Abstract
Education As science education moves toward more active classes, what can we learn about how student socialization affects learning? Zwolak et al. used social network analysis to investigate the academic and social experiences of students in an introductory Modeling Instruction (active learning) physics course. Students were asked to list the names of fellow students with whom they had a meaningful interaction five times throughout the semester. Using centralities, which are measures of position within the social network, intrapersonal interactions between students were quantified. Results showed that students with a higher centrality at the end of the semester were more likely to persist in physics (i.e., continue through the sequence of courses), suggesting that social integration may help in keeping students in science, technology, engineering, and math disciplines. Phys. Rev. Phys. Educ. Res. 10.1103/PhysRevPhysEducRes. 13.010113 (2017).
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