Residential Mobility Research Brief
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Perfect Strangers: Residential Mobility and Educational and
Behavioral Outcomes in Metro Nashville Public Schools
Adam Voight, Maury Nation, and Beth Shinn
“Home is where one starts from.”
– T.S. Eliot
The focus of this research brief is the residential mobility of students in Metro-Nashville Public Schools (MNPS)
middle schools. The purpose is to provide a summary of key findings from survey research conducted collaboratively by
Metro-Nashville Public Schools and Peabody College of Vanderbilt University. The research demonstrates the
deleterious effect that residential mobility has on the educational and behavioral outcomes of students who experience the
instability as well as the negative effect that aggregate mobility at the school level has on students in the school.
Housing issues have taken on greater significance in light of the recent economic recession and
foreclosure crisis. In the Nashville Metropolitan area, the past five years have seen higher home
vacancy and mobility rates, alongside larger average household sizes1. Housing instability has been
connected to a variety of negative outcomes for homeowners and communities, but it may have
particularly harmful effects on children and their educational experience, especially when it is
associated with a change of schools. The adjustment that is required in moving homes during
childhood and adolescence can create a stressful home environment that negatively impacts
children’s education and early life outcomes. Children who change schools may miss key educational
material, hampering their school performance. Further, children and parents who relocate must
often develop new social networks and thus may not be privy to important information related to
school success. Also, children attending a new school may feel socially marginalized, potentially
leading to problem behavior and disengagement from school. Residential mobility is not frequently
considered among the range of issues with which school must cope, but there are steps that schools
can take to engage this risk factor. This report uses data from 11 MNPS middle schools and
summarizes key findings related to residential mobility and student educational outcomes. Middle
school is a period during which youth may be particularly vulnerable to residential instability due to
their rapid social development. This report first describes the scope of residential mobility among
middle school students; it then examines the relationship between mobility and educational
outcomes; finally, it suggests possible avenues for schools to address problems associated with
mobility.
2. The Landscape of Residential Mobility in MNPS Middle Schools2
According to the U.S. Census, 18.2% of the population in the Nashville metropolitan area reported
in 2008 that they had changed their primary residence during the preceding year. Compared to the
national mobility rate of 15.0%, Nashville has a relatively high incidence of residential mobility1. This
citywide trend of high mobility is reflected in the mobility rates of MNPS middle school students3.
As Figure 2.1 shows, less than 25% of MNPS middle school students live at the same address
continuously over a six year period. Almost 70% of middle school students move between one and
three times during the same period. A smaller number, approximately 10%, are highly mobile,
moving residences four or more times in six years. Moving homes is not an uncommon experience
for students in MNPS middle schools.
20
15
10
5
0
Percent of students
25
Residential Mobility Research Brief
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0
1
2
3
4
5
6
Residential moves over six years (2003-2009)
Figure 2.1 – Number of residential moves over six years (2003-2009) for MNPS middle school students
Overall, on average MNPS middle school students moved almost two times in six years. This
number varies according to students’ backgrounds. Is this experience of relocation equal for all
students, or is it associated more strongly with students of different backgrounds? Students who are
eligible for the free and reduced lunch program (FRPL)—which is often considered a proxy for
socioeconomic status (SES)—have moved almost twice as frequently compared to students who are
not eligible, as shown in Table 2.1. Further, Black students are the most frequent movers of any
racial group, followed by Latino/a students and White students, respectively. These patterns are
consistent with national trends4.
Table 2.1 – Average number of residential moves over six years (2003-2009), by race and socioeconomic status
Student characteristics
Average number of
moves
Eligible for free/reduced lunch
Not eligible for free/reduced lunch
1.89
1.09
Black
Latino/a
White
2.00
1.70
1.36
Total
1.71
Below, Figure 2.2 depicts the interaction of race and socioeconomic status, showing that low-SES
Black students moved over twice as often as high-SES White students. MNPS middle school
students of all backgrounds experience residential mobility to some degree, but Black, Latino/a, and
low-SES students appear to be more frequent movers.
