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Effects of student mobility — March 2017


What does the research say about the negative effects of student mobility?


Following an established REL West research protocol, we conducted a search for research reports as well as descriptive study articles on the negative effects of student mobility. The sources included ERIC and other federally funded databases and organizations, research institutions, academic research databases, and general Internet search engines. (For details, please see the methods section at the end of this memo.)

We have not evaluated the quality of references and the resources provided in this response. We offer them only for your reference. Also, we searched for references through the most commonly used sources of research, but the list is not comprehensive and other relevant references and resources may exist.

Research References

Blazer, C. (2009). The effect of poverty on student achievement. Miami, FL: Research Services, Miami-Dade County Public Schools. Retrieved from

From the abstract: “There is a strong relationship between students’ socioeconomic status and their levels of academic achievement. Although educators should be held accountable for improving the performance of all students, including those living in poverty, schools alone can’t eliminate the negative factors associated with poverty that lead to a large achievement gap between low income students and their more affluent peers. Factors that have a negative effect on poor students’ achievement but are beyond schools’ control include a higher incidence of prenatal adversity, illness and injury, exposure to pollutants, nutritional problems, residential mobility, and a lack of educational activities and materials in the home. This Information Capsule reviews studies conducted on the relationship between poverty and student achievement, including the effects of both individual poverty and school poverty concentration on academic performance. Research indicates that low income students tend to have significantly lower levels of academic achievement than their more affluent peers. The number of disadvantaged students attending a school also affects student performance: students at all income levels have been found to have lower levels of achievement when they attend schools with high poverty concentrations. Data collected within Miami-Dade County Public Schools confirmed that as poverty concentrations in the District’s schools increase, academic performance declines. Finally, strategies to help schools raise low income students’ achievement levels are summarized.”

Grigg, J. (2012). School enrollment changes and student achievement growth: A case study in educational disruption and continuity. Sociology of Education, 85(4), 388–404. Retrieved from

From the abstract: “Students in the United States change schools often, and frequent changes are associated with poor outcomes along numerous dimensions. These moves occur for many reasons, including both promotional transitions between educational levels and nonpromotional moves. Promotional student mobility is less likely than nonpromotional mobility to suffer from confounding due to unobserved factors. Using panel data from students enrolled in grades 3 to 8 in the Metropolitan Nashville Public Schools during the implementation of a major change in school attendance policies, this article investigates the potential influence of four types of school changes—including promotional student mobility—on test score growth in reading and mathematics. All types of changes are associated with lower achievement growth during the year the enrollment change occurred, representing approximately 6 percent of expected annual growth, or 10 days of instruction. This incremental deficit is particularly concerning for disadvantaged students since they change schools more frequently. The results suggest that being new to a school does influence student achievement net of other factors; they also imply that important social ties are ruptured when students change schools.”

Gruman, D. H., Harachi, T. W., Abbott, R. D., Catalano, R. F., & Fleming, C. B. (2008). Longitudinal effects of student mobility on three dimensions of elementary school engagement. Child Development, 79(6), 1833–1852. Retrieved from

From the abstract: “Working within the developmental science research framework, this study sought to capture a dynamic and complex view of student mobility. Second- through fifth-grade data (N = 1,003, predominantly Caucasian) were drawn from a longitudinal study, and growth curve analyses allowed for the examination of mobility effects within the context of other factors that put children at risk, including behavior problems and family stress. School changes predicted declines in academic performance and classroom participation but not positive attitude toward school. Time-varying factors such as peer acceptance and teacher support had a positive influence on the growth trajectories of child outcomes. Additionally, teacher support had a particularly strong influence on positive attitudes toward school among children who had more school changes.”

Isernhagen, J. C., & Bulkin, N. (2011). The impact of mobility on student performance and teacher practice. Journal of At-Risk Issues, 16(1), 17–24. Retrieved from

From the abstract: “This article examines the effects that high mobility can have on highly mobile students, non-mobile students, teachers, and schools, with particular focus on the effect of high mobility on academic achievement. A mixed-methods study with data collected from public schools in Nebraska during the 2007–2008 and 2008–2009 school years finds that highly mobile students scored lower on criterion-referenced assessments than their non-highly mobile peers. The article also provides recommendations of strategies that can be implemented to help address mobility-related issues based on data from qualitative interviews. These strategies are grouped into categories of transition programs, administrative procedures, classroom strategies, and support for teachers.”

