Students Changing Schools During the School Year Report, No. 5!"#$%&'()*+, Students Changing Schools...

EdPolicyWorks Report, No. 5October 2017

Students Changing Schools During the School Year:

Student Mobility in Virginia and the Challenged School Divisions

Luke C. Miller and Katharine Sadowski

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STUDENTS CHANGING SCHOOLS DURING THE SCHOOL YEAR: STUDENT MOBILITY IN VIRGINIA AND THE CHALLENGED SCHOOL DIVISIONS

Luke C. Miller and Katharine Sadowski

EdPolicyWorks, University of Virginia

26 April 2017 Introduction

Ask any teacher to identify two things he or she does at the start of each school year that facilitates having a successful year, and you are likely to hear about the importance of establishing norms of classroom behavior and assessing the knowledge students start the year with so as to determine how best to structure the year’s curriculum and instruction. With the teacher and students adjusted to each other, amazing things are possible. Students who change schools (and thus classrooms) during the school year present a disruption to this process both for the students who change schools but also for their classmates that do not.

Some degree of student mobility during the school year is inevitable because not all changes

in a student’s family and residential circumstances can be coordinated with the school year. Families dealing with financial challenges, for example, may also be struggling to stay on top of rent or a mortgage. Housing instability may require these families to move residences and their children to change schools. Within-year mobility, while inevitable, is not random, and some schools and students are impacted more than others.

Eager to support local school divisions in their efforts to address mobility, the Virginia

Governor’s Children’s Cabinet commissioned this report to provide a rich descriptive picture of the within-year mobility in Virginia and in the three Challenged School Divisions in particular—Norfolk, Petersburg, and Richmond—between 2004-05 and 2014-15.1 We divide our analysis into two parts. First, we analyze mobility for all students in Virginia and the three Challenged Divisions to provide a general context. Then we compare trends between homeless students and all other students to highlight the particular challenges homeless students face in attending one school throughout the entire school year.

In our analysis, we examine two measures of mobility—the stability and churn rates. We

highlight variation across division, grade, and time. We then turn to the timing of student mobility by analyzing how mobility varies by month, time of month, and season. Finally, we characterize the geographic dimension of mobility by identifying the divisions to which students move when they transfer out of the Challenged School Divisions. We preface our comparative analysis of mobility across homeless status with an exploration of how homelessness, a significant factor in mobility, varies across the divisions and across time.

Our analysis reveals there to be a considerable amount of within-year mobility in Virginia and among homeless students in particular. In 2014-15, the stability rate among all Virginia students was 94%, meaning that 94% of all Virginia students who were enrolled at the start of the year

1 The Children’s Cabinet identified these three divisions for their Challenged School Initiative because they had the highest number of unaccredited schools.

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continued to be enrolled at the same school for the entire year. Among homeless students, only 70% have stabile enrollment. The rates were lower among students in the Challenged School Divisions overall (87% in Richmond and 88% in Petersburg and Norfolk) and among homeless students in particular (64% in Norfolk, 66% in Richmond, and 79% in Petersburg).

The churn rate, a more holistic measure of within-year mobility, reflects the total number of

times students enter or exit a school (i.e., churn events). In 2014-15, there were 16 churn events per 100 students in Virginia statewide, and there was meaningfully more churn among students in the Challenged School Divisions: 26 events per 100 students in Norfolk, 31 events in Richmond, and 37 events in Petersburg. The churn rates were significantly higher among homeless students: 89 statewide, 57 Petersburg, 86 in Richmond, and 93 in Norfolk.

Our analysis provides an initial examination of within-year student mobility in Virginia and is

intended to support a nascent policy and research agenda within the commonwealth. It is descriptive in nature and does not demonstrate how any student or school characteristic causes a student to change schools during the school year or how mobility causes student educational outcomes to differ between students that do and do not change schools during the school year. Accordingly, the findings presented here serve as the basis for generating hypotheses regarding efforts to reduce mobility and its negative consequences for students in Virginia. Student Mobility

One fundamental feature of our public school system is students transferring among schools. Nearly all students make a structural transition as they are promoted from elementary schools to middle schools to high schools. Many students, however, also experience non-structural transitions (collectively referred to as school mobility). There are meaningful differences between the two (Rumberger, 2015). Structural transitions are the result of a positive event—promotion to the next grade—and occur almost exclusively between school years. School mobility, on the other hand, can be triggered by both positive and negative events, including homeless (the focus of this paper) and often occurs during the school year. A large body of research highlights the negative relationship between school mobility and educational and behavioral outcomes (see Reynolds, Chen, & Herbers, 2009, for a meta-analysis). The academic achievement of students who change schools for non-promotional reasons lag behind their non-mobile peers (Alexander, Entwisle, & Dauber, 1996; Gruman, Harachi, Abbott, Catalano, & Fleming, 2008; Kerbow, 1996). Additional research indicates that school mobility not only suppresses the achievement of the mobile students but also reduces the achievement gains of the non-mobile students at the schools into which they move (Hanushek, Kain, & Rivkin, 2004). Switching schools is associated with a higher risk of dropping out of high school (Gasper, DeLuca, & Estacion, 2012; Herbers, Reynolds, & Chen, 2013). Mobile students have been found to have difficulty making new friends and adjusting socially at their new schools (Dupere, Archambault, Leventhal, Dion, & Anderson, 2015; Rumberger, Larson, Ream, & Palardy, 1999; South & Haynie, 2004). Highly mobile students are also more likely to have both unrecognized education needs because their exposure to adults in schools is too short for their needs to be detected and identified and unmet educational needs because these students move on before schools are able to put services in place for them (Julianelle & Foscarinis, 2003).

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Residential mobility is a significant cause of school mobility, and homelessness is an extreme version of residential mobility (Crowley, 2003). Students who experience homelessness also experience other difficult family circumstances such as poverty, single-parent households, and mental health problems (Miller, 2015). Homeless students have higher rates of school mobility than other low-income students (Buckner, Bassuk, & Weinreb, 2001; Rafferty, Shin, & Weitzman, 2004; Tierney, Gupton, & Hallett, 2008), and the negative consequences of homelessness and school mobility compound placing these students further behind their peers academically (Fantuzzo, LeBoeuf, Chen, Rouse, & Culhane, 2012; Miller, 2011).

The federal McKinney-Vento Homeless Education Assistance Act seeks to mitigate the negative

effects of homelessness. The law guarantees students the option of remaining in their school of origin once they become homeless. While the decision to change schools remains with the family, schools are required to work with homeless students and their families to determine whether remaining in the school of origin is feasible and what the school can do to make that happen including the provision of transportation (James & Lopez, 2003). In prioritizing stable school enrollment for homeless students, the law acknowledges the disruptive consequences of within-year mobility. Data, Measures, and Analysis Strategy Data. The current analysis makes use of data obtained through the Virginia Longitudinal Data System (VLDS). These data span the school years 2004-05 to 2014-15. For every student enrolled in a public school, we observe the school and grade level (kindergarten through 12th grade) in which they are enrolled and the date they enroll and exit each school. From these data, we construct a database that includes a record for each school at which each student was enrolled in each school year (e.g., a student who attends three schools in 2007-08 will have three records for that school year). We exclude from the database enrollment records for students in non-traditional schooling situations (hospital and homebound care, for example) and records linked to non-regional school divisions such as the Virginia School for the Deaf and Blind. Finally, we remove enrollment records for students enrolled in school for more than 190 days within a year as well as records that indicate a student was enrolled in more than one school at a time (about 0.25%). This results in a database of 14,220,555 student-by-school-by-year enrollment records. Measures. Our analysis focuses on several key concepts, measures of which we construct from these data.

Throughout this report, we draw comparisons between students who are at any point during the school year identified as homeless and all other students. The VLDS data identify whether a student is homeless at any point during the school year. Each division is required to appoint a homeless education liaison who is responsible for identifying homeless students and ensuring these students receive the services to which they are entitled under the McKinney-Vento Homeless Assistance Act of 2001. Due to the small sample of homeless students, we pool the four homeless categories (unsheltered, sheltered, doubled-up, and hotels/motels) into a single group. (See Appendix B for the definitions of each homeless category.) This measure of homelessness was first collected during the 2008-09 school year.

In order to identify students who change schools during the school year, we must first identify whether students are enrolled at the beginning and end of the school year. We deduce the

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first day of the school year by assuming that the school year started the date on which the greatest number of students entered the school (i.e., the modal entry date). We identify a separate first day of school for each school in each year. This approach allows us to detect cases like that in Petersburg in 2014-15 in which the two schools on a year-round calendar started before the division’s other schools. We consider students to be enrolled at the beginning of the school year if they enroll within 2 days of the first day of school. This allows for some delay in schools entering students into the enrollment database. Students are enrolled at the end of the year if their status is active in the end-of-year report to VDOE. With the first and last days of each school’s school year identified, we calculate the percent of students who are enrolled at the beginning of the year and the percent who are enrolled at the end of the year. To calculate the beginning-of-the-year enrollment rates, we assign each student to the school and division in which he first enrolls that year. Similarly, we assign each student to the school and division in which he last enrolls that year to calculate the end-of-the-year enrollment rate. Assigning students in this manner allows us to estimate the total number of students who should have been enrolled at the beginning and end of the year (the denominator in the percentages). This assignment also reflects the fact that, while students can change schools during the course of a year, they can be enrolled at one and only one school at the start of the year and one and only one school at the end of the year.