2
1
High SES
te
W
hi
o/
a
La
t in
ac
k
Bl
ia
n
As
te
W
hi
o/
a
La
t in
Bl
As
ia
n
ac
k
0
Average number of moves
3
Residential Mobility Research Brief
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Low SES
Figure 2.2 – Average number of residential moves over six years (2003-2009), by race and socioeconomic status
Figure 2.3 offers an alternative way of understanding differences in mobility by race. Breaking down
the frequency of mobility into three different categories—no moves, one to three moves, and more
than three moves—shows that 80% of Black middle school students in MNPS move at least once
over six years, with 40% experiencing extreme mobility, over three moves. By comparison, a third of
White students stay in the same home during the six-year period, while fewer than a quarter are
extremely mobile.
Asian
Black
12%
16%
25%
40%
44%
63%
Latino/a
27%
20%
White
21%
33%
53%
No moves
More than three moves
46%
One to three moves
Figure 2.3 – Residential mobility over six years (2003-2009), by race
Residential Mobility Research Brief
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3. The Relationship between Residential Mobility and Educational Success
Residential mobility is important because it has been associated with a variety of relevant outcomes
for cities, neighborhoods, homeowners, and children. Families move for many reasons, and the data
examined here do not distinguish a residential move made for positive reasons versus one made
under duress. However, a substantial body of research has demonstrated that residential moves,
made for any reason, may have a negative effect on students’ achievement, aptitude, and retention5.
Table 3.1 shows that MNPS middle school students with moderate and extreme levels of mobility
score lower on achievement tests of math and reading and have more absences and disciplinary
referrals.
Table 3.1 – Average educational and behavioral outcomes by residential mobility category
Number of moves
0
1-3
>3
Math
TCAP
Reading
TCAP
Absences
Disciplinary
referrals
48
42
38
47
42
37
6.4
6.8
9.4
1.5
1.9
2.8
Notes: (1) TCAP scores are reported in Normal Curve Equivalent scores; (2) absences are combined
excused and unexcused absences
30
40
50
There is an average ten-point difference in terms of Normal Curve Equivalent6 (NCE) scores in the
Math and Reading TCAP between students who have not moved at all during a six-year period
compared to those who are highly mobile. Figures 3.1 and 3.2 graphically depict the changes in math
and reading scores, respectively, by race and socioeconomic status as residential mobility increases.
0
1
2
3+
Residential moves over six years (2003-2009)
All students
Black
Low SES
Latino/a
Figure 3.1 – Math TCAP scores (in NCEs) and number of residential moves over six years (2003-2009), by race
and socioeconomic status
Residential Mobility Research Brief
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30
40
50
Regression analyses confirm that the decrease in Math and Reading TCAP scores associated with
more residential moves, shown in Figures 3.1 and 3.2, is statistically significant, even when race and
socioeconomic status are taken into consideration7. These analyses suggest that for the entire
population of middle school students in MNPS, race and socioeconomic status being equal, one
could expect highly mobile students to score almost three NCE points lower on their Reading and
Math TCAP compared to residentially stable students, with roughly two and half additional absences
during the academic year and almost one additional disciplinary referral. Highly mobile students
demonstrate poorer educational outcomes.
0
1
2
3+
Residential moves over six years (2003-2009)
All students
Black
Low SES
Latino/a
Figure 3.2 – Reading TCAP scores (in NCEs) and number of residential moves over six years (2003-2009), by
race and socioeconomic status
4. Schools with Highly Mobile Students
There are certain consequences for students who change residences, but there may be additional
consequences for students who attend schools with high overall rates of mobility. That is, even if a
student does not move herself, her educational outcomes may be affected by a school peer group
that is highly mobile. A school with a large number of highly mobile students deals with significant
academic and environmental challenges. A high turnover of students often leads to disruption of
class curricula as teachers backtrack to accommodate the content knowledge of new students.
Further, social relationships among students and between students and teachers are complicated by a
changing enrollment8. Perhaps most fundamentally, serial residential mobility in childhood can limit
the social capital to which a student has access, as her relationships with the community and school
are often interrupted9. Highly mobile students may lack social support and suffer from lowered selfconcepts10.