McEachin, A., & Atteberry, A. (2015). Lost in transition: The impact of middle school transitions on student learning trajectories. Evanston, IL: Society for Research on Educational Effectiveness. Retrieved from

From the abstract: “The effect of student mobility on student outcomes has garnered much attention by researchers and policy-makers over the past few decades. The extant research relies on annual tests, typically measured each spring, to estimate the effect of structural moves on student achievement. The current literature does not allow researchers to evaluate whether the negative shock occurs at the start of the school year, or develops over time as students adjust to their new setting. Using a unique data set that includes both fall and spring test scores, McEachin and Atteberry evaluate whether students’ fall achievement before instruction occurs, is affected by the structural move, and whether students’ school-year achievement growth is affected as well. Preliminary results suggest that students experience a negative shock to achievement at the start of the year. These results have the potential to shed new light on the impact of structural transitions, and implications for policy and practice. While this preliminary work is suggestive that middle school transitions are hard on students—regardless of which grade level they experience them in, more nuanced modeling approaches will more formally compare the subsequent learning trajectories of pre-treatment similar students in relation to if and when they experience middle school transitions.”

Ou, S., & Reynolds, A. J. (2008). Predictors of educational attainment in the Chicago Longitudinal Study. School Psychology Quarterly, 23(2), 199–229. Retrieved from

From the abstract: “The authors investigated a comprehensive set of predictors of high school completion and years of completed education for youth in the Chicago Longitudinal Study, an ongoing investigation of over 1500 low-income, minority children who grew up on high-poverty neighborhoods. The study sample included 1286 youth for whom educational attainment could be determined by age 20. Predictors were measured from birth to high school from participant surveys and administrative records on educational and family experiences as well as demographic attributes. Results from regression analyses indicated that the model explained 30.4% of the variance in years of completed school. The model also predicted accurately 73.3% of youths’ observed high school completion status and 72.6% of their high school graduation status. The strongest predictors of educational attainment were maternal educational attainment, school absences and mobility, grade retention, and youth’s educational expectations. Findings indicate that students’ expectation and school mobility are targets of intervention that can promote children’s educational persistence.”

Rose, B. A. (2013). Examining variation in effects of student mobility using cross-classified, multiple membership modeling. Evanston, IL: Society for Research on Educational Effectiveness. Retrieved from

From the abstract: “Research on the effectiveness of educational interventions usually is based on samples of students who remain in the same school over time. In contrast, most students transfer schools at least once during their K–12 school career, not including normative transfers such as those from elementary to middle school (Rumberger, 2002). Even when looking at just the two years prior to the 1998 NAEP, one-third of fourth graders, 19 percent of eighth graders, and 10 percent of twelfth graders had changed schools at least once (Rumberger, 2002). Mobility is higher among low-income and minority populations (Rumberger, 2002). While many studies have investigated the relationship of student mobility with achievement (Alexander, Entwisle, & Dauber, 1996; Reynolds, Chen, & Herbers, 2009; Rumberger & Larson, 1998; Tucker, Marx, & Long, 1998), the degree to which this relationship might vary among schools has not been fully investigated; in other words, are some schools more effective with mobile students than others? Data for the current study were obtained from a prior study of student mobility in a mid-Atlantic state that took place in 2001–2003. (A full description is available in Rogers, 2004.) This study examined complete school history data from a statewide sample of students in order to investigate the relationship between mobility and reading achievement in the sixth year of schooling. Cross-classified, multiple membership models were used to accurately account for students’ membership in multiple schools during Year 6 as well as prior years. The relationship between mobility and reading scores was found to be non-significant on average, but examination of the variance components revealed that the impact of student mobility on reading achievement varied significantly among schools. Furthermore, the covariance estimate suggests that mobility gaps are especially large in schools with higher overall levels of achievement. This suggests that further research is necessary that more closely examines the contextual effects of mobility.”