Annual Measures of the Percent of Students Enrolled at the Beginning and End of the School Year

Beginning − of − year𝒅 = 100 × # students enrolled in a school in Division 𝒅 on the first day of the school′s school year

# students who first enroll at a school in Division 𝒅 that year

End − of − year𝒅 = 100 × # students enrolled at a school in Division 𝒅 on the last day of the school′s school year

# students who last enroll at a school in Division 𝒅 that year

We characterize within-year school mobility with two statistics—the stability rate and the churn rate. Each statistic captures a distinct dimension of mobility. The stability rate measures the percent of students who have a stable school enrollment throughout the entire school year. A student has a stable enrollment if he attends a single school continuously from the start to the end of the school year.

We calculate a division’s (or the state’s) stability rate by simply averaging this indicator across students within the division (or state). If every student enrolled in Division A at the start of the year did not change schools and was enrolled at the same school at the end of the year, Division A’s stability rate would equal 100%. Every student has a stable enrollment. If all students in Division A switched schools during the year, the division would have a 0% stability rate. No student has a stable enrollment. We calculate this statistic only among students who are enrolled at the start of the year as

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shown in the box below as these are the only students who have a non-zero probability of having a stable enrollment.2

Annual Measures of School Mobility

Stability𝒅 = 100 × # students attending a single school in Division 𝒅 continuously between the start and end of the year

# students enrolled in Division 𝒅 at the start of the year

Churn𝒅 = 100 × # of students entering + # exiting schools in Division 𝒅 between the start and end of the year

# students ever enrolled at a school in Division 𝒅 during the year

The churn rate captures the degree of student mobility by measuring the number of churn events per student. A churn event occurs anytime a student enters or exits a school at any point after the start of the school year and before the end of the school year. The churn rate increases with churn events.

Every student without a stable enrollment will generate at least one churn event for a

division. For example, when a student who is enrolled at the beginning of the year transfers out (exits), say in January, one churn event is assigned to the division. When this student later enrolls (enters) at another school, a churn event is generated in that division. Should this student change schools within the same division, both churn events (exiting the first and entering the second) are assigned to the division. Similarly, when a student enrolls in a school after the start of the year and transfers out before the end of the year, this student’s mobility pattern generates two churn events for the division.

We calculate a division’s churn rate as the number of churn events divided by the number of

unique students enrolled in the division at any point during the school year as shown in the box above. Each student is counted only once in the denominator, despite how many times he or she enters or exits the same division. For ease of interpretation, we multiply this by 100 and interpret the statistic as the number of churn events per 100 students.3 These two measures of student mobility are similar to those used in other states’ analyses but differ in one key respect. Our measures reflect mobility whenever it occurs during the course of the entire school year. Many states’ measures capture only the student movement that occurs after schools report their fall membership to the state (i.e., September 30th or October 1st).4 Schools have been in session for nearly a month by this point and, as our analysis shows, roughly half of all

2 An alternate definition of the stability rate (adopted in some of the literature) includes in the denominator all students enrolled at School A at any point during the school year. Using this alternate definition, the stability rates would be lower than those we report if students enrolled at the school after the start of the year. This is because none of these additional students were enrolled at School A at the start of the year and thus cannot have stable enrollment by definition. As the number of students entering after the start of the school year increases, the difference in stability rates using the preferred and alternate definition will increase. 3 An alternative definition of churn (adopted in some of the literature) would capture the percent of students who change schools. With this definition, each student can generate at most one churn event per division. It does not distinguish between a student that transfers in and out of a school during the year and a student who only transfers in or transfers out. The first student’s mobility pattern represents more churn (and thus more potential disruption to the classroom) than does the second student’s mobility pattern. It therefore undercounts student turnover. 4 Some states also ignore movement that occurs late in the year, say after May 15th or June 1st.

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movements across schools occur before October. By examining the entire school year, our measures provide a more complete picture of student mobility among Virginia’s schools. Analytic Strategy. The analysis that follows is descriptive in nature. It is intended to highlight policy-relevant patterns and correlations between student characteristics and within-year school mobility. This analysis is not designed to highlight the causal effect of any of these characteristics on mobility, and readers should not draw causal inferences.

Throughout this report, we present statistics for each of the three Challenged School Divisions separately. We also include statistics for the all students in Virginia (including students enrolled in the three focus divisions) to position the three focus divisions within the state context for within-year school mobility. As shown in Table 1, students in the Norfolk, Petersburg, and Richmond school divisions, compared to students statewide, are more likely to be Black, less likely to be White, and more likely to be economically disadvantaged. They are also less likely to pass statewide exams in core academic subjects and less likely to graduate from high school.

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Table 1. Descriptive statistics on Virginia’s Challenged School Divisions, 2014-15

Norfolk Public

Schools

Petersburg City Public

Schools

Richmond Public

Schools Virginia

# Schools 40 8 35 1,861

Enrollment

Total 32,290 4,318 23,957 1,279,773

Pre-K 2,174 342 1,713 32,784

K-5 15,680 2,061 12,042 580,117

6-8 6,517 843 4,520 287,731

9-12 7,863 1,072 5,682 382,141

Student Demographics

% Black 61.0 92.2 76.1 23.0

% Hispanic 7.3 4.6 11.5 13.8

% White 22.4 2.0 9.5 51.3

% Other 7.3 2.8 0.2 11.9

% Economically Disadvantaged 66.5 60.4 62.9 40.0

% LEP 3.3 4.0 8.1 10.1

% Students with Disabilities 12.4 10.1 16.1 12.3

Academic Indicators

% Passing English 67 58 59 79

% Passing Mathematics 72 57 62 79

% Passing Writing 69 49 48 77

% Passing History 80 72 72 86

% Passing Science 74 66 66 82

Virginia On-Time Graduation Rates

2014 Cohort 4-year Rate (%) 81 84 81 90

2013 Cohort 5-year Rate (%) 80 79 78 90

Federal Graduation Indicators a

2014 Cohort 4-year Rate (%) 75 71 71 85

2013 Cohort 5-year Rate (%) 76 70 68 86 a The Federal Graduation Indicator is a graduation rate that includes only Standard Diplomas and Advanced Studies Diplomas. It differs from the Virginia On-Time Graduation Rate, which includes all State Board of Education-approved diplomas.

SOURCE: Virginia Fall Membership Database (www.doe.virginia.gov/statistics_reports/enrollment/fall_membership/index.shtml) and Virginia School Report Cards (https://p1pe.doe.virginia.gov/reportcard/)

Results To provide some helpful context for interpreting the mobility results, we begin with an examination of the likelihood students are enrolled at the beginning and end of the school year. We then discuss the stability rates, the churn rates, and the timing of between-division moves including the divisions to which students transfer before turning to a comparative analysis to highlight differences between homeless and all other students. Beginning- and end-of-year enrollment. One source of the disruption mobility can cause is students not being enrolled at the beginning of the school year. In 2014-15, 95% of Virginia students were enrolled at the beginning of the school year with Richmond and Norfolk having similar rates (94%). Petersburg’s switch to a year-round calendar for two of it schools (and the associated earlier first day of school) appears to have suppressed it’s beginning-of-the-year

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enrollment rate to 87% down from 94% a year earlier. These rates have ticked upwards since 2004-05. (See Table A1 in appendix A for additional statistics.) The average student is somewhat more likely to be enrolled at the end of the year than they are to be enrolled at the beginning of the year. Between 2004-05 and 2014-15, Virginia students are roughly 1 percentage point more likely to be enrolled at the end than the beginning of the year. This difference is larger in Richmond and Petersburg (2 percentage points) and smaller in Norfolk (0.1 percentage points). (See Table A2 in appendix A for additional statistics). Stability. Fewer students have stable enrollment in the three challenged school divisions than students statewide as shown in Figure 1. Among students who are enrolled at the start of the 2014-15 school year, 94% of all Virginia students continued to be enrolled at the same school for the entire year compared to 87% in Richmond and 88% in Petersburg and Norfolk.

Figure 1. Stable enrollment rates by division, 2014-15 SOURCE: See Table A3 in appendix A for statistics.

