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Running head: THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS IN
PENNSYLVANIA’S SCHOOL ACCOUNTABILITY SYSTEM
A Doctoral Capstone Project
Submitted to the School of Graduate Studies and Research
Department of Secondary Education and Administrative Leadership
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Education
Brian Michael Stamford
California University of Pennsylvania
July 2020
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
©Copyright by
Brian Michael Stamford
All Rights Reserved
July 2020
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Acknowledgements
First, I would like to thank God for the grace and blessings that are bestowed
upon me every day; without such peace of mind and sound health this would not have
been possible.
The completion of this work would not have been possible without the guidance
of many people, some of whom I would like to acknowledge in this section, in no
particular order. I would like to thank my faculty chair, Dr, Kevin Lordon. Kevin, I
appreciate your patience in guiding me through the challenges of this task, as well as the
motivation you have provided. I also thank my external committee member, Dr. Paul
Cindric for his perspective, intellect and advice on not only the completion of this project
but also in the workplace. I appreciate the gentle pushing and encouragement by my
supervisor, Rosanne Javorsky, who planted the seed for my embarking on this journey.
Several people had an impact on me professionally early in my career. I thank
Art Molitor, who early on taught me the ‘art’ of teaching, reminding me to put down the
lesson plan and connect with the students. I appreciate Dr. David Myers for coming into
my classroom one day and encouraging me to take a step towards educational
administration; I may not have considered the possibilities without that visit.
I would like to thank my parents Larry and Susan Stamford for the sacrifices they
made to provide a stable foundation for me, as well as their demonstrated faith in me. To
my siblings, Robin Leighty and Craig Stamford, I truly do appreciate your tolerance for
some of my first-born traits. I would also like to acknowledge the mother of my children,
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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Karin Stamford, for her work and sacrifice in helping me raise two amazing young men.
I thank Bob and Carlene Painter for helping me to believe in myself and to see the
importance of ‘magic’ in the world.
To my children Nolan and Nathan Stamford – I hope that one day you will have
children of your own so that you will understand how important you are to me. Thank
you for always being there to play, explore, laugh, and now that you are young men, talk
about the world in which we live and even give advice. You are the reason I strive to be
a better person every day. Just remember – if you treat others with respect and always
give your best every day, you can’t ever be upset with yourself.
Rebecca Boozer, I thank you for the mental stimulation, picking me up when I
needed it, and for challenging me when I thought I didn’t need it. I am a better person
now because of you.
Finally, I appreciate the unwavering mantra of my cooperating teacher, Jim Egros.
No matter the situation, the possibility of personal gain or loss, economics, politics, or
self-serving behaviors, Jim always brought conversations and decisions back to what
really mattered with one question – but what’s best for the kids? Jim – in twenty five
years, I haven’t stopped reminding every teacher, administrator, board member, and
parent to keep that as a compass.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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Table of Contents
Acknowledgements
iv
List of Tables
xiii
List of Figures
xiv
Abstract
xv
CHAPTER I. Introduction
1
Background
1
Identification of the Capstone Focus
2
Research Questions
2
Expected Outcomes
3
Fiscal Implications
4
Summary
5
CHAPTER 2. Review of Literature
6
Mobility Defined
6
Mobility
7
Lack of common measurement and definitions
8
Causes of mobility
9
Mobility’s effect on achievement
10
Mobility affects attendance, impacting achievement
13
Mobility’s effect on the system
13
Theoretical Foundations Impacting Mobility
15
Self-concept theory
15
Self-actualization theory
17
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Constructivism
19
Psychological theory
19
Developmental-ecological theory
19
Social-cultural theory
21
Relational framework
21
Policy and Practice
23
Systems of accountability
23
Pennsylvania’s system of accountability
23
School improvement identification in Pennsylvania
24
Stakeholder perceptions
25
Educational accountability systems across the nation
26
Staff practice and attitudes towards mobile students
29
Administrative practice towards mobility
31
System-level practices impacting mobility
32
Policy that impacts mobility
33
Summary
36
CHAPTER 3. Methodology
Purpose
37
37
Problem
38
Research questions
38
Setting and participants
38
Intervention and Research plan
40
Connection to fiscal implications
42
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Research Design, Methods & Data Collection
viii
43
Multiple forms of data
43
Timing of the data collection
47
Choices and organization of the data
48
Achievement
48
Growth
49
Attendance rate
49
Graduation rate
49
Career readiness benchmark
50
English language learner proficiency
50
Procedures for aggregating and examining the data
50
Flagging students in files
50
Identifying students factoring into achievement and growth
50
Process of random selection
51
Identifying students factoring into the additional indicators
51
Data analysis
52
Statistical analysis
52
Institutional Review Board (IRB)
53
Validity
54
Summary
55
CHAPTER 4. Data Analysis and Results
Data Analysis
Key terms definitions referenced in the process
57
57
58
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Pennsylvania’s system of accountability
59
Descriptions of the six indicators examined
59
Achievement
59
Growth
60
Attendance Rate
60
Graduation Rate
60
Career Readiness Benchmark
61
English Language Learner Proficiency
61
Definition of transient
61
School improvement identification
62
Collecting the sample data
63
Identifying attributed students and triangulating data
64
Identifying and flagging transient students
65
Calculating the rate of transiency in each group for each indicator
65
Creating stable and adjusted groups
66
Bivariate pictures of correlation
67
Pearson correlation
68
SPSS software
69
Examining change in score indicators caused by transiency rate
70
Examining relationship between levels of transients and reported indicators
71
Results
72
Research question one – findings
Career readiness benchmarks
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Attendance
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Math growth
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ELA growth
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Math achievement
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ELA achievement
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Graduation and EL proficiency
74
Research question two – findings
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Career readiness benchmarks
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Attendance
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Math growth
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ELA growth
77
Math achievement
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ELA achievement
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Graduation and EL proficiency
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Discussion
78
Findings on the relationship between rate of transiency and indicator value
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Findings on the impact of transiency on school improvement indicators
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Findings interpreted by indicator
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Attendance
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Math growth
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ELA growth
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Math achievement
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ELA achievement
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THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Career readiness benchmarks
Summary
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83
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CHAPTER 5. Conclusions & Recommendations
Conclusions
87
88
Effectiveness
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Application to the researchers’ institutional setting
89
Specific findings and interventions to be shared with participant schools
Implications
Fiscal implications
90
92
92
Implication 1: Pennsylvania School Improvement System – New
92
Implication 2: Research-Based Practices
93
Implication 3: A Shift in Local Expenditures
93
Implication 4: Personnel
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Implication 5: Application of this Project for Local Audits
94
Implications for practice and policy
95
Implication 6: Systems of Accountability
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Implication 7: School Improvement Identification
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Implication 8: Stakeholder Perceptions
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Implication 9: Staff Practice and Attitudes
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Implication 10: Building-Level Practices
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Implication 11: System-Level Practices
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Implication 12: Policy
Future Directions for Research (Recommendations)
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THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Future plans
State-level actions
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Pennsylvania School Improvement Identification and Planning
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Classroom Diagnostic Tools
101
Pennsylvania Intermediate Unit Leadership
102
Local-level actions
102
Communicating Results to District Administrators
103
Informing Local Consultation
103
Promoting Supports for Transient Students in Remote Learning.
103
Building Additional Services and Supports
104
Recommendations for future research
Summary
104
106
References
107
APPENDIX A. IRB Review Request
122
APPENDIX B. IRB Request Approval
134
APPENDIX C. LEA Action Planning Template for Transient Cohorts
135
APPENDIX D. Workflow for Comparing Transient Student Performance to Stable 137
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List of Tables
Table 1. Bivariate Correlation Results Between Transiently Right and Change
72
Table 2. Bivariate Correlation Results Between Adjusted Cohort and Value Change 75
Table 3. Bivariate Correlation Results Between Transiently Rate and Absolute Value 76
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List of Figures
Figure 1. Maslow’s Hierarchy of Needs
18
Figure 2. Relational Framework for Student Mobility
22
Figure 3. Tracking Turnover Across the Country: States that Track Student Turnover 27
Figure 4. Tracking Turnover Across the Country: Turnover Data is Posted
27
Figure 5. Tracking Turnover Across the Country: District Level Data is Posted
28
Figure 6. Tracking Turnover Across the Country: School Level Data is Posted
28
Figure 7. Future Ready PA Index
44
Figure 8. SPSS Software. Bivariate Correlation Menu
53
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Abstract
Considerable amounts of financial resources and human capital are dedicated to school
improvement efforts in the state of Pennsylvania each year. The factors that guide school
improvement designation stem from federal education legislation, and include
achievement, academic growth, attendance, graduation, EL proficiency, and career
readiness. At the same time, many of the schools designated for school improvement also
experience high rates of student transiency. The purpose of this study is to examine the
effect that mobile students have on school accountability indicators, and by extension, on
school improvement designations. The school improvement accountability data from two
school districts with a combined total of eight schools was examined. Transient students
were identified, and mock school accountability indicators were calculated, controlling
the percentage of transient students in the group to the regional average of 8%. These
controlled-score accountability indicators were then compared to published all-student
group values in an effort to identify the impact of high percentages of mobile students
using a bivariate correlation analysis. The results of the study suggested a strong
correlation between transiency rate and change in school accountability indicators for
attendance, math growth, math achievement, and ELA achievement, and a moderate
correlation with career readiness benchmarks. Of all the school accountability factors
examined, the only factor with which student mobility had a small correlation was ELA
growth.
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CHAPTER 1
Introduction
This chapter will provide an introduction to the action research project. The
identification of and significance of the problem will be introduced, as well as the
research questions. The purpose of the study will be presented, and key terms will be
defined. Finally the financial impact as well as personal significance of the study will be
discussed.
Background
This study is of personal significance to the author, as his work is often embedded
in school improvement. By being able to better identify factors that result in school
improvement designation, the researcher hopes to provide better targeted responses and
services to schools, maximizing return on fiscal investment.
The researcher is currently employed with one of Pennsylvania’s 29 intermediate
units. As part of his job responsibilities, he is frequently called upon to offer consulting to
local school districts, focusing on various school improvement efforts. These efforts
relate to school accountability indicators of success, including academic achievement,
academic growth, career readiness benchmarks, attendance, and graduation rate. The
researcher also provides feedback and guidance at a regional and state level on this topic.
The researcher provides targeted support to schools after they have been identified. The
supports that are offered are largely aligned to efforts to improve curriculum, assessment,
and instruction, but currently do not target support for transient students.
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The topic was selected for several reasons. Themes and patterns that result from
the research can be used to better direct fiscal resources and human resources. Research
that supports a correlation between student mobility and decreased school accountability
indicators will guide schools towards developing better supports for transient students,
which in theory should lead to higher success rates for this marginalized group. The
researcher’s work as a steering committee member on several statewide initiatives will
allow him to inform more global actions based on the research. A correlation between
student mobility and school accountability indicators would point to a need for greater
consideration of this challenge when evaluating schools. This will allow for greater fiscal
responsibility as money will be directed towards a factor that contributes to the scores
that lead to school improvement designation.
Identification of the Capstone Focus
The federal Every Student Succeeds Act (ESSA) mandates that beginning in the
2018-2019 school year, states identify the lowest performing schools for three levels of
school improvement effort. In contrast to the previous federal legislation (No Child Left
Behind), ESSA mandates that schools look at factors beyond reading and math
proficiency. Pennsylvania looks at achievement, academic growth, graduation rate,
attendance, English language learner proficiency, and career readiness benchmarks. A
low score relative to other state schools, in combination of these indicators results in a
school being identified for school improvement.
Many of the schools designated for school improvement also experience high
student mobility. Decades of research show there is a correlation between student
mobility and success in school; kids who move more generally perform worse. If school
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
improvement designations are based on factors affected by student mobility, are school
districts with a high percentage of student mobility more likely to be designated for
school improvement?
This study focuses on student mobility in schools and its relationship on school
accountability ratings based on research showing the connection between transiency and
school success. The researcher posits that if a school has a high number of mobile
students, indicators of school success will be lower than average, and this would be
reflected in state school accountability ratings. If this relationship exists, schools with
higher levels of transient students would want to be aware of the correlation, and will
direct fiscal resources in an effort to support this marginalized subgroup, to potentially
avoid school improvement designation as well as to provide these students with more
opportunity for success.
Research Questions
The study will examine the research questions. Is there a significant relationship
between student mobility and a school’s accountability rating? How do schools with a
high transiency rate fare in PAs accountability system when controlling for student
mobility?
Expected Outcomes
This study will examine the impact that high numbers of mobile students has on
school accountability system indicators in Pennsylvania. The accountability data from
two school districts will be examined. One urban school district has been designated
under a school improvement category, and the other is a suburban school district which
has not been designated for school improvement but contains several schools with a
3
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higher-than-average transiency rate. Mobile students will be flagged in each school, and
a new set of school indicators will be created for each school, adjusted to the national
student mobility norm. These new adjusted scores will be compared to the actual scores
to determine the effect of high student mobility in Pennsylvania’s school accountability
system. Additionally, transiency rates and school accountability indicators will be
examined to determine what correlation, if any, exists between the level of student
mobility in a building and the actual values reported to the state.
Fiscal Implications
The results of this study are of great significance to not only individual school
districts, but also to the state as well. From a fiscal standpoint, millions of dollars a year
are being spent on school improvement.
At a state level, Pennsylvania is committing significant financial resources into
efforts to improve schools. While these efforts are based on research-informed cycles of
improvement, and utilize best practices, they do not consider the impact of mobility on
initial designation. In other words, if a school is designated for school improvement, does
it need improved curriculum, instruction, and assessment, or does it merely suffer from a
high student mobility rate? If the state is directing money into helping schools and
teachers better align curricula to standards, and better design instruction, it would be
fiscally responsible to make sure that the money was going to the schools and challenges
that need that help.
From the standpoint of schools, schools that are identified for school
improvement are adjusting resources in an attempt to improve student academic
performance. It would be a wise use of already finite district money if a school district
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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discovered that it wasn’t curriculum, instruction, or assessment which was in need of
improvement, but rather, student mobility rates were resulting in designation. If this was
the case, these schools could use their valuable financial resources to put into place better
supports for transient students to increase the likelihood of their success.
Summary
This paper will examine the role of student mobility on school accountability
indicators within Pennsylvania’s school accountability framework. It will examine the
impact that high percentages of transient students have on achievements, academic
growth, career readiness benchmarks, English language learner proficiency, attendance,
and graduation rate, all which factor into designation in Pennsylvania’s three school
improvement categories. Recommendations for revisions to the state’s school
accountability system will be provided, as well as best practices that schools may
implement to better support transient students. The research began with a review of the
literature related to transiency and school accountability, as reported in the next chapter.
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CHAPTER 2
Review of Literature
This chapter will review the literature related to student mobility and its impact on
achievement. The review of literature will be divided into three parts. Mobility in general
will be presented as it will help develop understanding of how this can be defined,
measured, and of its impact on students and schools. Next, theoretical foundations
impacting student mobility and its impact on achievement and measures of success will
be laid out. Finally, practice and policy will be reviewed, including efforts to factor
student mobility into state accountability systems. A summary of the findings will
conclude the review of the literature.
Mobility Defined
In educational literature, student mobility is frequently referenced. The definition
of this, however, is not often comparable across districts or research studies. Kerbow
(1996) states that to gain a very clear meaning of the amount of mobility in a school, it is
important to separate students entering and students exiting a school from those with
stable participation. For the purpose of this paper, mobility will refer to a student
withdrawing from one school and enrolling at another. The word transiency will also be
used to describe this phenomenon. Finally, students who remain continuously enrolled in
a school will be referred to as stable.
There is a significant statistical difference in achievement of groups of students
when comparing students of mobility with students of stability (Mullins, 2011). Student
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mobility causes a range of issues that span across student achievement and social
emotional development, classroom planning and instruction, and school resources
(Kerbow, 1996).
Mobility.
Frequent moves by students from one school to another put students, their
teachers, and their peers at a disadvantage. Additionally, researchers have found that a
high level of mobile students are also economically disadvantaged. Fowler-Finn (2001)
reports, “stability and family, residents, school and school attendance support better
learning. Those who need stability the most, the poor appear to have the least” (p. 36).
The General Accounting Office reports that large urban districts serving a
disproportionate percentage of students living in poverty experience mobility rates as
high as 40% (GAO, 1994). The GAO’s report goes on to highlight the alarming statistic
that the United States has one of the highest mobility rates of all developed countries.
One common lens in which researchers have analyzed mobility data is defining a
mobile student as someone who had moved at any time in their school tenure. Data from
9915 families was reviewed and determined that in the families in which a child
experienced a move during his or her lifetime, significant negative impacts were
experienced (Wood & Halfon, 1993). Researchers found that frequent family relocation
resulted in increased risk of children failing grades and experiencing frequent behavioral
problems. Transient students experience behavioral problems ranging from poor or
incomplete work completion to major classroom disruption. Demie et al. (2005) defines
student mobility as a child joining or leaving school at a point other than the normal age
at which children start or finish their education at that school. Students who demonstrate
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movement or changes of school, either once or on repeated occasions, at times other than
their normal age to do so at a school can be defined as mobile (Strand & Demie, 2007;
Dobson, 2008).
The most recent United States Census, conducted in 2010, reported that 9.7% of
the US population moved during the year prior to that census (Mateyka, 2015). Mobility
rates differ by geographic region, with the southeast and southwest experiencing the
greatest mobility. Rates of mobility change over time as well. Migration estimates from
the Current Population Survey Annual Social and Economic Supplement (CPS-ASEC),
posted on the census.gov website, show a mobility rate for 2017-2018 of 8% in the
northeast United States (“Geographical Mobility”, 2018).
Lack of common measurement and definitions.
There is little common language for both measuring and defining mobility. It has
been found in previous research that the recency of mobility matters. The more recent
the move to a new school, the greater its possible effect on student achievement and
assimilation (Green & Daughtry, 1961). In the first year in which a student moves to a
different school, progress on learning experiences the most severe loss. This negative
impact on achievement continues at a lesser rate in subsequent years. During this initial
transition year, transient students also encounter the most difficulty with settling into a
new culture and making social connections. One of the earliest researchers of student
mobility examined students who moved at any point during their elementary years.
According to Kerbow (1996), an examination of Chicago area elementary school students
found that only 38% had attended the same school throughout their elementary years.
This highlights how prevalent transiency is in some parts of the nation. In fact,
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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considerable numbers of students experience multiple moves during their school tenure.
13% of the students had attended two or more schools during a six-year period.
Kerbow (1996) identified three groups of students at schools: stable students who
remained at a school from one year to the next, in-mobile students who moved into a
school, and out-mobile students who moved out of the school. The researcher found that
each of these groups of students would experience different levels of achievement. Stable
students experienced the best student achievement levels, while the two mobile groups
experienced lower achievement levels based on different circumstances. Kerbow’s
research examined the stable student group achievement versus that of the other two.
Fowler-Finn (2001) calculated the mobility rate for a school by the total of new
student entries and withdrawals during the year divided by the total enrollment on the
first day of school. This research goes on to state that each entry and withdrawal impacts
not only the transient students, but also the stable students, the teachers, and the district.
An example of this would be if a school experiences a 10% loss of students and a 10%
gain of students. In this case, the researcher considers the school to have a net transiency
rate of 20%. Eddy (2011) defined student mobility as “admittance to more than one
school in a given district over the period of one academic year”. Wasserman (2001)
found that the impact of student mobility on student achievement is greater for schools
with higher mobility.
Causes of mobility.
Previous research has identified numerous causes of student mobility. One of the
most detrimental times to move is during a school year. While moves at any time during
a student’s tenure are disruptive, moves during the school year result in the greatest
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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negative impact. There are multiple reasons for academic year moves. Seasonal jobs,
such as construction, tourism and farming as well as job and military transfers require
families to sometimes relocate during the school year (Lash & Kirkpatrick, 1990).
Additionally, changes within the family such as divorce or job loss sometimes necessitate
this as well. Rumberger et al. (1999) found that parents list three main reasons for
moving their children to another school: the students were forced to leave the school,
they moved to another residence in a different school district, or they wanted to switch
schools. Zehr (2007) reports that transiency is often related to poverty, and that students
in poor families sometimes move around with different family members.
Another reason for a high transiency rate of students is that households often tend
to move more frequently during the early stages of family formation and expansion
(Dobson, 2008). As a family grows, there is a greater need for a larger living space and
an enhanced emphasis on living in a safe community. Migration studies often show a
flow of young families from inner-city areas to suburbs and rural neighborhoods. The
Family Housing Fund (1998) conducted interviews and found that most mobility fell into
one of four categories: coping with life, forced moves, lifestyle moves, or upward
mobility. Researchers also found that a lack of family stability and inadequate affordable
housing also impacted transiency rates of those in the study.
Mobility’s effect on achievement.
Decades of research have shown the detrimental impact that mobility has on
student success in school. In a recent study of mobile students in Texas, mobile students
were found to be outperformed by non-mobile students on state math assessments
(Shoho, 2010). Williams (2003) found that when mobile students are removed from a
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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value-added growth analysis, school scores increased. Value added growth analyses
compare cohorts of students to themselves. This type of statistical analysis examines the
change between the entering achievement level of a given group of students to the exiting
achievement level. Proponents of value-added analysis point to the fact that children are
essentially compared to themselves in this type of reporting. However, if a student moves
during a school year, and that move has a significant impact on achievement, then the
student will likely perform at a lower rate than was expected. This would affect a
school’s value-added report at the classroom and at the school level.
Learning difficulties may be magnified if students enter classrooms at a different
point in the curriculum or state standards than they had been exposed to in their previous
schools (Kerbow, 1996). Although all schools in a state must align instruction to the
same standards, there is great variation from district to district, and even classroom to
classroom. For example, a student may leave a biology class in which that teacher started
the year with cells and cell processes and in the second half of the year moves on to
biodiversity, and in that student’s new school, the biology teacher may teach those
concepts in reverse. This places students at an extreme disadvantage when it comes to
experiencing an efficient flow of instruction and curriculum. Students experience these
learning difficulties in the first year that they move, but the student often has an
adjustment period beyond that initial year. In this way then, a mobile student’s
adjustment period truly extends over the course of several years. Deficiencies
accumulate. State standards and local curricula are intentionally designed and aligned
with vertical and horizontal structure. Curricula are often horizontally coherent, which
allows for student learning to progress in a logical manner based on the design of the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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curriculum. Curricula are also vertically coherent, which means that what students learn
at one grade level in a course prepares them for the next course in the sequence. A wellwritten district curriculum would be purposefully structured and logically sequenced to
allow optimal learning. As curricula vary from district to another, mobile students are at
a disadvantage in that they have not progressed through a district’s intentional learning
plan.
