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Guided Problem Solving and Group Programming: A Technology-Enhanced Teaching-Learning Strategy for Engineering Problem Solving

机译:指导式问题解决和小组编程:工程问题解决的技术增强型教学策略

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An important goal of undergraduate engineering education is to develop students' ability to solve complex, real world problems. Such problems involve the building of physical and mathematical models of real-world scenarios, identifying correct parameters of the model, devising numerical solution methods, and optimizing the solution. In typical engineering courses, solution methods are demonstrated in problem-solving tutorials while programming is relegated to homework or lab, wherein students may not get ample feedback on their choices of optimization or solution evaluation. In this paper, we propose a strategy, Guided Problem Solving and Group Programming (GPGP) to overcome this gap. Students work in peer groups within class, to build and implement their mathematical models and solutions, then write programs to do optimization and evaluation. We implemented this strategy in a 4th year electrical engineering course in which GPGP was done four times over the semester. We assessed students' performance on dimensions of problem solving such as representing the problem, developing solution, making justification for proposed solution and monitoring and evaluating problem space and solutions across the semester and found a statistically significant improvement. Further students perceived that they had learned engineering problem solving via GPGP and reported enjoying the strategy in class.
机译:本科工程教育的一个重要目标是提高学生解决复杂的现实世界问题的能力。这些问题包括建立实际场景的物理和数学模型,确定模型的正确参数,设计数值解法以及优化解法。在典型的工程课程中,在解决问题的教程中演示了解决方法,而将编程工作委托家庭作业或实验室进行,其中学生可能无法获得关于他们对优化或解决方案评估选择的充分反馈。在本文中,我们提出了一种策略,即引导问题解决和小组编程(GPGP),以克服这一差距。学生在班级内的同龄人小组中工作,以建立和实施他们的数学模型和解决方案,然后编写程序进行优化和评估。我们在第4年的电气工程课程中实施了该策略,该课程在整个学期中完成了GPGP四次。我们评估了学生在问题解决方面的表现,例如代表问题,制定解决方案,为拟议的解决方案辩护以及在整个学期监控和评估问题空间和解决方案,并发现了统计学上的显着改进。进一步的学生认为他们已经通过GPGP学习了解决工程问题的方法,并报告在课堂上喜欢这种策略。

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