Educational commitment and social networking: The power of informal networks

作     者：Justyna P. Zwolak Michael Zwolak Eric Brewe 

作者机构：Department of Teaching and Learning Florida International University Miami Florida 33199 USA Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA Center for Nanoscale Science and Technology National Institute of Standards and Technology Gaithersburg Maryland 20899 USA Drexel University Physics Department Philadelphia Pennsylvania 19104 USA Drexel University School of Education Philadelphia Pennsylvania 19104 USA 

出 版 物：《Physical Review Physics Education Research》 (Phys. Rev. Phys. Educ. Res.)

年 卷 期：2018年第14卷第1期

页      面：010131-010131页

核心收录：

基　　金：National Science Foundation, NSF Norsk Sykepleierforbund, NSF Division of Physics, PHY, (1344247) Division of Physics, PHY 

主　　题：Learning environment Network formation & growth 

摘      要：The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic and social integration has been long thought to be important for students’ persistence. Yet, it is rarely investigated. In particular, the relative impact of in-class and out-of-class interactions remains an open issue. Here, we demonstrate that, surprisingly, for students whose grades fall in the “middle of the pack, the out-of-class network is the most significant predictor of persistence. To do so, we use logistic regression combined with Akaike’s information criterion to assess in- and out-of-class networks, grades, and other factors. For students with grades at the very top (and bottom), final grade, unsurprisingly, is the best predictor of persistence—these students are likely already committed (or simply restricted from continuing) so they persist (or drop out). For intermediate grades, though, only out-of-class closeness—a measure of one’s immersion in the network—helps predict persistence. This does not negate the need for in-class ties. However, it suggests that, in this cohort, only students that get past the convenient in-class interactions and start forming strong bonds outside of class are or become committed to their studies. Since many students are lost through attrition, our results suggest practical routes for increasing students’ persistence in STEM majors.