The Family Housing Fund (1998) examined mobility’s effect on academic
achievement. This research found that mobile students had lower attendance levels, and
that students absent 20% of the time scored twenty points lower on the California
achievement tests in reading. The research also found that reading scores were 50% lower
for students who exhibited mobility three or more times than were the scores for stable
students.
One of the ways in which mobility impacts achievement is through the need for
adjustment to peer groups, the classroom and the school. When a student moves into a
new school, one of the key priorities for that student is making adjustments. This
emphasis on adjustment results in less available time for learning. Fowler-Finn (2001)
writes:
Each withdrawal and each entry takes a toll on the student who is moving, on the
students who remain, on teachers, on support staff, on the office and on parents –
schools spend a lot of time on activities that impede direct uninterrupted
instruction. (P. 36)
There is a profound impact of frequent mobility on student academic achievement
in the early years of a child’s school experience. The impact of transiency begins early in
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
13
a child’s education. Reynolds (1990) reported that in a study of pre-kindergarten and
kindergarten programs, mobility had a negative effect on achievement. This may be
attributed to the interruption of learning at a time in which the acquisition of key skills is
vital (Franco, 2013). Krenicki (1999) examined student results related to the New Jersey
Early Warning Test and found that student mobility negatively impacted student scores
and reading and mathematics. Kerbow et al. (2003) found that the academic growth of
highly mobile students is less than the growth of stable students with similar
characteristics. Gamble (2004) examined the effect of student mobility on student
achievement under Tennessee’s school accountability system. Gamble found that student
mobility was shown to affect student achievement in both reading and mathematics.
Correlational analyses indicate that high levels of school mobility are significantly related
to poor academic performance (Felner et al, 1981).
Kariuki & Nash (1999) found that students who experience mobility several times
in their school tenure suffer even greater achievement loss. Researchers found a statistical
difference between groups of students with one move and those that made multiple
moves. Students removed three or more times were often eligible for special education.
Mobility affects attendance, impacting achievement.
Mobility affects attendance rates as well. For every day that a student does not
attend school, the student misses additional knowledge and important contact with peers
and teachers. Support for school attendance is important for all students, especially those
who are transient. Mobile students are at great risk for falling behind academically and
developmentally, resulting in the students falling even further behind, exasperating the
situation (Hinz & Snapp, 2003). As students fall behind, they become frustrated and this
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
14
results in greater absenteeism. In one study, researchers found that mobility seemed to
have a slightly greater impact on attendance then on achievement (Parke & Kanyongo,
2012). Rumberger et al. (1998) found that in a study of California students, children who
made even one school change between grade 8 and 12 were less likely to graduate from
high school than students who remain stable in the same school. A recent analysis of
student mobility versus graduation rate in the state New Jersey found a statistically
significant variable that negatively influenced graduation rate. Schools that have high
mobility rates tend to have low graduation rates (Ross, 2014).
Mobility’s effect on the system.
Student mobility also takes a toll on school systems. Sanderson (2003) reported
that urban schools faced with high mobility rates are often forced to commit large blocks
of time towards the paperwork related to intake and outflow of transient students.
Schools must collect a tremendous amount of information to enter into a student
information system. Demographic information, household information medical forms,
and media releases represent just some of the paperwork that must be completed. Schools
must also dedicate time and effort to administering district required assessments when
students enter school. For example, if a school utilizes a diagnostic assessment for
planning and instruction purposes, school personnel must administer this assessment to
the new student. This process takes additional staff time and can be quite burdensome
and a school district with high transiency. Additionally, records are sometimes lost in the
shuffle, presenting a challenge for the new school, as staff must communicate with a
student prior school in an attempt to obtain school records. This challenge often results
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
15
in additional testing and evaluation of the new student, further taxing the system in terms
of personnel and finances.
Schafft (2003) reported that the effect of school mobility is even more
pronounced in smaller, limited resource districts. In these districts, mobility resulted in
increased administrative costs, and great unpredictability in planning and budgeting.
Small districts often do not have room to absorb additional costs for testing or salary time
spent; personnel in small districts often have multiple roles and do not have time in their
schedules to accommodate assessment and intake work with new students. Kerbow
(1996) found that in some schools, class rosters changed frequently. This resulted in
making planning difficult. Some students may move into the classroom in the middle of
the unit and would be lacking necessary prerequisite skills. Not only is it difficult to a
reverse course and offer remediation, this also makes assessment of the content more
difficult. Teachers reported less time to collaborate with peers, less time to truly focus on
the student learning, and less time to innovative in their planning and instruction. These
classrooms became more focused on reviewing contents rather than introducing new
skills and knowledge. This resulted in slowing the pace of the class for all students,
mobile and stable.
Theoretical Foundations Impacting Mobility
Self-concept theory.
Some research shows that there is a connection between moving between schools
and self-concept. The self-concept theory relates to the beliefs, opinions, and attitudes
towards our existence. Self-concept controls what we think about ourselves and how we
think and behave throughout our lives. Long (1972) suggests that mobility causes an
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
16
interruption and a smooth flow of peers, teachers, curricular and teaching materials, and
general social and academic support systems. When a student moves from a school in
which they have valued friendships with peers and trusted relationships with adults, to a
new school, the absence of these things impacts their perception of the world. This
hypothesis aligns with other work supporting the impact of stressful life events on
children. In adjusting to a school transfer, mobile students are forced to adapt to new
peers and to new academic and behavioral standards (Jason et al., 1992). What is
considered a norm in one classroom may not be a norm in another. Teacher expectations
may vary. Different modalities of learning may be incorporated from one classroom to
the next. For example, a student may move into a new classroom in which that teacher
expects quality cooperative learning work when that student never received any modeling
or instruction on what effective groupwork entails. If a student fails to work in adherence
to norms of the new classroom, that student may experience frustration and a lack of
confidence.
A student’s self-concept is a factor that determines success of the outcome of the
move. Hendershott (1989) reported that social support attenuates a negative effect of
mobility on measures of self-concept. As students continue to struggle to connect
socially and academically, they become frustrated, and their self-esteem suffers. This in
turn leads to problem behaviors, which consequently, causes academics to erode even
more. Attending a new school in conjunction with the pressure of forging new
friendships and fitting in may negatively impact children’s self-esteem and their
perception of their own existence.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
17
Self-actualization theory.
Much of Maslow’s work is a conceptual model that is impacted by mobility.
Self-actualization derives from being able to leverage one’s abilities and resources to
reach their potential. Maslow’s hierarchy of needs is made up of physiological, safety,
love, self-esteem, and self-actualization. Figure 1 shows Maslow’s pyramid of needs.
Beginning at the bottom, each level needs to be taken care of before one can address the
needs at the next level. Maslow connects the role of motivation in learning, theorizing
that people follow each of these levels of need in sequence, and that learning is dependent
on the foundational components of this hierarchy. The bottom tier in this hierarchy
involves basic physiological needs: food, water, and shelter. As mobile students tend to
hail from families who are struggling financially, these students often lack the basic
physiological and safety needs of the first two levels of the foundation (Kerbow, 1996).
Mobile families often have limited access to food and healthcare, and often include nontraditional living arrangements that sometimes pose safety issues (Kerbow, 1996; Schafft,
2006). Even if moving to a new school does not impact physiological or safety needs, it
often does impact the third tier –love and belonging. This is the tier in which the
importance of connections to peers and friendships is realized. New students lack peer
and teacher relationships, and this takes time and effort to develop. Such relationships
lead to students feeling accepted and belonging; the absence of these impacts learning.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
18
Figure 1
Maslow’s hierarchy of needs. Adapted from “Maslow’s hierarchy of needs”, by J.
Finkelstein, 2006.
https://commons.wikimedia.org/wiki/File:Maslow%27s_hierarchy_of_needs.png
One of the biggest concerns of mobile students is making friends and fitting in. The third
tier of Maslow’s pyramid involves feeling loved and accepted. It relates to our need to
feel as if we belong to a specific social group. It involves both feeling loved and feeling
love towards others. Rhodes (2008) found that students experience emotional anxiety
related to this, and an inability to focus on their studies until they felt secure in their
social setting. This aligns to Maslow’s hierarchy of needs, of which safety represents the
third tier (Maslow, 1987).
The fourth tier focuses on self-esteem. This is associated with a student feeling
confident and respected by others (Maslow, 1987). A student cannot demonstrate
confidence until the first three tiers are experienced. The self-worth that comes from
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
19
feeling safe and secure and belonging enhances the environment in which learning can
take place.
Constructivism.
The concept of constructivism can be used to explain the impact of mobility on
student achievement. Active learning occurs during the transition to a new school.
Students learn about their own inner beliefs, strengths and challenges, and they learn
about those around them, including peers, school staff, and families (Rhodes, 2008). The
experiences they face help them to develop the ability to cope and assimilate into a new
culture; unfortunately, some students are unable to construct a proper framework for
assimilating and experience social, emotional, and academic issues. When students
struggle to maintain a proper structure in which they can interact with course materials
and grow, learning is impacted.
Psychological theory.
In the absence of conditions conducive to personal growth, mobile students can
suffer. The adjustment of being a transfer student can impact a student’s psychological
well-being, social and academic competence and behaviors, and eventually achievement.
Mobile students face many challenges in assimilating to a new school, including the
psychological challenge of coping with a new school environment (Holland, 1974), and
adjusting to new standards and classroom routines (Jason et al., 1992).
Developmental-ecological theory.
Developmental ecological theory goes a step further in that it acknowledges not
only the impact of mobility on mobile children, but also how mobility affects teachers
and peers in the classroom as well. The needs of mobile children can negatively affect
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
20
instruction for other students and cause a general disruption to learning (Bronfenbrenner,
2005). This has been confirmed by additional research, finding that when teachers adjust
their routines to accommodate mobile students this leads to changes or repetition in
lesson plans (GAO, 1994). This theory also suggests that there are impactful transactions
that occur between a student and his or her peers and teachers, and over time, this creates
important pathways to social, emotional, and academic development. If a child has a
history of success in developing connections with peers and teachers, this can be built
upon in the future, and the child has an advantage. Mobile students often do not have the
luxury of developing such connections, and this unsuccessful history of social
transactions breeds future difficulty with adjustment.
At a workshop convened by the National Research Council in June 2009, one
paper examined the consequences of student transiency from a developmental perspective
(Beatty 2010):
Children’s body function, brain development, capacities for dealing with stress,
and behavior change over time, and these variations may make them more or less
vulnerable to—or able to withstand—the effects of mobility. Parents as well as
children may perceive and handle a move differently depending on the child’s
developmental stage...Disruptions in this development can have a snowball effect,
which explains how mobility has the potential to harm children...Specifically,
mobility (particularly repeated mobility) can disrupt children’s routines, the
consistency of their care and health care, and their relationships, as well as
learning routines, relationships with teachers and peers, and the curriculum to
which they are exposed. (p.6)
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
21
In other words, mobility is detrimental to a student’s emotional and academic growth,
and this causes gaps in their development. Subsequent moves only magnify gaps that
develop in these foundational developmental milestones.
Social-cultural theory.
Researchers have commonly identified sociocultural theory as a foundation for
understanding the impact of mobility on educational outcomes. Coleman (1998) posits
that social capital theory argues that children build vital connections with their peers and
teachers which are critical for their own personal development and success, and mobility
removes the opportunity to build these connections. Developing connections and
friendships with peers takes time. Stable students have the advantage of benefiting from
already established relationships with peers and are at an advantage. Vygotskiĭ’s (1978)
socio-cultural theory explains that success in school is highly dependent on social success
and cultural relevance. When students move into a new setting, they struggle to connect
with peers; for some, these connections never develop. It is difficult for some students to
succeed in an environment in which they do not yet understand the culture.
Relational framework.
In an examination of mobility of students in schools across the US, Spencer
(2017) examined existing literature and presented a framework that defines student
mobility. Spencer’s framework also outlines the relationships between the causes and
effects of mobility within several different contexts. Figure 2 highlights the types,
motivators and consequences of student mobility. Considering all of these variables is
important when interpreting the results of student mobility studies, as they are
interrelated. This framework displays the different types of mobility, and how they are
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
22
caused by different motivators. These types of mobility include structural, structural,
voluntary, non-voluntary, reactive, and strategic. In addition, each of these types of
mobility results in varying consequences. Spencer’s (2017) framework also highlights
additional factors that must be considered in mobility studies, such as the relationship
between motivators and distal outcomes of mobility. The presence of variables that may
be correlated with motivators, type, and consequences of mobility must also be
considered. Finally, the potential impacts of operational considerations must be
considered as well.
Figure 2
Relational framework for student mobility. Adapted from “An examination of student
mobility in U.S. public schools”, by K. Spencer, 2018.
https://repository.upenn.edu/cgi/viewcontent.cgi?article=4377&context=edissertations
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
23
Policy and Practice
Systems of accountability.
School accountability is a prime topic these days, from local parent teacher
organization meetings to the halls of legislators. In accordance with the Every Student
Succeeds Act (ESSA), states are accountable for creating an evaluation system for
schools and determining a way for focusing resources on low performing schools and
traditionally underserved students demonstrate low achievement. States are mandated to
establish long term goals for student achievement growth, graduation rates, and English
language proficiency. States must also select several additional measures upon which
schools can be evaluated. As part of this process, states must identify schools in need of
improvement based on the performance of all students, and of student subgroups (U.S.
Department of Education, 2019).
Pennsylvania’s system of accountability.
Pennsylvania has created a system for measuring the success of schools using
multiple measures. A new reporting system, the Future Ready PA Index, features a
dashboard approach to school and student group performance. The Future Ready PA
Index illustrates student and school success on eleven indicators using a color-coded
system (Pennsylvania Department of Education, 2019). Six of these indicators are used
in the process for identifying schools in need of school improvement.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
These indicators are as follows (federal accountability school improvement
indicators denoted with an *):
•
Percent Proficient or Advanced on Pennsylvania State Assessments*
•
Meeting Annual Growth Expectations*
•
Percent Advanced on Pennsylvania State Assessments
•
English Language Growth and Attainment*
•
Regular Attendance*
•
Grade 3 ELA and Grade 7 Math Early Indicators of Performance
•
Career Standards Benchmark*
•
High School Graduation Rate*
•
Industry-Based Learning
•
Rigorous Courses of Study
•
Post-Secondary Transition to School, Military, or Work
School improvement identification in Pennsylvania.
In a process termed annual meaningful differentiation by federal statute, states
must designate schools, at least every three years, into three designations:
•
Comprehensive Support and Improvement (CSI): Schools facing
significant challenges in achievement, growth, and any of the other four
areas highlighted above
24
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
•
25
Additional Targeted Support and Improvement (A-TSI): schools
experiencing poor performance by one or more student groups belong a
specified threshold
•
Targeted Support and Improvement (TSI): schools experiencing poor
performance by one or more student groups in danger of approaching a
specified threshold
Schools are identified for one of the levels of school improvement if they have
both low achievement scores and low growth profiles (below statewide minimum values)
and poor performance on additional ESSA-required indicators. If mobility impacts
student achievement and growth as well as graduation rates, can a high mobility rate lead
to a school improvement designation?
Stakeholder perceptions.
Parents place high value in published accountability ratings. Research
surrounding parent perceptions of state school accountability reporting show that 80% of
parents place value in reported test score summaries (Owens & Peltier, 2002).
Unfortunately for school systems with high student transiency rates, while it is easy for a
parent to view a website and see a number, it’s not as simple to understand factors that
influence that number. It is often common practice for external stakeholders, including
the media, to compare the values assigned to an indicator for two separate schools.
Without context, it could appear that the school with a higher value is the better school;
however, one needs to take into account a variety of factors including mobility. When
parents review these school accountability ratings without context, parents in a school
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
26
district with high mobility may decide to leave the district for a district for another that is
perceived to be better in serving students.
There are numerous factors that the state should keep in the forefront when
designing an accountability system. An accountability system must evaluate each school
in terms of its own context (Sirotnik, 1999). Such systems must go beyond test scores to
include a variety of additional factors. Sewell et al. (1982) found that mobility is a very
important intervening variable in achievement and must be controlled during
interpretation of achievement progress for reporting and decision-making purposes.
Educational accountability systems across the nation.
Currently, only about half of all states collect data on mobile students or post such
data (Blashe et al. 2018). The information that is collected is not consistent, which
makes state by state comparisons very difficult. While federal mandates require schools
to identify students with some extenuating circumstances, such as homelessness, the
federal government does not define how transient students would be viewed, nor does it
mandate that they be tracked. Some states count only students who switch mid-year,
while others include students who move outside of the academic school year. Florida, for
example, tracks students who move between the months of October and February.
Massachusetts defines mobile students as ones who move between October and June.
Texas is perhaps the closest to define incomplete mobility. Students in a school for less
than 83% of the school year are referred to as mobile. Figure 3 identifies the twenty-nine
states that track student turnover by any means. Not all of these states publish the results.
Figure 4 displays the twenty-four states who post such data. As Figure 5 highlights, only
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
27
twenty-one states post district-level mobility data. At the school-level, this statistic is
even smaller. Figure 6 identifies the seventeen states that display school level mobility
data. Pennsylvania is currently not one of the states that posts or even collects data on
student mobility.
Figure 3
Tracking turnover across the country: states that track student turnover [graphic].
(2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
Figure 4
Tracking turnover across the country: turnover data is posted [graphic]. (2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
28
Figure 5
Tracking turnover across the country: district level data is posted [graphic]. (2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
Figure 6
Tracking turnover across the country: school level data is posted [graphic]. (2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
29
Staff practice and attitudes towards mobile students.
Controlling for outside factors, the single biggest impact on student success is the
teacher. Staff practice and attitudes towards mobile students can have a significant impact
on their success. From a teacher’s perspective, student mobility can be disruptive (Lash
& Kirkpatrick, 1990). Not only do such students require immediate attention, but they
must learn the rules and routines of the new school and classroom, which put a strain on
teachers. School days do not have extra transition time built-in to assist mobile students
with transition; instead, teachers must take time away from their already short class
periods to help acclimate new students to classroom culture. Teachers in classrooms with
multiple mobile students often end up reviewing old material instead of introducing new
material, which impacts the stable students in the class (Rothstein, 2004). This slowing
down of the pacing of the classroom impacts academic growth of stable students as well.
Pennsylvania’s value-added assessment system measures students against their past
growth. If a classroom teacher slowed the pace of instruction to reteach material to new
students, the existing students in the class would likely not achieve as high as statistical
modeling would expect, and this would result in potentially poor growth values assigned
to this classroom and also to its teacher.
Rumberger et al. (1999) suggest the teachers should review the cumulative
records of new students to assess grades, attendance, and important background
information. Contacting the prior teacher is an effective way to learn more about that
student and the background the student brings (Kerbow, 1996). It is difficult to plan
instruction when a teacher does not know what academic knowledge a new student
brings. Because of this, assessments are a necessary part of the intake process. Hartman
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
30
(2006) reports that not knowing the academic abilities of new students negatively impacts
a teacher’s planning and instruction process and puts an overall strain on the system and
its resources.
Chow (2014) found that teachers should prioritize fostering supportive
relationships with mobile students and their parents as a means to promote their success.
When teachers have more contact with parents, they can learn more about the student’s
needs and home environment and provide necessary structure in the classroom to meet
those needs. Parents can also learn about teacher expectations, as well as classroom and
school culture. Strong teacher-parent connections lead to meaningful and productive
conversations, which will better help the transient student in the adjustment period.
Cloer (2015) studied teachers at an elementary school and their perception
towards mobile students. The goal of the project was to solicit teacher perceptions about
the success or failure of mobile students. Teachers indicated that upon the arrival of a
new student, they would examine initial enrollment paperwork and learn about the new
student through talking. Examining cumulative records was another action undertaken by
teachers, but this sometimes requires dedicated time. Sadly, even though all teachers
interviewed placed value in talking with parents of a new student, they indicated that
parents do not always make themselves available to meet. All teachers agreed that the
presence of mobile students significantly impacts planning and instruction, and that it is
difficult to plan without knowing what background the student brings. Teachers also
agreed that placing students in groups is difficult without knowledge of a student’s prior
experience with group work. All teachers found it was important to assign the new
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
31
student a friend or a buddy to guide them around the school. The important role of
counselors in this process was also mentioned as a vital support to new students.
Cloer (2015) also found that teachers expressed concern for increased behavior
issues. New students do not understand class procedures and routines, and thus, may
interrupt the flow of the class. Mobile students often demonstrate poor adjustments and
experience increased behavioral issues resulting in less time on task and less stability
(Rumberger et al., 1999).
Administrative practice towards mobility.
Procedures put in place by administration, as well as general administrative
support directly affects the achievement of mobile students. Just as a teacher is the single
biggest factor in the success of a classroom, an administrator is the single biggest factor
in the success of a school. In a study of student mobility, high rankings of school
leadership and usefulness of its professional development programs was found to
correlate positively with performance (Heywood & Thomas, 1997). Franke et al. (2003)
describe an informal intake process at one school in which an informal family history and
child academic assessment take place. It is during such informal intake meetings that
school staff may ‘get to know’ student. Even if all of the prior school records have been
received by the new school, personal meetings often provide richer information and
context, beyond that which can be found in student academic files. At the same school,
front desk staff are sensitive to the issues of new and transient students and are respectful
of their circumstances. This is important because the front office is often seen as the first
contact points for communications, questions, and concerns.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
32
System-level practices impacting mobility.
Filipelli & Jason (1992) suggest that as part of a child’s transition to a new school,
educators and perhaps mental health professionals should assess stressful life events in
the lives of transfer students. This way, schools might be able to identify potential
roadblocks to transition. Adults might be ignorant to the primary concerns of the
children themselves; while adults may be interested in making sure the student is
properly scheduled and has a bus stop, the child may be more concerned immediately
where to sit for lunch and dress code. Students may also come with adverse childhood
experiences affecting their ability to transition. Identifying these experiences and their
impact on the present can help social workers design an effective transition plan for the
student. Huffman (2013) writes about the value of school social workers who can work
with at-risk students to build attendance plans, and work with parents to overcome
barriers.
