In order to join virtual sessions, you must be registered and logged-in(Were you registered for the in-person meeting in Denver? if yes, just log in.) 
Note: All session times are in Mountain Daylight Time.

Student Mobility: Patterns, Predictors, and Consequences

Authors: Katharine Bao*,
Topics: Social Geography, Urban Geography, Spatial Analysis & Modeling
Keywords: student mobility; network; gravity model; education
Session Type: Paper
Presentation File: No File Uploaded


Nearly one-half of all students make a non-structural change in the school they attend between kindergarten and third grade, and by the eighth grade more than 62 percent have changed schools at least once (Burkam, Lee, and Dwyer, 2009). Students in large, urban school districts are even more likely to move than students in rural settings, making student mobility particularly important for metropolitan districts. Mobile students make it more difficult for schools and districts to enact effective and transformative policies and programs to improve student learning. We investigate the pattern of student mobility in the Houston region using 5-year Texas public school data. To explore communities where schools are tied together by student mobility, we then use network analysis to identify 6 sub-regions/markets. We found that, while those networks are not necessarily bounded by school district, they show strong cluster pattern spatially and serve demographically and academically distinct sets of students. We also examine a series of factors at the student, school, and neighborhood level associated with mobility and the consequences of mobility.



To access contact information login