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计算工作实例如何与消退策略相结合，从而有效地促进学生在工程中定性和定量表征的流畅性发展。这将通过以下目标来完成：目标1：利用对复杂任务学习的研究来开发和实现一套计算工作示例。目的2：通过基于设计的研究，采用自然主义和准实验调查来检验基础研究问题。目标3：传播成果，确保在预期受众中产生广泛影响。基础研究问题是：“计算工作实例如何有效地促进学生从定性表征到定量表征的流畅性发展？”我们将采用基于设计的研究方法，结合现象学方法和定量方法来进行调查。本研究的长期目标是建立一个综合的基于证据的研究项目，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策略，为下一代科学家和工程师准备解决复杂的跨学科问题。更广泛的影响和重要性：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，计算正在对发现和创新产生重大影响。为了为复杂的跨学科工作创造新的机会，培训和参与能够成功地整合和利用计算的下一代劳动力工程师必须成为现代工程教育的一个组成部分。图形表示和计算问题解决结果的其他视觉表示是科学研究以及解决工作场所工程中复杂问题的核心。具体来说，它们在工程中被用作深入了解物质世界的工具，进一步解释有关问题的信息，确定其组成部分之间的关系，并提供潜在的解决方案。未来的工程师需要培养流畅的表达能力，或者是在不同类型的媒体中，以视觉和物理方式描述使用计算工具获得的问题和解决方案的能力。这项研究的结果将包括在工程学科课程中设计和整合计算工作实例的一套原则。这些发现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、更有信心地利用计算在工程中的作用。本研究由工程教育与中心部的工程教育研究计划提供支持。

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.