Smith et al. (2008) highlighted that a commitment to screening students
immediately upon enrollment, using intentional placement, instituting progress
monitoring, and adjusting as necessary provides mobile students with a great opportunity
to succeed in school. This suggests a shift from a reactive approach to students moving
in, to a more proactive approach, one that has been carefully considered and planned
beforehand, and implemented in a system in which transient students do not fall through
the cracks. This involves providing diagnostic screenings, such as those in math and
reading, to identify not only needs but also strengths. The screenings will help inform
class placement and planning for instruction. The progress monitoring of mobile students
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
33
provided the school with a means of evaluating the success of a student’s assimilation,
and an early warning of potential roadblocks.
Fisher & Matthews (1999) conducted a qualitative study examining factors that
lead to increased school stability for mobile students. The most effective measure schools
took was supporting families with wraparound services. The researchers found that
students benefit from increased interaction with staff who exhibited a caring demeanor
and high expectations. The stability of consistent programming and clear guidelines and
policies helped address the academic and social needs of the students. Effective programs
placed high value on the creation of positive relationships with families. Increased
school stability was supported by school administration in their shared leadership,
demand of high levels of collegiality, and their continued evaluation of the program with
an emphasis on continuous improvement.
One way of reducing student mobility might be if schools provide information to
parents about the harmful effects of changing schools. Kerbow (1996) suggests that if
parents were made more aware of the value of stable environments for children, mobility
will be reduced, and additionally, relationships with families may be more firmly
established. Many urban schools have high levels of mobility. Some of these schools
make many attempts to implement programs and practices to help families (Nakagawa et
al., 2002). However, it was found that these attempts did not result in greater
involvement from the families.
Policy that impacts mobility.
Unfortunately, researchers have found that student mobility has not received
much attention from policymakers. One reason is that transiency is often seen as
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
34
inevitable and out of the school’s control (Rumberger & Larson, 1998). Pupil mobility
has implications for many policy areas, including school funding and goal-setting
(Demie, 2002). State and local policies can have a considerable impact on the success of
mobile students. Rural, chronically mobile students have escaped the attention of schools
and public policymakers (Schafft, 2006). This often goes unrecognized, in part because
the numbers of students entering and exiting schools usually balance out, so the net
enrollment changes are not noticeable. Nationally, the lack of attention paid to transiency
is likely because the students don’t fit into federal subgroup categories, and thus escape
from being under the lens of federal and state accountability.
It is difficult to hold schools accountable when indicators are based on factors
outside of the schools control, such as transiency (Delong, 2002). Student mobility poses
unique problems. Administrators at high mobility schools should be given fund
allocations to create new programs and learning opportunities specifically targeting
mobile students (Williams, 2003). Even the US General Accounting Office has proposed
that policymakers focus greater attention on the needs of mobile students. GAO’s (1994)
report suggested that the US Department of Education can play a role in helping mobile
children by ensuring that they have access to federally funded education programs and
encouraging states to implement more effective student record transfer systems, and to
support local education agencies in accommodating mobile students. Wasserman (2001)
suggests that achievement test results for schools need to be interpreted taking variation
in student mobility into consideration. School choice advocates often point to school
choice as a way to reduce the impact of student mobility (Coleman-Weathersbee, 2018).
If states allow school choice programs, then students may not have to change schools
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
35
when their place of residence changes. Rumberger (2016) suggested that school districts
might also be flexible with school boundaries and provide transportation and support to
families considering moving.
Gamble (2004) recommends that states have an obligation to collaborate with
school systems intensively, to ensure that all stakeholders are informed of the needs of
mobile students. It is also important that the presence and plight of mobile students be
made visible and understood by all. Better informed staff are better prepared to meet the
needs of transient students.
Policymakers should shift their focus from assigning numerical ratings to schools,
towards more socially desirable educational outcomes, such as whether students learn
what they need to learn and whether these learning outcomes are equally distributed
(Longanecker & Blanco, 2003). Housing and community development policy should
focus on investment in low income communities, which would result in less families
leaving, and thus lower student mobility (Metzger, Fowler, Anderson & Lindsay, 2016).
Overwhelming evidence shows that most school mobility is a function of involuntary
residential moves, and a governmental program to increase the supply of affordable
housing can help stem transiency (Hartman, 2006). This type of investment would
enhance social capital and assets within the community. Heinlin & Shinn (2000)
proposed that school systems can work with community groups to reduce disruptive
moves. Once such program studied involved parents, educators, landlords, social
workers, and politicians and led to a 38% reduction in transiency.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
36
Summary
School accountability is an important issue in education today. Schools are being
identified as in need of school improvement based on academic and behavioral indicators
of success. These indicators of success are negatively impacted by student mobility. The
goal of this literature review was to define mobility, identify its connections to indicators
of achievement and success, and review how student mobility is factored into statewide
school accountability models. Descriptions of student mobility were highlighted in an
effort to develop an operational definition of mobility for the purpose of this action
research project. Most popular definitions of student mobility defined mobile students as
those who have moved within the current school year, though there exists some evidence
that suggests that mobility impacts student achievement beyond just the year in which the
student experienced a move. Theoretical frameworks related to student mobility were
reviewed, suggesting how transiency can have a negative impact on student achievement.
Transiency impacts students at a deep level, resulting in developmental, social, emotional
and academic deficits. Much of this relates to Maslow’s hierarchy of needs. Finally, a
review of state and federal accountability models was conducted, finding that there is
disparity from one state to another in terms of whether or not student mobility is factored
into indicators of school success.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
37
CHAPTER 3
Methodology
The purpose of this chapter is twofold: it will introduce the research methodology
for this action research project, and it will discuss its various implications. A
comprehensive review of the literature shows that research supports a correlation
between student mobility and indicators of school success. There also exists a great
disparity between districts and sometimes schools within districts related to levels of
student transiency. Additionally, Pennsylvania’s system of school accountability
provides a report of student success in a number of federally-mandated areas, but it does
not consider levels of student mobility.
This chapter will first re-introduce and develop the research questions. The
methodology selected will be highlighted, including a justification for the research design
as well as a detailed description of the statistical data analysis. Background information
on the researcher and participants will be provided. Data collection, procedures and data
analysis will be described. Finally, threats to validity, trustworthiness, ethical concerns,
and fiscal implications will be reviewed.
Purpose
This action research project examined the impact of student mobility on school
accountability indicators. A causal comparative research design was utilized, as the
researcher’s intent was to conclude a cause and effect correlation between student
mobility and overall score accountability indicators.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
38
Problem.
Many of the schools designated for school improvement also experience high
student mobility. Decades of research show there is a correlation between student
mobility and success in school; kids who move more generally perform worse. If school
improvement designations are based on factors affected by student mobility, are school
districts with a high percentage of student mobility more likely to be designated for
school improvement?
Research questions.
This action research project was initiated to answer two questions. Is there a
significant relationship between student mobility and a school’s accountability
indicators? How do schools fare in Pennsylvania’s school accountability system when
controlling for levels of student mobility?
Setting and Participants
The school districts taking part in the research project were selected as they
represented various levels of student mobility, and ones in which district leaders
indicated great interest in the results of the study. In order to examine the impact of
mobility, the research required subjects (schools) with significant levels of transiency, in
order to examine correlation. One school district chosen has been identified for school
improvement by the state, based on school accountability indicators. The other school
district has not been designated for school improvement, but some within the school
district have voiced concerns relating to the challenges posed by the levels of student
mobility they face. Both school districts chosen are led by superintendents who have
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
39
great interest in the results of the study, as intend to use the work to inform decisions
relating to fiscal and human capital resources.
Each school district is unique in its composition and community, but both school
districts experience a significant student mobility rate. In an effort to maintain
confidentiality of the data, the school districts will be referred to as school district X and
school district Y.
District X is located in a suburb in western Pennsylvania. In the past, the district
has received a number of awards celebrating its academic success, including a Blue
Ribbon Schools award. The district serves over 3000 students with a staff of over 500.
Over the past 10 years, the communities that comprise the district have experienced a
shift in businesses and housing. Transitional housing has become more readily available
in the district, which results in greater migration of students. District X has not been
designated for school improvement yet, but the administration continues to pay close
attention to indicators of academic success of all students, and is committed to adjusting
programs and offerings as needed.
District Y is a smaller suburban school district located in a city with a high
poverty rate. It is ranked in the bottom 5% in numerous state and national school
rankings. The communities that comprise this district have experienced a sharp decline in
longtime residents, and the district currently experiences a very high rate of student
mobility. The school district receives a high percentage of annual revenue from the state,
placing it among districts receiving the highest state funding in Pennsylvania. A
tremendous amount of financial resources are being funneled into improving academic
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
40
achievement for students in this district, and the superintendent is committed to utilizing
these resources efficiently.
Schools were recruited using a variety of strategies. The opportunity to discuss
partnering was mentioned at a role-alike meeting of western Pennsylvania schools. The
researcher also targeted schools by reaching out to superintendents and asking them to
consider participation in the study.
There were several unsuccessful attempts in the process to solicit partners for this
project. Several school districts indicated interest initially, but declined to participate as
the study involved student data. Two superintendents mentioned to the researcher that
they would be concerned if the research showed that there is a little correlation between
student mobility and indicators of academic success; this may cause some to infer that a
district is doing a disservice to all students, whether or not those students are
continuously enrolled. Two cyber-charter schools indicated interest early in the process,
but later backed out prior to granting final permission to participate. While the schools
did not provide a reason, between initial interest and final agreement, legislation was
introduced in the states which would drastically impact cyber charter schools. It is
speculated on the part of the researcher that the schools decided not to participate due to
the timing of this potential legislation that may drastically impact this type of school in
the future. A study that had a potential to show any deficiencies in a school may be
frowned upon when the school may likely be under increased public scrutiny.
Intervention and Research Plan
Positivism gives rise to quantitative methodology (Mukherji & Albon, 2015). This
research was approached with a positivism epistemology (Age, 2011), as it uses a
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
41
systematic, scientific approach to the way the research is conducted, and results
examined. Because positivism is grounded in objectivity and discrete data sets, it
supports quantitative methodology. In examining the role a positivist methodology plays
in quantitative research, Mukherji & Albon (2015) posit that “correlational studies are
used in situations when it is difficult or impossible to use experiments, but the researcher
wants to see if there is a relationship between two variables”. This describes a limiting
factor of studying student mobility, as a researcher cannot use an experimental approach
to examine student mobility. The role of the researcher in this case was limited to data
collection, data analysis, and interpretation in an objective manner. Using extant
accountability data provides quantifiable observations. These observations led to a
statistical analysis that is judged only by logic and free from subjectivity and
interpretation. This approach was selected by the researcher as it is a scientific approach
to examining data that leads to results that can be often generalized across a field. In
alignment to the researcher’s own beliefs regarding the importance of an objective,
impartial examination of data, positivist research is likely conducted to establish
correlational or causal relationships that can be generalized and shown to be objective
(Paré, 2004).
Hendricks (2017) explains that through the action research process, practitioners
use the knowledge generated through their research to inform practice as well as guide
and improve systems at a higher level. As the researcher has spent several years
embedded in school improvement work, action research provides a systemic approach to
pinpointing challenges to school improvement.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
42
The approach also allows valuable fiscal resources earmarked for school
improvement to be redirected towards research-identified solutions. As an action
researcher, the author will be able to ground future work in the results of this project.
Having a local, regional, and state role in school improvement efforts, the findings will
be acted upon in a manner that should directly impact students, staff, and administrators
in the state. As action research, the project will inform the ethics of school improvement
efforts based on objective work. This effort will also connect existing research with
systemic practices and thinking.
Connection to fiscal implications.
The research design will result in findings that will have several fiscal
implications, both locally, as well as at a state and national level. The process outlined in
this research project is one that could be replicated at no cost in any Pennsylvania school.
Schools may wish to audit their success with transient students by using the same files to
examine the academic success of mobile students. As the process would be free, it would
not require payment to any outside firm and thus would be a fiscally responsible
commitment on the part of district leaders.
Also, at a school level, schools may redirect taxpayer money from content
specific expenses to supports for transient students. Schools have only a finite amount of
money to spend and targeting the groups of students most in need would provide the most
success from the resources they have.
At a state level, over two million dollars will be spent over the next few years on
school improvement efforts. At the time, the system as it is currently organized provides
content-specific advisers to schools in school improvement at a great cost. The results of
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
43
this study may inform the state in making changes to its school improvement staffing,
providing more transition coordinators to schools to help those students most in need.
Research Design, Methods & Data Collection
This research was designed as a quantitative correlational study. The goal of the
study is to describe the relationship between transiency rate and school accountability
indicator values, and also to establish a relationship between these two factors. As such,
the project uses a causal comparative design (Schenker & Rumrill, 2004), intended to
identify relationships between independent and dependent variables. A hallmark of this
type of design is that it examines data after actions have occurred. The researcher hopes
to determine whether or not the school accountability indicators, as independent
variables, are affected by student mobility, as a dependent variable. Causal comparative
research design is an effective way to examine relationships between variables when it is
not possible to manipulate the actual variables themselves. As it would the impossible
and unethical to intentionally move students between schools, this type of design allows a
researcher to examine the effect of such actions outside of the experimental procedures.
While other means of research may result in more compelling recommendations based on
causation, the research questions associated with this project would be difficult to
examine with other methods.
Multiple forms of data.
There are seven key sources of data required as part of this action research
project. It is important to note that all data files identified students by PAsecureID,
which is a statewide, randomly assigned identification number for students in the state of
Pennsylvania. At no point were student names shared with the researcher.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
44
The first source of data examined was the school accountability values posted on
Pennsylvania’s Future Ready PA Index website at https://futurereadypa.org. This site is
updated each fall to reflect the success of Pennsylvania schools during the previous
school year. It is an aggregate of school progress measures relate to academic success and
college and career readiness. As viewed in Figure 7, this index includes assessment
measures, on-track measures and readiness indicators.
Figure 7
Future Ready PA Index. School Performance ã 2020. Retrieved April 23, 2020 from
https://futurereadypa.org. Screenshot by author.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
45
This website evaluate scores on 11 indicators. Six of these are federally-mandated and are
the measures used to designate schools for school improvement. Those six federally
mandated measures are academic achievement, academic growth, attendance, graduation
rate, English learner proficiency, and career readiness benchmarks. Future Ready PA
Index values in each of the six areas were noted for each of the schools involved in the
study. The values posted on the website will be compared to the adjusted values
determined by the researcher when controlling for percentage of transient students.
Pennsylvania assessments in grades three through eight are administered each
spring. High school assessments in the state can be administered throughout the year with
a cycle beginning in the summer and ending each spring. The results of these assessments
are provided to districts in a single file known as the district accountability file. This file
is made available to district superintendents each year in June, through a restricted access
site known as PA eDirect (https://www.drcedirect.com/). This file contains state
assessment results for all students in the district. The file also contains information
related to whether or not each student was attributed to a school for reporting purposes or
not. It is this file that was obtained from each participating district that allows the
researcher to identify which students would be included in achievement and growth
reporting.
The other reports necessary for completion of this project were all pulled from
each district’s student information system. Several of these are part of the process of data
submissions to the state known as PIMS submission. The Pennsylvania Information
Management System (PIMS) is the means by which the state aggregates data from
schools for reporting and analysis. One such required file is a report known as the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
46
student-career standards benchmark report, which is uploaded at the end of the school
year and contains all of the information necessary for calculating career readiness
percentages.
Another necessary data source is known as the student calendar fact template.
This report provides necessary information to calculate attendance rates. Attendance is
reported on the Future Ready PA Index as a lagging indicator, meaning that the number
reported on the website is the value from not the previous school year but the year prior
to that. A lagging indicator is necessary when a variety of circumstances result in an
inability to be able to aggregate final information related to a given indicator in a timely
fashion. Another data source is known as the frozen graduate cohort data, which is also a
lagging indicator. This report would identify students in the prior year enrolled in high
school for four years who graduated. This data will assist the researcher in determining
graduation rates.
There is a sixth federally-mandated indicator of success that factors into the
Future Ready PA Index, but was not necessary to gather from the participating schools.
The percent of English language learners who achieve proficiency is also reported on the
system, but is only reported for schools with a minimum N-count of 20. None of the
schools participating in this project had an enrollment of English learners at that level,
and thus, that data is not available nor reported on the website.
One final piece of data collected from each of the districts identified enrollment
dates of students. For the purpose of this research, mobile students were defined as those
not continuously enrolled for at least one year. This enrollment information was used to
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
47
flag mobile students in the system, and to be used when creating adjusted student groups
as detailed in the procedure section that follows.
All of this data was obtained through each of the school district’s PIMS
administrators. (The Pennsylvania Information Management System, or PIMS, is a
statewide, longitudinal information management system designed to assist schools in
submitting timely data in a consistent format.) The researcher worked with each
superintendent to collaborate with this data administrator to pull the necessary reports
from their student information system for use in the project. One strategy that proved
helpful was accessing the PIMS manuals on the PIMS website and determining the
specific names of the reports needed. Entering into meetings with data administrators,
knowing the specific names of the reports needed helped to streamline the process, and
the data administrators expressed appreciation for the succinct specificity.
Data files were downloaded to a local, password-protected laptop, and saved in a
password-protected folder. Only the researcher maintained access and password to this
laptop. At the conclusion of the project, all files in this folder were permanently deleted.
Timing of the data collection.
The timing of the data collection was based upon the extant data required for
analysis. State accountability indicators are posted to a public website in the fall,
reflecting the prior year’s results. Data factoring into these results is drawn from a series
of data uploads initiated by the school district, through the summer just prior to the fall
release of school accountability indicators. Because of this, all available data for
examining a prior year’s success is available for collection by mid-summer. The data for
this research project was collected during February 2020, reflecting performance during
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
48
the 2018-2019 school year, with the exception of two lagging indicators, attendance and
graduation.
Choices and organization of the data.
The data collected and analyzed was classified into four categories. The data was
obtained from the source that informs Pennsylvania’s school accountability system and
the same attribution rules were applied. It is important to note that the state created
specific rules as to which students are attributed to a school and which students cannot be
attributed to a school. The rationale for the creation of attribution roles is based on the
fact that there are some students who are enrolled in a school for a minimal amount of
time that would not likely allow the organization enough time to make an academic
impact.
Achievement.
This indicator represents the percentage of students who scored proficient or
advanced on a state assessment. The Pennsylvania System of School Assessment (PSSA)
exam is administered to students in grades three through eight for mathematics and
English language arts, and grades four and eight for science. Additionally, students are
administered tests in Algebra, Biology, and Literature in high school, but this action
research study examined state assessments in grades three through eight only, as
reporting at the high school is more complex and obtaining the high school assessment
data in a format that would allow for validity may prove challenging. These state
assessments rank students in four proficiency levels – below basic, basic, proficient, and
advanced. Two groups of students do not factor into state calculations: students enrolled
after October 1, and first year English language learners. As the Future Ready PA Index
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
49
reports achievement at a subject specific, building-wide level, sample groups will be
defined by building, separated by content area.
Growth.
This indicator represents how a given group of students has grown from an
academic standpoint relative to their entering achievement. The same attribution rules
that are applied to achievement are also applied to growth. As the Future Ready PA
Index reports growth at a subject-specific, building-wide level, sample groups will be
defined by building, separated by content area.
Attendance Rate.
Attendance is defined as the percentage of students enrolled in a school for 90
school days or more, who are present for 90% or more of the days. This measure is a
lagging indicator. A lagging indicator is one that is the value from not the school year of
interest but the year before that. (The reason for this is that the complete data set that
comprises some indicators, such as attendance, cannot be fully collected by state for a
considerable length of time after the school year ends.) As the Future Ready PA Index
reports attendance at a building-wide level, sample groups will be defined by building.
Graduation Rate.
This represents the percentage of students who graduated from a school in a fouryear cohort. This measurement is also a lagging indicator. As the Future Ready PA Index
reports graduation at a twelfth grade building level, sample groups will by building
cohort.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
50
Career Readiness Benchmark.
This represents the percent of students who have satisfied requirements related to
career education as mandated by the state. This is reported by grade span, with reporting
occurring at the end of grade 5, grade 8, and grade 11. Accordingly, sample groups will
be aggregated based on these reporting rules.
English Language Learner Proficiency.
This indicator provides a measure of English learner growth and attainment of
English language proficiency. This is evaluated through the use of a state mandated
assessment known as ACCESS for ELLs.
Procedures for aggregating and examining the data.
After obtaining agreement to participate from superintendents, and then obtaining
the necessary data from the school district PIMS administrators, the process began with
flagging transient students in each of the files.
Flagging students in files.
As none of these files or submissions require a specially defined transiency field,
the researcher had to manually flag each transient student in each file. This was
accomplished by sorting each file by PAsecureID, then creating a column labeled
transient and placing an indicator in this column for each student who had not been
continuously enrolled in the school for at least one year.
Identifying students factoring into achievement and growth.
Each district’s district accountability file was manipulated to remove all students
who were not attributed to a school, remove all students enrolled after October 1, and
remove all students who were flagged as first year English language learner students.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
51
These students are not factored into the values on the Future Ready PA Index. The
remaining data was manipulated to determine the percent proficient/advanced for each
score and this number was compared to its value on the Future Ready PA Index site to
ensure fidelity. Once it was verified that the remaining data is the data that factored into
school accountability, then an adjusted cohort was created for each school, based on a
nationwide regional transiency rate of 8%. If a school had a rate of transiency at higher
than 8%, then the transient students would be removed, and through a process of random
selection, only 8% would be added back to the file (see process that follows). Finally,
proficient/advanced values were calculated again using this adjusted cohort.
Process of random selection.
When the number of transient students exceeded 8%, those students were pulled
out of a file and placed into a separate spreadsheet. The students were first sorted in
ascending order by PAsecureID. Each student was assigned a number beginning with the
number one. A random number generator (https://www.calculator.net/) was used to
randomly select a quantity of numbers that would equal 8% of the total student
population. These randomly selected students were then added back to the day to file.
This new group of students was identified as the adjusted group.
Identifying students factoring into the additional indicators.
For the additional indicators (career readiness, graduation, and attendance) a
similar procedure was followed. Students not attributed to a school were removed and
transient students were identified. If a school exceeded the 8% threshold of transient
students, they were removed and 8% selected for a random sampling and added back to
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
52
the group to form an adjusted cohort. Each of these adjusted groups were compared to
the formal group in the data analysis phase of the project.
