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Physical Review Physics Education Research
written by Benjamin P. Schermerhorn, Gina Passante, Homeyra R. Sadaghiani, and Steven J. Pollock
Undergraduate quantum mechanics (QM) uses a variety of notations, each with their own advantages and constraints, for representing quantum states and carrying out individual calculations. An example of this can be seen when calculating expectation values, which can be solved using several different methods. Analysis of written exam data given at three universities (teaching spins-first QM) showed students were more likely to use matrix or integral calculation in situations where it is much simpler to use a summation method. By adapting the structural features framework by Gire and Price, we are able to answer questions regarding how and why students use different methods. We analyze student responses to expectation value problems administered in interviews conducted at two universities in the middle and end of the semester to highlight specific areas of difficulty and features of the methods which led to students' choices of one method over another.
Physical Review Physics Education Research: Volume 15, Issue 2, Pages 020144
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Access Rights:
Free access
License:
This material is released under a Creative Commons Attribution 4.0 license.
Rights Holder:
American Physical Society
DOI:
10.1103/PhysRevPhysEducRes.15.020144
NSF Numbers:
DUE-1626280
DUE-1626594
DUE-1626482
Keywords:
Expectancy Value Theory, QM computation, quantum mechanics computation, structural features framework
Record Creator:
Metadata instance created June 15, 2020 by Lyle Barbato
Record Updated:
January 31, 2023 by Caroline Hall
Last Update
when Cataloged:
November 26, 2019
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AIP Format
B. Schermerhorn, G. Passante, H. Sadaghiani, and S. Pollock, , Phys. Rev. Phys. Educ. Res. 15 (2), 020144 (2019), WWW Document, (https://doi.org/10.1103/PhysRevPhysEducRes.15.020144).
AJP/PRST-PER
B. Schermerhorn, G. Passante, H. Sadaghiani, and S. Pollock, Exploring student preferences when calculating expectation values using a computational features framework, Phys. Rev. Phys. Educ. Res. 15 (2), 020144 (2019), <https://doi.org/10.1103/PhysRevPhysEducRes.15.020144>.
APA Format
Schermerhorn, B., Passante, G., Sadaghiani, H., & Pollock, S. (2019, November 26). Exploring student preferences when calculating expectation values using a computational features framework. Phys. Rev. Phys. Educ. Res., 15(2), 020144. Retrieved July 15, 2024, from https://doi.org/10.1103/PhysRevPhysEducRes.15.020144
Chicago Format
Schermerhorn, B, G. Passante, H. Sadaghiani, and S. Pollock. "Exploring student preferences when calculating expectation values using a computational features framework." Phys. Rev. Phys. Educ. Res. 15, no. 2, (November 26, 2019): 020144, https://doi.org/10.1103/PhysRevPhysEducRes.15.020144 (accessed 15 July 2024).
MLA Format
Schermerhorn, Benjamin P., Gina Passante, Homeyra Sadaghiani, and Steven Pollock. "Exploring student preferences when calculating expectation values using a computational features framework." Phys. Rev. Phys. Educ. Res. 15.2 (2019): 020144. 15 July 2024 <https://doi.org/10.1103/PhysRevPhysEducRes.15.020144>.
BibTeX Export Format
@article{ Author = "Benjamin P. Schermerhorn and Gina Passante and Homeyra Sadaghiani and Steven Pollock", Title = {Exploring student preferences when calculating expectation values using a computational features framework}, Journal = {Phys. Rev. Phys. Educ. Res.}, Volume = {15}, Number = {2}, Pages = {020144}, Month = {November}, Year = {2019} }
Refer Export Format

%A Benjamin P. Schermerhorn %A Gina Passante %A Homeyra Sadaghiani %A Steven Pollock %T Exploring student preferences when calculating expectation values using a computational features framework %J Phys. Rev. Phys. Educ. Res. %V 15 %N 2 %D November 26, 2019 %P 020144 %U https://doi.org/10.1103/PhysRevPhysEducRes.15.020144 %O application/pdf

EndNote Export Format

%0 Journal Article %A Schermerhorn, Benjamin P. %A Passante, Gina %A Sadaghiani, Homeyra %A Pollock, Steven %D November 26, 2019 %T Exploring student preferences when calculating expectation values using a computational features framework %J Phys. Rev. Phys. Educ. Res. %V 15 %N 2 %P 020144 %8 November 26, 2019 %U https://doi.org/10.1103/PhysRevPhysEducRes.15.020144


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