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From a middle school student’s perspective, the worst part about transferring schools is the need to make new friends. But is that the only negative impact of mobility on students? In this paper, we use a fixed effects linear least-squares statistical regression model to explore the relationship between student academic performance and student mobility in the Bethel School District in Eugene, Oregon. Our client, United Way of Lane County, has struggled with student mobility as the organization refines its new Promise Neighborhoods project, aimed at distressed neighborhoods in Lane County. Student mobility may limit United Way’s ability to improve the educational and developmental outcomes of students. We use voter registration data to estimate total mobility in Lane County and in the Promise Neighborhoods. We also use Bethel School District student transfer codes and statewide state test scores as data. Due to the structure of our data, we cannot draw a definitive conclusion regarding the direction of causality between mobility and learning. However, we can say with confidence that, at a minimum, there is a significant relationship between disruption to learning and high levels of mobility – a good starting point for United Way as they continue to explore mobility and refine their Promise Neighborhoods project.

Signaling for Attention: Mobility and Student Performance in United Way’s Promise Neighborhoods