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Students' network integration as a predictor of persistence in introductory physics courses
Journal article   Open access   Peer reviewed

Students' network integration as a predictor of persistence in introductory physics courses

Justyna P. Zwolak, Remy Dou, Eric A. Williams and Eric Brewe
Physical review. Physics education research, v 13(1), p010113
10 Mar 2017
DOI: https://doi.org/10.1103/PhysRevPhysEducRes.13.010113
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1103/physrevphyseducres.13.010113View
Published, Version of Record (VoR)CC BY V4.0,  Open
url
https://doi.org/10.1103/PhysRevPhysEducRes.13.010113View
Published, Version of Record (VoR) Open

Abstract

Education & Educational Research Education, Scientific Disciplines Social Sciences
Increasing student retention (successfully finishing a particular course) and persistence (continuing through a sequence of courses or the major area of study) is currently a major challenge for universities. While students' academic and social integration into an institution seems to be vital for student retention, research into the effect of interpersonal interactions is rare. We use network analysis as an approach to investigate academic and social experiences of students in the classroom. In particular, centrality measures identify patterns of interaction that contribute to integration into the university. Using these measures, we analyze how position within a social network in a Modeling Instruction (MI) course-an introductory physics course that strongly emphasizes interactive learning-predicts their persistence in taking a subsequent physics course. Students with higher centrality at the end of the first semester of MI are more likely to enroll in a second semester of MI. Moreover, we found that chances of successfully predicting individual student's persistence based on centrality measures are fairly high-up to 75%, making the centrality a good predictor of persistence. These findings suggest that increasing student social integration may help in improving persistence in science, technology, engineering, and mathematics fields.

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19 Record Views
54 citations in Web of Science
52 citations in Scopus

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UN Sustainable Development Goals (SDGs)

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#4 Quality Education

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Collaboration types
Domestic collaboration
Web of Science research areas
Education & Educational Research
Education, Scientific Disciplines
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