模拟课程的统一考核方法[兼教授急]

I. Milanović, T. Eppes, Kamau C. Wright
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引用次数: 2

摘要

为了支持我们课程的数字化转型,模拟作业被嵌入到本科流体力学和传热讲座课程中,以及计算工程技术选修课中。每门课程将模拟、应用程序构建和基于探究的学习(IBL)与十项课外作业相结合,并在技术报告中记录。热流体学采用有限元分析和CFD工具进行教学,而CFD和有限元分析则采用教材进行教学。这种新的、高影响力的实践有助于加深对理论概念的理解,使学生接触到现代工程工具,并培养学生的研究能力,而“讲座”时间仅用于基础理论主题。本研究的主要目标是扩展模拟和IBL在本科热流体课程中的实施,并创建一个模板,以便在其他主题线程中这样做。这是通过以下方式实现的:(1)在战略上平衡支持技能培养的分步指导,以及指导发现过程和培养高阶思维技能的探究式任务;(2)提供清晰详细的评分标准,指导学生在获得技能和执行IBL的过程中;(3)设计便于跨课程进行的学生作业评估策略;(4)基于指示学习成果实现的定量和定性数据,评估学生对整体数字化转型工作的理解和效果。这项研究建立在作者以前在模拟和IBL领域报道的工作基础上,涵盖了个别课程和课程序列。虽然定量数据包括使用分数、学生调查和课程评估来评估学生对选定概念的理解和信心,但所描述的方法的影响是用定性数据来说明的,包括几个学生工作的例子及其对他们专业发展的影响。
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Unified Assessment Approach for Courses With Simulation Component [And Professors in Hurry]
In support of the digital transformation of our programs, simulation assignments are embedded in undergraduate fluid mechanics and heat transfer lecture-based courses, as well as in the Computational Engineering technical electives. Each course integrates simulations, application building, and inquiry-based learning (IBL) with ten assignments performed outside the class and documented in technical reports. FEA and CFD tools are employed to teach thermo-fluids, and in turn, course material is used to teach CFD and FEA. This new, high-impact practice facilitates a deeper understanding of theoretical concepts, exposes students to modern engineering tools, and develops students’ research capacity while the ‘lecture’ time is dedicated for the fundamental theoretical topics only. The main goal of this study was to expand on the implementation of simulations and IBL in undergraduate thermo-fluids courses and create a template to do so in other topical threads. This was accomplished by: (1) strategically balancing step-by-step instructions supporting skill-building, with inquiry-based tasks guiding discovery process and developing higher order thinking skills; (2) providing clear and detailed grading criteria guiding students both in the process of gaining skills and performing IBL; (3) designing strategies for the assessment of student work that are easily transported across the curriculum; and (4) assessing students’ understanding and the effect of the overall digital transformation effort based on quantitative and qualitative data indicative of the achievement of learning outcomes. This study builds on the authors’ previously reported work in the area of simulations and IBL that covered individual courses as well as course sequences. While quantitative data includes assessment of students’ understanding and confidence in comprehension of select concepts using grades, student surveys, and course evaluations, the impact of the described approach is illustrated with qualitative data including several examples of student work and its influence on their professional development.
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