Stability rates among all students statewide generally increase through 8th grade, decrease in

the 9th grade (typically the start of high school), and decrease again in the 12th grade, as shown in Figure 2. There is more variability in the stability rate across the grades in the three Challenged School Divisions. Two common features, however, are present among these divisions. First, as with the state as a whole, the stability rate drops in each division in the first year of high school (9th grade in Norfolk and Richmond, 10th grade in Petersburg). The percent of 9th graders with a stable enrollment relative to that of 8th graders is 5 percentage points lower in Richmond (83 versus 88%) and 6 percentage points less in Norfolk (85 versus 91%). Similarly in Petersburg, the 10th grade stability rate is 6 percentage points less than the 9th grade rate (86 versus 92%).

The second common feature among the three Challenged School Divisions is that the

stability rate steadily climbs through the remaining high school grades. The stability rate increases 7 percentage points in Petersburg (86 to 93%), 8 points in Norfolk (85 to 93%), and 9 points in Richmond (83 to 92%). While many factors may be driving this pattern, one potential may be that students least likely to have stabile enrollments drop out of school earlier in their high school careers than students in other divisions, thus removing them from the calculations for the later grades.

93.6%

Virginia

88.3%

Norfolk

87.7%

Petersburg

86.7%

Richmond

All Students

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Figure 2. Stable enrollment rates by division and grade, 2014-15 SOURCE: See Table A4 in appendix A for statistics.

Since 2004-05 as shown in Figure 3, the stability rates among all students in Virginia have

increased just over 1 percentage point (or 1.5%) meaning that mobility has decreased among those students who are enrolled at the start of the school year. Stability rates also increased in Norfolk (0.8 percentage points or 1.0%) and Richmond (6 percentage points or 8%). They decreased slightly in Petersburg (0.2 percentage points or 0.2%).

Figure 3. Stable enrollment rates by division and school year, 2004-05 to 2014-15 SOURCE: See Table A5 in appendix A for statistics.

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Among all students, stability rates have changed most for the high school grades as shown in Figure 4. This is most pronounced in Richmond where the high school stability rate increased 19 percentage points (or 29%). This increase is largely driven by what appear to be artificially low stability rates in 2004-05 and 2005-06 when many likely high school completers are listed as “inactive” on the end of the year report. Excluding these years, the stability rate still increased 6 percentage points (or 8%). The high school stability rate decreased in Petersburg 2 percentage points (or 3%) and increased slightly in Norfolk by 1 percentage point (or 1%).

Figure 4. Stable enrollment rates by division, grade cluster, and school year, 2004-05 to 2014-15 SOURCE: See Table A6 in appendix A for statistics.

Churn. An analysis of the churn rates is a nice companion to the stability rate analysis. Whereas the stability rate measures whether students changed schools at least once during the year, the churn rate reflects the number of moves.

In 2014-15, there was meaningfully more churn among students in the Challenged School Divisions than among all students in Virginia as shown in Figure 5. There were 16 between-school churn events per 100 students in Virginia compared to 26 in Norfolk, 31 in Richmond, and 37 in Petersburg.5

5 Whereas all churn events, by definition, involve students changing schools, most school entries and exits during the school year also involve students changing divisions. It is important to note that division size plays an important role here. We would expect between-division churn events to be more common in Petersburg than the other divisions because there is only one school serving grades 6 through 12; in order to change schools, students in these grades must change divisions, with a few exceptions. For this reason, we focus on between-school rather than between-division churn events in this analysis.

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Figure 5. Churn rates by division, 2014-15 SOURCE: See Tables A7 in appendix A for statistics.

The frequency of churn events generally decreases as students advance from kindergarten

through 12th grade as shown in Figure 6. Transitioning to high school appears to be related to a spike in churn events. For example, the churn rate increases between the 8th and 9th grades in Norfolk and Richmond and between the 9th and 10th grades in Petersburg as students move from middle/junior high schools to high schools.6 The jump in the Petersburg churn rate for the 9th grade relative to the 8th grade is also connected to the transition to high school despite both the 8th and 9th grades being housed in the same school. There is a meaningfully large number of 10th graders who exit Petersburg High School to enroll as 9th graders in Vernon Johns Junior High School.

The transition from elementary to middle school does not trigger a similar large increase in

the churn rate. With the exception of Petersburg, there is less churn among 6th graders than among 5th graders.

6 The increase between the 8th and 9th grades in Petersburg is related to 10th graders exiting Petersburg High School to enroll as 9th graders in Vernon Johns Junior High School.

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Figure 6. Churn rates by division and grade, 2014-15 SOURCE: See Tables A8 in appendix A for statistics.

Since 2004-05, the churn rate among all Virginia students decreased 18% (or 3 events per

100 students) as shown in Figure 7. The churn rate also decreased in Norfolk (9% or 3 events) and Richmond (34% or 16 events). In Petersburg, the rate at which students change schools remained rather steady with two noticeable spikes in 2011-12 and 2014-15.

Figure 7. Churn rates by division and year, 2004-05 to 2014-15 SOURCE: See Table A7 in appendix A for statistics.

Churn has decreased since 2004-05 in all grade clusters (elementary, middle, and high school)

in Virginia statewide as well as in Norfolk and Richmond as shown in Figure 8. The frequency of

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churn events increased in Petersburg in each grade cluster, particularly in middle school where the churn rate increased 63% (or 14 events per 100 students).

Figure 8. Churn rates by division, grade cluster, and year, 2004-05 to 2014-15 SOURCE: See Tables A9 in appendix A for statistics.

When Churn Occurs. Having examined the trends and patterns in stability and churn rates, we now turn to the timing of school transfers. When during the school year do students change schools? For this analysis, we present the distribution of all the within-year school entries and exits by month, season, and time of month. We focus on 2014-15 here as the distributions have changed very little since 2004-05 (statistics for other years are available in Tables A10-A12 in appendix A).

The majority of moves occur before October as shown in Figure 9. Almost 60% of moves occur in September in Norfolk and Richmond. In Petersburg with two schools shifting to a year-round calendar in 2014-15, the early moves are a bit more spread out with 40% occurring in September, 17% in August, and 8% in July. In 2013-14, the year before two schools switched to a year-round calendar, 57% of moves occurred in September (see Table A10 for statistics). Grouping moves by season further emphasizes that students are more likely to move schools at the beginning of the year. Statewide 71% of moves occur in the fall (July-November) compared to only 6% in the spring (April-June). Moves in the Challenged School Divisions are somewhat more concentrated in the fall relative to the state.

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Figure 9. Timing of churn by division and month or season, 2014-15 NOTE: Fall includes July through November, winter includes December through March, and spring includes April through June. SOURCE: See Tables A10 and A11 in appendix A for statistics.

Churn is also concentrated in the beginning portion of the month as shown in Figure 10.

Within Virginia, 61% of moves occur during the first 10 days of the month. An even larger portion of moves happen early in the month in Richmond and Norfolk (67%). Moves are least likely to occur toward the end of the month (the 21st through 31st day).

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Figure 10. Timing of churn by division and time of month, 2014-15 NOTE: The beginning of the month includes the 1st through 10th day, the middle of the month includes the 11th through the 20th of the month, and the end of the month includes the 21st through 31st day. SOURCE: See Tables A12 in appendix A for statistics.

Where Students Move. Finally, we looked at where students moved to when they transferred out of one of the Challenged School Divisions during the three most recent years, 2012-13 through 2014-15.7 Unsurprisingly, the vast majority of students transferred to contiguous divisions as shown in Figure 11. In Richmond, 78% of the students moved to either Chesterfield or Henrico Counties. In Norfolk, 72% of students moved to either Chesapeake, Portsmouth, or Virginia Beach. In Petersburg, 67% of the students moved to either Chesterfield County, Colonial Heights, Dinwiddie County, Hopewell, or Prince George’s County. As shown in Table A14 in Appendix A, the divisions which receive students from the Challenged School Divisions during the year are by and large the same divisions which send students to the Challenged School Divisions.

7 We exclude moves where we do not observe the division to which the student transferred.

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Figure 11. Divisions to which students transfer mid-year, 2012-13 to 2014-15 NOTE: The two divisions without data are the Quantico and Dahlgren military bases. SOURCE: See Table A13 in appendix A for select statistics.

Homelessness and Mobility. Housing instability (of which homelessness is an extreme case) is a meaningful contributor to school mobility. Below we compare mobility among homeless students to mobility among all other students. We begin with an examination of homelessness rates before presenting the rest of our comparative analysis in the same order as above.

Prevalence of Homelessness. Roughly 1.5% of students attending Virginia’s public schools are homeless at some point during the 2014-15 school year. While Norfolk’s homelessness

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rate is similar to the commonwealth’s (1.8%), the rates were much higher in Richmond (5.6%) and Petersburg (10.8%) as shown in Figure 12. The homelessness rate increased since 2008-09 in each division and the commonwealth but particularly in Richmond (41% or 1.6 percentage points) and Petersburg (44% or 3.3 percentage points).8

Figure 12. Homelessness rate by division, 2008-09 to 2014-15 SOURCE: See Table A15 in appendix A for additional statistics.

