测量计算线性代数课程对学生在后续数值方法课程中的考试成绩的影响

Hongxuan Chen, Matthew West, S. Hilgenfeldt, Mariana Silva
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引用次数: 0

摘要

中西部一所大型公立大学开设了一门新的计算线性代数课程。这门新课程取代了传统线性代数课程的部分讲课时间,在翻转课堂的实验室环境中教授应用计算材料。我们比较了参加新计算课程和传统课程的学生在随后的数值方法课程中的考试成绩,同时控制了学生在先决计算机科学和数学课程中的表现。我们发现,对于数学背景较少的学生(即需要在大学学习微积分2的学生),学习新的计算线性代数课程对他们在后续课程中的平均考试成绩有显著的积极影响。具有更初级数学背景的学生(即已经获得微积分2学分的学生)的表现不受计算课程与传统课程背景的显著影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring the Impact of a Computational Linear Algebra Course on Students' Exam Performance in a Subsequent Numerical Methods Course
A new computational linear algebra course was developed and offered at a large public university in the Midwest. This new course traded off some of the lecture time in the pre-existing traditional linear algebra course for applied computational materials taught in a flipped-classroom lab setting. We compare exam performance in a subsequent numerical methods course from students having taken either the new computational or traditional course, while controlling for student performance in prerequisite computer science and mathematics courses. We find that for students with less mathematics background (i.e., those who needed to take Calculus 2 at the university), taking the new computational linear algebra course has significant positive impact on their average exam performance in the subsequent course. The performance of students with more initial mathematics background (i.e., those who already had credit for Calculus 2) is not significantly affected by the computational vs. traditional course backgrounds.
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