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Physical Review Physics Education Research
written by Onofrio Rosario Battaglia, Benedetto Di Paola, and Claudio Fazio
[This paper is part of the Focused Collection on Quantitative Methods in PER: A Critical Examination.] A relevant aim of research in education is to find and study the reasoning lines that students deploy when dealing with problematic situations. This can be done through an analysis of the answers students give to a questionnaire. In this paper, we discuss some methodological aspects involved in the quantitative analysis of a questionnaire by means of two different clustering methods, a hierarchical one and a nonhierarchical one. We start from the coding procedures needed to obtain analyzable data from the questionnaire and from a definition of a correlation coefficient suitable for measuring student similarity in the case of binary coding of student answers. Then, criteria to choose the optimal number of clusters are discussed, and for the same purpose a new coefficient is introduced that measures the total amount of information we can obtain from a clustering solution. We show that each cluster can be characterized by its centroid that summarizes the answers most frequently given by the cluster students to the questionnaire. Finally, an example of the application of these procedures to a student sample is given, and a comparison between the two clustering methods is discussed.

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Physical Review Physics Education Research: Volume 15, Issue 2, Pages 020112
Subjects Levels Resource Types
Education Foundations
- Assessment
= Self Assessment
- Research Design & Methodology
= Data
= Statistics
Education Practices
- Active Learning
= Modeling
General Physics
- Physics Education Research
- Graduate/Professional
- Reference Material
= Research study
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Free access
License:
This material is released under a Creative Commons Attribution 4.0 license.
Rights Holder:
American Physical Society
DOI:
10.1103/PhysRevPhysEducRes.15.020112
Keywords:
cluster analysis, cluster analysis algorithms, cluster analysis research, hierarchical cluster analysis, non-hierarchical cluster analysis
Record Creator:
Metadata instance created August 23, 2019 by Sam McKagan
Record Updated:
March 1, 2023 by Caroline Hall
Last Update
when Cataloged:
July 3, 2019
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AIP Format
O. Battaglia, B. Di Paola, and C. Fazio, , Phys. Rev. Phys. Educ. Res. 15 (2), 020112 (2019), WWW Document, (https://doi.org/10.1103/PhysRevPhysEducRes.15.020112).
AJP/PRST-PER
O. Battaglia, B. Di Paola, and C. Fazio, Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples, Phys. Rev. Phys. Educ. Res. 15 (2), 020112 (2019), <https://doi.org/10.1103/PhysRevPhysEducRes.15.020112>.
APA Format
Battaglia, O., Di Paola, B., & Fazio, C. (2019, July 3). Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples. Phys. Rev. Phys. Educ. Res., 15(2), 020112. Retrieved May 6, 2024, from https://doi.org/10.1103/PhysRevPhysEducRes.15.020112
Chicago Format
Battaglia, O, B. Di Paola, and C. Fazio. "Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples." Phys. Rev. Phys. Educ. Res. 15, no. 2, (July 3, 2019): 020112, https://doi.org/10.1103/PhysRevPhysEducRes.15.020112 (accessed 6 May 2024).
MLA Format
Battaglia, Onofrio, Benedetto Di Paola, and Claudio Fazio. "Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples." Phys. Rev. Phys. Educ. Res. 15.2 (2019): 020112. 6 May 2024 <https://doi.org/10.1103/PhysRevPhysEducRes.15.020112>.
BibTeX Export Format
@article{ Author = "Onofrio Battaglia and Benedetto Di Paola and Claudio Fazio", Title = {Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples}, Journal = {Phys. Rev. Phys. Educ. Res.}, Volume = {15}, Number = {2}, Pages = {020112}, Month = {July}, Year = {2019} }
Refer Export Format

%A Onofrio Battaglia %A Benedetto Di Paola %A Claudio Fazio %T Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples %J Phys. Rev. Phys. Educ. Res. %V 15 %N 2 %D July 3, 2019 %P 020112 %U https://doi.org/10.1103/PhysRevPhysEducRes.15.020112 %O application/pdf

EndNote Export Format

%0 Journal Article %A Battaglia, Onofrio %A Di Paola, Benedetto %A Fazio, Claudio %D July 3, 2019 %T Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples %J Phys. Rev. Phys. Educ. Res. %V 15 %N 2 %P 020112 %8 July 3, 2019 %U https://doi.org/10.1103/PhysRevPhysEducRes.15.020112


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Unsupervised quantitative methods to analyze student reasoning lines: Theoretical aspects and examples:

Is Part Of Focused Collection of Physical Review PER: Quantitative Methods in PER: A Critical Examination

A link to the full collection in which this article appears: Quantitative Methods in PER: A Critical Examination

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