Almost invariably, the homelessness rate is highest for elementary students (grades K-5) and

lowest for high school (grades 9-12) as shown in Table A15 in appendix A. In 2014-15, the rate for elementary students was twice that of high school students in Norfolk (1.1 versus 2.2%), 60% larger in Petersburg (7.6 versus 12.1%), and 29% larger across all students in Virginia (1.3 versus 1.7%). Among students in Richmond, the gap in homelessness between elementary and high school students has shrunk over time such that in 2014-15 the rates for elementary and high school students were nearly equal (5.5 and 5.6%, respectively).

In Virginia and in each division, homelessness has increased at a greater rate for high school

students than for other students since 2008-09. Among all students in Virginia, the rate increased 74% for high schoolers, 51% for middle schoolers, and 22% for elementary students. Homelessness increased the most among high schoolers in Petersburg (150%) and the least among elementary students in Norfolk (9.6%).

Beginning- and end-of-year enrollment. One source of the disruption mobility can cause is students not being enrolled at the beginning of the school year. Homeless students are meaningfully less likely to be enrolled at the start of the school year than other students (see Table A1 and A2 in Appendix A). In Petersburg in 2014-15, 83% of homeless students were enrolled at the start of the year compared to 88% of other students. The difference in beginning-of-the-year

8 It is important to recall that the Governor’s Children’s Cabinet identified Norfolk, Petersburg, and Richmond as Challenged School Divisions because of a high number of unaccredited schools and not because these divisions had the most homeless students.

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enrollment rates in Richmond is double what it is in Petersburg (95 versus 84%) and almost four times larger in Norfolk (94 versus 74%). Statewide 96% of non-homeless students and 78% of homeless students were enrolled at the beginning of the year. Since 2004-05, this difference has increased in Norfolk (14 versus 20 percentage points) and decreased in Petersburg (10 versus 5 percentage points) and Richmond (21 versus 11 percentage points). It has remained relatively constant statewide. The average student is somewhat more likely to be enrolled at the end of the year than they are at the beginning of the year. And while homeless students are less likely to be enrolled at the end of the year than other students, the difference is considerably smaller, in fact near zero in some cases, than the difference in the beginning-of-the-year enrollment rates.

Stability. As shown in Figure 13, stability rates are lower for homeless students than all other students. Among all homeless students in Virginia, 70% are enrolled at the end of the year in the school they attended at the beginning of the school. This is 24 percentage points lower than the stability rate for all other students. A similarly sized difference in stability rates between homeless and all other students is evident in Norfolk (64 versus 89%) and Richmond (66 versus 88%). The difference is much smaller difference in Petersburg (79 versus 89%) where stability among homeless students is 8 percentage points higher than among homeless students statewide.

Figure 13. Stable enrollment rates by division and homelessness, 2014-15 SOURCE: See Table A3 in appendix A for statistics.

There are several features to point out in Figure 14 in which we display how the stability rates, averaged over the three-year period between 2012-13 to 2014-15, varied across grades for homeless students and all other students.9 The first thing to note is the increased variability in the stability rate across grades for homeless students relative to all other students. In Richmond, for

9 We present 3-year averages rather than statistics from only 2014-15 because the sample of homeless students within a specific grade in a single year in a specific division can be rather small resulting in a noisier trend line.

70.3%

Virginia

63.8%

Norfolk

78.7%

Petersburg

66.4%

Richmond

Homeless Students93.9%

Virginia

88.6%

Norfolk

88.7%

Petersburg

87.7%

Richmond

All Other Students

93.9%

Virginia

88.6%

Norfolk

88.7%

Petersburg

87.7%

Richmond

All Other Students

93.9%

Virginia

88.6%

Norfolk

88.7%

Petersburg

87.7%

Richmond

All Other Students

19

example, the homeless stability rate varies from 64% for 3rd and 5th graders to 89% for 12th graders whereas for all other students the stability rate ranges from 84% for 9th graders to 93% for 12th graders. Second, echoing the finding from Figure 13, homeless students in Petersburg are more likely to have stabile enrollments than homeless students statewide in 12 of the 13 grades. Homeless students in Norfolk are less likely to have stable enrollment than homeless students statewide in all grades.

Figure 14. Stable enrollment rates by division, grade, and homelessness, 2012-13 to 2014-15 SOURCE: See Table A16 in appendix A for statistics.

Since 2008-09, stability rates have tended to increase for homeless students while remaining rather unchanged for all other students (Figure 15, first panel). The stability rate among homeless students in Richmond, for example, increased 11 percentage points (or 19%) since 2008-09 compared to a 1 percentage point (or 1%) increase among other students. Stability among homeless students in Norfolk increased 4 percentage points (7%) compared to an increase of only 0.6 percentage points among all other students. The increases statewide where similar to those in Norfolk (4 and 0.4 percentage points). On the other hand, in Petersburg, stability decreased ever so slightly for both groups (0.5 and 0.2 percentage points).

50

60

70

80

90

100

Sta

ble

Enro

llment (%

)

KG 1 2 3 4 5 6 7 8 9 10 11 12

Grade

Homeless Students

50

60

70

80

90

100

Sta

ble

Enro

llment (%

)

KG 1 2 3 4 5 6 7 8 9 10 11 12

Grade

All Other Students

Norfolk Petersburg Richmond Virginia

20

Figure 15. Stable enrollment rates by division, grade cluster, homelessness, and school year, 2004-05 to 2014-15 SOURCE: See Tables A5 and A6 in appendix A for statistics.

While this pattern of a greater change over time in the stability rate for homeless students than for other students tends to holds for all three grade clusters in Virginia statewide and in the three Challenged School Divisions (Figure 15, second through fourth panels), there are noticeable differences in the magnitude of the change among homeless students across grades levels. In Richmond, the homeless stability rate increased 6 percentage points (or 9%) among middle school students, 9 percentage points (17%) among elementary students, and 18 percentage points (31%) among high school students. The magnitude of the changes in the homeless stability rate are even more pronounced in Norfolk where the elementary rate increased 11 percentage points (20%), the

21

high school rate changed less than a percentage point, and the middle school rate decreased 14 percentage points (21%). Among homeless students in Petersburg, the stability rate increased 14 percentage points (or 21%) for high school students while decreasing 2 percentage points (or 2%) for elementary and middle school students.

Churn. We now turn to our analysis comparing churn between homeless and all other students. As a reminder, the difference between the stability rate and churn rate is that the churn rate reflects the total number of times students enter and exit any school whereas the stability rate only reflects whether students ever exit the school at which they began the school year.

Churn among homeless students occurred at significantly higher rates than among all other

students. Among Virginia students, churn among homeless students is over 6 times more common than among all other students (90 versus 15 events per 100 students). It is also the case in the three Challenged School Divisions that homeless students are more likely to experience churn than are all other students; however the difference is not as large as it is in Virginia statewide. In Norfolk there were 93 between-school churn events per 100 homeless students, a rate almost 4 times higher than the 25 events per 100 other students (Figure 16). Churn among homeless students is just over 3 times higher than among other students in Richmond and almost twice as high in Petersburg.

Figure 16. Churn rates by division and homelessness, 2014-15 SOURCE: See Tables A7 in appendix A for statistics.

The frequency of churn events generally decreases as students advance from kindergarten through 12th grade as shown in Figure 17. This pattern is evident for both homeless and other students. Transitioning to high school appears to be related to a spike in churn events for all other students. For example, the churn rate increases between the 8th and 9th grades in Norfolk and Richmond and between the 9th and 10th grades in Petersburg as students move from middle/junior

22

high schools to high schools.10 This increase in churn events among homeless students is only evident in Norfolk with churn decreasing between 8th and 9th grade in Richmond and decreasing between 9th and 10th grades in Petersburg. A different pattern is evident with the transition from elementary to middle school. Among homeless students, churn increases in the 6th grade relative to the 5th grade in all three Challenged School Divisions plus a small increase in Virginia statewide. The churn rate among all other students also increase in the 6th relative to 5th grades in the three Challenged School Divisions.

Figure 17. Churn rates by division, grade, and homelessness, 2012-13 to 2014-15 SOURCE: See Tables A16 in appendix A for statistics.

Since 2008-09, the churn rate decreased for homeless students in all three Challenged School Divisions and in Virginia statewide as seen in Figure 18 (first panel). It also decreased among all other students except in Petersburg where the churn rate increase 17% which is attributable to a spike in 2014-15.

There is no consistent pattern in the change in the churn rate between homeless and other students across the three grade clusters across the three Challenged School Divisions (Figure 18, second through fourth panels). In Norfolk, churn decreased among homeless and, to a lesser extent, non-homeless students in all grade clusters except among homeless middle school students for whom the churn rate increased 32% (or 24 churn events). In Petersburg, churn increased among non-homeless students in all grade clusters and for homeless middle school students but decreased among homeless elementary and high school students. Only in Richmond did churn become less common for homeless and other students in all three grade clusters.

