Computational Worked Examples for Scaffolding Student Representational Fluency

技术描述：本工程教育研究项目的目标是确定如何计算工作的例子加上褪色策略可以有效地支架学生的发展在工程中的定性和定量表示的代表性流畅性。这将通过这些目标来实现：目标1：使用复杂任务学习的研究，开发和实施一套计算工作的例子。目标2：通过基于设计的研究，使用自然主义和准实验调查来检查基础研究问题。目标三：传播结果以确保在目标受众中产生广泛的影响。基本的研究问题是：“计算工作的例子如何有效地支持学生从定性到定量表征的表征流畅性的发展？“我们将使用基于设计的研究将现象学方法与定量方法相结合来进行这项调查。这项研究的长期目标是建立一个综合的基于证据的研究计划，以实践为中心，研究人们如何发展表征流畅性，并利用这些知识制定战略，使下一代科学家和工程师能够解决复杂的跨学科问题。计算通过支持医疗保健、能源、经济竞争力和国家安全方面的进步，对发现和创新产生了重大影响。能够成功整合和利用计算的下一代劳动力工程师的培训和参与必须成为现代工程教育的一个组成部分，以便为复杂的跨学科工作创造新的机会。计算问题解决结果的图形表示和其他视觉表示是科学研究以及工作场所工程中复杂问题解决方案的核心。具体来说，它们在工程中被用作工具，以深入了解物质世界，进一步解释有关问题的信息，识别其组件之间的关系，并提供潜在的解决方案。未来的工程师需要发展代表性的流畅性，或描述问题的能力，并使用计算工具获得解决方案，在不同类型的媒体视觉和物理术语。这项研究的成果将包括一套原则的设计和集成的计算工作的例子在工程学科课程。研究结果将增加工程发现和创新成功的机会，并将帮助美国更快，更好地利用计算在工程中的作用，并有更大的信心。

Technical Description:The goal for this Research in Engineering Education project is to identify how computational worked examples coupled with a fading strategy can effectively scaffold student development of representational fluency across qualitative and quantitative representations in engineering. This will be accomplished through these objectives: Objective 1: Use research on complex task learning to develop and implement a set of computational worked examples. Objective 2: Use naturalistic and quasi-experimental investigations through design-based research to examine the foundational research question. Objective 3: Disseminate results to ensure broad impacts among intended audiences.The foundational research question is: "How computational worked examples can effectively scaffold student development of representational fluency translating from qualitative to quantitative representations?" We will approach this investigation using design-based research coupling phenomenographic methods with quantitative methods. The long-term goal of this research is to establish an integrated evidence based program of research to practice centered on how people develop representational fluency, and to use this knowledge to develop strategies that will prepare the next generation of scientists and engineers to be capable of addressing complex interdisciplinary problems.Broader Impact and Importance:Computing is having major implications in discovery and innovation by supporting advances in healthcare, energy, economic competitiveness, and national security. Training and engagement of the next generation of work force engineers able to integrate and take advantage of computation successfully must be an integral part of modern engineering education in order to create new opportunities for complex interdisciplinary work. Graphical representations and other visual representations of the results of computational problem solving are central to scientific research as well as to the solution of complex problems in workplace engineering. Specifically, they are used in engineering as tools to gain insight into the material world, further interpret information about a problem, identify relationships between its components, and provide potential solutions to it. Future engineers need to develop representational fluency, or the ability to describe a problem and solutions obtained using computational tools visually and in physical terms, across diverse types of media. The outcomes of this research will include a set of principles for the design and integration of computational worked examples in engineering disciplinary courses. Findings will boost the chances for engineering discovery and innovation success and will help the United States take advantage of the role of computation in engineering sooner, better, and with greater confidence.This research is supported by the Research in Engineering Education Program of the Engineering Education and Centers Division.