The average number of moves that students experience varies across schools, and these averages are
shown below in Table 4.1 for all 11 of the middle schools included in this report. The overall
student mobility average for all of the schools in the data is 1.74 moves. The average number of
moves ranges from a low of 1.24 in West End Middle School to a high of 2.12 in W.A. Bass Middle
School. What are the implications of student body mobility on the educational outcomes of students
in these schools?
Table 4.1 – Residential moves per student over six years (2003-2009), by school
School
Average moves
per student
Apollo M.S.
Bailey M.S.
Bellevue M.S.
Cameron M.S.
Donelson M.S.
Ewing Park M.S.
Jere Baxter M.S.
McMurray M.S.
Neely’s Bend M.S.
W.A. Bass M.S.
West End M.S.
1.64
2.00
1.38
1.65
1.73
1.87
1.90
1.76
1.81
2.12
1.24
40
50
60
Figure 4.1, below, is similar to the figures in the above section that depict the relationship between
residential mobility and academic achievement by race and socioeconomic status. The difference
here is that instead of modeling individual student mobility on the horizontal axis, school-average
mobility is shown. That is, moving from left to right on the horizontal axis indicates an increase in
average student mobility at the school level. Using the school average from Table 4.1, for example,
West End Middle School would be located at the far left end of the horizontal axis (with an average
student mobility of 1.24) and W.A. Bass Middle School would be at the far right end (with an
average student mobility of 2.12).
30
Math TCAP score (2009)
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1.2
1.4
1.6
1.8
2.0
Average number of moves of students in school
All students
Black
Low SES
Latino/a
Figure 4.1 – School-average reading TCAP scores (in NCEs) and school-average residential moves over six
years (2003-2009), by race and socioeconomic status
Residential Mobility Research Brief
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6
5
4
Absences (2009)
7
Figure 4.1 shows that schools with more mobile students have lower average Math TCAP scores.
Multilevel regression analyses confirm that this relationship is statistically significant, even when
controlling for school demographics and quality11. Regression analyses also show that school-average
residential mobility is significantly associated with a greater number of absences and a decreased
overall perception of school climate. The relationship between school-average residential mobility
and absence is depicted in Figure 4.2. Students in schools with very low average levels of mobility—
such as West End Middle School—miss an average of four days per academic year. Students in
schools with high average mobility—such as W.A Bass Middle School—are absent an average of
seven days per year.
1.2
1.4
1.6
1.8
2.0
Average number of moves of students in school
Figure 4.2 – School-average absences and school-average residential moves over six years (2003-2009), by race
and socioeconomic status
The relationship between school-average residential mobility and school climate is worth particular
mention. School climate is often measured by averaging individuals’ perceptions of some
characteristic of the school—in this case, the relationships among students. In Section 3, above,
there was no significant relationship found between a student’s personal experience of mobility and
that student’s perceptions of school climate. That is to say, moving frequently does not impact one’s
feelings about the school. However, in the regression models used to examine mobility at the school
level, a significant relationship was found between school-average mobility and school-average
perceptions of school climate. In other words, a school with a large number of highly mobile
students is more likely to have low climate, but these low climate perceptions are not being driven
by the students who move frequently. The results suggest that it is the more stable students in the
school whose perceptions of school climate are damaged by a large proportion of highly mobile
peers.
The relationship between school-average residential mobility and school climate is shown graphically
below in Figure 4.3. The difference in school climate between a school with extremely low average
mobility and a school with extremely high average mobility is .25. School climate was measured
using a scale of 1 to 5 that asked students to agree or disagreement with statements about the nature
Residential Mobility Research Brief
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3.4
of relationships among students at their school. The standard deviation between schools is .14, thus
a difference of .25 is very powerful. School-average residential mobility is strongly related to school
climate.
Cameron
Apollo
3.2
West End Bellevue
3.1
Neeley's Bend
Bass
3
Donelson
Ewing Park
Bailey
2.9
School climate
3.3
McMurray
Jere Baxter
1.2
1.4
1.6
1.8
2
2.2
Average residential moves of students in school
Figure 4.3 – School-average residential mobility and school climate in 11 MNPS middle schools
The empirical findings from Sections 3 and 4 provide compelling evidence that residential mobility
is an important factor in the educational experience of MNPS middle school students. Individual
students who move frequently are subject to lower academic achievement, more absences, and more
disciplinary problems. Additionally, schools with many highly mobile students suffer from poorer
overall achievement, lower attendance, and inferior school climate.