10 The increase between the 8th and 9th grades in Petersburg is related to 10th graders exiting Petersburg High School to enroll as 9th graders in Vernon Johns Junior High School.

50

60

70

80

90

100

Sta

ble

Enro

llment (%

)

KG 1 2 3 4 5 6 7 8 9 10 11 12

Grade

Homeless Students

50

60

70

80

90

100

Sta

ble

Enro

llment (%

)

KG 1 2 3 4 5 6 7 8 9 10 11 12

Grade

All Other Students

Norfolk Petersburg Richmond Virginia

23

Figure 18. Churn rates by division, grade cluster, homelessness, and year, 2008-09 to 2014-15 SOURCE: See Table A7 and A9 in appendix A for statistics.

When Churn Occurs. Having examined the trends and patterns in stability and churn rates,

we again turn to the timing of school transfers. Again, we present results for 2014-15 only as the distributions have changed very little since 2008-09. (Statistics for other years are available in Tables A10-12 in appendix A.) Consistent with the findings for all students above, churn for both homeless and all other students is concentrated in the beginning portion of the month as shown in Figure 19. Homeless students’ moves tend to be somewhat more spread out over the month, though, with the exception

24

of Petersburg whose homeless students’ churn rate by time of month is nearly identical to all other students.

Figure 19. Timing of churn by division, time of month, homelessness, and year, 2014-15 NOTE: The beginning of the month includes the 1st through 10th day, the middle of the month includes the 11th through the 20th of the month, and the end of the month includes the 21st through 31st day.

SOURCE: See Tables A12 in appendix A for statistics.

The distributions of school moves across the months and season are very similar between homeless and other students and thus very similar to the distributions among all students shown above in Figure 9. (See Table A12 for statistics).

Where Students Move. There are no appreciable difference between homeless and all other students in the divisions to which they move when they leave a Challenged School Division (see Table A13 in Appendix A). In Petersburg, however, homeless students are more likely to transfer to non-neighboring divisions than are other students (44 versus 31%). As shown in Table A14 in Appendix A, the divisions which receive students from the Challenged School Divisions during the year are by and large the same divisions which send students to the Challenged School Divisions. Conclusion

In this report we examined trends in two measures of within-year mobility in Virginia (the stability and churn rates) and in the three Challenged School Divisions and found a considerable amount of school mobility. Between 2004-05 and 2014-15, the stability rate increased slightly in Norfolk to 88% and Virginia statewide to 94%. Richmond experienced a larger increase to 87% while the stability rate in Petersburg decreased slightly to 88%. Between 2004-05 and 2014-15, the churn rate meaningfully decreased to 26 events per 100 students in Norfolk, to 31 events in Richmond, and to 16 events among all Virginia students. The churn rate remained rather steady in Petersburg (37 in 2014-15).

We also highlight higher instances of mobility among homeless students relative to other students. In 2014-15, the 70% stability rate among homeless students in Virginia was 25% lower than the rate for all other students. Homeless students in Norfolk are 28% less likely to have stable enrollment, 24% less likely in Richmond, and 11% less likely in Petersburg. Similarly, the churn rates

56.1

28.0

15.9

62.0

20.5

17.5

61.2

21.5

17.3

50.9

29.9

19.2

0

20

40

60

80

En

terin

g a

nd/o

r E

xitin

g (

%)

NPS PCPS RPS Virginia

Homeless Students

67.8

19.0

13.2

61.6

20.7

17.7

68.3

18.8

13.0

56.0

27.6

16.3

0

20

40

60

80

En

terin

g a

nd/o

r E

xitin

g (

%)

NPS PCPS RPS Virginia

All Other Students

Beginning of month Middle of month End of month

25

are many times higher among homeless students than other students: 3.7 times higher in Norfolk, 1.7 times higher in Petersburg, and 3.1 times higher in Richmond.

Our analysis serves as an initial examination of within-year student mobility in Virginia and is intended to support a nascent policy and research agenda within the commonwealth. It raises questions which future research should endeavor to unpack so as to inform policies and programs. How does mobility in Virginia compare to mobility in other states? There are likely lessons to be learned from states with both lower and higher mobility; yet, comparing mobility rates across states is complicated by variations in how states calculate their mobility statistics. Not all states, for example, account for mobility throughout the entire school year, from the first to the last day of the school year. Rather, many begin tracking mobility starting on the state’s fall enrollment day (typically the end of September or start of October) and stop tracking mobility on a specific date in May or June by which time not all schools have closed for the summer. States also differ in the enrollment figure used to calculate a churn rate. Some states use the fall enrollment figures, others use the average daily membership, and still others use the total number of students ever enrolled during the school year.

What are the causes of mobility in Virginia? There are many factors that lead students to make non-promotional moves and effective policies and programs will be designed to address those factors. Rumberger (2015) categorizes school mobility along two dimensions – whether the school or the family/student initiated the school change and whether the school change was voluntary or involuntary. For example, students often must change schools when their families change residences. This family-initiated cause of student mobility may be voluntary (the family moves to accept a job promotion or to enroll their child in a better school) or involuntary (the family moves because of a lost job, home foreclosure, eviction, or because they are homeless). Schools initiate voluntary mobility, for example, when they are required under accountability systems to inform parents of their right to transfer their child to another school. Involuntary school-initiated mobility can result when schools close or when overcrowding requires students be reassigned to different schools. Given data limitations, we are only able to examine one factor – homelessness. Richer data are essential to identifying mobility’s causes in Virginia.

Whatever policies and programs Virginia and school divisions choose to implement to address mobility should be designed around at least two goals: to reduce instances of mobility and, when mobility does occur, to ameliorate its negative consequences. This report leverages available data to provide valuable information to inform these policy discussions.

26

References Alexander, K. L., Entwisle, D. R., & Dauber, S. L. (1996). Children in motion: School transfers and

elementary school performance. The Journal of Educational Research, 90(1): 3-12. Buckner, J. C., Bassuk, E. L., & Weinreb, L. (2001). Predictors of academic achievement among

homeless and low-income housed children. Journal of School Psychology, 39(1): 45-69. Crowley, S. (2003). The affordable housing crisis: Residential mobility of poor families and school

mobility of poor children. The Journal of Negro Education, 72(1): 22-38. Dupere, V., Archambault, I., Leventhal, T., Dion, E., & Anderson, S. (2015). School mobility and

school-age children’s social adjustment. Developmental Psychology, 51(2): 197-210. Fantuzzo, J. W., LeBoeuf, W. A., Chen, C., Rouse, H. L., & Culhane, D. P. (2012). The unique and

combined effects of homelessness and school mobility on the educational outcomes of young children. Educational Researcher, 41(9): 393-402.

Gasper, J., DeLuca, S., & Estacion, A. (2012). Switching schools: Revisiting the relationship between

school mobility and high school dropout. American Educational Research Journal, 49(3): 487-519.

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.

Hanushek, E. A., Kain, J. F., & Rivkin, S. G. (2004). Disruption versus Tiebout improvement: The

costs and benefits of switching schools. Journal of Public Economics, 88: 1721-1746. Herbers, J. E., Reynolds, A. J., & Chen, C. (2013). School mobility and developmental outcomes in

young adulthood. Development and Psychopathology, 25: 501-515. James, B. W., & Lopez, P. D. (2003). Transporting homeless students to increase stability: A case

study of two Texas districts. The Journal of Negro Education, 72(1): 126-140. Julianelle, P. F., & Foscarinis, M. (2003). Responding to the school mobility of children and youth

experiencing homelessness: The McKinney-Vento Act and beyond. The Journal of Negro Education, 72(1): 39-54.

Kerbow, D. (1996). Patterns of urban student mobility and local school reform. Journal of Education

for Students Placed at Risk, 1(2): 147-169. Miller, P. M. (2011). A critical analysis of the research on student homelessness. Review of Educational

Research, 81(3): 308-337. Miller, P. M. (2015). Families’ experiences in different homeless and highly mobile settings:

Implications for school and community practice. Education and Urban Society, 47(1): 3-32.

27

Rafferty, Y., Shin, M., & Weitzman, B. C. (2004). Academic achievement among formerly homeless adolescents and their continuously housed peers. Journal of School Psychology, 42(3): 179-199.

Reynolds, A. J., Chen, C., & Herbers, J. E. (2009). School mobility and educational success: A

research synthesis and evidence on prevention. Washington, D.C.: Workshop on the Impact of Mobility and Change on the Lives of Young Children, Schools, and Neighborhoods, Board on Children, Youth, and Families, National Research Council.

Rumberger, R. W. (2015). Student mobility: Causes, consequences, and solutions. Boulder, CO:

National Education Policy Center. Rumberger, R. W., Larson, K. A., Ream, R. A., & Palardy, G. J. (1999). The educational

consequences of mobility for California students and schools. Berkeley, CA: Policy Analysis for California Education.