Rumberger, R. W. (2015). Student mobility: Causes, consequences, and solutions. Boulder, CO: National Education Policy Center. Retrieved from

From the abstract: “Student mobility is a widespread and often unheralded problem facing American schools. The majority of elementary and secondary school children make at least one non-promotional school change over their educational careers, with many children making multiple moves. They do so for a variety of reasons. School changes are most often initiated by families and frequently involve a change of residences due to reasons that are either voluntary (for example, changing jobs or moving to a better home) or involuntary (for example, getting evicted or having a family disruption such as a divorce). But schools can also initiate school changes, such as when students are expelled or when schools are closed. The research literature suggests that changing schools can harm normal child and adolescent development by disrupting relationships with peers and teachers as well as altering a student’s educational program. The most consistent and severe impacts are on test scores and high school graduation, with less consistent findings on student behavior. The gravest harms follow from multiple moves and those accompanied by disruptions in the home. Because causes and consequences are varied and complex, recommendations for addressing the issue must be adaptable and applicable to the unique sets of circumstances. School procedures should focus on reducing unnecessary mobility and on making the mobility experience, when necessary, as positive as possible.”

Schafft, K. A. (2005). The incidence and impacts of student transiency in upstate New York’s rural school districts. Journal of Research in Rural Education, 20(15), 1–13. Retrieved from

From the abstract: “Chronic student mobility, and in particular the mobility of students from low-income backgrounds, poses a serious yet underdocumented problem for rural schools. This article combines analyses of state-level school district data with survey and interview data to examine the patterns of low-income student mobility in upstate New York, and to assess the impacts on, and responses by, schools and other community institutions. The incidence and effects of student mobility are particularly pronounced in smaller, limited-resource districts. School district administrators report significant negative consequences due to the fiscal and administrative costs associated with high-need, highly mobile students. Student transiency not only requires extra administrative resources from teachers, guidance counselors, and other school staff, but the unpredictability of the movement vastly complicates planning and budgeting processes. Results portray a significant, high-need segment of the upstate New York population that is largely unrecognized, untargeted, and both socially and academically at risk.”

Schwartz, A. E., Stiefel, L., & Cordes, S. A. (2015). Moving matters: The causal effect of moving schools on student performance (Working paper #01-15). New York, NY: Institute for Education And Social Policy. Retrieved from

From the abstract: “The majority of existing research on mobility indicates that students do worse in the year of a school move. This research, however, has been unsuccessful in isolating the causal effects of mobility and often fails to distinguish the heterogeneous impacts of moves, conflating structural moves (mandated by a school’s terminal grade) and non-structural moves (induced by residential mobility or by access to a better school) for example. Moreover, there is little evidence on the effects beyond the first year of a move. In this paper, we obtain credibly causal estimates of the impact of mobility on performance in both the short and long run, addressing heterogeneity in the impacts of mobility and the endogeneity of moving. We do so using richly detailed longitudinal data for five cohorts of New York City public school students making standard academic progress from grades 1–8. We estimate the impact of moving to a new school in a model with student fixed effects and two alternative sets of instrumental variables—the grade span of a student’s first grade school and foreclosure/building sale—to isolate the causal effect of mobility that is likely planned and mobility that is likely due to unanticipated shocks, respectively. We find negative short-term as well as long-term effects of the structural moves built into the school system. Non-structural moves, however, have a positive effect on academic performance if they are made to join a new school at the beginning of that school’s grade span and, thus, more likely made for strategic reasons. Robustness checks indicate results are not sensitive to inclusion of school quality measures, pre-move trends in mobility, or alternative samples. In the conclusions, we discuss the importance of findings on the heterogeneous impact of school moves to the literature and to policy makers.”

Voight, A., Shinn, M., & Nation, M. (2012). The longitudinal effects of residential mobility on the academic achievement of urban elementary and middle school students. Educational Researcher, 41(9), 385–392. Retrieved from

From the abstract: “Residential stability matters to a young person’s educational development, and the present housing crisis has disrupted the residential stability of many families. This study uses latent growth-curve modeling to examine how changing residences affects math and reading achievement from third through eighth grade among a sample of urban elementary and middle-school students. Results show that residential moves in the early elementary years have a negative effect on math and reading achievement in third grade and a negative effect on the trajectory of reading scores thereafter. Further, there is a negative contemporaneous effect of mobility on math scores in third through eighth grade but no such contemporaneous effect on reading scores. Implications for research and practice are discussed.”