5. Program and Policy Implications for Schools
Urban school districts are already greatly overburdened with the task of helping their students to be
successful. School decision-makers may look at residential mobility as a phenomenon that is outside
of their school walls and thus out of their control. To a degree, this sentiment is valid. However,
there are real steps that schools can take to address issues related to residential mobility among their
students. The following recommendations are drawn from the research literature on residential
mobility and offer concrete strategies for schools12.
Strategies for individual schools:
• Provide educational supports for mobile students, such as tutoring, afterschool programs, summer
programs, and transportation within high mobility zones.
• Provide supplementary non-academic resources for mobile students, such as individual and group
counseling and other student services, nutrition programs, and recreational opportunities.
• Reduce risk and stress by making efforts to reduce student and teacher turnover, teaching stress
management skills, and providing crisis services, such as transition planning.
• Support mobile students’ parents in developing parenting skills, fostering bonds with other
competent and caring adults, and fostering school engagement.
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Strategies for the school district:
• Improve accessibility and transferability of records to ease the transition of students from one
school to another.
• Increase the stability of key aspects of academic curricula across schools in the district.
Most simply, the knowledge that residential mobility is a risk factor for lower achievement, lower
attendance, and higher problem behavior can help to understand the needs of the student body.
This report concludes that residential mobility is an issue that should be taken seriously in MNPS
middle schools. By identifying these students and targeting them for additional resources, schools
may have the ability to overcome the challenges associated with residential mobility.
Who are the truly at-risk students?
Table 3.1, above, showed that students who are highly mobile—that is, students who have more
than three residential moves over a seven-year period—score ten NCE points lower on the Math
and Reading TCAP than students experience no moves, and they have more absences and
disciplinary referrals. These students should be a priority for schools when they determine who to
target for the aforementioned interventions. However, over 16% of the MNPS middle school
population has moved more than three times, and given the finite resources with which schools
work, it may be difficult (if not unrealistic) to follow the abovementioned strategies for such a large
proportion of the student body.
A profile for students who are extraordinarily at-risk due to residential mobility can be illustrated by
analyzing data only for students who are highly mobile. Among the highly mobile group of students,
significant gaps in outcomes are evident for the following groups:
Table 5.1 – Group differences in educational and behavioral outcomes among highly mobile students
Groups
Math
TCAP
Reading
TCAP
Absences
Black v. non-Black
FRPL v. non-FRPL
ELL v. non-ELL
SPED v. non-SPED
-9.5
-13.2
-15.8
-15.6
-8.3
-12.7
-22.2
-12.2
-1.4
3.6
-2.8
5.2
Disciplinary
referrals
1.9
1.1*
-0.4*
2.2
Notes: (1) TCAP scores are reported in Normal Curve Equivalent scores; (2) absences are combined
excused and unexcused absences; (3) * = non-significant differences, statistically; (4) differences in gender
and grade level did not predict significant outcome gaps
Table 5.1 shows that among the highly mobile population of MNPS students being Black and
eligible for the free/reduced priced lunch program, English language learned services, and special
education services all serve as “double” risk factors for highly mobile students. Students eligible for
special education services have more absences and disciplinary referrals than their peers, as well,
among this highly mobile subgroup. These differences in educational and behavioral outcomes by
group are indeed evident in the full population of students, not just the highly mobile subgroup.
Nevertheless, looking at factors that compound the potentially harmful effects of residential
mobility may help direct scarce resources to those most in need. For example, only 2% of students
are both highly mobile and eligible for special education services. This is a much more manageable
Residential Mobility Research Brief
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proportion of students to target for supplemental services than the 16% of the student population
that is highly mobile.