South, S. J., & Haynie, D. L. (2004). Friendship networks of mobile adolescents. Social Forces, 83(1):

315-350. Tierney, W. G., Gupton, J. T., & Hallett, R. E. (2008). Transitions to adulthood for homeless

adolescents: Education and public policy. Los Angeles: Center for Higher Education Policy Analysis.

28

Appendix A

Table A1. Percent of students who are enrolled at the beginning of the school year by division, homelessness, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Norfolk Public Schools

All Students 92.7 92.6 92.9 93.1 92.9 93.7 93.7 93.8 93.7 93.9 93.9

Homeless Students 79.3 76.8 77.2 76.1 70.4 75.9 73.9

All Other Students 93.1 93.9 94.0 94.1 94.1 94.2 94.2

Petersburg City Public Schools

All Students 93.4 92.4 92.2 92.4 91.3 93.3 94.2 90.3 94.5 94.3 87.5



Richmond Public Schools

All Students 90.8 92.1 91.3 91.0 90.9 92.6 92.3 91.4 92.8 93.0 94.4


All Other Students 91.5 93 92.9 92.0 93.2 93.6 94.9

Virginia All Students 94.5 94.6 94.6 94.4 94.3 95.3 95.6 95.1 95.3 95.4 95.4



Table A2. Percent of students who are enrolled at the end of the school year by division, homelessness, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


All Students 92.6 92.2 92.5 93.0 93.4 94.0 93.8 93.9 94.4 94.5 94.1




All Students 93.1 93.4 93.4 94.9 94.8 94.4 94.9 94.9 95.8 94.6 95.4




All Students 88.8 89.7 93.3 93.9 95.0 94.5 94.6 95.2 95.5 96.0 95.7



Virginia

All Students 94.9 95.2 95.4 95.7 96.1 96.2 96.3 96.3 96.4 96.4 96.4



29

Table A3. Percent of students with stable enrollment by division, homelessness, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


All Students 87.5 87.6 86.8 87.2 87.7 88.4 88.4 88.1 88.8 88.8 88.3




All Students 87.8 87.5 86.6 88.3 88.3 89.1 87.5 87.4 88.3 86.5 87.7




All Students 80.5 82.1 84.2 84.8 85.7 86.2 85.7 86.5 87.4 88.7 86.7






30

Table A4: Percent of students with stable enrollment by division and grade, 2014-15

Kinder-garten

1st Grade

2nd Grade

3rd Grade

4th Grade

5th Grade

6th Grade

7th Grade

8th Grade

9th Grade

10th Grade

11th Grade

12th Grade


All Students 85.6 86.8 88.8 86.8 88.2 90.1 89.3 88.8 90.4 84.6 89.6 91.3 92.6


All Students 86.0 84.9 84.1 84.2 90.5 86.7 87.7 93.0 91.3 91.0 85.4 87.6 93.2


All Students 86.6 86.6 86.4 88.0 85.7 86.8 89.1 86.9 86.7 82.6 85.1 86.1 91.7

Virginia

All Students 91.9 92.3 92.8 93.2 93.7 94.5 95.1 94.8 95.0 93.6 93.9 94.2 92.0

31

Table A5. Percent of students with stable enrollment by division, homelessness, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


All Students 87.5 87.6 86.8 87.2 87.7 88.4 88.4 88.1 88.8 88.8 88.3




All Students 87.8 87.5 86.6 88.3 88.3 89.1 87.5 87.4 88.3 86.5 87.7




All Students 80.5 82.1 84.2 84.8 85.7 86.2 85.7 86.5 87.4 88.7 86.7






Table A6. Percent of students with stable enrollment by division, grade cluster, homelessness, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


K-5 Students All Students 87.2 88.1 87.1 87.1 87.2 88.1 88.1 87.6 88.0 87.9 87.6



6-8 Students

All Students 87.8 88.0 87.3 88.1 89.4 90.0 89.5 89.6 90.0 90.2 89.5



9-12 Students

All Students 87.5 86.3 85.8 86.5 87.3 87.7 87.9 87.7 89.6 89.5 88.7




K-5 Students

All Students 86.1 85.1 84.2 86.6 85.3 87.7 86.0 85.9 86.8 85.3 85.9



6-8 Students

All Students 89.9 90.9 88.4 87.5 91.6 93.5 90.7 91.3 91.0 88.4 90.8



(continued on next page)

32

Table A6. Percent of students with stable enrollment by division, grade cluster, homelessness, and year, 2004-05 to 2014-15 (cont.)

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

9-12 Students

All Students 88.7 88.4 89.1 91.6 91.2 88.4 88.1 87.2 89.1 87.5 89.0




K-5 Students

All Students 86.8 88.3 86.7 87.5 86.8 88.0 87.4 87.6 89.4 89.9 86.7



6-8 Students

All Students 81.7 85.3 83.7 82.9 86.0 86.6 86.2 86.3 84.9 86.5 87.6



9-12 Students

All Students 67.0 66.7 79.8 81.1 83.2 82.4 81.9 84.4 85.1 88.0 86.1



Virginia

K-5 Students

All Students 92.3 92.4 92.7 92.7 92.9 93.2 93.2 93.2 93.2 93.1 93.1



6-8 Students

All Students 93.5 93.6 93.8 94.1 94.5 94.8 94.8 94.8 94.8 95.0 95.0



9-12 Students

All Students 91.2 91.6 91.7 92.2 92.9 92.9 93.2 93.3 93.5 93.8 93.4



33

Table A7. Number of churn events (school entries or exits) per 100 students by division, homelessness, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


All Students 29.0 29.4 30.2 28.9 28.7 26.2 27.0 27.0 25.7 25.5 26.3




All Students 27.8 30.1 32.0 29.3 31.6 28.6 30.2 37.2 27.7 30.2 36.6




All Students 46.2 41.3 42.1 40.1 38.9 35.1 36.7 35.0 31.9 28.4 30.7



Virginia

All Students 19.3 19.2 19.0 18.9 18.6 16.7 16.3 16.5 16.1 15.8 15.8



34

Table A8. Number of churn events (school entries or exits) per 100 students by division and grade, 2014-15

Kinder-garten

1st Grade

2nd Grade

3rd Grade

4th Grade

5th Grade

6th Grade

7th Grade

8th Grade

9th Grade

10th Grade

11th Grade

12th Grade


All Students 36.4 28.5 25.4 27.5 25.0 23.0 23.7 23.4 21.5 32.4 26.6 20.9 15.9


All Students 42.6 47.1 44.9 38.8 32.0 35.3 44.1 37.6 25.1 35.1 37.4 22.5 14.7


All Students 35.8 30.8 29.5 27.5 30.0 29.4 29.8 30.1 31.1 38.8 30.1 32.7 20.5

Virginia

All Students 23.5 19.2 17.9 17.0 15.7 14.0 12.7 13.0 12.6 16.6 14.5 13.5 14.8

35

Table A9. Number of churn events (school entries or exits) per 100 students by division, homelessness, grade cluster, and year, 2004-05 to 2014-15

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014


K-5 Students

All Students 30.9 30.3 31.9 31.0 30.8 27.9 28.4 29.3 27.5 27.2 28.0



6-8 Students

All Students 27.3 29.0 28.6 26.9 26.2 23.1 24.6 23.0 23.4 23.9 22.9



9-12 Students

All Students 27.0 28.2 28.6 26.6 26.6 25.5 26.3 25.7 24.1 23.5 25.6




K-5 Students

All Students 32.4 35.7 38.2 34.7 37.1 30.4 32.7 39.3 29.9 33.6 40.8



6-8 Students

All Students 21.7 21.6 25.5 28.5 24.1 22.7 23.3 29.3 22.0 25.5 35.4



9-12 Students

All Students 26.2 28.4 27.4 21.1 27.6 29.6 30.8 39.5 27.9 27.1 28.4




K-5 Students

All Students 35.5 31.8 35.1 33.6 34.7 30.2 32.3 31.9 26.6 25.4 30.6



6-8 Students

All Students 47.5 38.5 44.2 44.6 38.8 32.6 33.6 32.9 37.4 32.8 30.3



9-12 Students

All Students 64.6 62.1 53.2 48.6 46.8 46.0 47.9 43.5 38.6 31.4 31.2



Virginia

K-5 Students

All Students 20.3 20.4 20.1 20.3 20.3 18.1 17.8 18.3 18.0 18.0 17.9




36

Table A9. Number of churn events (school entries or exits) per 100 students by division, homelessness, grade cluster, and year, 2004-05 to 2014-15 (cont.)

