Understanding College Students’ Major Choices Using Social Network Analysis
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Concerns about the low completion rates in community colleges have led policy makers and administrators to examine interventions that aim to increase persistence and success by making colleges easier to navigate for students. One of the best supported and most well researched of the current reforms is guided pathways which aims to simplify student decision making. Meta majors, the grouping of all available majors into a handful of buckets, is an important components of these whole school reforms. In this paper I test an underlying assumption of this reform—that there are consistent groupings of majors that students would consider choosing—using tools from social network analysis. I draw on these consideration networks to examine how different groups of students cluster majors together; differences in how various groups of students group majors provides insight into how such interventions could increase efficiency or exacerbate inequality. These findings provide guidance for schools on what factors to consider when forming meta major groupings.
KeywordsCommunity colleges Success and persistence in higher education Decision making Social network analysis
I’d like to thank Sean Reardon, Eric Bettinger, Tom Dee, Michal Kurlaender, Davis Jenkins, Peter Crosta, and Eliza Evans for valuable feedback and advice at various stages of this Project. Funding for this Project came from Institute of Education Sciences Grant R305B090016, The Kimball Family Graduate Fellowship at Stanford University, and the Jack Kent Cooke Foundation.
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