Characterizing active learning environments in physics using network analysis and classroom observations

This study uses social network analysis and the classroom observation protocol for undergraduate STEM (COPUS) to characterize six research-based introductory physics curricula. Peer Instruction, Modeling Instruction, ISLE, SCALE-UP, Context-Rich Problems, and Tutorials in Introductory Physics were i...

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Autores principales:	Kelley Commeford, Eric Brewe, Adrienne Traxler
Formato:	article
Lenguaje:	EN
Publicado:	American Physical Society 2021
Materias:	Special aspects of education LC8-6691 Physics QC1-999
Acceso en línea:	https://doaj.org/article/2e03c7c8dd2c4a8184525f82a3234817
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spelling	oai:doaj.org-article:2e03c7c8dd2c4a8184525f82a32348172021-11-22T16:26:42ZCharacterizing active learning environments in physics using network analysis and classroom observations10.1103/PhysRevPhysEducRes.17.0201362469-9896https://doaj.org/article/2e03c7c8dd2c4a8184525f82a32348172021-11-01T00:00:00Zhttp://doi.org/10.1103/PhysRevPhysEducRes.17.020136http://doi.org/10.1103/PhysRevPhysEducRes.17.020136https://doaj.org/toc/2469-9896This study uses social network analysis and the classroom observation protocol for undergraduate STEM (COPUS) to characterize six research-based introductory physics curricula. Peer Instruction, Modeling Instruction, ISLE, SCALE-UP, Context-Rich Problems, and Tutorials in Introductory Physics were investigated. Students in each curriculum were given a survey at the beginning and end of term, asking them to self-identify peers with whom they had meaningful interactions in class. Every curriculum showed an increase in the average number of student connections from the beginning of term to the end of term, with the largest increase occurring in Modeling Instruction, SCALE-UP, and Context-Rich Problems. Modeling Instruction was the only curriculum with a drastic change in how tightly connected the student network was. Transitivity increased for all curricula except Peer Instruction. We also spent one week per research site in the middle of the term observing courses using COPUS. From these observations, the student COPUS profiles look nearly the same for Tutorials, ISLE recitations, and Context-Rich Problems discussion sections. This is likely due to the large resolution of activities that can be coded as “other group activity,” suggesting the need for a more detailed observation instrument.Kelley CommefordEric BreweAdrienne TraxlerAmerican Physical SocietyarticleSpecial aspects of educationLC8-6691PhysicsQC1-999ENPhysical Review Physics Education Research, Vol 17, Iss 2, p 020136 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Special aspects of education LC8-6691 Physics QC1-999
spellingShingle	Special aspects of education LC8-6691 Physics QC1-999 Kelley Commeford Eric Brewe Adrienne Traxler Characterizing active learning environments in physics using network analysis and classroom observations
description	This study uses social network analysis and the classroom observation protocol for undergraduate STEM (COPUS) to characterize six research-based introductory physics curricula. Peer Instruction, Modeling Instruction, ISLE, SCALE-UP, Context-Rich Problems, and Tutorials in Introductory Physics were investigated. Students in each curriculum were given a survey at the beginning and end of term, asking them to self-identify peers with whom they had meaningful interactions in class. Every curriculum showed an increase in the average number of student connections from the beginning of term to the end of term, with the largest increase occurring in Modeling Instruction, SCALE-UP, and Context-Rich Problems. Modeling Instruction was the only curriculum with a drastic change in how tightly connected the student network was. Transitivity increased for all curricula except Peer Instruction. We also spent one week per research site in the middle of the term observing courses using COPUS. From these observations, the student COPUS profiles look nearly the same for Tutorials, ISLE recitations, and Context-Rich Problems discussion sections. This is likely due to the large resolution of activities that can be coded as “other group activity,” suggesting the need for a more detailed observation instrument.
format	article
author	Kelley Commeford Eric Brewe Adrienne Traxler
author_facet	Kelley Commeford Eric Brewe Adrienne Traxler
author_sort	Kelley Commeford
title	Characterizing active learning environments in physics using network analysis and classroom observations
title_short	Characterizing active learning environments in physics using network analysis and classroom observations
title_full	Characterizing active learning environments in physics using network analysis and classroom observations
title_fullStr	Characterizing active learning environments in physics using network analysis and classroom observations
title_full_unstemmed	Characterizing active learning environments in physics using network analysis and classroom observations
title_sort	characterizing active learning environments in physics using network analysis and classroom observations
publisher	American Physical Society
publishDate	2021
url	https://doaj.org/article/2e03c7c8dd2c4a8184525f82a3234817
work_keys_str_mv	AT kelleycommeford characterizingactivelearningenvironmentsinphysicsusingnetworkanalysisandclassroomobservations AT ericbrewe characterizingactivelearningenvironmentsinphysicsusingnetworkanalysisandclassroomobservations AT adriennetraxler characterizingactivelearningenvironmentsinphysicsusingnetworkanalysisandclassroomobservations
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Characterizing active learning environments in physics using network analysis and classroom observations

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