Table 5.2 – Proportion of MNPS middle school students
Student characteristics
Highly mobile
Highly mobile and Black
Highly mobile and FRPL
Highly mobile and ELL
Highly mobile and SPED
Percentage
of students
16.1
9.2
14.8
1.9
1.8
Table 5.2 shows the percentage of middle school students in MNPS who are highly mobile and
members of a second at-risk group. For schools looking for a place to start addressing the issue of
residential mobility among their students, students who are eligible for English language learner and
special education services may be a manageable subpopulation with which to begin. Schools with a
broader approach to targeting at-risk students with supplemental services may consider including all
highly mobile students among their service groups.
U.S. Census Bureau. (2008). Selected social characteristics in the United States: 2008. 2008 American Community Survey.
Retrieved July 25, 2010 from http://factfinder.census.gov.
1
The data used for this report is drawn from a sample of approximately 5,000 students in 11 middle schools in MNPS.
These 11 schools were selected due to their high incidences of “indirect assaults” (i.e., behavior that can be characterized
as disrespectful, noncompliant, disruptive, threatening/intimidating, use of profanity, displaying gang signs, and repeated
rules violation). The descriptive and inferential statistics presented herein are based on these 11 schools and may not be
wholly representative of all 37 middle schools in the district.
2
A residential mobility index was created to make mobility between students comparable. MNPS records indicate, on an
annual basis, whether or not a student’s home address remains the same from the previous year. If it does not, the
student is said to have had a change of address from the previous year, but there is no indication of whether the student
experienced multiple changes of address within any given year. There are six years of data collection and therefore six is
the maximum number of moves that any one student may have in the data. Because of this, the mobility index artificially
deflates the true overall rate of student mobility. Further, because some students have been in the sample for the full six
years of data collection while others (for example: fifth-graders or students who transfer into MNPS from an outside
district) have not, the total residential moves that the student has experienced while in MNPS is divided by the number
of years that they have been a student in MNPS and then multiplied by six:
3
Mobility Index = (Total moves while in MNPS / Number of years in MNPS) x 6
This index acts as an estimate for the number of residential moves that the student would have on record had they been
in MNPS for the full six years of data collection, 2003 to 2009.
Burkam, D., Lee, V., & Dwyer, J. (2009, June 29). School mobility in the early elementary grades: Frequency and impact from
nationally representative data. Presented at the Workshop on the Impact of Mobility and Change on the Lives of Young
Children, Schools, and Neighborhoods, Washington, D.C.
4
Residential Mobility Research Brief
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Astone, N. M., & McLanahan, S. S. (1994). Family structure, residential mobility, and school dropout: A research note.
Demography, 31(4), 575–584.; Burkam, D., Lee, V., & Dwyer, J. (2009, June 29). School mobility in the early elementary grades:
Frequency and impact from nationally representative data. Presented at the Workshop on the Impact of Mobility and Change on
the Lives of Young Children, Schools, and Neighborhoods, Washington, D.C.; Reynolds, A. J., Chen, C., & Herbers, J.
E. (2009, June 29). School mobility and educational success: A research synthesis and evidence on prevention. Presented at the
Workshop on the Impact of Mobility and Change on the Lives of Young Children, Schools, and Neighborhoods,
Washington, D.C.; Temple, J. A., & Reynolds, A. J. (1999). School Mobility and Achievement: Longitudinal Findings
From an Urban Cohort. Journal of School Psychology, 37(4), 355–377.
5
Normal Curve Equivalent transformations were introduced by the U.S. Department of Education to allow for
comparison of test scores over time and across sites. According to the Tennessee Department of Education website,
“The Normal Curve Equivalent shows your student’s scores using a scale that ranges from 1–99. Scores from 1–34 are
Below Average, 35–65 are Average, and 66–99 are Above Average” (available online at
http://www.state.tn.us/education/assessment/doc/Form_R_Parent.pdf).