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

6-8 Students

All Students 16.8 16.8 16.3 15.9 15.3 13.5 13.2 13.5 13.1 12.8 12.7



9-12 Students

All Students 19.7 19.3 19.4 19.1 18.3 16.9 16.2 16.2 15.6 14.7 14.9



37

Table A10. Distribution of churn events (school entries or exits) across months by division, homelessness, and year, 2004-05 to 2014-15

2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)


All Students 55.5 56.2 56.1 57.1 58.7 56.1 56.3 57.7 58.2 56.9 59.6



All Students 9.2 9.1 8.7 8.4 9.4 8.4 8.1 8.3 9.3 8.4 8.4



All Students 6.7 6.7 7.5 7.0 5.8 5.8 7.2 5.9 6.2 5.9 6.4



All Students 4.3 4.3 3.7 4.3 4.3 3.7 3.5 3.1 3.2 4.2 4.4



All Students 7.5 8.1 9.4 8.5 7.3 8.2 7.5 8.5 7.2 7.0 6.5



All Students 6.8 5.7 5.4 5.3 5.7 6.8 6.2 6.4 4.8 6.6 4.8



All Students 3.8 4.7 4.7 4.0 4.9 5.3 5.1 5.0 5.3 5.2 5.2



All Students 4.3 3.3 2.8 3.9 2.3 3.7 3.6 2.8 3.4 3.7 2.8



All Students 1.8 1.8 1.5 1.5 1.4 1.7 2.3 2.2 2.1 1.7 1.5



All Students 0.2 0.2 0.1 0.1 0.2 0.3 0.2 0.2 0.3 0.5 0.3




All Students 7.6

Homeless Students 8.7

All Other Students 7.4

All Students 17.3

Homeless Students 17.1

All Other Students 17.3

All Students 58.4 54.8 57.8 54.9 58.0 53.1 51.8 54.9 50.8 57.3 39.8




38

Table A10. Distribution of churn events (school entries or exits) across months by division, homelessness, and year, 2004-05 to 2014-15 (cont.)

2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)

All Students 9.2 11.0 8.8 13.1 8.9 10.0 10.8 10.1 7.6 6.6 5.5



All Students 6.0 8.0 7.3 5.6 6.6 6.5 8.7 4.7 6.8 5.3 4.5



All Students 3.9 2.5 3.7 3.0 5.0 4.3 2.5 3.5 4.4 3.7 3.6



All Students 7.2 7.1 6.5 6.3 8.4 8.6 5.8 6.3 8.8 8.7 6.1



All Students 5.4 6.7 6.7 6.3 5.5 6.3 9.5 9.2 9.0 6.7 5.9



All Students 4.1 4.2 5.0 3.4 3.6 4.6 5.4 5.6 5.9 4.9 4.5



All Students 3.7 2.6 2.9 5.1 2.4 4.0 2.8 2.3 4.4 3.6 3.3



All Students 2.2 2.5 1.2 1.9 1.3 2.3 2.5 3.0 2.1 2.7 1.7



All Students 0.0 0.6 0.1 0.4 0.3 0.2 0.2 0.4 0.2 0.5 0.2




All Students 0.1 0.2 0.4 0.2 0.7

Homeless Students 0.1 0.0 0.2 0.0 0.4

All Other Students 0.1 0.2 0.4 0.3 0.7

All Students 57.1 57.3 53.7 52.2 54.3 52.8 52.1 51.7 53.4 55.0 58.4



All Students 8.8 8.0 8.6 9.5 8.9 9.2 8.1 9.9 9.3 9.8 8.3



All Students 7.5 7.5 8.0 7.0 7.2 7.6 7.7 7.3 7.0 6.4 5.9



All Students 2.6 2.8 3.2 3.6 4.9 4.1 3.5 3.4 3.9 4.6 4.4




39


2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)

All Students 6.2 7.4 7.7 8.8 7.2 7.7 7.4 8.7 8.4 5.7 7.4



All Students 6.2 6.8 8.6 8.0 7.6 6.7 9.4 6.8 6.8 5.5 4.3



All Students 4.5 4.4 4.8 4.1 4.9 6.3 5.7 5.6 5.0 5.2 6.0



All Students 3.9 3.0 2.6 4.6 3.1 3.2 3.2 3.9 3.3 4.9 2.9



All Students 2.7 2.1 2.3 1.7 1.5 1.9 2.4 2.2 2.4 2.0 1.7



All Students 0.4 0.8 0.4 0.5 0.4 0.6 0.3 0.3 0.2 0.6 0.2



Virginia

All Students 1.1 1.2 1.5 2.0 2.3 1.3 1.1 1.0 1.3 0.8 0.5



All Students 12.6 14.0 12.4 13.2 13.8 13.1 13.1 15.2 16.8 13.9 14.5



All Students 43.5 42.3 42.1 40.9 41.3 40.7 42.5 39.8 38.2 42.2 42.5



All Students 7.4 7.9 8.2 8.3 7.6 7.4 7.1 7.5 7.8 7.7 7.5



All Students 7.2 6.8 6.8 6.5 5.9 6.8 6.9 6.7 6.6 5.9 5.9



All Students 3.5 3.2 3.4 3.4 4.2 4.0 3.4 3.4 3.5 4.0 4.3



All Students 8.1 8.7 9.6 9.4 8.4 8.6 8.0 9.1 9.1 7.9 8.8



All Students 5.7 5.7 5.5 5.7 6.1 5.9 6.6 6.2 5.5 6.1 4.8




40


2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)

All Students 4.4 4.8 4.8 4.4 5.0 5.5 5.3 4.9 4.5 5.1 5.6



All Students 4.1 3.1 3.6 4.3 3.4 4.0 3.4 3.7 4.4 3.8 3.2



All Students 2.0 2.0 1.9 1.8 1.8 2.1 2.2 2.1 2.0 2.2 1.8



All Students 0.3 0.3 0.3 0.3 0.4 0.5 0.4 0.4 0.4 0.5 0.6



Table A11. Distribution of churn events (school entries or exits) across season by division,

homelessness, and year, 2004-05 to 2014-15

2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)


Fall All Students 71.4 72.0 72.4 72.5 73.9 70.3 71.6 71.8 73.7 71.2 74.4



Winter

All Students 22.4 22.8 23.3 22.0 22.1 23.9 22.3 23.0 20.5 23.0 20.9



Spring

All Students 6.2 5.2 4.4 5.4 4.0 5.7 6.1 5.2 5.8 5.9 4.6




Fall

All Students 73.6 73.8 73.8 73.6 73.5 69.6 71.3 69.7 65.2 69.2 74.7



Winter

All Students 20.5 20.5 21.9 19.0 22.5 23.8 23.2 24.7 28.1 23.9 20.1



Spring

All Students 5.9 5.7 4.2 7.4 4.0 6.5 5.5 5.7 6.7 6.9 5.2




41

Table A11. Distribution of churn events (school entries or exits) across season by division, homelessness, and year, 2004-05 to 2014-15 (cont.)

2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)


Fall

All Students 73.4 72.7 70.3 68.7 70.4 69.6 68.1 69.1 70.0 71.4 73.2



Winter

All Students 19.6 21.3 24.3 24.4 24.6 24.8 26.0 24.5 24.1 21.0 22.0



Spring

All Students 7.0 5.9 5.4 6.8 5.0 5.7 5.9 6.4 5.9 7.5 4.8



Virginia Fall

All Students 71.9 72.3 70.9 70.8 70.8 69.3 70.6 70.2 70.7 70.4 70.9



Winter

All Students 21.7 22.3 23.4 22.8 23.6 24.0 23.3 23.6 22.6 23.0 23.6



Spring

All Students 6.4 5.4 5.8 6.4 5.5 6.7 6.0 6.2 6.8 6.5 5.5



Note: Seasons are defined as follows: fall includes July through November, winter includes December through March, and spring includes April through June.

42

Table A12. Distribution of churn events (school entries or exits) across portion of month by division, homelessness, and year, 2004-05 to 2014-15

2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)


Beginning of Month

All Students 63.0 58.6 58.7 63.9 67.5 59.9 60.9 59.3 65.4 66.0 67.0



Middle of Month

All Students 22.6 26.3 25.1 21.6 17.9 25.8 23.4 25.1 21.5 21.4 19.6



End of Month

All Students 14.4 15.1 16.2 14.5 14.6 14.3 15.6 15.6 13.1 12.6 13.3




Beginning of Month

All Students 63.8 61.0 60.7 63.9 62.4 55.8 65.3 51.8 66.2 63.2 61.7



Middle of Month

All Students 24.2 24.4 24.4 22.7 23.2 27.8 22.5 32.5 19.9 25.3 20.6



End of Month

All Students 12.0 14.6 14.8 13.4 14.4 16.3 12.2 15.6 13.8 11.5 17.7




Beginning of Month

All Students 60.5 58.6 55.8 60.9 65.1 53.8 59.1 55.3 60.7 63.8 67.2



Middle of Month

All Students 25.3 25.4 29.2 24.4 20.6 29.7 25.8 26.6 24.3 21.1 19.2



End of Month

All Students 14.3 16.0 15.0 14.7 14.3 16.4 15.1 18.1 15.0 15.1 13.6




43

Table A12. Distribution of churn events (school entries or exits) across portion of month by division, homelessness, and year, 2004-05 to 2014-15 (cont.)