Xu, Z., Hannaway, J., & D’Souza, S. (2009). Student transience in North Carolina: The effect of school mobility on student outcomes using longitudinal data. Washington, DC: National Center for Analysis of Longitudinal Data in Education Research. Retrieved from

From the abstract: “This paper describes the school mobility rates for elementary and middle school students in North Carolina and attempts to estimate the effect of school mobility on the performance of different groups of students using student fixed effects models. School mobility is defined as changing schools at times that are non-promotional (e.g., moving from middle to high school). We used detailed administrative data on North Carolina students and schools from 1997 to 2005 and followed four cohorts of 3rd graders for six years each. School mobility rates were highest for minority and disadvantaged students. School mobility rates for Hispanic students declined across successive cohorts, but increased for Black students. Findings on effects were most pronounced in math. School mobility hurt the math performance of Black and Hispanic students, but not the math performance of white students. School mobility improved the reading performance of white and more advantaged students, but had no effect on the reading performance of minority students. “Strategic” school moves (cross-district) benefitted or had no effect on student performance, but “reactive” moves (within district) hurt all groups of students. White and Hispanic students were more likely to move to a higher quality school while Blacks were more likely to move to a lower quality school. The negative effects of school mobility increased with the number of school moves.”

Other References

Bradbury, K., Burke, M. A., & Triest, R. K. (2014). Within-school spillover effects of foreclosures and student mobility on student academic performance (Working paper No. 15-6). Boston, MA: Federal Reserve Bank of Boston. Retrieved from

From the abstract: “Aside from effects on nearby property values, research is sparse on how foreclosures may generate negative externalities. Employing a unique dataset that matches individual student records from Boston Public Schools—including test scores, demographics, home address moves, and school changes—with real estate records indicating whether the student lived at an address involved in foreclosure, we investigate the degree to which the test scores of students attending high-foreclosure schools suffer, even among students not directly experiencing foreclosure. We also explore the impact on individual test scores of school-level (by grade and year) student mobility—that is, inflows of new students to a school during the school year—including mobility induced by residential moves (in some cases caused by foreclosures) and mobility arising for other reasons. We find fairly robust evidence that higher student mobility at a school, induced by residential moves, imposes significant negative effects on test scores of students at the receiving school. Beyond this channel, school-level foreclosure prevalence does not appear to generate externalities. Since we also find that residential-move-induced school changes appear to harm the outcomes of the school-changers themselves, policies that seek to limit such changes within the academic year may uniformly raise test scores, at least in the short run.”


Keywords and Search Strings

The following keywords and search strings were used to search the reference databases and other sources:

[“Negative effects” OR “effects”] AND [“student mobility” OR “mobile student”]

Databases and Resources

We searched ERIC for relevant resources. ERIC is a free online library of over 1.6 million citations of education research sponsored by the Institute of Education Sciences. Additionally, we searched Google Scholar and PsychInfo.

Reference Search and Selection Criteria

When we were searching and reviewing resources, we considered the following criteria:

  • Date of the Publication: References and resources published for the last 15 years, from 2002 to present, were included in the search and review.
  • Search Priorities of Reference Sources: Search priority is given to study reports, briefs, and other documents that are published and/or reviewed by IES and other federal or federally funded organizations and academic databases, including ERIC, EBSCO databases, JSTOR database, PsychInfo, PsychArticle, and Google Scholar.
  • Methodology: Following methodological priorities/considerations were given in the review and selection of the references: (a) study types – randomized controlled trials, quasi experiments, surveys, descriptive data analyses, literature reviews, policy briefs, etc., generally in this order; (b) target population, samples (representativeness of the target population, sample size, volunteered or randomly selected, etc.), study duration, etc.; and (c) limitations, generalizability of the findings and conclusions, etc.

This memorandum is one in a series of quick-turnaround responses to specific questions posed by educational stakeholders in the West Region (Arizona, California, Nevada, Utah), which is served by the Regional Educational Laboratory West at WestEd. This memorandum was prepared by REL West under a contract with the U.S. Department of Education’s Institute of Education Sciences (IES), Contract ED-IES-17-C-00014524, administered by WestEd. Its content does not necessarily reflect the views or policies of IES or the U.S. Department of Education nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.