Data analysis.
The data analysis phase began immediately following the creation of adjusted
cohort groups to compare to the formal cohort groups. Raw data files were manipulated
to isolate students attributed for school accountability. Transient students were flagged in
the files. Indicator values were calculated at the all student group level, a stable student
only level, and if applicable, and adjusted group controlled to 8% transient students
determined through random sampling. SPSS software was used to conduct a correlation
analysis on the data.
Statistical analysis.
The statistical analysis took place using SPSS software. This software, produced
by IBM, is the leading platform for statistical analysis in higher education, and is widely
used in industry. SPSS software was selected as it provides an effective way to manage
and analyze data, and a wide range of options to view the results.
The study examined the data in two ways. First, indicators were compared to
percent of mobile students in the sample group. Second, the concentration of mobile
students was compared to the change in each indicator’s value between the all student
group and the stable student group.
SPSS software was used to determine correlation and statistical significance of
the results. A bivariate measures of correlation analysis was utilized. Bivariate
correlation analysis is conducted to examine the relationship between two different
variables. The analysis produces a value that represents the relationship between a
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
53
change in A when there is a change in B. As the focus of this action research project is
an examination of the empirical relationship between student mobility and school
accountability factors, a bivariate correlation analysis will help examine the hypotheses
of association between the multiple sets of data.
The process for completing a bivariate correlation test using SPPS software
entails selecting the analyze function, then correlate. In the bivariate correlation option
menu, the two variables to be tested (i.e. % transient and math growth score) were pulled
into the test box. The following items were also selected: Pearson correlation coefficients,
two-tailed significance, and flag significant correlations. Following this setup, the test
process was run. (See Figure 8.)
Figure 8
SPSS Software. Bivariate correlations menu ã2015 IBM. Screenshot by author
Institutional Review Board (IRB).
To ensure that no district felt coerced to participate, the researcher held numerous
conversations with each participating district superintendent, providing not only the
purpose and rationale for the project, but also a detailed description of the methodology
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
54
and data analysis. Each superintendent was also provided with a copy of the IRB review
request, on which the researcher committed to maintaining confidentiality. As part of this
IRB review request, and in subsequent emails, each superintendent was assured of and
acknowledged the fact that they retained the right to withdraw from participation at any
time. Consent forms to participate were signed by each superintendent.
In adherence to university policy, an IRB request was submitted to the IRB
Review Board in November. 2019 (Appendix A). The IRB proposal was approved on
November 14, 2019 (Appendix B).
In order to make sure that the data collected was handled and stored in a
confidential manner, the researcher requested data files without name association. No
personally identifiable information was shared. This anonymous data was saved on a
local password-protected computer in a password-protected folder and the data was
deleted at the end of the project. There is no risk of bias in this study, as students were
not identified by name, and adjusted school accountability indicators were calculated
using district-provided files.
Validity
The purpose of this research was to determine the effect of transiency on school
accountability ratings. In research it is important to consider if observed variation can be
attributable to other causes aside from changes in the independent variable. When
considering threats to the internal validity, or credibility, of the results, history and
maturation, two common internal validity threats were not present in the study. Another
common internal validity threat is selection, and this was negated by the random
sampling methods used by the researcher.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
55
It is also important examine external validity or transferability, which relates to
how the results of a study can be generalized across subjects and settings. While the
experimental process did provide ecological validity, it is possible that the design led to a
small threat in population validity. While the researcher took many steps to solicit
partners for the project, only two school districts would participate. As the
Commonwealth has 499 school districts, it is possible that the two school district selected
are not completely representative of the majority, which might impact the ability to
generalize the conclusions across the Commonwealth.
Finally, the researcher made all efforts to ensure objectivity in this study. The
data that was collected followed a strict format aligned to state data-collection protocols
and consistent among all school districts. Random sampling took place using a wellaccepted process utilized in research around the globe. Student names were not shared,
nor did the researcher and superintendents have any discussion regarding expected
outcome of the analysis.
As the project was limited to analyzing extant data, no human subjects were
involved. The only potential discomfort to a school would be if the data showed that
regardless of student mobility all students are underachieving; this would serve as a
discomfort as it would be a sign of an ineffective system.
Summary
The purpose of this chapter was to explain the methodology used to answer the
action research questions. A discussion of the methodology, participants, data collection,
procedures, and data analysis followed. An empirical methodology of philosophical
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
56
positivism was used to develop the research, which examined the effect of transient
populations on school accountability indicators.
A quantitative data analysis was conducted utilizing information provided to
school districts through the Pennsylvania school accountability system. The method of
research was to examine the six school accountability indicators that factor into school
improvement designation. The process for examining these and their impact on mobility
involved isolating the transient students from the stable students, then conducting a
statistical analysis to look for a relationship between the percentage of transient students
in a school and its accountability values. The accountability values from eight schools in
Pennsylvania were examined. The schools exhibited diversity in terms of socioeconomic
composition.
The methodology proved to be internally valid and faced only a small threat in
external validity, in terms of population validity. The researcher ensured that the project
was completed in an ethical manner, and that no human subjects were involved, and no
personally-identifiable information was provided. Proper protocol was followed in
adherence to the institutions IRB policy. Chapter 4 will outline results of the study and
demonstrate in action the methodology described in this chapter.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
57
CHAPTER 4
Data Analysis and Results
The purpose of this chapter is to present the results of the statistical testing and
analysis. A grounded theory methodology of positivism was used to answer the research
questions. For each of the two research questions, the data analysis and associated
descriptive correlations will be shared, along with supporting methodology to allow the
study to be replicated. The processes used to filter the raw accountability files to isolate
attributed students as well as to flag transient students will be shared, as well as the
calculations that led to the indicators that were studied. Included in this chapter will be
graphics and tables used to visually display and emphasize the results of the study. The
chapter will conclude with a reflection on each research question and concluding answers
drawn from the data. This action research project sought to find answers to two questions.
Is there a significant relationship between student mobility and a school’s accountability
indicators? How do schools fare in Pennsylvania’s school accountability system when
controlling for levels of student mobility?
Data Analysis
For the purpose of the study, mobility and transiency will appear interchangeable.
Mobility will be defined as students who have not been continuously enrolled in the same
school for twelve months. An average student mobility rate of 8% was utilized as
reported in the Current Population Survey Annual Social and Economic Supplement
posted on the census.gov website (“Geographical Mobility”, 2018). Based on research
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
58
that indicates that transiency impacts academic achievement and school success, the
researcher assumed that the presence of mobile students in a school would adversely
affect state accountability indicators. Based on this assumption, the researcher also
speculated that when controlling for the number of mobile students in a group, the
school’s accountability numbers would likely experience an increase, perhaps high
enough to prevent a school improvement designation. Will the data analysis support these
hypotheses?
Key terms and definitions referenced in the process.
Before presenting the process by which the researcher analyzed the data, it is
important to provide the reader with an explanation of key terms and definitions
referenced in the process. A description of these key terms follows.
Pennsylvania’s system of school accountability.
The data analysis created modified students groups (controlled for transiency rate)
which were then compared to numbers publicly posted on Pennsylvania’s Department of
Education website. Pennsylvania has created a system for measuring the success of
schools using multiple measures. This system, the Future Ready PA Index, features a
dashboard approach to school and student group performance. The Future Ready PA
Index illustrates student and school success on eleven indicators using a color-coded
system (Pennsylvania Department of Education, 2019). Per federal guidelines, six of the
eleven indicators are used in the process of identifying schools in need of school
improvement (U.S. Department of Education, 2019). Since this action research examined
the impact of transiency on school improvement, these six indicators were examined in
each of the three analyses as part of this project.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
59
These indicators are as follows (the six federal accountability school improvement
indicators examined in the project identified with an *):
•
Percent Proficient or Advanced on Pennsylvania State Assessments*
•
Meeting Annual Growth Expectations*
•
Percent Advanced on Pennsylvania State Assessments
•
English Language Growth and Attainment*
•
Regular Attendance*
•
Grade 3 ELA and Grade 7 Math Early Indicators of Performance
•
Career Standards Benchmark*
•
High School Graduation Rate*
•
Industry-Based Learning
•
Rigorous Courses of Study
•
Post-Secondary Transition to School, Military, or Work
Descriptions of the six indicators examined.
Achievement.
This indicator represents the percentage of students who scored proficient or
advanced on a state assessment. The Pennsylvania System of School Assessment (PSSA)
exam is administered to students in grades three through eight for mathematics and
English language arts, and grades four and eight for science. Additionally, students are
administered tests in Algebra, Biology, and Literature in high school, but this action
research study examined state assessments in grades three through eight only, as
reporting at the high school is more complex and obtaining the high school assessment
data in a format that would allow for validity may prove challenging. These state
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
60
assessments rank students in four proficiency levels – below basic, basic, proficient, and
advanced. Two groups of students do not factor into state calculations: students enrolled
after October 1, and first year English language learners. As the Future Ready PA Index
reports achievement at a subject specific, building wide level, sample groups will be
defined by building, separated by content area.
Growth.
This indicator represents how a given group of students has grown from an
academic standpoint relative to their entering achievement. The same attribution rules
that are applied to achievement are also applied to growth. As the Future Ready PA
Index reports growth at a subject-specific, building-wide level, sample groups will be
defined by building, separated by content area.
Attendance Rate.
Attendance is defined as the percentage of students enrolled in a school for 90
school days or more, who are present for 90% or more of the days. This measure is a
lagging indicator. A lagging indicator is one that is the value from not the school year of
interest but the year before that. (The reason for this is that the complete data set that
comprises some indicators, such as attendance, cannot be fully collected by state for a
considerable length of time after the school year ends.) As the Future Ready PA Index
reports attendance at a building-wide level, sample groups will be defined by building.
Graduation Rate.
This represents the percentage of students who graduated from a school in a fouryear cohort. This measurement is also a lagging indicator. While eight schools
participated in this project, only one of these schools was a high school; therefore the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
61
researcher did not examine graduation rate as an n-count of one would not provide
statistical significance.
Career Readiness Benchmark.
This represents the percent of students who have satisfied requirements related to
career education as mandated by the state. This is reported by grade span, with reporting
occurring at the end of grade 5, grade 8, and grade 11. Accordingly, sample groups will
be aggregated based on these reporting rules.
English Language Learner Proficiency.
This indicator provides a measure of English learner growth and attainment of
English language proficiency. This is evaluated through the use of a state-mandated
assessment known as ACCESS for ELLs. This indicator is only reported for schools that
have a minimum student group of 20 English learners; none of the schools participating
in this project met this requirement, thus the researcher omitted this indicator from the
correlation analysis.
Definition of transient.
As examined in the review of the literature, there is little common language for
both measuring and defining mobility. It has been found in previous research that the
recency of mobility matters. The more recent the move to a new school, the greater it’s
possible effect on student achievement and assimilation (Green & Daughtry, 1961). In
the first year in which a student moves to a different school, progress on learning
experiences the most severe loss. This negative impact on achievement continues at a
lesser rate in subsequent years. During this initial transition year, transient students also
encounter the most difficulty with settling into a new culture and making social
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
62
connections. Additionally, the Current Population Survey Annual Social and Economic
Supplement (CPS-ASEC), posted on the census.gov website, shows a mobility rate for
2017-2018 of 8% in the northeast United States and defines mobility as those who have
moved ‘within the past twelve months’(“Geographical Mobility”, 2018). For these
reasons, for the purpose of this action research, transient students will be defined as
students who have not been continuously enrolled in the same school for 12 months.
School improvement identification.
In a process termed annual meaningful differentiation by federal statute, states
must designate schools, at least every three years, into three designations:
•
Comprehensive Support and Improvement (CSI): Schools facing
significant challenges in achievement, growth, and any of the other four
areas highlighted above
•
Additional Targeted Support and Improvement (A-TSI): schools
experiencing poor performance by one or more student groups belong a
specified threshold
•
Targeted Support and Improvement (TSI): schools experiencing poor
performance by one or more student groups in danger of approaching a
specified threshold
Schools are identified for one of the levels of school improvement if they have
both low achievement scores and low growth profiles (below statewide minimum values)
and poor performance on additional ESSA-required indicators. If mobility impacts
student achievement and growth as well as graduation rates, can a high mobility rate lead
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
63
to a school improvement designation? With this key background developed and defined,
collection of the data began.
Collecting the sample data.
The first step in this process was to collect the data that would be examined. This
study examined student accountability data from eight Pennsylvania schools. Four of
these schools are elementary buildings with a K-4 configuration. The economically
disadvantaged rate at the schools ranges from a low of 40% through a high of 68%. One
school is a K-6 building configuration with a 74% economically disadvantaged rate. Two
schools are middle schools, one 5-6 building and one 7-8 building, with economically
disadvantaged rates of 53% and 60% respectively. The eighth building examined in this
study is a high school with an economically disadvantaged rate of 47%. With the
exception of the 7-8 and high school buildings, all of the other buildings have been
federally-designated as Title I.
Once permission to participate was obtained from superintendents of districts
involved in this study, the researcher identified the state mandated uniform data file
submissions that factor into state accountability indicators. Each district’s data manager
exported the requested files from the district’s student information management system,
removing student names as an added layer of confidentiality. These files were shared
with the researcher. In addition, the district data managers also provided a file containing
student enrollment information from June 1, 2016 through May 31, 2019. This
information was used to flag transient students in the accountability files. With these
files in hand, the next step was to determine which students in these files are factored into
(attributed) to school accountability values.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
64
Identifying attributed students and triangulating data.
Upon receipt of the accountability files, the next step in the process was to
identify which students in the files are attributed to the schools. This was necessary
because there are some students who may be enrolled in school, but due to
Pennsylvania’s school accountability attribution business rules, the students do not factor
into calculations. For achievement and growth, the district accountability file was filtered,
removing students who were not attributed to any district school. Additionally, first year
English language learners, as well as those students enrolled after October 1, were
removed. In order to confirm the accuracy of the filtering and to ensure the triangulation
of data, proficiency rates were calculated for each school and compared to those
published on the Future Ready PA Index website.
For career readiness benchmarks, the exported file contains all students to be
attributed, and thus, no additional filtering of exempt students was necessary. Care only
had to be taken to filter for each school and create separate groups as such. The file
necessary for calculating attendance contains all student attendance data including those
who attended for only a partial year. The researcher had to apply the business rules of
selecting only those students who attended for 90 or more days. Finally, the file necessary
for calculating graduation rate required students attributed to other schools to be filtered
from it. As with the attendance and growth files, these files were triangulated to ensure
that the starting indicator values matched those on the Future Ready PA Index website.
Now that the researcher identified which students ‘count’ towards accountability, the next
step was to determine which of those students could be considered transient.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
65
Identifying and flagging transient students.
After the data from the accountability files was filtered for accuracy in matching
the state report and values, the next step was to identify and flag transient students in the
file. For the purpose of this action research project, transient students are defined as
those students who have not been continuously enrolled for at least one year prior to the
start of a given school year. This project focused on school accountability indicators from
the 2018-2019 school year, with attendance and graduation being lagging indicators,
reporting from the 2017-2018 school year. As such, it was necessary to obtain enrollment
information from June 1, 2016 through May 31, 2019. Once the accountability files were
filtered for attributed students and accuracy checked, transient students could be flagged
in the files.
In flagging students in the achievement, growth and career readiness files, the
researcher identified students who enrolled on or after August 24, 2017. These students
would be flagged in the files. The PAsecureIDs of transient students were pasted into
each accountability file, and a conditional highlighting rule was applied which helped to
quickly identify transient students in the file. A column was added to denote this
attribute. The same process took place for the attendance and graduation accountability
files; however, as these two indicators are lagging, students who are enrolled on or after
August 24, 2016 were defined as transient. Once transient students were identified, this
allowed for transiency rates to be calculated for each group for each indicator.
Calculating the rate of transiency in each group for each indicator.
As each accountability indicator has its own attribution rules, and the exports
from student information management systems are specific to the report, there is
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
66
variation between transiency rates for a given school for each indicator. A rate of
transiency was calculated for each school for each indicator. The rate was calculated by
comparing the number of transient students in a group to the total number of students in
the group. The transiency rate was defined by the percentage of transient students in the
group. This was used in two ways. The first was to identify if a school had a transiency
rate higher than the 8% national average. If so, the school was assigned an adjusted
cohort controlled to 8%. The other key aspect in identifying the transiency rate is for use
in the correlation analysis that follows.
Creating stable and adjusted groups.
The data in the original files obtained from participating districts contained the
information that resulted in the indicators posted on the Future Ready PA Index website,
and this included all stable and mobile students. As this action research project examined
whether the inclusion of mobile students impacts the indicator values, it was important to
create two separate groups for each school and indicator. These two groups would be
compared in the analysis to determine the impact that the addition of transient students
has on a school’s accountability values. The first additional group set was defined as
only stable students, and did not include any mobile students. This was pertinent as it
provided an overall indicator value for a group if it did not include any transient students.
For schools and indicators that had a mobility rate higher than 8%, an adjusted group was
created as well. This adjusted group was important as it was used to examine whether or
not a school’s accountability values are lower when the percentage of mobile students is
higher than average.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
67
The process for creating the adjusted group began with removing the transient
students from the file. Random numbers were then assigned to this list of transient
students, and a random number generator was used to select students to add back to the
file. Students were randomly selected and added back to the accountability file until the
transiency rate for the group was calculated at 8%. This became the adjusted group.
These three sets of sampling groups – all, stable, and adjusted – were then analyzed for
correlation.
Bivariate measures of correlation.
This study sought to examine the effect of transiency on achievement indicators
and focused on exploring the correlation between two different sets of variables: the
relationship between transiency and change in indicator value, and the relationship
between transiency and the actual value. Bivariate analysis was selected as a means of
answering the problem statement, as this analysis provides an effective method to show
whether or not there is any association between transiency and accountability indicators.
Bivariate correlation analysis is one that examines the relationship between two different
variables. The analysis produces a value that represents the relationship between a
change in A when there is a change in B. For example, a bivariate analysis could be
used to examine the percentage of electric vehicles in a community compared to the
number of charging stations; it might also be used to examine the relationship between
the number of web browser ads displayed for face masks and the number of online mask
purchases. In the case of this action research project, the researcher was examining the
relationship between two variables: the rate of transiency and each of the indicator
values. Bivariate analysis is an effective way to solve this problem, as it shows the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
68
researcher the relationship between transiency and indicator values. If the levels of
transiency are known, it might be easier to predict the indicator value. Data analyses
results that show a strong correlation between transiency rates and school accountability
indicators will provide an answer to the researcher’s problem examining whether high
transiency rates affect school improvement designation.
Pearson correlation.
A bivariate correlation analysis produces a Pearson correlation coefficient that can
be used to identify the strength of a relationship. Additionally, this analysis also
identifies whether there is statistical significance with the relationship. One important
limitation of this analysis to note is that a bivariate Pearson correlation does not identify
causation, but rather correlation or association between sets of variables.
A bivariate Pearson correlation begins with a null hypothesis H0 that assumes a
true correlation value p0 of 0. An alternative hypothesis HA represents the actual
correlation as p1, with an assumed value not equal to 0. This can be represented as:
If H0 holds a p0 of 0, no correlation exists;
If HA holds a p0 not equal to 0, some correlation exists
This analysis examines what, if any, correlation exists supporting an HA with a p0 not
equal to 0. The correlation coefficient of the sample is identified as r, and is calculated
(using the SPSS software) as:
rab =
cov(a,b)
var(a) • var(b)
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
69
with (a,b) representing the variables in consideration, cov(a,b) is the covariance between
a and b, and var(a) and var(b) representing the sample variance of a and b, respectively.
Adhering to Cohen (1988), the strength of the correlation is defined by:
strong correlation
|r|>.5
moderate correlation .3<|r|<.5
weak correlation
.1<|r|<.3
As Pearson Correlation values can be positive or negative, absolute values are used in
considering strength of relationship. The value in the use of a Pearson Correlation
analysis in this project is that its results will show the strength of the relationship between
the rate of student transiency and the school accountability values. A challenge in
conducting a Pearson Correlation analysis is the mathematical computations necessary;
using software that automates the process, including reporting, mitigates this challenge.
SPSS software.
Conducting multiple correlation analyses by hand can be very time-consuming,
and thus, a commercial software package was utilized for this purpose. This software
allows the researcher to more easily input data from the school accountability files, and
quickly view automated correlation analysis results. Statistical Package for Social
Sciences (SPSS) is a software package published by IBM that allows complex statistical
data analysis. This software is one of the leading data analysis tools used by social
scientists, researchers, educators, and many others in higher education. It offers a
familiar interface for inputting data, and powerful tools for conducting regression and
correlation analysis, as well as producing visualizations. SPSS was used in this study’s
correlation analysis. The software provided the researcher with a statistical correlation
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
70
between each experimental group and each of the accountability indicators. This was then
used by the researcher to identify whether or not a significant correlation existed, as well
as to prepare recommendations for future action and research. With accountability files
obtained, attributed and transient student identified, and transiency rates calculated, the
correlation analyses could begin.
Examining change in school indicators caused by transiency rate.
Is there a significant relationship between a school’s rate of student mobility and
its school accountability indicators? Can a correlation be made between the percentage
of transient students in a school group’s student composition and the impact that
subgroup has on the schools indicator value? In order to address this, a correlation
analysis was conducted examining the relationship between change in indicator value at
each school when comparing the all-student group with the stable-only student group. In
other words, can a connection be made between how many transient students are in a
school population and how this affects its indictor value? The researcher was looking for
how significant of an impact that transiency rate has on a school accountability values
(and thus, on its ‘effectiveness’, as reported on the Future Ready PA Index). The
following analyses were conducted using the bivariate correlation analysis tool in SPSS:
•
Change in Math Growth Indicator vs. Transiency Rate
•
Change in Attendance Indicator vs. Transiency Rate
•
Change in ELA Achievement Indicator vs. Transiency Rate
•
Change in Math Achievement Indicator vs. Transiency Rate
•
Change in Career Readiness Indicator vs. Transiency Rate
•
Change in ELA Growth Indicator vs. Transiency Rate
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
71
Examining relationship between levels of transiency and reported indicators.
