Networks identify productive forum discussions

Discussion forums provide a channel for students to engage with peers and course material outside of class, accessible even to commuter and nontraditional populations. Forums can build classroom community and aid learning, but students do not always take up these tools. We use network analysis to co...

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Bibliographic Details
Main Authors: Adrienne Traxler, A. Gavrin, Rebecca Lindell
Format: Article
Language:English
Published: American Physical Society 2018-09-01
Series:Physical Review Physics Education Research
Online Access:http://doi.org/10.1103/PhysRevPhysEducRes.14.020107
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spelling doaj-c084fabe19f643d9acb853b384231c992020-11-24T23:10:34ZengAmerican Physical SocietyPhysical Review Physics Education Research2469-98962018-09-0114202010710.1103/PhysRevPhysEducRes.14.020107Networks identify productive forum discussionsAdrienne TraxlerA. GavrinRebecca LindellDiscussion forums provide a channel for students to engage with peers and course material outside of class, accessible even to commuter and nontraditional populations. Forums can build classroom community and aid learning, but students do not always take up these tools. We use network analysis to compare three semesters of forum logs from an introductory calculus-based physics course. The networks show dense structures of collaboration that differ significantly between semesters, even though aggregate participation statistics remain steady. After characterizing network structure for each semester, we correlate students’ centrality—a numeric measure of network position—with final course grade. Finally, we use a backbone extraction procedure to clean up “noise” in the network and clarify centrality-grade correlations. We find that more central network positions are positively linked with course success in the two semesters with denser forum networks. Centrality is a more reliable indicator of grade than non-network measures such as postcount. Backbone extraction destroys these correlations, suggesting that the noise is in fact signal and further analysis of the discussion transcripts is required.http://doi.org/10.1103/PhysRevPhysEducRes.14.020107
collection DOAJ
language English
format Article
sources DOAJ
author Adrienne Traxler
A. Gavrin
Rebecca Lindell
spellingShingle Adrienne Traxler
A. Gavrin
Rebecca Lindell
Networks identify productive forum discussions
Physical Review Physics Education Research
author_facet Adrienne Traxler
A. Gavrin
Rebecca Lindell
author_sort Adrienne Traxler
title Networks identify productive forum discussions
title_short Networks identify productive forum discussions
title_full Networks identify productive forum discussions
title_fullStr Networks identify productive forum discussions
title_full_unstemmed Networks identify productive forum discussions
title_sort networks identify productive forum discussions
publisher American Physical Society
series Physical Review Physics Education Research
issn 2469-9896
publishDate 2018-09-01
description Discussion forums provide a channel for students to engage with peers and course material outside of class, accessible even to commuter and nontraditional populations. Forums can build classroom community and aid learning, but students do not always take up these tools. We use network analysis to compare three semesters of forum logs from an introductory calculus-based physics course. The networks show dense structures of collaboration that differ significantly between semesters, even though aggregate participation statistics remain steady. After characterizing network structure for each semester, we correlate students’ centrality—a numeric measure of network position—with final course grade. Finally, we use a backbone extraction procedure to clean up “noise” in the network and clarify centrality-grade correlations. We find that more central network positions are positively linked with course success in the two semesters with denser forum networks. Centrality is a more reliable indicator of grade than non-network measures such as postcount. Backbone extraction destroys these correlations, suggesting that the noise is in fact signal and further analysis of the discussion transcripts is required.
url http://doi.org/10.1103/PhysRevPhysEducRes.14.020107
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