Network analysis of students’ conceptual understanding of mathematical expressions for probability in upper-division quantum mechanics

IF 4.7 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-07-15 DOI:10.1103/physrevphyseducres.20.020102
William D. Riihiluoma, Zeynep Topdemir, John R. Thompson
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Abstract

One expected outcome of physics instruction is for students to be capable of relating physical concepts to multiple mathematical representations. In quantum mechanics (QM), students are asked to work across multiple symbolic notations, including some they have not previously encountered. To investigate student understanding of the relationships between expressions used in these various notations, a survey was developed and distributed to students at six different institutions. All of the courses studied were structured as “spins-first,” in which the course begins with spin-1/2 systems and Dirac notation before transitioning to include continuous systems and wave function notation. Network analysis techniques such as community detection methods were used to investigate conceptual connections between commonly used expressions in upper-division QM courses. Our findings suggest that, for spins-first students, Dirac bras and kets share a stronger identity with vectorlike concepts than are associated with quantum state or wave function concepts. This work represents a novel way of using well-developed network analysis techniques and suggests such techniques could be used for other purposes as well. Published by the American Physical Society 2024

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学生对高年级量子力学概率数学表达式概念理解的网络分析
物理教学的一个预期结果是让学生能够将物理概念与多种数学表示法联系起来。在量子力学(QM)中,学生需要使用多种符号表示法,包括一些他们以前从未接触过的符号表示法。为了调查学生对这些不同符号表达式之间关系的理解,我们编制了一份调查表,并分发给六所不同院校的学生。所研究的所有课程都是 "自旋优先 "结构,即课程从自旋-1/2 系统和狄拉克符号开始,然后过渡到连续系统和波函数符号。网络分析技术(如群落检测方法)被用来研究高年级量子力学课程中常用表达式之间的概念联系。我们的研究结果表明,对于自旋第一的学生来说,与量子态或波函数概念相比,狄拉克布拉斯和凯特与矢量概念有更强的一致性。这项工作代表了一种使用成熟网络分析技术的新方法,并表明这种技术也可用于其他目的。 美国物理学会出版 2024
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊介绍: ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.
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