课题基金 / 基金详情

Articulate Virtual Laboratories for Science and Engineering Education

Articulate Virtual Laboratories for Science and Engineering Education
为科学与工程教育打造虚拟实验室
批准号:
9453078
负责人:
Kenneth Forbus
金额:
$90.11万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1995
资助国家:
美国
项目状态:
已结题
起止时间:
1995-04-15 至 2000-05-31

项目摘要

项目成果

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中文摘要
翻译
9453078 FORBUS这个项目的目标是开发可连接的虚拟实验室(AVL),通过脚手架和指导学生完成概念设计任务来教授科学和工程原理。我们正在测试的教育猜想是,清晰的虚拟实验室将使学生能够(A)从根本上学习基本原理,比他们本来无法表现的更好。为了验证这些猜测,西北大学和牛津大学的工科本科生以及埃文斯顿镇高中的高中生将使用我们的原型实验室作为他们课程作业的一部分。我们相信,清晰的虚拟实验室可以极大地改善工程和科学教育。设计经验对工程教育至关重要,并为学习基本物理原理提供了强大的激励环境:如果不使用广泛的物理原理,就无法设计喷气发动机、冰箱或发电厂。让学生专注于基础知识的设计环境,对基础科学和工程学的教学可能是非常有价值的,并可以更好地激发对科学学习的兴趣。在典型的课堂环境中很难提供设计体验,因为许多有趣的物理制品(如发电厂、喷气式发动机和冰箱)构建和实验成本很高或很危险。Articate虚拟实验室将通过使学生能够在模拟环境中廉价且安全地设计、分析和测试人工制品来解决这些问题。他们将为学生提供指导,以帮助他们理解基本原则,帮助他们练习建模、分析和设计物理系统所需的技能,并通过最大限度地减少学生探索的不启发性方面来提供良好的实验室助理所提供的监督。创建精通艺术的虚拟实验室需要综合涉及几项人工智能技术的进展。定性物理学为科学家和工程师的隐性知识提供了正式的表示,这些知识将他们的专业知识与他们基于经验的直觉联系起来,使软件能够使用与领域专家认为自然的方法和概念类似的方法和概念。组合建模为计算机辅助建模提供了表示和推理技术(例如,如何将某个领域的专业知识应用于对真实世界的情况进行建模,以便能够对其进行正式分析)。真理维护系统提供推理服务,并为构建系统结果的解释和以帮助学生理解学习领域的推理提供原材料。符号代数和约束传播提供了数学解决方案。类比处理技术提供了从精心设计的设计和实例库中检索结果并将其应用于实际情况的能力,以便指导学生。我们正在开发两个原型铰接式虚拟实验室,与西北大学和牛津大学的工程学教师合作,后者愿意与他们的学生一起使用它们。首先是热力循环,这是一种用于发电厂、推进系统、制冷系统和热泵的概念设计的理想化方法。要掌握热力学循环的设计和分析,需要对大量的热力学有深刻的理解。第二个问题与反馈控制器有关。反馈和控制理论的概念渗透到现代科学和工程中。虽然设计最优控制器需要数学分析,但我们相信,如果有适当的支架,高中生可以掌握许多重要的反馈概念。***
英文摘要
9453078 Forbus The goal of this project is to develop articulate virtual laboratories (AVLs) that teach science and engineering principles by scaffolding and coaching students in conceptual design tasks. The educational conjecture we are testing is that articulate virtual laboratories will enable students to (a) learn fundamental principles radically be better than they would otherwise be unable to perform. To test these conjectures, our prototype laboratories will be used by engineering undergraduates from Northwestern University and Oxford University as part of their course work, and by high school students from Evanston Township High School. We believe that articulate virtual laboratories could dramatically improve engineering and science education. Design experience is essential to engineering education, and provides a powerful motivating context for learning fundamental physical principles: One cannot design a jet engine, refrigerator, or power plant without using a broad range of physical principles. Design environments that scaffold students, allowing them to focus on fundamentals, could prove invaluable for instruction in basic science as well as engineering, and could better motivate interest in science learning. Design experiences are difficult to provide in typical classroom settings, because many interesting physical artifacts (such as power plants, jet engines, and refrigerators) are expensive or dangerous to build and experiment with. Articulate virtual laboratories will address these problems by enabling students to design, analyze, and test artifacts in a simulated environment, cheaply and safely. They will provide coaching for students, in order to help them understand fundamental principles, to help them practice the skills needed to model, analyze, and design physical systems, and to provide the kind of supervision that a good laboratory assistant provides by way of minimizing unenlightening aspects of student explorations. Creating art iculate virtual laboratories requires synthesizing advances involving several AI technologies. Qualitative physics provides formal representations for the tacit knowledge of scientists and engineers that connects their professional knowledge to their experience-based intuitions, enabling software to use methods and concepts similar to those deemed natural by domain experts. Compositional modeling provides representations and reasoning techniques for computer-assisted modeling (e.g., how to apply professional knowledge of a domain to modeling real-world situations so that they can be formally analyzed). Truth- maintenance systems provide reasoning services and the raw material for constructing explanations of the system's results and reasoning in terms that help students understand the domain of study. Symbolic algebra and constraint propagation provide mathematical solutions. Analogical processing techniques provide the ability to retrieve and apply results from libraries of worked out designs and examples to notel situations, in order to coach students. We are developing two prototype articulate virtual laboratories, in collaboration with engineering faculty at Northwestern University and at Oxford University who are willing to use them with their students. The first concerns thermodynamic cycles, an idealization used in the conceptual design of power plants, propulsion systems, refrigeration systems, and heat pumps. To master the design and analysis of thermodynamic cycles requires a deep understanding of a substantial body of thermodynamic. The second concerns feedback controllers. The concepts of feedback and control theory permeate modern science and engineering. While mathematical analyses are required to design optimal controllers, we believe that many of the important concepts of feedback could be grasped by high school students, given appropriate scaffolding. ***
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会议论文
RI: Doctoral Student Workshop at the Fourth Annual Conference on Advances in Cognitive Systems
  • 批准号:
    1637643
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.0万
  • 财政年份:
    2016
  • 负责人:
    Kenneth Forbus
  • 依托单位:
SGER: Comparison and Explanation in Learning and Development
  • 批准号:
    0628941
  • 项目类别:
    Standard Grant
  • 资助金额:
    $0.0万
  • 财政年份:
    2006
  • 负责人:
    Kenneth Forbus
  • 依托单位:
ITR: Analogy, Knowledge Integration, and Task Modeling Tools for Intelligence Analysts
  • 批准号:
    0325315
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $95.0万
  • 财政年份:
    2003
  • 负责人:
    Kenneth Forbus
  • 依托单位:
Computer-Supported Graphical Representations for Learning Modeling
  • 批准号:
    9909744
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $103.08万
  • 财政年份:
    1999
  • 负责人:
    Kenneth Forbus
  • 依托单位:
海外基金