How do schools fare in Pennsylvania’s school accountability system when
controlling for levels of mobility? If a school with a higher than average level of transient
students had a level of student mobility as low as the national average, would its
accountability indicator values be higher? Can one infer that when a school has a higher
level of student transiency, its school accountability values will be correspondingly lower
and thus, the school would be more susceptible to school improvement designation? In
order to address this, two different correlation analyses were conducted. The first
analysis examined the relationship between indicator value when comparing the stableonly student group at each school and an adjusted group controlled for the national
average of 8% mobility. The analyses conducted using the bivariate correlation analysis
tool in SPSS were:
•
Career Readiness Indicator for all-student group vs. adjusted group
•
Math Achievement Indicator for all-student group vs. adjusted group
•
ELA Achievement Indicator for all-student group vs. adjusted group
The second analyses examined the percent of transient students in a school group
compared to its value reported on the Future Ready PA Index website. The following
analyses were conducted using the bivariate correlation analysis tool in SPSS:
•
Attendance Indicator vs. Transiency Rate
•
ELA Achievement Indicator vs. Transiency Rate
•
Math Achievement Indicator vs. Transiency Rate
•
Math Growth Indicator vs. Transiency Rate
•
Career Readiness Indicator vs. Transiency Rate
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
•
72
ELA Growth Indicator vs. Transiency Rate
The following section of this chapter will discuss the results of these analyses.
Results
Research question one - findings.
Is there a significant relationship between a school’s rate of student mobility and its
school accountability indicators? Table 1 displays the results of the analyses that were
conducted. For each set of variables examined, the correlation coefficient between the
variables as well as the significance of the relationship is displayed.
The key point to note in this table is the ‘Strength of Relationship’ column. Of
the six analyses conducted, it was found that four of the six show a strong relationship
between the rate of transiency and the change indicator value at that school; the
remaining two show a moderate relationship. This means that yes, there exists a
significant relationship between the rate of student mobility and indicator values.
Table 1
Bivariate correlation results between transiency rate and change in examined indicators
for each school.
Analysis
Change in Math Growth
Indicator vs. Transiency Rate
Change in Attendance
Indicator vs. Transiency Rate
Change in ELA Achievement
Indicator vs. Transiency Rate
Change in Math Achievement
Indicator vs. Transiency Rate
Change in Career Readiness
Indicator vs. Transiency Rate
Change in ELA Growth
Indicator vs. Transiency Rate
Pearson
Correlation (r)
-.982
Strength of
Relationship
Strong
Statistical
Significance(p)
.018
-.961
Strong
.002
-.635
Strong
.126
-.630
Strong
.130
-.450
Moderate
.703
-.356
Moderate
.557
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
73
Career readiness benchmarks.
Career readiness benchmarks are reported as the percentage of students who, by
the end of grades five, eight, and 11, have completed a mandated number of career
readiness artifacts. As seen in Table 1, a moderate correlation of -.450 was found
between the rate of transiency and the change in career readiness benchmark value. This
demonstrated that an increased rate of transiency results in a decreased career readiness
indicator value.
Attendance.
Attendance is defined as the percentage of students enrolled in a school for 90 or
more school days who were present for 90% or more of those school days. As seen in
Table 1, a strong correlation of -.961 with a statistical significance of .002 was found
between the rate of transiency and the change in attendance value. This demonstrated
strong evidence that an increased rate of transiency results in a decreased attendance
indicator value.
Math growth.
Academic growth in math will be defined using Pennsylvania’s PVAAS model of
growth, which examines the entering achievement for a group of students compared to
the exiting achievement of the same group of students. It will be calculated by creating
custom reports populated with the students in each examined goup. As seen in Table 1, a
strong correlation of -.982 with a statistical significance of .018 was found between the
rate of transiency and the math growth value. This demonstrated strong evidence that an
increased rate of transiency results in a decreased math growth indicator value.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
ELA growth.
Academic growth in ELA is defined in the same manner. As seen in Table 1, a
small correlation of -.356 was found between transiency rate and ELA growth value.
This demonstrated only small evidence that an increased rate of transiency results in a
decreased ELA growth indicator value.
Math achievement.
Achievement in math will be defined as the percentage of students who scored
proficient or advanced on the current year’s math state assessments (PSSA or Keystone
Exam). As seen in Table 1, a large correlation of -.630 was found between the rate of
transiency and the math achievement levels. This demonstrated strong evidence that an
increased rate of transiency results in a decreased math achievement indicator value.
ELA achievement.
Achievement in ELA will be defined in the same manner. As seen in Table 1, a
strong correlation of -.635 was found between the rate of transiency and the ELA
achievement levels. This demonstrated strong evidence that an increased rate of
transiency results in a decreased ELA achievement indicator value.
Graduation and EL proficiency.
English learner proficiency indicators were omitted from this analysis because
there was not an n-count to be reported on the Future Ready PA Index. The graduation
indicator was omitted as there was only one participating high school in this action
research project.
74
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
75
Research question two – findings.
How do you schools fare in Pennsylvania’s state school accountability system
when controlling for transiency? Table 2 displays the results of the analyses that were
conducted. For each set of variables examined, the correlation coefficient between the
variables as well as the significance of the relationship is displayed.
The key point to note in this table is the ‘Strength of Relationship’ column. Of
the three analyses conducted, it was found that all show a strong relationship between the
school indicator value for the all-student group and the group adjusted to 8%; this means
that decreasing the rate of transiency for each school does had a direct impact on all
values examined, increasing the school indicator values.
Table 2
Bivariate correlation results between cohorts adjusted to 8% transiency rate and change
in indicator value examined for each school.
Analysis
Career Readiness
Indicator vs. 8%
Transiency Rate
Math Achievement
Indicator vs. 8%
Transiency Rate
ELA Achievement
Indicator vs. 8%
Transiency Rate
Pearson Correlation
(r)
1
Strength of
Relationship
Strong
Statistical
Significance (p)
.000
1
Strong
.000
1
Strong
.000
How does transiency affect the indicators that factor into school improvement
designations? In order to examine the last research question, a correlation analysis
between transiency rate and absolute values of indicators was conducted. Table 3
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
76
displays the results from this analysis. For each set of variables examined, the correlation
coefficient between the variables as well as the significance of the relationship is
displayed.
The key point to note in this table is the ‘Strength of Relationship’ column. Of
the six analyses conducted, it was found that three of the six show a strong relationship
between the rate and transiency and the indicator value at that school; one of the
remaining three shows a moderate relationship. This means that an increased rate of
transiency in a school could have a negative impact on four of the six values examined as
reported on the Future Ready PA Index. If increased transiency rates lead to decreased
accountability values, this makes school with high mobility rates more susceptible to
being designated for school improvement.
Table 3
Bivariate correlation results between transiency rate for each school and the absolute
(reported) values of each indicator for that respective school
Analysis
Attendance Indicator
vs. Transiency Rate
ELA Achievement
Indicator vs.
Transiency Rate
Math Achievement
Indicator vs.
Transiency Rate
Math Growth
Indicator vs.
Transiency Rate
Career Readiness
Indicator vs.
Transiency Rate
ELA Growth Indicator
vs. Transiency Rate
Pearson Correlation
(r)
-.920
Strength of
Relationship
Strong
Statistical
Significance (p)
.009
-.779
Strong
.221
-.639
Strong
.361
-.414
Moderate
.586
-.270
Weak
.826
-.204
Weak
.742
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
77
Career readiness benchmarks.
As seen in Table 3, a small correlation of -.270 was found between the rate of
transiency and the absolute value of career readiness benchmarks. This demonstrated
only small evidence that an increased rate of transiency results in a decreased career
readiness indicator value, which could lead to greater likelihood of school improvement
designation.
Attendance.
As seen in Table 3, a large correlation of -.920 with a statistical significance of
.009 was found between the rate of transiency and the absolute value of attendance rate.
This demonstrated strong evidence that an increased rate of transiency results in a
decreased attendance indicator value, which could lead to greater likelihood of school
improvement designation.
Math growth.
As seen in Table 3, a moderate correlation of -.414 was found between the rate of
transiency and the absolute value of math growth. This demonstrated evidence that an
increased rate of transiency results in a decreased math growth indicator value, which
could lead to greater likelihood of school improvement designation.
ELA growth.
As seen in Table 3, a small correlation of -.204 was found between the rate of
transiency and the absolute value of ELA growth. This demonstrated only small
evidence that an increased rate of transiency results in a decreased ELA growth indicator
value, which could lead to greater likelihood of school improvement designation.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
78
Math achievement.
As seen in Table 3, a large correlation of -.639 was found between the rate of
transiency and the absolute value of math achievement. This demonstrated strong
evidence that an increased rate of transiency results in a decreased math achievement
indicator value, which could lead to greater likelihood of school improvement
designation.
ELA achievement.
As seen in Table 3, a large correlation of -.779 was found between the rate of
transiency and the absolute value of ELA achievement. This demonstrated strong
evidence that an increased rate of transiency results in a decreased ELA achievement
indicator value, which could lead to greater likelihood of school improvement
designation.
Graduation and EL proficiency.
English learner proficiency indicators were omitted from this analysis because
there was not an n-count to be reported on the Future Ready PA Index. The graduation
indicator was omitted as there was only one participating high school in this action
research project.
Discussion
This action research project examined two questions: is there a significant
relationship between a school’s rate of transiency and its accountability indictor? How to
schools fare in Pennsylvania’s school accountability system when controlling for
transiency? An interpretation of the analyses results will be discussed in the next section.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
79
Findings on the relationship between rate of transiency and indicator value.
Is there a significant relationship between a school’s rate of transiency and its
accountability indicator? It was assumed that there would be a strong relationship
between the percentage of transient students in a school population and its accountability
values. This was supported by the results of the project. Four of the six indicators
examined showed a strong relationship between the rate of transiency and the change
indicator value for the schools; the remaining two show a moderate relationship. This
provides statistical evidence that there is a significant relationship between the rate of
student mobility and each of the indicator values examined. The indicators with the
strongest relationship to rate of transiency were found to be math growth and attendance,
followed by ELA achievement and math achievement. ELA growth and career readiness
showed a moderate relationship.
There are implications of these results at several levels. At a school level, this is
important because it provides evidence of the need for support of mobile students, in all
of the six areas examined. At a student level, what interventions are in place to assist the
students? What supports do schools have in place to ensure that the unique needs of the
students are met? At a state level, this is important because it supports an existing body of
work relating to the challenges faced by students who move between districts. As the
state is committed to equity for all students, this often-marginalized group should be
provided with statewide assistance. The state is investing millions of dollars over the
next few years in school improvement efforts, and this supports the researcher’s belief
that research-based supports that address the challenge of student mobility be provided.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
80
Findings on the impact of transiency on school improvement indicators.
How do you schools fare in Pennsylvania’s school accountability system when
controlling for transiency? It was assumed that an increased percentage of mobile
students would lead to decreased school accountability indicators, and this in turn would
lead to a greater likelihood of school improvement designation for schools which
experience a high level of student mobility. The bivariate Pearson Correlation analysis of
the impact of transiency rate on the values of school accountability indicators found a
strong correlation for its impact on math and ELA achievement, as well as in attendance.
A moderate correlation was found to math growth; a small correlation was found for both
ELA growth and career readiness benchmark values. As a result, schools with a higher
level of transiency will likely experience accountability indicator numbers that are lower,
and it is reasonable to infer that these schools will more likely be identified for school
improvement. The results of this project showed that for schools with a greater than
average level of transiency, when this rate was reduced to the national average, their
school accountability values increased. This would make them less likely to be identified
for school improvement designation.
This is important for schools as a school improvement designation carries a
negative stigma. No school wants to be identified for school improvement. The results of
this research will inform not only the participant schools, but schools across the
Commonwealth that their levels of transient students do impact their accountability
scores; there is a significant correlation between the percentage of transient students and
the change in their value. In other words, the more transient students they have, the lower
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
81
their values will likely be. This in turn will make them more susceptible to being
identified for school improvement. Recommendations based on this will be provided in
the next chapter. This is also important for the state as it identifies a potential flaw in its
school improvement designation system. As mentioned earlier in this paper,
Pennsylvania’s accountability system does have some measures in place to ensure that
students with a short tenure at a school are not included for identification purposes, but
the research shows that these business rules do not consider all of the transient students.
Just as Pennsylvania recently passed legislation which will factor the poverty rate of a
school district into teacher and school leader evaluations, the state may wish to consider
factoring transiency rates into the process as well. Additionally, Pennsylvania is
investing significant money over the next few years in school improvement efforts, and
the research suggests that one subgroup of students not currently the subject of focused
effort – mobile students – could benefit from research-based supports.
Findings interpreted by indicator.
While each of the schools may experience variation among transient population,
stable student body, staffing and leadership, and other external factors, commonality was
found in the impact of mobile students on each building’s school accountability indicator
value.
Attendance.
The outcome of the analysis for attendance showed a large correlation, with high
statistical significance, between attendance values and transiency rates. This corresponds
with what can be found in a review of existing literature. Arriving at a new school,
students can feel frustrated in their current academic levels compared to those of their
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peers, and this sometimes results in greater absenteeism. Parke and Kanyongo (2012)
found that student mobility has a profound impact on attendance, even greater than on
achievement. What this means in terms of the research problem is that when a school has
a high level of transient students, its attendance indicator value will likely be decreased,
and this makes it more likely that the school could be designated for school improvement.
Mathematics growth.
The results also showed large and moderate correlations between rates and
mathematics growth. The meaning of this in relation to the research problem is that
increased levels of student mobility result is a decrease in math growth values, and since
these values factor into school improvement designation, make the school more
susceptible to school improvement designation. This is likely due to the impact of lost
instruction or content not mastered. Growth calculations consider past academic
performance and predict or project where students are expected to score on the next
assessment, but they do not take into account a student’s history of mobility. This is
consistent with decades of research that show a detrimental effect of mobility on student
success in school. When mobile students are removed from a value-added growth
analysis, school scores increase (Williams, 2003). Without a business rule of removing
the scores of mobile students, the math growth indicators were negatively impacted.
ELA growth.
Interestingly, in contrast to math growth, the results of the correlation studies
showed only a small relationship between transiency and growth in English language
arts. What this means in terms of the research problem is that when a school has a high
level of transient students, there is only small evidence that its ELA growth indicator
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value will likely be decreased, which results in only a small effect on whether the school
could be designated for school improvement. The reason for this disparity between
content areas is not apparent in the results. The researcher speculates that it could be due
to the fact that mathematics is a more discrete subject and English language arts skills
extend across multiple curricular areas, the impact of missed instruction is greater in
mathematics. PA Core Standards for mathematics have a great variety of discrete topics
in each grade level, and the mastery of each is crucial for success in vertical progression
(K-12) through the subject area. Specific eligible content in a math course might be
addressed for two weeks in one grade, and not revisited until over an entire year later. If
as a result of a recent transition, a student fails to master eligible content in a specific
reporting category, or even worse, is not exposed to that content, an entire school year
might pass until the student has the opportunity to develop that content again. State core
standards for ELA represent an integrated model of literacy, one in which components
are closely connected (Common Core Standards Initiative, 2020). Skills are introduced
and embedded throughout a typical ELA curriculum, which allows for more opportunities
for students to interact with content. This more integrated design, with its more multiple
opportunities to revisit and refine skills, may explain why students tend to score closer to
their projected scores in ELA than in mathematics.
Math achievement.
The results of the study show a strong correlation between transiency and
mathematics achievement scores in all analyses. Across the board, mathematics
achievement scores were lower when the transiency rate was higher. The meaning of this
in relation to the research problem is that increased levels of student mobility result is a
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decrease in math achievement values, and since these values factor into school
improvement designation, make the school more susceptible to school improvement
designation. This aligns to the decades of research that show the detrimental impact of
transiency on student success in school. Shoho (2010) found a similar correlation in a
similar study examining Texas state math assessments. As curricula vary widely from
one district to another, this places transient students at a significant disadvantage when
they arrive at a new school, because they have not progressed through that particular
district’s vertically- and horizontally-aligned curricula.
ELA achievement.
The action research project results also demonstrated a large correlation between
transiency rate and ELA achievement values. What this means in terms of the research
problem is that when a school has a high level of transient students, its ELA achievement
indicator value will likely be decreased, and this makes it more likely that the school
could be designated for school improvement. A considerable body of research supports
this finding. A study of a New Jersey state exam found that student transiency negatively
impacted student scores in reading (Krenicki, 1999). California students experiencing
several moves, when administered the California achievement test in reading,
demonstrated reading scores that were 50% lower (The Family Housing Fund, 1998).
Career readiness benchmarks.
Finally, the results of the study showed only a moderate correlation between
transiency rate and its impact on school indicator, and small correlation between the rate
and absolute value. The meaning of this in relation to the research problem is that
increased levels of student mobility only moderately impact this indicator, which
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demonstrates that it could have some impact on school improvement identification. Of
all in-school indicators examined, this is the one that schools can most readily help
students to accomplish, possibly due to the fact that career readiness work is exploratory
in nature and less dependent on mastery of a sequence of academic skills. Unlike the
sequential nature of math and ELA content, career and work standards are more universal
and subject to personal choice and teacher acceptance. Even if a transient student has
experienced gaps in academic learning in the past, or may be at a lower academic level
compared to his peers in the current school, helping the student provide evidence of
career awareness would likely be on affected by this. Helping students show evidence of
career awareness and preparation requires a less-intense level of effort than academic
content.
Summary
This chapter highlighted the results of the correlation analysis, linking the
research questions to the evidence that was found. The school accountability data for
eight schools was obtained and examined in an effort to understand the impact of student
mobility on school accountability indicators.
A bivariate Pearson correlation analysis was conducted, seeking to determine a
relationship between three sets of considerations: (a) transiency rate and change in
school indicator values, (b) school absolute values and values adjusted to 8% transiency,
and (c) transiency rates and absolute school values. Based on the strength of relationship
found between the rate of transiency and how that affected the indicator at the school, this
means that the addition of transient students to a group has a negative impact on
accountability values. Transiency rates had a statistically strong connection to math
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growth, attendance, ELA achievement, and math achievement. These rates had a
statistically moderate connection to career readiness and ELA growth.
The data analysis also found that when controlling the number of transient
students in a score to the national average of 8%, this had a direct impact on all
indicators, increasing their value, which demonstrated that the more transient students in
a group, the lower their accountability values. If increased transiency rates lead to
decreased accountability values, this makes schools with high mobility rates more
susceptible to being designated for school improvement. In summary, one research
question asked is there a significant relationship between student mobility and a schools
accountability indicators. The answer is yes; higher levels of transient students lead to
lower accountability values. The second question asked about the impact this might have
on school improvement designation. The answer is it could have a direct and negative
impact on this, as the resulting lower values put the score at greater risk for school
improvement status. Chapter 5 provides a critical analysis of the results, implications all
these results at a local and state level, and recommendations for further research.
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CHAPTER 5
Conclusions & Recommendations
This chapter provides a discussion of the findings to help answer the following
research questions: Is there a significant relationship between student mobility and a
school’s accountability indicators? How do schools fare in Pennsylvania’s school
accountability system when controlling for levels of student mobility?
This action research project was a study based on quantitative grounded theory.
The purpose of the project was to examine the role of student mobility on Pennsylvania’s
school accountability framework. This final chapter provides a discussion of the major
findings as they relate to impact on students and schools, the theoretical foundations
impacting student mobility, its impact on achievement and measures of success, and
practice and policy. The chapter also includes a discussion of fiscal implications, as well
as implications for theory and research, and practice. Recommendations for future
research will also be provided. The chapter concludes with future plans for work in the
researcher’s field informed by the findings.
Prior to embarking on this project, the researcher predicted that an increased
percentage of mobile students would negatively impact school accountability indicators.
The analysis indicated a strong correlation between transiency rate and achievement
scores and attendance. The theory that the addition of transient students to a school’s
population would impact school accountability indicators was supported by findings that
demonstrate a large correlation between transiency rates and math achievement scores,
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ELA achievement scores, math growth values, and attendance. This has significant
implications for the researcher as applied to his profession; further action related to the
findings will be addressed later in this chapter.
Conclusions
This section of the final chapter will discuss the effectiveness of the research, its
applicability and replicability, and the implications of the research.
Effectiveness.
When reflecting on the results of action research, it is important to consider both
the efficacy and the effectiveness of the project. Efficacy considers whether the project
worked in the experimental setting as designed. Effectiveness considers whether the
project will work in a real world setting.
When considering efficacy, it appears that the design of the project was
successful. The researcher was able to obtain the necessary data files from each school
district, as well as identify the school accountability indicators as defined by the state.
Using the data provided, and adhering to student confidentiality by using PAsecureIDs,
the researcher was also able to identify and isolate transient students in each population
group. The selected SPSS analyses were able to provide correlation data that could be
successfully used to either support or reject the hypotheses.
When considering effectiveness, one must consider the applicability of the
research design in a broader spectrum. Could the project be applied statewide in all
schools? Yes. This research would provide results with confidence due to the consistent
methods of data collection, reporting, and analysis at the school and state levels.
Pennsylvania requires every school district to collect consistent data in a statewide
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system in which every school district reports accountability information following a
defined set of standards. The implication of this is that a researcher could obtain the
necessary files from every school district in the state without exception. Additionally,
given that the information obtained would be in a consistent format from every school
district, conducting the analyses with a greater n-group would also be possible. Just as the
researcher was able to complete a bivariate correlation analysis comparing data from
eight schools, the same analysis could be completed comparing data from 2000 schools.
Another factor supporting the effectiveness of this research is the fact that school
accountability indicators values are compiled and reported following a standard protocol,
and reported on the state website. These accountability indicators are reported for every
school district in Pennsylvania, with only a few exceptions.
Application to researcher’s institutional setting.
The researcher’s intent related to action and communication based on the results
of this project was impacted by the COVID-19 crisis of 2020. The results of this study
would have been discussed at great length with district leaders of participating schools in
spring 2020. The results also would have been shared at a statewide level, for action and
discussion at the same time. In March 2020, the priority at both the district level and the
state level shifted to a very narrow focus on support of continuity of education; with that
said, discussions not directly impacting continuity of education or the reopening of
schools were sidelined.
The researcher has already briefly shared the results with the district leaders. Due
to a shift in focus in schools, a more comprehensive review of the results has been
delayed. At a later time, when planning for the reopening of schools subsides, the
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researcher will meet with leaders from each participating school to share the results. He
plans to engage the stakeholders in discussions involving the findings and
recommendations put forth in this paper.