2004

(%)

2005

(%)

2006

(%)

2007

(%)

2008

(%)

2009

(%)

2010

(%)

2011

(%)

2012

(%)

2013

(%)

2014

(%)

Virginia

Beginning of Month

All Students 55.3 58.6 57.2 60.6 62.1 57.7 59.9 54.1 56.4 60.5 60.8



Middle of Month

All Students 22.2 24.9 27.2 25.2 25.4 29.4 26.3 29.1 29.5 28.5 30.3



End of Month

All Students 22.5 28.3 27.5 25.9 24.0 23.5 24.3 27.1 24.0 20.6 18.1



Note: Each month is divided into three portions as follows: the beginning of the month includes the 1st through 10th day, the middle of the month includes the 11th through the 20th of the month, and the end of the month includes the 21st through 31st day.

44

Table A13. Ten divisions to which most students move during the year by division and homelessness, 2012-13 to 2014-15

Norfolk Public Schools Petersburg City Public Schools Richmond Public Schools

Division % of

moves Division % of

moves Division % of

moves

All Students

Virginia Beach City 37.1 Chesterfield County 19.5 Henrico County 43.2

Chesapeake City 22.2 Hopewell City 16.1 Chesterfield County 34.8

Portsmouth City 13.1 Prince George County 14.4 Petersburg City 2.3

Hampton City 6.1 Dinwiddie County 10.8 Hopewell City 1.7

Newport News City 4.7 Richmond 9.3 Hanover County 1.5

Suffolk City 4.4 Henrico County 7.1 Newport News City 1.3

York County 1.0 Colonial Heights City 5.8 Norfolk 0.9

Fairfax County 1.0 Sussex County 4.6 Fairfax County 0.8

Richmond 0.8 Greensville County 1.4 Caroline County 0.7

Chesterfield County 0.7 Brunswick County 1.1 Dinwiddie County 0.7

Homeless Students



Portsmouth City 12.2 Richmond 16.8 Petersburg City 2.9

Newport News City 7.5 Dinwiddie County 5.9 Hopewell City 2.1

Hampton City 6.3 Sussex County 5.9 Newport News City 2.1

Northampton County 2.4 Prince George County 5.0 Charles City County 1.5

Fairfax County 2.0 Henrico County 4.0 Fairfax County 1.2

Suffolk City 2.0 Colonial Heights City 4.0 Hanover County 1.2

York County 1.6 W’burg-James City County 4.0 Dinwiddie County 0.9

Chesterfield County 1.2 Nottoway County 2.0 Nottoway County 0.9

All Other Students


Chesapeake City 22.7 Prince George County 16.2 Chesterfield County 36.4

Portsmouth City 13.1 Hopewell City 15.5 Petersburg City 2.2


Suffolk City 4.7 Richmond 8.0 Hanover County 1.5

Newport News City 4.4 Henrico County 7.5 Newport News City 1.1

York County 1.0 Colonial Heights City 6.0 Norfolk 0.9

Fairfax County 0.9 Sussex County 4.4 Caroline County 0.9

Richmond 0.7 Greensville County 1.5 Virginia Beach City 0.8

Isle of Wight County 0.7 Brunswick County 1.1 Fairfax County 0.7

45

Table A14. Ten divisions from which most students move into a Challenged School Division during the year by division and homelessness, 2012-13 to 2014-15

Norfolk Public Schools Petersburg City Public Schools Richmond Public Schools

Division % of

moves Division % of

moves Division % of

moves

All Students



Portsmouth City 12.0 Richmond City 11.9 Petersburg City 2.9

Newport News City 5.4 Prince George County 9.0 Newport News City 1.6


Suffolk City 3.5 Colonial Heights City 4.9 Prince William County 0.9

Isle of Wight County 1.0 Henrico County 4.3 Hampton City 0.9

Richmond City 1.0 Sussex County 3.4 Hanover County 0.8

Fairfax County 0.7 Brunswick County 1.6 Nottoway County 0.7

York County 0.7 Franklin City 1.3 Norfolk City 0.7

Homeless Students




Newport News City 7.1 Sussex County 6.4 Suffolk City 2.0

Suffolk City 4.3 Fairfax County 5.1 Albemarle County 1.6

Hampton City 3.8 Prince George County 5.1 Colonial Heights City 1.6

Henrico County 2.4 Colonial Heights City 5.1 Hanover County 1.3

Accomack County 1.9 Brunswick County 3.9 Hopewell City 1.3

Lynchburg City 1.4 Franklin City 3.9 Norfolk City 1.3

Manassas City 1.4 Dinwiddie County 2.6 Fairfax County 1.0

All Other Students




Newport News City 5.2 Prince George County 10.0 Newport News City 1.7


Suffolk City 3.6 Henrico County 5.0 Prince William County 0.9

Isle of Wight County 1.1 Colonial Heights City 5.0 Hampton City 0.9

Richmond City 1.0 Sussex County 2.8 Hanover County 0.8

Fairfax County 0.8 Greensville County 1.1 Cumberland County 0.7

Prince William County 0.7 Stafford County 1.1 Nottoway County 0.7

46

Table A15. Percent of students homeless by division, grade cluster, and year, 2008-09 to 2014-15

2008 2009 2010 2011 2012 2013 2014


All students 1.5 1.4 1.9 1.8 2.1 2.1 1.8

K-5 2.0 1.5 2.0 2.0 2.3 2.4 2.2

6-8 1.4 1.5 1.9 1.8 2.1 2.2 1.9

9-12 0.8 1.0 1.6 1.3 1.8 1.3 1.1


All Students 7.5 11.3 6.6 8.4 9.9 10.2 10.8

K-5 10.1 14.4 7.4 10.0 11.4 11.4 12.1

6-8 7.5 11.2 8.3 9.1 10.7 11.0 11.3

9-12 3.0 5.7 3.7 4.7 6.2 7.0 7.6


All Students 4.0 4.5 5.3 6.4 4.7 5.7 5.6

K-5 4.5 5.3 5.9 8.1 4.8 5.7 5.5

6-8 4.4 4.4 5.8 5.0 5.2 6.3 5.9

9-12 2.6 3.1 3.9 4.2 3.9 4.9 5.6

Virginia

All Students 1.1 1.2 1.4 1.5 1.5 1.5 1.5

K-5 1.4 1.5 1.7 1.8 1.8 1.7 1.7

6-8 1.1 1.1 1.3 1.4 1.4 1.5 1.3

9-12 0.8 0.9 1.1 1.2 1.3 1.3 1.3

47

Table A16: Percent of students with stable enrollment by division, homelessness, and grade, 2012-13 to 2014-15

Kinder-garten

1st Grade

2nd Grade

3rd Grade

4th Grade

5th Grade

6th Grade

7th Grade

8th Grade

9th Grade

10th Grade

11th Grade

12th Grade


Homeless Students 54.6 60.1 58.0 63.2 58.3 68.3 56.5 54.8 62.5 62.0 71.4 70.0 73.2

All Other Students 86.7 87.7 88.7 88.0 88.5 90.4 90.1 90.3 90.7 85.9 88.7 92.5 93.5







Virginia



Table A17. Number of churn events (school entries or exits) per 100 students by division, homelessness, and grade, 2012-13 to 2014-15

Kinder-garten

1st Grade

2nd Grade

3rd Grade

4th Grade

5th Grade

6th Grade

7th Grade

8th Grade

9th Grade

10th Grade

11th Grade

12th Grade










Virginia



48

Appendix B

According to VDOE’s Specifications for Completing the Student Record Collection, 2015-2016, the four categories of homeless students are defined as follows:

1. Unsheltered. Children and youth living in abandoned buildings, campgrounds and vehicles, space not meant for habitation, trailers or FEMA trailers, cars, bus and train stations, and abandoned in the hospital. Unsheltered may include substandard or inadequate housing that does not easily fit into any category as it is not governed by a specific definition and is judged on a case-by-case basis. An inadequate dwelling may shelter but it is not adequate housing.

2. Shelters. Children and youth living in shelters and transitional housing programs (homeless and domestic violence programs). Children and youth awaiting foster care placement.

3. Doubled-up. Children and youth (including runaway youth or unaccompanied youth) who live with relatives or friends due to being homeless.

4. Hotel/Motel. Children and youth living in hotels/motels due to a lack of alternative adequate accommodations.

Source: Division of Technology (July 29, 2015). Specifications for Completing the Student Record Collection, 2015-2016. Richmond, Virginia: Virginia Department of Education.

EdPolicyWorks Reports Series No. 5. October 2017Series available at: http://curry.virginia.edu/edpolicyworks/reports EdPolicyWorks Reports have not been peer-reviewed. Report directly retrieved from: http://curry.virginia.edu/uploads/epw/EdPolicyWorks_Report_5_VA_Student_Mobility.pdf

EdPolicyWorks University of Virginia

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