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Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics
Research characterizing common student ideas about particular physics topics has significantly impacted university-level physics teaching by providing knowledge that supports instructors to target their instruction and by informing curriculum development. In this work, we utilize a Natural Language Processing algorithm (Latent Dirichlet Allocation, or LDA) to identify distinct student ideas in a set of written responses to a conceptual physics question, with the goal of significantly expediting the process of characterizing student ideas. We preliminarily test the LDA approach by applying the algorithm to a collection of introductory physics student responses to a conceptual question about circuits, specifically attending to whether it is useful for characterizing instructionally-relevant student ideas. We find that for a large enough collection of student responses (N ? 500), LDA can be useful for characterizing the ideas students used to answer conceptual physics questions. We discuss some considerations that researchers may take into account as they interpret the results of the LDA algorithm for characterizing student's physics ideas.
Physics Education Research Conference 2022
Part of the PER Conference series Grand Rapids, MI: July 13-14, 2022 Pages 206-211
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Record Link
<a href="https://www.per-central.org/items/detail.cfm?ID=16233">Geiger, J, L. Goodhew, and T. Odden. "Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics." Paper presented at the Physics Education Research Conference 2022, Grand Rapids, MI, July 13-14, 2022.</a>
AIP Format
J. Geiger, L. Goodhew, and T. Odden, , presented at the Physics Education Research Conference 2022, Grand Rapids, MI, 2022, WWW Document, (https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602).
AJP/PRST-PER
J. Geiger, L. Goodhew, and T. Odden, Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics, presented at the Physics Education Research Conference 2022, Grand Rapids, MI, 2022, <https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602>.
APA Format
Geiger, J., Goodhew, L., & Odden, T. (2022, July 13-14). Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics. Paper presented at Physics Education Research Conference 2022, Grand Rapids, MI. Retrieved January 16, 2025, from https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602
Chicago Format
Geiger, J, L. Goodhew, and T. Odden. "Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics." Paper presented at the Physics Education Research Conference 2022, Grand Rapids, MI, July 13-14, 2022. https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602 (accessed 16 January 2025).
MLA Format
Geiger, Jon M., Lisa M. Goodhew, and Tor Ole B. Odden. "Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics." Physics Education Research Conference 2022. Grand Rapids, MI: 2022. 206-211 of PER Conference. 16 Jan. 2025 <https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602>.
BibTeX Export Format
@inproceedings{
Author = "Jon M. Geiger and Lisa M. Goodhew and Tor Ole B. Odden",
Title = {Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics},
BookTitle = {Physics Education Research Conference 2022},
Pages = {206-211},
Address = {Grand Rapids, MI},
Series = {PER Conference},
Month = {July 13-14},
Year = {2022}
}
Refer Export Format
%A Jon M. Geiger %A Lisa M. Goodhew %A Tor Ole B. Odden %T Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics %S PER Conference %D July 13-14 2022 %P 206-211 %C Grand Rapids, MI %U https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602 %O Physics Education Research Conference 2022 %O July 13-14 %O application/pdf
EndNote Export Format
%0 Conference Proceedings %A Geiger, Jon M. %A Goodhew, Lisa M. %A Odden, Tor Ole B. %D July 13-14 2022 %T Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics %B Physics Education Research Conference 2022 %C Grand Rapids, MI %P 206-211 %S PER Conference %8 July 13-14 %U https://www.compadre.org/Repository/document/ServeFile.cfm?ID=16233&DocID=5602 Disclaimer: ComPADRE offers citation styles as a guide only. We cannot offer interpretations about citations as this is an automated procedure. Please refer to the style manuals in the Citation Source Information area for clarifications.
Citation Source Information
The AIP Style presented is based on information from the AIP Style Manual. The AJP/PRST-PER presented is based on the AIP Style with the addition of journal article titles and conference proceeding article titles. The APA Style presented is based on information from APA Style.org: Electronic References. The Chicago Style presented is based on information from Examples of Chicago-Style Documentation. The MLA Style presented is based on information from the MLA FAQ. Developing a natural language processing approach for analyzing student ideas in calculus-based introductory physics:Know of another related resource? Login to relate this resource to it. |
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