As for application at a state level, the COVID-19 crisis has also sidelined many
discussions. Several planned school improvement protocol and policy meetings have
been canceled due to shifting priorities. It is the researcher’s intent to engage school
improvement leadership and statewide policy- and decision-makers in the findings and
recommendations learned as a result of this project.
On a personal level, the researcher has shared these findings with numerous
colleagues and peers in districts. Although the strong relationship between rates of
transiency and school accountability indicators have long been assumed by some in the
field, this project provides statistical evidence. Since completing the project, the
researcher has shared these findings and suggested policy change in multiple initiatives in
which he is involved, and he plans to intensify these efforts in the future.
Specific findings and interventions to be shared with participant schools.
•
In the analysis which included your school’s information, there was a strong
statistical correlation found between rate of transiency and accountability indicator
values. This means that the more transient student you have, the more likely you will
have lower indicator values.
•
Drawing off of this relationship, the lower your accountability indicators are, the
more likely you will be designated or re-designated for school improvement status.
•
The result of this project will provide you with statistical evidence that you might use
to embark on an effort to provide a more supportive environment for transient
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students, which would also reduce the chances that you will fall into school
improvement status.
•
The use of an action planning template created by the researcher as a result of this
project will be recommended. Appendix C displays the LEA Action Planning
Template for Transient Cohorts, based on the Council of Chief State School Officers
(2017) framework for improvement cycle. This framework is used by many states,
including Pennsylvania, to move from a compliance-based focus to an action-based
focus for school improvement.
•
While the procedure for this would vary from one school to another based on their
student information system vendor, the researcher will offer to work with each school
to examine the performance of transient students on additional, non-Future Ready
indicators of performance, such as grades, classroom and diagnostic assessments, and
discipline referrals.
•
Based on the results of this comprehensive examination, the school leaders will be
directed to local and state points of contact for assistance in building capacity based
on the needs that have been identified.
•
Finally, and not limited to participant schools, an additional resource will be shared.
Appendix D displays the Workflow for Comparing Transient Student Performance to
Stable Student Performance. This guide was created by the researcher as a means to
provide school districts with the ability to replicate this in part or in whole.
The following section discusses implications related to the study, and highlights actions
to impact change that the researcher plans to take based on the results.
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Implications.
The findings of this action research project result in numerous implications, both
fiscal implications, as well as policy and practice implications. These implications range
from actions that may be taken by the researcher to actions that must be considered at a
state-level.
Fiscal implications.
As school improvement efforts involve a considerable investment of money, both
at a local level and at the state level, the results of this project have numerous significant
fiscal implications. Decades of school improvement work have targeted low-performing
schools with considerable federal and state money to aid in improving academic
outcomes for students. These implications relate to how money is spent on staffing and
on resources.
Implication 1: Pennsylvania’s School Improvement System – New Positions.
Pennsylvania’s official system for school improvement is structured in alignment
with federal government education legislation. One aspect of the system involves
assigning personnel known as Core Team Members (CTM) to each underperforming
school. There are CTMs who specialize in general school improvement, math, ELA, and
data analysis. These core team members are funded by federal and state school
improvement money. The CTM’s engage in a process of data gathering, plan
development and implementation, and review following a school improvement cycle
designed by the state. Consideration for levels of mobile students and their needs is not
inherently part of this process. One fiscal implication that may result in substantial
positive results for underperforming schools would be shifting funding from existing
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CTM positions to create new core team members specializing in support for mobile
students. With a focus on the needs of not only mobile students, but the needs of their
teachers as well, consultants in this new position may be able to help mobile students
transition better. They may also be able to help schools develop a more substantial
support structure for mobile students, which should lead to better academic outcomes.
Having input into one aspect of school improvement leadership team for the state, the
researcher has already shared findings with several co-leads, and will continue to
advocate for this change within the sphere of his influence in the future.
Implication 2: Research-Based Practices.
Currently, Pennsylvania’s system for school improvement provides funding for
the purchase of research-based practices for school improvement. As this action research
project demonstrated, mobile students experience decreased academic success and
decreased attendance. Funds may be spent on the purchase of research-based products
and services that would improve teacher in-school practice towards mobile students. As
a state co-lead for school improvement as well as diagnostic assessment, the researcher
will apply this learning in the continued development of a research-based practices in
assessment portal.
Implication 3: A Shift in Local Expenditures.
School improvement money is often spent on purchasing new curriculum
packages for use with the whole student body. If transient students are the student
subgroup responsible for decreased accountability scores, then schools may wish to shift
funding from global curriculum packages to interventions and supports for mobile
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students. The researcher will recommend this shift to leadership of the schools who
participated in this project, as well as school leaders across the state.
Implication 4: Personnel.
School districts operate on very finely-tuned budgets, and staffing is often a
challenging task. Classroom teachers often struggle to accommodate the needs of mobile
students, while continuing to push stable students to higher achievement levels. Schools
may wish to shift funding to allow for personnel with an expertise in student transition to
assist buildings and teachers with this challenge. The researcher will use these findings
to recommend staffing changes in support of transient students. These recommendations
will be provided to central administration staff from the schools who participated in the
project.
Implication 5: Replication of this Project for Local Audits.
This project was completed at no cost using readily available data that is
aggregated and reported by every public school building in Pennsylvania. Schools who
wish to audit their success in engaging mobile students are able to replicate this process
at no cost to taxpayers. District leaders who initiated this analysis would demonstrate
fiscal responsibility in the management of district resources.
One means of modifying this project to allow for easier replication would be the
elimination of the statistical analysis using SPSS software. A district might still identify
transient students, flag the students as such in the districts accountability file, then create
modified accountability indicators examining the non-mobile group. While this
replication would not include a correlation analysis, since the results of this action
research already indicate that a correlation exists, the process of replication would help a
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district determine if the same pattern is present locally. The researcher plans to create a
document to be shared locally to help guide districts through replicating this process. Not
only would this provide another value-added service of the intermediate unit, but would
also provide a useful tool for schools to use.
Implications for practice and policy.
There are numerous implications for practice and policy informed by the results
of this action research project. Considerations related to student mobility can be
classified into: systems of accountability, school improvement identification, stakeholder
perceptions, staff practice and attitudes, building-level practice, system-level practice,
and policy.
Implication 6: Systems of Accountability.
In accordance with the Every Student Succeeds Act (ESSA), all states must create
a system for evaluating schools to determine a way for focusing resources on
underperforming schools as well as traditionally underserved students who demonstrate
low academic performance. Pennsylvania’s Future Ready PA Index is designed to
adhere to these federal regulations. There is a protocol in place for determining which
students are attributed to schools and which students are not. This does provide some
safeguards that prevent students who were enrolled for only a short period of time to
factor into school accountability ratings; however, even when considering those
exclusions, the inclusion of some students with a history of mobility into school ratings
does have a detrimental effect on these scores. Pennsylvania (and states with similar
protocols) may wish to revisit attribution roles and consider changes to better account for
student mobility between schools. For example, the state may wish to consider the
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exclusion of students who have not been continuously enrolled for one entire academic
year. While the researcher cannot take definitive action to change this accountability
system, he will share the results with decision-makers who might be able to impact
change.
Implication 7: School Improvement Identification.
Pennsylvania’s system for school improvement is based on a process defined in
federal statutes, known as annual meaningful differentiation. This process involves two
levels of examination. The first level considers building achievement and growth scores.
If a building demonstrates low values in both of these indicators, a second level of
consideration is given to for other factors, which include attendance, graduation, career
readiness benchmarks, and English learner proficiency. This action research project
demonstrated that mobility significantly impacts student achievement and growth as well
as attendance. As a result, as long as mobile students are still attributed to school
buildings in annual meaningful differentiation, then it stands to reason that buildings with
high mobility rates might more frequently be identified as in need of school
improvement. The state may wish to consider rate of student mobility when examining
the six indicators used to determine school improvement designation. The researcher
plans to meet with leaders within the Pennsylvania Department of Education to discuss
the results of this project.
It is important to note that in response to the COVID-19 pandemic of 2020, the
United States Department of Education granted a waiver to the state of Pennsylvania,
waiving it’s a requirement to identify schools in the 2020-2021 school year in one
category of school improvement, and it’s possible that identification in the other category
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as a school improvement might also be waived. This pause on designation provides a
unique opportunity for the state to consider the implications of this research, and conduct
a broader analysis, before reengaging in process several years down the line. This also
provides the participants school districts to consider the results of this project and put into
place structures to support the needs of transient students before the next round of school
improvement identification resumes. It is possible with a comprehensive action plan
informed by this research, a score may be able to avoid designation in the future.
Implication 8: Stakeholder Perceptions.
Many parents place a high value in the accountability ratings published on state
school effectiveness websites. Owens and Peltier (2002) found that 80% of parents place
value on reported school summaries. As there is a strong correlation between student
mobility and many of the indicators put it on the future ready index, it stands to reason
that schools with high mobility rates may be perceived by parents as failing a significant
majority of students, when in reality, the numbers are low in large part due to the
transient population. While the state does publish a page of demographic information for
each school, mobility rates are not defined or identified. Pennsylvania may wish to adopt
a policy of reporting mobility rates by school. The state may even wish to use a visual
reporting, for example a scatterplot, to identify schools who are high-performing despite
their rate of student mobility. Additionally, it is often common practice for the media to
compare values assigned to indicators between schools. Without context, it may appear
that a school with a higher value is a better school, while in reality, one of the schools
may have a higher rate of student transiency. The state may wish to create and release
documents addressing the importance of considering mobility when evaluating a school’s
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accountability indicators. The researcher plans to share the results of this project with
consultants with the Pennsylvania Training and Technical Assistance Network
(PaTTAN), to bolster their current efforts in this realm.
Implication 9: Staff Practice and Attitudes.
The implications of this study’s results on staff practices prove challenging. From
a teacher’s perspective, student mobility can be disruptive. Mobile students require
immediate and ongoing attention. In addition to the need for getting caught up, the
students also need to learn the rules and routines of their new school and classroom.
These tasks put an extra burden on teachers who already have limited time to provide
appropriate instruction for large numbers of students. As the results of this study showed
a significant correlation between student mobility and academic success, teachers may
wish to consider the following actions to help minimize the impact of mobility on both
the transient students themselves, as well as the rest of the class:
•
Reviewing the cumulative records of new students to assess grades, attendance,
and important background information
•
Administering diagnostic intake assessments to identify student academic
strengths and weaknesses
•
Fostering supportive relationships with mobile students and their parents
•
Ensuring that students understand behavior expectations, procedures and routines,
in order to limit behavioral issues
The researcher is responsible for designing and facilitating professional development for
hundreds of teachers in the region. He will continue to share the results of this research in
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an effort to change teacher perceptions related to this challenge. Additionally, this will be
shared with participating districts so they may better inform their own staff.
Implication 10: Building-Level Practices.
School accountability indicators reflect on building administrators. As a
significant percentages of mobile students can negatively impact these values,
administrators may wish to employ several strategies to help mitigate the challenges
posed by transient students:
•
Implement high-quality professional development programs aimed at increasing
teacher awareness of the challenges faced by mobile students
•
Design a formal intake process in which an informal family history and child
academic assessment can take place
•
Conduct personal meetings with new students and their parents
•
Ensure that front desk staff are sensitive to the issues of transient students and
respectful of the challenges they face
The researcher plans to meet with building and central administrators from participating
school districts to share the results and these recommendations.
Implication 11: System-Level Practices.
As transiency tends to affect entire school systems and is not limited at a building
level, there are a number of district-level implications as well. These implications
include:
•
Designing districtwide student mobility awareness programs and building
capacity in all adults who come in contact with children, from bus drivers to
cafeteria aides to teachers
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Providing access to mental health professionals to help assess stressful life events
in the lives of the students
•
Tasking social workers with building assimilation and attendance plans, and
working with parents
•
Instituting screening in progress monitoring plans to ensure that mobile students
quickly acclimate and experience success
The researcher plans to meet with building and central administrators from participating
school districts to share the results and these recommendations.
Implication 12: Policy.
As student mobility is a challenge faced by schools nationwide, from rural
schools to urban schools, an emphasis on policy may help. Based on the results of this
action research project, implications for policy include:
•
State and federal education legislation that mandates a new federal reporting
subgroup comprised of mobile students
•
Fund allocations earmarked to create new programs and learning opportunities
targeting this group
•
School choice programs and/or flexible district boundary programs may reduce
transiency and result in better academic success for students
Future Directions for Research (Recommendations)
Future plans
As a result of completing this action research project, the researcher has identified
five areas in which lessons learned will be applied. These actions fall into two categories:
state-level actions and local actions.
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State-level actions.
The researcher holds leadership positions on several Pennsylvania state
educational initiatives. From this scope of influence, the results of this action research
will be applied at a high-level through three projects.
Pennsylvania School Improvement Identification and Planning.
Pennsylvania’s state system of school improvement identification examines
school performance in six areas: academic achievement, academic growth, attendance,
graduation, career readiness benchmarks, and English language learner proficiency rate.
The system does not currently factor student mobility rates into identification. As a
member of the leadership team tasked with designing and implementing some aspects of
the school improvement process in the state, the researcher will share the findings of this
project and propose a revised set of procedures for school improvement identification that
will factor in school mobility rate, or somehow otherwise consider the levels of transient
students. Additionally, it will be recommended that the school improvement program
establish core team member positions with a focus on student mobility and other out of
school challenges. As the project showed that there is a correlation between student
mobility rate and accountability indicator values, and these values are used to identify
schools for school improvement, then an assumption can be made that schools receiving
school improvement services might benefit from supports for transient students.
Classroom Diagnostic Tools.
The researcher is also a state co-lead for a diagnostic assessment known as the
Classroom Diagnostic Tools (CDT). The CDT is offered at no cost to all Pennsylvania
schools, and is a computer adaptive diagnostic assessment that can be administered in
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grades three through 12, in all state assessment tested subject areas. At this time,
approximately 60% of schools in the state of Pennsylvania utilize the CDT. One of the
biggest challenges facing teachers when a new student enrolls in their classroom is
quickly identifying gaps in that student’s content knowledge and understanding. The
CDT is a powerful tool that can be used to provide a detailed report of student
comprehension aligned to Pennsylvania academic eligible content. As part of ongoing
promotion of the tool, marketing materials will be created and distributed to schools
across Pennsylvania promoting the value of administering the CDT to newly-enrolled
students. Schools will be encouraged to embed the use of the CDT into a formal intake
process for mobile students. Once the results of the test are available, teachers of the
students will be able to examine vertical learning progressions and will be able to quickly
identify gaps in learning.
Pennsylvania Intermediate Unit Leadership.
As a state role-alike lead for curriculum and instruction consultants across
Pennsylvania’s twenty-nine intermediate units, the researcher plans to share the results of
this research with peers across the state. Statewide, all intermediate units retain
consultants to work with local school districts in various school improvement efforts, and
the impact of student mobility on various school effectiveness indicators would be key
information to inform this work.
Local-level actions.
The researcher currently holds the position of Program Director in the Teaching
and Learning division of a regional education agency (known as intermediate units in
Pennsylvania). In this position, he routinely provides consultation and professional
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103
development to local district and school administrators and teachers. He is also
responsible for assisting in the development of additional services and professional
development, based on district needs, research, and best practice. The results of this
action research project will inform local work in four areas.
Communicating Results to District Administrators.
Results of this project will be shared with district administrators through rolealike meetings with superintendents and curriculum directors. Districts will be surveyed
as to the formal and informal processes in place to assist transition for mobile students.
As the researcher has a high interest in not only the academic success of mobile students,
but also the overall success of schools, assistance will be offered to local districts with an
interest in developing or refining programs to improve transition for mobile students.
Informing Local Consultation.
The researcher routinely meets with administrators and teachers from 42 local
school districts. These consultations often focus on root cause analysis and strategic
planning. Informed by the results of this action research project, levels of mobile students
and the supports in place to assist them will now be considered in these consultations.
When analyses take place examining student academic and organizational success by
subgroup, when possible, a ‘transient’ student subgroup will now be included in the study
and subsequent discussion and planning.
Promoting Supports for Transient Students in Remote Learning.
In response to the COVID-19 crisis of 2020, the researcher’s institution has
recently received several rounds of grant funding to offer professional learning
opportunities to western Pennsylvania educators related to remote learning. As a co-lead
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
104
for the Reimaging and Reinventing Education project, he is responsible for developing
and implementing professional development focusing on building teacher capacity to
more effectively offer remote learning. One of the strands of best practices is flexibility
for learners with diverse needs. The researcher has already begun crafting a professional
development module aimed at communicating the results of this research and providing
strategies for schools and teachers to welcome and accommodate students who may have
moved into the district but due to remote learning, are visiting their new classroom for the
first time in only a remote setting.
Building Additional Services and Supports.
The researcher plans to work with the program director for Teaching and
Consultation (TAC) to further refine and expand on existing professional development in
consulting related to transient students. The TAC staff routinely provide assistance to
schools in the support of underserved populations of students. It will be recommended
that services specializing in mobile students be substantially enhanced. This updated
strand of services and professional development will serve to help schools design formal
intake processes for transient students, and to build systemic supports to aid the students
in the transition. Additionally, these services would offer professional development to
teachers to build their capacity in helping mobile students to acclimate to a new
classroom, and to quickly experience academic success.
Recommendations for future research.
Informed by the results of this action research project, research may be conducted
to examine the impact of student mobility on school accountability through additional
lenses. Building on a limitation previously addressed, future research might study this
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
105
issue by examining a larger sample size of at least 330, representing a minimum of 10%
of the schools in the state. While similar studies have been completed in other states
examining the impact of student mobility on accountability indicators, additional research
might focus on the impact of those students on school improvement designation in those
states as well. It is also possible that the implications for policy and practice apply on a
national level.
As some schools already have existing programs in place to screen transient
students and to provide necessary support, additional research could examine this
relationship in these schools to determine whether or not the interventions put in place
result in reducing the impact of mobility on accountability indicators. Comparisons
could be drawn between schools with transient-focused interventions in place and schools
without, and analyses conducted to examine the effectiveness of those interventions.
As there are multiple external factors that affect student performance, future
research might focus on out-of-school conditions that impact the academic performance
of mobile students. Such research might examine number of moves, locations, family
background, and community supports. Finally, additional action research might be
conducted to examine the impact of transient students at the teacher-level, classroomlevel and system-level. What burdens are placed on teachers as a result of students
moving in? What are the implications on classroom instruction when a teacher must help
a student socially and academically assimilate? What are the system-level challenges that
impact a district’s ability to effectively help mobile students transition and experience
academic success?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
106
Summary
Decades of research have shown the negative impact of mobility on student
academic and behavioral success. Building on that research, this action research project
found that the impact of that correlation also affects most Pennsylvania school
accountability indicators.
The results of the study suggested a strong correlation between transiency rate and
change in school accountability indicators for attendance, math growth, math
achievement, and ELA achievement, and a moderate correlation with career readiness
benchmarks. Of all the school accountability factors examined, the only factor with
which student mobility had a small correlation was ELA growth.
While Pennsylvania’s Future Ready PA Index does report success on federally
mandated indicators by subgroup, mobile students are not considered. This marginalized
group can be difficult to identify and label, and their progress or lack thereof may not be
as evident as that of other groups of students with stable residence, but it is the
responsibility of the state and our school systems to provide supports. The results of the
study showed that mobile students negatively impact accountability indicators utilized for
school improvement designation. Hopefully, the funds set aside for improving
underperforming schools might be utilized for providing services and supports for this
group of students that often goes unnoticed.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
107
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THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
APPENDICES
121
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APPENDIX A
Proposal Number
IRB Review Request
Date Received
IRB Review Request
Institutional Review Board (IRB) approval is required before beginning any research and/or
data collection involving human subjects
Submit this form to instreviewboard@calu.edu or Campus Box #109
Project Title:
The Impact of Student Mobility on School Ratings in Pennsylvania’s School Accountability System
Researcher/Project Director
Brian Stamford
Phone #. 724-989-8983
E-mail Address. STA0255@calu.edu
Faculty Sponsor (if researcher is a student)
Dr. Kevin Lordon
lordon@calu.edu
Department Department of Secondary Education and Administrative Leadership
Anticipated Project Dates. September 1, 2019
to May 31, 2020
Sponsoring Agent (if applicable)
Project to be Conducted at
Project Purpose:
Allegheny Intermediate Unit, Homestead, PA
Thesis
Research
Class Project
Other
Keep a copy of this form for your records.
Required IRB Training
All researchers must complete an approved Human Participants Protection training course. The training requirement can
be satisfied by completing the CITI (Collaborative Institutional Training Initiative) online course at
http://www.citiprogram.org New users should affiliate with “California University of Pennsylvania” and select the “All
Researchers Applying for IRB Approval”course option. A copy of your certification of training must be attached to this IRB
Protocol. If you have completed the training within the past 3 years and have already provided documentation to the IRB,
please provide the following:
Previous Project Title
Date of Previous Project IRB Approval
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
123
Please attach a typed, detailed summary of your project AND complete items 2
through 6.
1. Provide an overview of your project-proposal describing what you plan to do and how you
will go about doing it. Include any hypothesis(ses)or research questions that might be
involved and explain how the information you gather will be analyzed. All items in the
Review Request Checklist, (see below) must be addressed.
In accordance with federal education accountability regulations, the Pennsylvania Department of
Education recently designated hundreds of schools in the state as in need of school improvement.
Many of these schools have a higher rate of poverty than their peers, and research shows that with
increased poverty comes increased student mobility. Student mobility negatively impacts student
achievement and academic success. A quantitative correlational study is needed to investigate the
impact that high populations of mobile students have on a school’s school improvement
designation. The results of this study will inform all schools) as to the importance of providing
proper academic supports for mobile students, as well as offer evidence to support a change in
Pennsylvania’s school accountability system to take into consideration the rates of student
mobility.
2. Section 46.11 of the Federal Regulations state that research proposals involving human
subjects must satisfy certain requirements before the IRB can grant approval. You should
describe in detail how the following requirements will be satisfied. Be sure to address each
area separately.
(text boxes will expand to fit responses)
a.
How will you insure that any risks to subjects are minimized? If there are
potential risks, describe what will be done to minimize these risks. If there are risks,
describe why the risks to participants are reasonable in relation to the anticipated
benefits.