6
The statistical model employs a multilevel design to account for the grouping of students by school and the subsequent
lack of independence between students in the same school. Residential mobility is included in the model as a set of
binary variables (yes = 1, no = 0) to indicate the number of moves a student has made over the six year period from
2003-2009. Binary variables for students who are Black, Latino/a, and eligible for the free and reduced lunch program
are included in the model alongside residential mobility as covariates. The output for the regressions with (a) Math
TCAP, (b) Reading TCAP, (c) attendance, (d) disciplinary referrals, and (e) perception of school relational climate
(SD=0.67) is given below:
7
Outcome variable
One residential move over
six years (2003-2009)
Two residential moves
Three or more residential
moves
Free/reduced lunch
program eligible
Black
Latino/a
N (students)
* p<.10
** p<.05
Math
TCAP
Reading
TCAP
Absences
-1.290
(1.31)
-1.538
(1.13)
-2.714 **
(1.14)
-6.664 ***
(1.65)
-7.281 ***
(1.13)
-1.166
(1.36)
4700
*** p<.01
-2.423
(1.54)
-1.851
(1.04)
-2.734
(1.14)
-7.040
(1.53)
-6.142
(1.55)
-2.870
(2.30)
4670
0.283
(0.37)
0.644
(0.36)
2.408
(0.31)
2.858
(0.49)
-2.858
(0.55)
-3.837
(0.59)
4906
*
**
***
***
*
***
***
***
***
Disciplinary
referrals
Perceptions of
school climate
0.293
(0.28)
0.186
(0.22)
0.697
(0.24)
0.865
(0.24)
1.303
(0.20)
-0.535
(0.25)
4289
-0.002
(0.03)
-0.006
(0.03)
0.017
(0.03)
0.045
(0.04)
-0.060
(0.04)
0.089
(0.05) *
4483
***
***
***
**
National Research Council and Institute of Medicine. (2010). Student Mobility: Exploring the Impact of Frequent Moves on
Achievement: Summary of a Workshop. A. Beatty, Rapporteur. Committee on the Impact of Mobility and Change on the
Lives of Young Children, Schools, and Neighborhoods. Board on Children, Youth, and Families, Division of Behavioral
and Social Sciences and Education. Washington, DC: The National Academies Press.
8
Petit, B., & McLanahan, S. (2003). Residential mobility and children’s social capital: Evidence from an experiments.
Social Science Quarterly, 84(3), 632-649.
9
Hendershott, A. B. (1989). Residential mobility, social support, and adolescent self-concept. Adolescence, 24(93), 217232.
10
The statistical model employs a multilevel design to account for the grouping of students by school and the
subsequent lack of independence between students in the same school. Only school-level variables are included in the
model. Average student residential mobility over the six-year period from 2003 to 2009 is included in the model as a
continuous variable. The proportion of students in the school who are eligible for the free or reduced lunch program
11
Residential Mobility Research Brief
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(FRLP) and the average years of experience among teachers in the school are the two covariates included in the model.
The output for the regressions with (a) Math TCAP, (b) Reading TCAP, (c) attendance, (d) disciplinary referrals, and (e)
perception of school relational climate (SD=0.67) is given below:
Outcome variable
Average student residential
mobility in school
Proportion of students in
school eligible for FRLP
Average years of experience
among teachers in school
N (schools)
* p<.10
** p<.05
Math
TCAP
-13.550 **
(6.60)
-20.626 ***
(6.23)
-0.127
(0.32)
11
*** p<.01
Reading
TCAP
Absences
-7.040
(7.58)
-25.647 ***
(7.17)
0.087
(0.37)
11
4.378 *
(2.25)
-3.823 *
(2.12)
-0.120
(0.11)
11
Disciplinary
referrals
-3.189 **
(1.62)
2.575 *
(1.53)
-0.229 ***
(0.08)
11
Perceptions of
school climate
-0.654 **
(0.29)
0.472 *
(0.27)
-0.003
(0.01)
11
Note: The variables “Average student residential mobility in school” and “Proportion of students in school eligible for
FRLP” are highly collinear, and this multicollinearity appears to be distorting the parameter estimates in the model with
disciplinary referrals as an outcome. In a model with the FRPL proportion variable held out, the residential mobility
variable has a significant effect in a negative direction.
General Accounting Office. (1994). Elementary school children: Many change schools frequently, harming their education.
Washington, D.C.: General Accounting Office.; National Research Council and Institute of Medicine. (2010). Student
mobility: Exploring the impact of frequent moves on achievement: Summary of a workshop. A. Beatty, Rapporteur.
Committee on the impact of mobility and change on the lives of young children, schools, and neighborhoods. Board on Children, Youth,
and Families, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies
Press.
12