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Complex problem-solving using conceptual and formal knowledge.

机译:使用概念和形式知识解决复杂的问题。

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摘要

Our research is concerned with understanding how people solve problems in scientific domains such as physics, chemistry, computer science, and related disciplines. Specifically, we are interested in how people use a formal scientific language, such as differential equations or chemical formulae, (i.e. a formal representation) in conjunction with conceptual knowledge of the domain, to solve the wide range of problems of which engineers and scientists are capable.;Many traditional psychological models of these domains suggest that problem solving occurs as an orderly sequence of phases. Shifting from one phase to the next is accompanied by a representational shift.;We investigated the adequacy of this model in accounting for expert problem solving behavior. Suspending two properties of the traditional model suggests two alternative models, the iterative model and the interactive model.;We hypothesize that the traditional model will be adequate to explain the way experts coordinate conceptual and formal knowledge for easy problems in which experts can retrieve a well-practiced schema. However, we suggest that it will not be adequate to explain experts' behavior on more difficult problems.;To address these issues we performed two experiments. In Study One, we asked expert problem solvers to "think aloud" while solving easy and difficult mechanics problems and to give confidence ratings of their solutions. We coded the protocols according to the kind of knowledge subjects were using, and analyzed the ways in which their protocols drew upon conceptual and formal representations. As expected, in the more difficult problems expert behavior could not be adequately characterized by the traditional model. Instead the interactive model was necessary. We also characterize the kinds of representational transitions that occurred and discuss their function.;In Study Two, we examined the generality of the findings by replicating the experiment in a different domain, algorithm design. Again, we found support for the interactive model.;The results of the two studies support the notion that only the interactive model is adequate to account for the kinds behaviors exhibited by expert problem solvers.
机译:我们的研究关注于了解人们如何解决科学领域的问题,例如物理学,化学,计算机科学和相关学科。具体来说,我们对人们如何使用形式化的科学语言(例如微分方程或化学式)(即形式表示)以及该领域的概念知识感兴趣,以解决工程师和科学家所面临的广泛问题这些领域的许多传统心理学模型表明,解决问题的过程是阶段性的有序序列。从一个阶段转移到下一个阶段伴随着代表性的转移。我们研究了该模型在解决专家问题解决行为方面的充分性。暂停传统模型的两个属性可以提出两个替代模型,即迭代模型和交互模型。我们假设,传统模型足以解释专家对概念和形式知识进行协调的方式,以解决专家可以轻松找到的问题。实践模式。但是,我们建议不足以解释专家在更棘手的问题上的行为。为了解决这些问题,我们进行了两个实验。在研究一中,我们要求专业的问题解决者在解决简单和困难的力学问题时“大声思考”,并给出解决方案的置信度。我们根据受试者所使用的知识种类对协议进行了编码,并分析了其协议以概念和形式表示为基础的方式。不出所料,在更棘手的问题中,传统模型无法充分表征专家的行为。相反,交互式模型是必需的。我们还表征了发生的代表性转换的种类并讨论了它们的功能。在研究二中,我们通过在不同领域(算法设计)中复制实验来检验了发现的一般性。再次,我们发现了对交互式模型的支持。两项研究的结果支持以下观点:只有交互式模型才足以说明专家问题解决者所表现出的各种行为。

著录项

  • 作者

    Bauer, Malcolm Ignatius.;

  • 作者单位

    Princeton University.;

  • 授予单位 Princeton University.;
  • 学科 Psychology Experimental.;Education Educational Psychology.;Education Curriculum and Instruction.;Education Sciences.
  • 学位 Ph.D.
  • 年度 1991
  • 页码 186 p.
  • 总页数 186
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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