There is no risk of any kind, since the project is limited to analyzing extant data; no
human subjects will be involved. Only potential discomfort to the schools I work with
would be the data showing that regardless of student mobility, most students are under
achieving; this would serve as a discomfort as it would be a sign of an ineffective
system.
b.
How will you insure that the selection of subjects is equitable? Take into account
your purpose(s). Be sure you address research problems involving vulnerable
populations such as children, prisoners, pregnant women, mentally disabled persons, and
economically or educationally disadvantaged persons. If this is an in-class project
describe how you will minimize the possibility that students will feel coerced.
One suburban and one urban school were approached to partner on this research; the
schools represents typical schools in the state. Participation is voluntary and the
schools are enthusiastic to participate.
c.
How will you obtain informed consent from each participant or the subject’s
legally authorized representative and ensure that all consent forms are appropriately
documented? Be sure to attach a copy of your consent form to the project summary.
A consent form will explain the process and will require each school’s signature to
participate. A copy of the consent form is attached to this request. Consent is required
and was obtained from each school’s superintendent (attached).
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
124
d.
Show that the research plan makes provisions to monitor the data collected to
insure the safety of all subjects. This includes the privacy of subjects’ responses and
provisions for maintaining the security and confidentiality of the data.
All data will be provided to me without name association; no personally identifiable
information will be shared with me; this anonymous data will be saved on my local
computer and will be deleted at the end of the project. The principal researcher will
have access to this data. Based on criteria provided by the researcher, the LEAs Will
separate accountability data into two groups of students based on those defined as
mobile and those defined as stable residence. The school districts will then remove
student names and PA Secure IDs from the dealer before providing it to the
researcher. There will be no identifying information in these accountability files. Each
school’s provided data will contain the following six school success indicators as
identified by federal accountability regulations: math/ELA achievement, math/ELA
growth, attendance, graduation rate, career benchmark completion, and EL
proficiency. These measures can be found reported at: https://futurereadypa.org
3. Check the appropriate box(es) that describe the subjects you plan to target.
Adult volunteers
Mentally Disabled People
CAL University Students
Economically Disadvantaged People
Other Students
Educationally Disadvantaged People
Prisoners
Fetuses or fetal material
Pregnant Women
Children Under 18
Physically Handicapped People
Neonates
4. Is remuneration involved in your project?
5. Is this project part of a grant?
Yes or
Yes or
No
No. If yes, Explain here.
If yes, provide the following information:
Title of the Grant Proposal
Name of the Funding Agency
Dates of the Project Period
6.
Does your project involve the debriefing of those who participated?
Yes or
No
If Yes, explain the debriefing process here.
7. If your project involves a questionnaire or interview, ensure that it meets the requirements
indicated in the Survey/Interview/Questionnaire checklist.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
125
California University of Pennsylvania Institutional Review Board
Survey/Interview/Questionnaire Consent Checklist (v021209)
This form MUST accompany all IRB review requests
Does your research involve ONLY a survey, interview or questionnaire?
YES—Complete this form
NO—You MUST complete the “Informed Consent Checklist”—skip the remainder of this form
Does your survey/interview/questionnaire cover letter or explanatory statement include:
[_] (1) Statement about the general nature of the survey and how the data will be
used?
[_] (2) Statement as to who the primary researcher is, including name, phone, and
email address?
[_] (3) FOR ALL STUDENTS: Is the faculty advisor’s name and contact information
provided?
[_] (4) Statement that participation is voluntary?
[_] (5) Statement that participation may be discontinued at any time without penalty
and all data discarded?
[_] (6) Statement that the results are confidential?
[_] (7) Statement that results are anonymous?
[_] (8) Statement as to level of risk anticipated or that minimal risk is anticipated?
(NOTE: If more than minimal risk is anticipated, a full consent form is required—and
the Informed Consent Checklist must be completed)
[_] (9) Statement that returning the survey is an indication of consent to use the data?
[_] (10) Who to contact regarding the project and how to contact this person?
[_] (11) Statement as to where the results will be housed and how maintained? (unless
otherwise approved by the IRB, must be a secure location on University premises)
[_] (12) Is there text equivalent to: “Approved by the California University of
Pennsylvania Institutional Review Board. This approval is effective nn/nn/nn and
expires mm/mm/mm”? (the actual dates will be specified in the approval notice from
the IRB)?
[_] (13) FOR ELECTRONIC/WEBSITE SURVEYS: Does the text of the cover letter
or
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
126
explanatory statement appear before any data is requested from the participant?
[_] (14) FOR ELECTONIC/WEBSITE SURVEYS: Can the participant discontinue
participation at any point in the process and all data is immediately discarded?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
127
California University of Pennsylvania Institutional Review Board
Informed Consent Checklist (v021209)
This form MUST accompany all IRB review requests
Does your research involve ONLY a survey, interview, or questionnaire?
YES—DO NOT complete this form. You MUST complete the
“Survey/Interview/Questionnaire Consent Checklist” instead.
NO—Complete the remainder of this form.
1. Introduction (check each)
[x_] (1.1) Is there a statement that the study involves research?
[x_] (1.2) Is there an explanation of the purpose of the research?
2. Is the participant. (check each)
[x_] (2.1) Given an invitation to participate?
[x_] (2.2) Told why he/she was selected.
[x_] (2.3) Told the expected duration of the participation.
[x_] (2.4) Informed that participation is voluntary?
[x_] (2.5) Informed that all records are confidential?
[x_] (2.6) Told that he/she may withdraw from the research at any time without
penalty or loss of benefits?
[x_] (2.7) 18 years of age or older? (if not, see Section #9, Special Considerations
below)
3. Procedures (check each).
[x_] (3.1) Are the procedures identified and explained?
[x_] (3.2) Are the procedures that are being investigated clearly identified?
[x_] (3.3) Are treatment conditions identified?
4. Risks and discomforts. (check each)
[x_] (4.1) Are foreseeable risks or discomforts identified?
[_] (4.2) Is the likelihood of any risks or discomforts identified?
[_] (4.3) Is there a description of the steps that will be taken to minimize any risks or
discomforts?
[_] (4.4) Is there an acknowledgement of potentially unforeseeable risks?
[_] (4.5) Is the participant informed about what treatment or follow up courses of
action are available should there be some physical, emotional, or psychological harm?
[x_] (4.6) Is there a description of the benefits, if any, to the participant or to others
that may be reasonably expected from the research and an estimate of the likelihood
of these benefits?
[_] (4.7) Is there a disclosure of any appropriate alternative procedures or courses of
treatment that might be advantageous to the participant?
5. Records and documentation. (check each)
[x_] (5.1) Is there a statement describing how records will be kept confidential?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
128
[x_] (5.2) Is there a statement as to where the records will be kept and that this is a
secure location?
[x_] (5.3) Is there a statement as to who will have access to the records?
6. For research involving more than minimal risk (check each),
[_] (6.1) Is there an explanation and description of any compensation and other
medical or counseling treatments that are available if the participants are injured
through participation?
[_] (6.2) Is there a statement where further information can be obtained regarding the
treatments?
[_] (6.3) Is there information regarding who to contact in the event of research-related
injury?
7. Contacts.(check each)
[x_] (7.1) Is the participant given a list of contacts for answers to questions about the
research and the participant’s rights?
[x_] (7.2) Is the principal researcher identified with name and phone number and
email address?
[x_] (7.3) FOR ALL STUDENTS: Is the faculty advisor’s name and contact
information provided?
8. General Considerations (check each)
[x_] (8.1) Is there a statement indicating that the participant is making a decision
whether or not to participate, and that his/her signature indicates that he/she has
decided to participate having read and discussed the information in the informed
consent?
[x_] (8.2) Are all technical terms fully explained to the participant?
[x_] (8.3) Is the informed consent written at a level that the participant can
understand?
[x_] (8.4) Is there text equivalent to: “Approved by the California University of
Pennsylvania Institutional Review Board. This approval is effective nn/nn/nn and
expires mm/mm/mm”? (the actual dates will be specified in the approval notice from
the IRB)
9. Specific Considerations (check as appropriate)
[_] (9.1) If the participant is or may become pregnant is there a statement that the
particular treatment or procedure may involve risks, foreseeable or currently
unforeseeable, to the participant or to the embryo or fetus?
[_] (9.2) Is there a statement specifying the circumstances in which the participation
may be terminated by the investigator without the participant’s consent?
[x_] (9.3) Are any costs to the participant clearly spelled out?
[x_] (9.4) If the participant desires to withdraw from the research, are procedures for
orderly termination spelled out?
[_] (9.5) Is there a statement that the Principal Investigator will inform the participant,
or any significant new findings developed during the research that may affect them
and influence their willingness to continue participation?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
129
[_] (9.6) Is the participant is less than 18 years of age? If so, a parent or guardian must
sign the consent form and assent must be obtained from the child
[_] Is the consent form written in such a manner that it is clear that the
parent/guardian is giving permission for their child to participate?
[_] Is a child assent form being used?
[_] Does the assent form (if used) clearly indicate that the child can freely refuse
to participate or discontinue participation at any time without penalty or coercion?
[x_] (9.7) Are all consent and assent forms written at a level that the intended
participant can understand? (generally, 8th grade level for adults, age-appropriate for
children)
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
130
California University of Pennsylvania Institutional Review Board
Review Request Checklist
(v021209)
This form MUST accompany all IRB review requests.
Unless otherwise specified, ALL items must be present in your review request.
Have you:
[x_] (1.0) FOR ALL STUDIES: Completed ALL items on the Review Request
Form?
Pay particular attention to:
[x_] (1.1) Names and email addresses of all investigators
[x_] (1.1.1) FOR ALL STUDENTS: use only your CalU email
address)
[x_] (1.1.2) FOR ALL STUDENTS: Name and email address of
your faculty research advisor
[x_] (1.2) Project dates (must be in the future—no studies will be approved
which have already begun or scheduled to begin before final IRB approval—
NO EXCEPTIONS)
[x_] (1.3) Answered completely and in detail, the questions in items 2a
through 2d?
[x_] 2a: NOTE: No studies can have zero risk, the lowest risk is
“minimal risk”. If more than minimal risk is involved you MUST:
[x_] i. Delineate all anticipated risks in detail;
[x_] ii. Explain in detail how these risks will be minimized;
[x_] iii. Detail the procedures for dealing with adverse
outcomes due to these risks.
[x_] iv. Cite peer reviewed references in support of your
explanation.
[x_] 2b. Complete all items.
[x_] 2c. Describe informed consent procedures in detail.
[x_] 2d. NOTE: to maintain security and confidentiality of data, all
study records must be housed in a secure (locked) location ON
UNIVERSITY PREMISES. The actual location (department, office,
etc.) must be specified in your explanation and be listed on any
consent forms or cover letters.
[x_] (1.4) Checked all appropriate boxes in Section 3? If participants under
the age of 18 years are to be included (regardless of what the study involves)
you MUST:
[x_] (1.4.1) Obtain informed consent from the parent or guardian—
consent forms must be written so that it is clear that the
parent/guardian is giving permission for their child to participate.
[x_] (1.4.2) Document how you will obtain assent from the child—
This must be done in an age-appropriate manner. Regardless of
whether the parent/guardian has given permission, a child is
completely free to refuse to participate, so the investigator must
document how the child indicated agreement to participate
(“assent”).
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131
[x_] (1.5) Included all grant information in section 5?
[x_] (1.6) Included ALL signatures?
[x_] (2.0) FOR STUDIES INVOLVING MORE THAN JUST SURVEYS,
INTERVIEWS, OR QUESTIONNAIRES:
[x_] (2.1) Attached a copy of all consent form(s)?
[x_] (2.2) FOR STUDIES INVOLVING INDIVIDUALS LESS THAN 18
YEARS OF AGE: attached a copy of all assent forms (if such a form is used)?
[x_] (2.3) Completed and attached a copy of the Consent Form Checklist? (as
appropriate—see that checklist for instructions)
[x_] (3.0) FOR STUDIES INVOLVING ONLY SURVEYS, INTERVIEWS, OR
QUESTIONNAIRES:
[x_] (3.1) Attached a copy of the cover letter/information sheet?
[x_] (3.2) Completed and attached a copy of the
Survey/Interview/Questionnaire Consent Checklist? (see that checklist for
instructions)
[x_] (3.3) Attached a copy of the actual survey, interview, or questionnaire
questions in their final form?
[x_] (4.0) FOR ALL STUDENTS: Has your faculty research advisor:
[x_] (4.1) Thoroughly reviewed and approved your study?
[x_] (4.2) Thoroughly reviewed and approved your IRB paperwork?
including:
[x_] (4.2.1) Review request form,
[x_] (4.2.2) All consent forms, (if used)
[x_] (4.2.3) All assent forms (if used)
[x_] (4.2.4) All Survey/Interview/Questionnaire cover letters (if
used)
[x_] (4.2.5) All checklists
[x_] (4.3) IMPORTANT NOTE: Your advisor’s signature on the review
request form indicates that they have thoroughly reviewed your proposal and
verified that it meets all IRB and University requirements.
[x_] (5.0) Have you retained a copy of all submitted documentation for your records?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
132
Project Director’s Certification
Program Involving HUMAN SUBJECTS
The proposed investigation involves the use of human subjects and I am submitting the complete
application form and project description to the Institutional Review Board for Research Involving
Human Subjects.
I understand that Institutional Review Board (IRB) approval is required before beginning any
research and/or data collection involving human subjects. If the Board grants approval of this
application, I agree to:
1. Abide by any conditions or changes in the project required by the Board.
2. Report to the Board any change in the research plan that affects the method of using
human subjects before such change is instituted.
3. Report to the Board any problems that arise in connection with the use of human subjects.
4. Seek advice of the Board whenever I believe such advice is necessary or would be
helpful.
5. Secure the informed, written consent of all human subjects participating in the project.
6. Cooperate with the Board in its effort to provide a continuing review after investigations
have been initiated.
I have reviewed the Federal and State regulations concerning the use of human subjects in
research and training programs and the guidelines. I agree to abide by the regulations and
guidelines aforementioned and will adhere to policies and procedures described in my
application. I understand that changes to the research must be approved by the IRB before they
are implemented.
Professional (Faculty/Staff) Research
Project Director’s Signature
Student or Class Research
Student Researcher’s Signature
Supervising Faculty Member’s Signature
ACTION OF REVIEW BOARD (IRB use only)
The Institutional Review Board for Research Involving Human Subjects has reviewed this application to
ascertain whether or not the proposed project:
1.
2.
provides adequate safeguards of the rights and welfare of human subjects involved in the
investigations;
uses appropriate methods to obtain informed, written consent;
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
3.
4.
5.
133
indicates that the potential benefits of the investigation substantially outweigh the risk involved.
provides adequate debriefing of human participants.
provides adequate follow-up services to participants who may have incurred physical, mental, or
emotional harm.
Approved[_________________________________]
___________________________________________
_________________________
Chairperson, Institutional Review Board
Disapproved
Date
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
134
APPENDIX B
IRB Request Approval
Institutional Review Board
California University of Pennsylvania
Morgan Hall, 310
250 University Avenue
California, PA 15419
instreviewboard@calu.edu
Melissa Sovak, Ph.D.
Dear Brian,
Please consider this email as official notification that your proposal
titled “The Impact of Student Mobility on School Ratings in
Pennsylvania's School Accountability System” (Proposal #18-105)
has been approved by the California University of Pennsylvania
Institutional Review Board as amended.
The effective date of approval is 11/14/19 and the expiration date is
11/13/20. These dates must appear on the consent form.
Please note that Federal Policy requires that you notify the IRB
promptly regarding any of the following:
(1) Any additions or changes in procedures you might wish for your
study (additions or changes must be approved by the IRB before they
are implemented)
(2) Any events that affect the safety or well-being of subjects
(3) Any modifications of your study or other responses that are
necessitated by any events reported in (2).
(4) To continue your research beyond the approval expiration date of
11/13/20 you must file additional information to be considered for
continuing review. Please contact instreviewboard@calu.edu
Please notify the Board when data collection is complete.
Regards,
Melissa Sovak, PhD.
Chair, Institutional Review Board
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
135
APPENDIX C
LEA Action Planning Template for Transient Cohorts - DRAFT
In order to improve a school’s support structure for transient students, it is
important to build a plan that incorporates effective practices that drive
change in practice. The Chief Council of State School Officers (CCSSO)
proposes the cycle of improvement below upon which school improvement
efforts can be built.
The template that follows provides suggestions for actions to be taken at
each stage in this cycle in order to provide a more comprehensive approach
to supporting populations of transient students in schools. Should a district
decide to formalize the steps in this template, the framework is aligned to
Pennsylvania’s Future Ready Comprehensive Planning Portal, which should
allow for easy transferability between this planning document and the site.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Step
Set the Direction
Assess Needs
Create Plan
Implement Plan
Monitor Work
Adjust Course
Action
136
Suggestions
Review historical performance
of transient students; establish a
guidance committee; set student
focused SMART goals
Conduct a comprehensive review
of the performance and
experience of transient students
in your school; examine
practices, processes and
routines that might be
inequitable to transient students;
conduct a root cause analysis as
to why transient students are
struggling in your school
Create a plan with
implementation indicators
related to your goals and based
on your needs assessment;
recommend the use of screening
and intake tools for mobile
students
Consider implementation at a
system, building, and classroom
level; how will you meet the
goals?
How will you monitor the work
and progress of transient
students? Might you create a
flag in your student information
system to allow easier
monitoring? How will progress
be reported?
As the monitoring occurs, how
will you adjust the course?
Might you consider focus groups
of transient students? Might you
consider including transient
students in the process?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
137
APPENDIX D
Workflow for Comparing Transient Student
Performance to Stable Student Performance - DRAFT
Recent research has indicated a correlation between levels of student transiency and
Future Ready PA Index school accountability indicators (achievement, growth,
attendance, career readiness, graduation, and EL proficiency). Does the performance of
transient students in your school district align to this relationship? Use the process below
to disaggregate the results for students in your school. This document also includes an
optional section that allows for a correlational analysis examining data from multiple
schools. Note: as parts of this workflow involve a basic understanding of PIMS, it is
advised that this process is completed by or in cooperation with a district data manager.
STEP ONE: FILTER FOR ATTRIBUTED STUDENTS. All students who factor into
accountability can be found in the District Student Data File which is posted for
download on the pa.drcedirect.com website each June. District assessment coordinators
have access to download this file.
STEP TWO: FILTER FOR ATTRIBUTED STUDENTS. Not all the students in this file
factor into school accountability values. Remove the following students from this file
(see the column headers for titles):
• Students not attributed to the school code
• Students with a ‘Y’ in the ‘First Year ELL’ column
STEP THREE: VERIFY THAT THESE VALUES MATCH. Before proceeding, it is
important to verify that the content in this file matches the content that factored into
accountability indicators. To determine this, calculate proficiency or positive levels for
each of the sixth indicators using the data in this file and compare to those on the
futurereadypa.org website. If the values match, move on. If they do not, revisit step two.
Note: attendance and graduation are lagging indicators; therefore, those indicators would
come from data from the prior years’ District Student Data File
STEP FOUR: IDENTIFY TRANSIENT STUDENTS. In order to identify transient
students, complete a query of the student information management system to identify
students who enrolled within the past 12 months. Add a column to the District Student
Data File and flag the students as transient.
STEP FIVE: CALCULATE INDICATOR VALUES FOR THREE GROUPS. In order
to compare the performance of transient students to the all student body, you must create
three groups of students: all, stable (non-transient), and transient. Calculate the
accountability values for each of the six indicators for each of these three groups, then
move on to the questions for consideration portion of this document.
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138
QUESTIONS FOR CONSIDERATION: To examine the relationship between transient
students and stable students in your school, consider the questions below. Your response
to these questions will help guide school action planning related to transient students.
•
•
•
Is there a difference between the accountability values for the transient and nontransient groups? If so, what difference?
Do you notice any trends schoolwide or district-wide? Are these trends consistent
or is there variation between grades or schools?
Are there outliers? To what might you attribute this?
ROOT CAUSE ANALYSIS AND ACTION PLANNING: Now that you have identified
trends in your data it is time to action plan. Use the LEA Action Planning Template for
Transient Cohorts to create a plan for addressing the needs you have identified in your
district.
(OPTIONAL) CONDUCT A CORRELATIONAL ANALYSIS OF THE DATA: If you
are examining the data of multiple schools, you may wish to examine the correlation. Is
there a consistent relationship among those schools between transiency and
accountability indicators? One way to examine this is by conducting a bivariate
correlation test. While there are multiple ways to do this, one of the most popular
software packages for automating the process is IBM’s SPSS software. (If you are
unfamiliar with the software, it contains many useful tutorials.) In order to complete a
correlational analysis comparing the transiency rate at your schools and the school
accountability values, conduct a bivariate correlation test. In the bivariate correlation
option menu, pull the two variables to be tested into the test box, then select Pearson
correlation coefficient, two-tailed significance, and flag significant correlations.
In the example below, one would look for the Pearson correlation in the quadrant under
the opposing variable. Below you will note that the Pearson correlation is -.920.
Correlation is strong if this value is |p|>=.5
Correlations
AttendanceTra AttendanceAb
nsiencyRate
soluteValue
AttendanceTransiency Pearson
1
-.920**
Rate
Correlation (p)
Sig. (2-tailed)
.009
N
6
6
AttendanceAbsoluteVal Pearson
-.920**
1
ue
Correlation (p)
Sig. (2-tailed)
.009
N
6
6
**. Correlation is significant at the 0.01 level (2-tailed).
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS IN
PENNSYLVANIA’S SCHOOL ACCOUNTABILITY SYSTEM
A Doctoral Capstone Project
Submitted to the School of Graduate Studies and Research
Department of Secondary Education and Administrative Leadership
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Education
Brian Michael Stamford
California University of Pennsylvania
July 2020
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
©Copyright by
Brian Michael Stamford
All Rights Reserved
July 2020
ii
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
iv
Acknowledgements
First, I would like to thank God for the grace and blessings that are bestowed
upon me every day; without such peace of mind and sound health this would not have
been possible.
The completion of this work would not have been possible without the guidance
of many people, some of whom I would like to acknowledge in this section, in no
particular order. I would like to thank my faculty chair, Dr, Kevin Lordon. Kevin, I
appreciate your patience in guiding me through the challenges of this task, as well as the
motivation you have provided. I also thank my external committee member, Dr. Paul
Cindric for his perspective, intellect and advice on not only the completion of this project
but also in the workplace. I appreciate the gentle pushing and encouragement by my
supervisor, Rosanne Javorsky, who planted the seed for my embarking on this journey.
