来的科学家和工程师都将受益。我们对科学教育的理解的收获将远远超出这所大学的范围。
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:
    Keith Clay
  • 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
海外基金
基于分位数g-computation的多污染物联合空气质量健康指数构建及预测效果评价
  • 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:
    李嘉琛
  • 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:
    81903416
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    19.0万元
  • 批准年份:
    2019
  • 负责人:
    陈永杰
  • 依托单位: