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Physical Review Physics Education Research
written by K. K. Mashood, Kamakshi Khosla, Arjun Prasad, V. Sasidevan, Muhammed Ashefas CH, Charles Jose, and Sanjay Chandrasekharan
Recent educational policies advocate a radical revision of science curricula and pedagogy, to support interdisciplinary practices, a distinguishing feature of contemporary science. Computational modeling (CM) is a core methodology of interdisciplinary science, as such models allow intertwining of data and theoretical perspectives from multiple domains, to address complex problems such as climate change and pandemics. This integrative nature of CM could support the pedagogical transition to interdisciplinary science as well. Most approaches to introduce CM in science curricula are based on learning new practices, such as VPython programming or agent-based modeling. These approaches do not integrate CM with existing content, media, and teaching practices. To facilitate this integration, we present a more gradualist design, starting from derivation models in physics. This design was implemented as a set of teacher professional development modules, and presented to a group of physics teachers interested in introducing CM to undergraduate students. The analysis of their responses indicates that even this gradual transition to CM requires teachers to significantly revise their ideas about the nature of physics and physics learning (their personal epistemologies). We discuss how the teacher professional development modules were redesigned based on this finding.
Physical Review Physics Education Research: Volume 18, Issue 2, Pages 020136
Subjects Levels Resource Types
Education - Applied Research
- Active Learning
= Modeling
- Instructional Material Design
- Pedagogy
= Multidisciplinary
- Professional Development
- Technology
General Physics
- Physics Education Research
Other Sciences
- Mathematics
- Professional Development
- Reference Material
= Research study
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This material is released under a Creative Commons Attribution 4.0 license.
Rights Holder:
American Physical Society
DOI:
10.1103/PhysRevPhysEducRes.18.020136
Keywords:
derivation models, epistemology, model building in derivations
Record Creator:
Metadata instance created November 28, 2022 by Lyle Barbato
Record Updated:
April 10, 2023 by Caroline Hall
Last Update
when Cataloged:
November 23, 2022
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AIP Format
K. Mashood, K. Khosla, A. Prasad, V. Sasidevan, M. Ashefas CH, C. Jose, and S. Chandrasekharan, , Phys. Rev. Phys. Educ. Res. 18 (2), 020136 (2022), WWW Document, (https://doi.org/10.1103/PhysRevPhysEducRes.18.020136).
AJP/PRST-PER
K. Mashood, K. Khosla, A. Prasad, V. Sasidevan, M. Ashefas CH, C. Jose, and S. Chandrasekharan, Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations, Phys. Rev. Phys. Educ. Res. 18 (2), 020136 (2022), <https://doi.org/10.1103/PhysRevPhysEducRes.18.020136>.
APA Format
Mashood, K., Khosla, K., Prasad, A., Sasidevan, V., Ashefas CH, M., Jose, C., & Chandrasekharan, S. (2022, November 23). Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations. Phys. Rev. Phys. Educ. Res., 18(2), 020136. Retrieved April 21, 2024, from https://doi.org/10.1103/PhysRevPhysEducRes.18.020136
Chicago Format
Mashood, K, K. Khosla, A. Prasad, V. Sasidevan, M. Ashefas CH, C. Jose, and S. Chandrasekharan. "Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations." Phys. Rev. Phys. Educ. Res. 18, no. 2, (November 23, 2022): 020136, https://doi.org/10.1103/PhysRevPhysEducRes.18.020136 (accessed 21 April 2024).
MLA Format
Mashood, K. K., Kamakshi Khosla, Arjun Prasad, V. Sasidevan, Muhammed Ashefas CH, Charles Jose, and Sanjay Chandrasekharan. "Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations." Phys. Rev. Phys. Educ. Res. 18.2 (2022): 020136. 21 Apr. 2024 <https://doi.org/10.1103/PhysRevPhysEducRes.18.020136>.
BibTeX Export Format
@article{ Author = "K. K. Mashood and Kamakshi Khosla and Arjun Prasad and V. Sasidevan and Muhammed Ashefas CH and Charles Jose and Sanjay Chandrasekharan", Title = {Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations}, Journal = {Phys. Rev. Phys. Educ. Res.}, Volume = {18}, Number = {2}, Pages = {020136}, Month = {November}, Year = {2022} }
Refer Export Format

%A K. K. Mashood %A Kamakshi Khosla %A Arjun Prasad %A V. Sasidevan %A Muhammed Ashefas CH %A Charles Jose %A Sanjay Chandrasekharan %T Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations %J Phys. Rev. Phys. Educ. Res. %V 18 %N 2 %D November 23, 2022 %P 020136 %U https://doi.org/10.1103/PhysRevPhysEducRes.18.020136 %O application/pdf

EndNote Export Format

%0 Journal Article %A Mashood, K. K. %A Khosla, Kamakshi %A Prasad, Arjun %A Sasidevan, V. %A Ashefas CH, Muhammed %A Jose, Charles %A Chandrasekharan, Sanjay %D November 23, 2022 %T Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations %J Phys. Rev. Phys. Educ. Res. %V 18 %N 2 %P 020136 %8 November 23, 2022 %U https://doi.org/10.1103/PhysRevPhysEducRes.18.020136


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