Published, Version of Record (VoR)CC BY V4.0, Open
Abstract
Education & Educational Research Education, Scientific Disciplines Physics, Multidisciplinary Science & Technology Physical Sciences Physics Social Sciences
Collaborative learning environments in undergraduate introductory physics courses, such as those promoted by Modeling Instruction (MI), influence both student performance and student social interactions. Because collaborative learning is inherently a social activity, we applied Network Analysis methods to examine student social interactions within the classroom using a survey administered periodically in class. We then calculated centrality, which is a family of measures that quantify how connected or "central" a particular student is within the classroom social network. In order to understand what centrality means in this context, we investigated the relationships among centrality, student demographics, and student outcomes in a large-scale MI classroom with 70 students and 6 instructors. We addressed two research questions: "Is centrality predicted by sex, ethnicity, incoming GPA, or Force-Motion Concept Evaluation (FMCE) prescore?" and "Does centrality predict FMCE gain or final grade in course?" A series of linear regressions showed that centrality can be predicted by sex and incoming GPA, and is a predictor of FMCE gain.
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Details
Title
Understanding centrality: Investigating student outcomes within a classroom social network
Creators
Eric Williams - Florida International University
Eric Brewe - Florida International University
Justyna Zwolak - Florida International University
Remy Doti - Florida International University
Publication Details
2015 Physics Education Research Conference, pp 375-378
Conference
Physics Education Research Conference 2015 (College Park, Maryland, United States, 29 Jul 2015–30 Jul 2015)
Series
Physics Education Research Conference
Publisher
Amer Assoc Physics Teachers
Number of pages
4
Resource Type
Conference paper
Language
English
Academic Unit
Physics; School of Education
Web of Science ID
WOS:000375147300091
Other Identifier
9781931024280; 1931024286; 991021970299804721
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