Notional Machine in Mathematics and Introductory Computer Science Courses
Notional Machine in Mathematics and Introductory Computer Science Courses
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数学和计算机科学入门课程中的概念机
DOI：
10.1145/3545947.3576324
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Osera, Peter-Michael
中科院分区：
文献类型：
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作者：
Worden, Eamon;Song, Olivia;Osera, Peter-Michael
概念机器（NMs）是教师用来帮助学生理解某些概念的教学设备。虽然对国家机制进行了编目，但很少对国家机制的有效性进行评估。我们通过探索是什么使某些NM在各种计算机科学和数学课程中更有效，建立在这项研究的基础上。我们采访教授和学生，以评估在课堂上使用的NM。值得注意的是，我们发现，大多数学生都能够雇用他们的教授介绍的NM，和入门学生更喜欢模板样NM，而高层次的学生依赖于更多的概念NM。
Notional Machines (NMs) are a pedagogical device used by teachers in order to help students understand certain concepts. While NMs have been cataloged, the effectiveness of NMs has been rarely evaluated. We build upon this research by exploring what makes certain NMs more effective in various computer science and mathematics courses. We interview professors and students to assess NMs used in the classroom. Notably we found that most students are able to employ the NMs introduced by their professors, and that introductory students prefer template-like NMs, whereas upper level students rely on more conceptual NMs.