Several people had an impact on me professionally early in my career. I thank
Art Molitor, who early on taught me the ‘art’ of teaching, reminding me to put down the
lesson plan and connect with the students. I appreciate Dr. David Myers for coming into
my classroom one day and encouraging me to take a step towards educational
administration; I may not have considered the possibilities without that visit.
I would like to thank my parents Larry and Susan Stamford for the sacrifices they
made to provide a stable foundation for me, as well as their demonstrated faith in me. To
my siblings, Robin Leighty and Craig Stamford, I truly do appreciate your tolerance for
some of my first-born traits. I would also like to acknowledge the mother of my children,
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
v
Karin Stamford, for her work and sacrifice in helping me raise two amazing young men.
I thank Bob and Carlene Painter for helping me to believe in myself and to see the
importance of ‘magic’ in the world.
To my children Nolan and Nathan Stamford – I hope that one day you will have
children of your own so that you will understand how important you are to me. Thank
you for always being there to play, explore, laugh, and now that you are young men, talk
about the world in which we live and even give advice. You are the reason I strive to be
a better person every day. Just remember – if you treat others with respect and always
give your best every day, you can’t ever be upset with yourself.
Rebecca Boozer, I thank you for the mental stimulation, picking me up when I
needed it, and for challenging me when I thought I didn’t need it. I am a better person
now because of you.
Finally, I appreciate the unwavering mantra of my cooperating teacher, Jim Egros.
No matter the situation, the possibility of personal gain or loss, economics, politics, or
self-serving behaviors, Jim always brought conversations and decisions back to what
really mattered with one question – but what’s best for the kids? Jim – in twenty five
years, I haven’t stopped reminding every teacher, administrator, board member, and
parent to keep that as a compass.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
vi
Table of Contents
Acknowledgements
iv
List of Tables
xiii
List of Figures
xiv
Abstract
xv
CHAPTER I. Introduction
1
Background
1
Identification of the Capstone Focus
2
Research Questions
2
Expected Outcomes
3
Fiscal Implications
4
Summary
5
CHAPTER 2. Review of Literature
6
Mobility Defined
6
Mobility
7
Lack of common measurement and definitions
8
Causes of mobility
9
Mobility’s effect on achievement
10
Mobility affects attendance, impacting achievement
13
Mobility’s effect on the system
13
Theoretical Foundations Impacting Mobility
15
Self-concept theory
15
Self-actualization theory
17
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
vii
Constructivism
19
Psychological theory
19
Developmental-ecological theory
19
Social-cultural theory
21
Relational framework
21
Policy and Practice
23
Systems of accountability
23
Pennsylvania’s system of accountability
23
School improvement identification in Pennsylvania
24
Stakeholder perceptions
25
Educational accountability systems across the nation
26
Staff practice and attitudes towards mobile students
29
Administrative practice towards mobility
31
System-level practices impacting mobility
32
Policy that impacts mobility
33
Summary
36
CHAPTER 3. Methodology
Purpose
37
37
Problem
38
Research questions
38
Setting and participants
38
Intervention and Research plan
40
Connection to fiscal implications
42
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Research Design, Methods & Data Collection
viii
43
Multiple forms of data
43
Timing of the data collection
47
Choices and organization of the data
48
Achievement
48
Growth
49
Attendance rate
49
Graduation rate
49
Career readiness benchmark
50
English language learner proficiency
50
Procedures for aggregating and examining the data
50
Flagging students in files
50
Identifying students factoring into achievement and growth
50
Process of random selection
51
Identifying students factoring into the additional indicators
51
Data analysis
52
Statistical analysis
52
Institutional Review Board (IRB)
53
Validity
54
Summary
55
CHAPTER 4. Data Analysis and Results
Data Analysis
Key terms definitions referenced in the process
57
57
58
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
ix
Pennsylvania’s system of accountability
59
Descriptions of the six indicators examined
59
Achievement
59
Growth
60
Attendance Rate
60
Graduation Rate
60
Career Readiness Benchmark
61
English Language Learner Proficiency
61
Definition of transient
61
School improvement identification
62
Collecting the sample data
63
Identifying attributed students and triangulating data
64
Identifying and flagging transient students
65
Calculating the rate of transiency in each group for each indicator
65
Creating stable and adjusted groups
66
Bivariate pictures of correlation
67
Pearson correlation
68
SPSS software
69
Examining change in score indicators caused by transiency rate
70
Examining relationship between levels of transients and reported indicators
71
Results
72
Research question one – findings
Career readiness benchmarks
72
73
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
x
Attendance
73
Math growth
73
ELA growth
74
Math achievement
74
ELA achievement
74
Graduation and EL proficiency
74
Research question two – findings
75
Career readiness benchmarks
77
Attendance
77
Math growth
77
ELA growth
77
Math achievement
78
ELA achievement
78
Graduation and EL proficiency
78
Discussion
78
Findings on the relationship between rate of transiency and indicator value
79
Findings on the impact of transiency on school improvement indicators
80
Findings interpreted by indicator
81
Attendance
81
Math growth
82
ELA growth
82
Math achievement
83
ELA achievement
83
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Career readiness benchmarks
Summary
xi
83
85
CHAPTER 5. Conclusions & Recommendations
Conclusions
87
88
Effectiveness
88
Application to the researchers’ institutional setting
89
Specific findings and interventions to be shared with participant schools
Implications
Fiscal implications
90
92
92
Implication 1: Pennsylvania School Improvement System – New
92
Implication 2: Research-Based Practices
93
Implication 3: A Shift in Local Expenditures
93
Implication 4: Personnel
94
Implication 5: Application of this Project for Local Audits
94
Implications for practice and policy
95
Implication 6: Systems of Accountability
95
Implication 7: School Improvement Identification
96
Implication 8: Stakeholder Perceptions
97
Implication 9: Staff Practice and Attitudes
98
Implication 10: Building-Level Practices
99
Implication 11: System-Level Practices
99
Implication 12: Policy
Future Directions for Research (Recommendations)
100
100
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Future plans
State-level actions
xii
100
101
Pennsylvania School Improvement Identification and Planning
101
Classroom Diagnostic Tools
101
Pennsylvania Intermediate Unit Leadership
102
Local-level actions
102
Communicating Results to District Administrators
103
Informing Local Consultation
103
Promoting Supports for Transient Students in Remote Learning.
103
Building Additional Services and Supports
104
Recommendations for future research
Summary
104
106
References
107
APPENDIX A. IRB Review Request
122
APPENDIX B. IRB Request Approval
134
APPENDIX C. LEA Action Planning Template for Transient Cohorts
135
APPENDIX D. Workflow for Comparing Transient Student Performance to Stable 137
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
xiii
List of Tables
Table 1. Bivariate Correlation Results Between Transiently Right and Change
72
Table 2. Bivariate Correlation Results Between Adjusted Cohort and Value Change 75
Table 3. Bivariate Correlation Results Between Transiently Rate and Absolute Value 76
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
xiv
List of Figures
Figure 1. Maslow’s Hierarchy of Needs
18
Figure 2. Relational Framework for Student Mobility
22
Figure 3. Tracking Turnover Across the Country: States that Track Student Turnover 27
Figure 4. Tracking Turnover Across the Country: Turnover Data is Posted
27
Figure 5. Tracking Turnover Across the Country: District Level Data is Posted
28
Figure 6. Tracking Turnover Across the Country: School Level Data is Posted
28
Figure 7. Future Ready PA Index
44
Figure 8. SPSS Software. Bivariate Correlation Menu
53
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
xv
Abstract
Considerable amounts of financial resources and human capital are dedicated to school
improvement efforts in the state of Pennsylvania each year. The factors that guide school
improvement designation stem from federal education legislation, and include
achievement, academic growth, attendance, graduation, EL proficiency, and career
readiness. At the same time, many of the schools designated for school improvement also
experience high rates of student transiency. The purpose of this study is to examine the
effect that mobile students have on school accountability indicators, and by extension, on
school improvement designations. The school improvement accountability data from two
school districts with a combined total of eight schools was examined. Transient students
were identified, and mock school accountability indicators were calculated, controlling
the percentage of transient students in the group to the regional average of 8%. These
controlled-score accountability indicators were then compared to published all-student
group values in an effort to identify the impact of high percentages of mobile students
using a bivariate correlation analysis. The results of the study suggested a strong
correlation between transiency rate and change in school accountability indicators for
attendance, math growth, math achievement, and ELA achievement, and a moderate
correlation with career readiness benchmarks. Of all the school accountability factors
examined, the only factor with which student mobility had a small correlation was ELA
growth.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
1
CHAPTER 1
Introduction
This chapter will provide an introduction to the action research project. The
identification of and significance of the problem will be introduced, as well as the
research questions. The purpose of the study will be presented, and key terms will be
defined. Finally the financial impact as well as personal significance of the study will be
discussed.
Background
This study is of personal significance to the author, as his work is often embedded
in school improvement. By being able to better identify factors that result in school
improvement designation, the researcher hopes to provide better targeted responses and
services to schools, maximizing return on fiscal investment.
The researcher is currently employed with one of Pennsylvania’s 29 intermediate
units. As part of his job responsibilities, he is frequently called upon to offer consulting to
local school districts, focusing on various school improvement efforts. These efforts
relate to school accountability indicators of success, including academic achievement,
academic growth, career readiness benchmarks, attendance, and graduation rate. The
researcher also provides feedback and guidance at a regional and state level on this topic.
The researcher provides targeted support to schools after they have been identified. The
supports that are offered are largely aligned to efforts to improve curriculum, assessment,
and instruction, but currently do not target support for transient students.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
2
The topic was selected for several reasons. Themes and patterns that result from
the research can be used to better direct fiscal resources and human resources. Research
that supports a correlation between student mobility and decreased school accountability
indicators will guide schools towards developing better supports for transient students,
which in theory should lead to higher success rates for this marginalized group. The
researcher’s work as a steering committee member on several statewide initiatives will
allow him to inform more global actions based on the research. A correlation between
student mobility and school accountability indicators would point to a need for greater
consideration of this challenge when evaluating schools. This will allow for greater fiscal
responsibility as money will be directed towards a factor that contributes to the scores
that lead to school improvement designation.
Identification of the Capstone Focus
The federal Every Student Succeeds Act (ESSA) mandates that beginning in the
2018-2019 school year, states identify the lowest performing schools for three levels of
school improvement effort. In contrast to the previous federal legislation (No Child Left
Behind), ESSA mandates that schools look at factors beyond reading and math
proficiency. Pennsylvania looks at achievement, academic growth, graduation rate,
attendance, English language learner proficiency, and career readiness benchmarks. A
low score relative to other state schools, in combination of these indicators results in a
school being identified for school improvement.
Many of the schools designated for school improvement also experience high
student mobility. Decades of research show there is a correlation between student
mobility and success in school; kids who move more generally perform worse. If school
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
improvement designations are based on factors affected by student mobility, are school
districts with a high percentage of student mobility more likely to be designated for
school improvement?
This study focuses on student mobility in schools and its relationship on school
accountability ratings based on research showing the connection between transiency and
school success. The researcher posits that if a school has a high number of mobile
students, indicators of school success will be lower than average, and this would be
reflected in state school accountability ratings. If this relationship exists, schools with
higher levels of transient students would want to be aware of the correlation, and will
direct fiscal resources in an effort to support this marginalized subgroup, to potentially
avoid school improvement designation as well as to provide these students with more
opportunity for success.
Research Questions
The study will examine the research questions. Is there a significant relationship
between student mobility and a school’s accountability rating? How do schools with a
high transiency rate fare in PAs accountability system when controlling for student
mobility?
Expected Outcomes
This study will examine the impact that high numbers of mobile students has on
school accountability system indicators in Pennsylvania. The accountability data from
two school districts will be examined. One urban school district has been designated
under a school improvement category, and the other is a suburban school district which
has not been designated for school improvement but contains several schools with a
3
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
4
higher-than-average transiency rate. Mobile students will be flagged in each school, and
a new set of school indicators will be created for each school, adjusted to the national
student mobility norm. These new adjusted scores will be compared to the actual scores
to determine the effect of high student mobility in Pennsylvania’s school accountability
system. Additionally, transiency rates and school accountability indicators will be
examined to determine what correlation, if any, exists between the level of student
mobility in a building and the actual values reported to the state.
Fiscal Implications
The results of this study are of great significance to not only individual school
districts, but also to the state as well. From a fiscal standpoint, millions of dollars a year
are being spent on school improvement.
At a state level, Pennsylvania is committing significant financial resources into
efforts to improve schools. While these efforts are based on research-informed cycles of
improvement, and utilize best practices, they do not consider the impact of mobility on
initial designation. In other words, if a school is designated for school improvement, does
it need improved curriculum, instruction, and assessment, or does it merely suffer from a
high student mobility rate? If the state is directing money into helping schools and
teachers better align curricula to standards, and better design instruction, it would be
fiscally responsible to make sure that the money was going to the schools and challenges
that need that help.
From the standpoint of schools, schools that are identified for school
improvement are adjusting resources in an attempt to improve student academic
performance. It would be a wise use of already finite district money if a school district
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
5
discovered that it wasn’t curriculum, instruction, or assessment which was in need of
improvement, but rather, student mobility rates were resulting in designation. If this was
the case, these schools could use their valuable financial resources to put into place better
supports for transient students to increase the likelihood of their success.
Summary
This paper will examine the role of student mobility on school accountability
indicators within Pennsylvania’s school accountability framework. It will examine the
impact that high percentages of transient students have on achievements, academic
growth, career readiness benchmarks, English language learner proficiency, attendance,
and graduation rate, all which factor into designation in Pennsylvania’s three school
improvement categories. Recommendations for revisions to the state’s school
accountability system will be provided, as well as best practices that schools may
implement to better support transient students. The research began with a review of the
literature related to transiency and school accountability, as reported in the next chapter.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
6
CHAPTER 2
Review of Literature
This chapter will review the literature related to student mobility and its impact on
achievement. The review of literature will be divided into three parts. Mobility in general
will be presented as it will help develop understanding of how this can be defined,
measured, and of its impact on students and schools. Next, theoretical foundations
impacting student mobility and its impact on achievement and measures of success will
be laid out. Finally, practice and policy will be reviewed, including efforts to factor
student mobility into state accountability systems. A summary of the findings will
conclude the review of the literature.
Mobility Defined
In educational literature, student mobility is frequently referenced. The definition
of this, however, is not often comparable across districts or research studies. Kerbow
(1996) states that to gain a very clear meaning of the amount of mobility in a school, it is
important to separate students entering and students exiting a school from those with
stable participation. For the purpose of this paper, mobility will refer to a student
withdrawing from one school and enrolling at another. The word transiency will also be
used to describe this phenomenon. Finally, students who remain continuously enrolled in
a school will be referred to as stable.
There is a significant statistical difference in achievement of groups of students
when comparing students of mobility with students of stability (Mullins, 2011). Student
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
7
mobility causes a range of issues that span across student achievement and social
emotional development, classroom planning and instruction, and school resources
(Kerbow, 1996).
Mobility.
Frequent moves by students from one school to another put students, their
teachers, and their peers at a disadvantage. Additionally, researchers have found that a
high level of mobile students are also economically disadvantaged. Fowler-Finn (2001)
reports, “stability and family, residents, school and school attendance support better
learning. Those who need stability the most, the poor appear to have the least” (p. 36).
The General Accounting Office reports that large urban districts serving a
disproportionate percentage of students living in poverty experience mobility rates as
high as 40% (GAO, 1994). The GAO’s report goes on to highlight the alarming statistic
that the United States has one of the highest mobility rates of all developed countries.
One common lens in which researchers have analyzed mobility data is defining a
mobile student as someone who had moved at any time in their school tenure. Data from
9915 families was reviewed and determined that in the families in which a child
experienced a move during his or her lifetime, significant negative impacts were
experienced (Wood & Halfon, 1993). Researchers found that frequent family relocation
resulted in increased risk of children failing grades and experiencing frequent behavioral
problems. Transient students experience behavioral problems ranging from poor or
incomplete work completion to major classroom disruption. Demie et al. (2005) defines
student mobility as a child joining or leaving school at a point other than the normal age
at which children start or finish their education at that school. Students who demonstrate
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
8
movement or changes of school, either once or on repeated occasions, at times other than
their normal age to do so at a school can be defined as mobile (Strand & Demie, 2007;
Dobson, 2008).
The most recent United States Census, conducted in 2010, reported that 9.7% of
the US population moved during the year prior to that census (Mateyka, 2015). Mobility
rates differ by geographic region, with the southeast and southwest experiencing the
greatest mobility. Rates of mobility change over time as well. Migration estimates from
the Current Population Survey Annual Social and Economic Supplement (CPS-ASEC),
posted on the census.gov website, show a mobility rate for 2017-2018 of 8% in the
northeast United States (“Geographical Mobility”, 2018).
Lack of common measurement and definitions.
There is little common language for both measuring and defining mobility. It has
been found in previous research that the recency of mobility matters. The more recent
the move to a new school, the greater its possible effect on student achievement and
assimilation (Green & Daughtry, 1961). In the first year in which a student moves to a
different school, progress on learning experiences the most severe loss. This negative
impact on achievement continues at a lesser rate in subsequent years. During this initial
transition year, transient students also encounter the most difficulty with settling into a
new culture and making social connections. One of the earliest researchers of student
mobility examined students who moved at any point during their elementary years.
According to Kerbow (1996), an examination of Chicago area elementary school students
found that only 38% had attended the same school throughout their elementary years.
This highlights how prevalent transiency is in some parts of the nation. In fact,
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
9
considerable numbers of students experience multiple moves during their school tenure.
13% of the students had attended two or more schools during a six-year period.
Kerbow (1996) identified three groups of students at schools: stable students who
remained at a school from one year to the next, in-mobile students who moved into a
school, and out-mobile students who moved out of the school. The researcher found that
each of these groups of students would experience different levels of achievement. Stable
students experienced the best student achievement levels, while the two mobile groups
experienced lower achievement levels based on different circumstances. Kerbow’s
research examined the stable student group achievement versus that of the other two.
Fowler-Finn (2001) calculated the mobility rate for a school by the total of new
student entries and withdrawals during the year divided by the total enrollment on the
first day of school. This research goes on to state that each entry and withdrawal impacts
not only the transient students, but also the stable students, the teachers, and the district.
An example of this would be if a school experiences a 10% loss of students and a 10%
gain of students. In this case, the researcher considers the school to have a net transiency
rate of 20%. Eddy (2011) defined student mobility as “admittance to more than one
school in a given district over the period of one academic year”. Wasserman (2001)
found that the impact of student mobility on student achievement is greater for schools
with higher mobility.
Causes of mobility.
Previous research has identified numerous causes of student mobility. One of the
most detrimental times to move is during a school year. While moves at any time during
a student’s tenure are disruptive, moves during the school year result in the greatest
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
10
negative impact. There are multiple reasons for academic year moves. Seasonal jobs,
such as construction, tourism and farming as well as job and military transfers require
families to sometimes relocate during the school year (Lash & Kirkpatrick, 1990).
Additionally, changes within the family such as divorce or job loss sometimes necessitate
this as well. Rumberger et al. (1999) found that parents list three main reasons for
moving their children to another school: the students were forced to leave the school,
they moved to another residence in a different school district, or they wanted to switch
schools. Zehr (2007) reports that transiency is often related to poverty, and that students
in poor families sometimes move around with different family members.
Another reason for a high transiency rate of students is that households often tend
to move more frequently during the early stages of family formation and expansion
(Dobson, 2008). As a family grows, there is a greater need for a larger living space and
an enhanced emphasis on living in a safe community. Migration studies often show a
flow of young families from inner-city areas to suburbs and rural neighborhoods. The
Family Housing Fund (1998) conducted interviews and found that most mobility fell into
one of four categories: coping with life, forced moves, lifestyle moves, or upward
mobility. Researchers also found that a lack of family stability and inadequate affordable
housing also impacted transiency rates of those in the study.
Mobility’s effect on achievement.
Decades of research have shown the detrimental impact that mobility has on
student success in school. In a recent study of mobile students in Texas, mobile students
were found to be outperformed by non-mobile students on state math assessments
(Shoho, 2010). Williams (2003) found that when mobile students are removed from a
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
11
value-added growth analysis, school scores increased. Value added growth analyses
compare cohorts of students to themselves. This type of statistical analysis examines the
change between the entering achievement level of a given group of students to the exiting
achievement level. Proponents of value-added analysis point to the fact that children are
essentially compared to themselves in this type of reporting. However, if a student moves
during a school year, and that move has a significant impact on achievement, then the
student will likely perform at a lower rate than was expected. This would affect a
school’s value-added report at the classroom and at the school level.
Learning difficulties may be magnified if students enter classrooms at a different
point in the curriculum or state standards than they had been exposed to in their previous
schools (Kerbow, 1996). Although all schools in a state must align instruction to the
same standards, there is great variation from district to district, and even classroom to
classroom. For example, a student may leave a biology class in which that teacher started
the year with cells and cell processes and in the second half of the year moves on to
biodiversity, and in that student’s new school, the biology teacher may teach those
concepts in reverse. This places students at an extreme disadvantage when it comes to
experiencing an efficient flow of instruction and curriculum. Students experience these
learning difficulties in the first year that they move, but the student often has an
adjustment period beyond that initial year. In this way then, a mobile student’s
adjustment period truly extends over the course of several years. Deficiencies
accumulate. State standards and local curricula are intentionally designed and aligned
with vertical and horizontal structure. Curricula are often horizontally coherent, which
allows for student learning to progress in a logical manner based on the design of the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
12
curriculum. Curricula are also vertically coherent, which means that what students learn
at one grade level in a course prepares them for the next course in the sequence. A wellwritten district curriculum would be purposefully structured and logically sequenced to
allow optimal learning. As curricula vary from district to another, mobile students are at
a disadvantage in that they have not progressed through a district’s intentional learning
plan.
The Family Housing Fund (1998) examined mobility’s effect on academic
achievement. This research found that mobile students had lower attendance levels, and
that students absent 20% of the time scored twenty points lower on the California
achievement tests in reading. The research also found that reading scores were 50% lower
for students who exhibited mobility three or more times than were the scores for stable
students.
One of the ways in which mobility impacts achievement is through the need for
adjustment to peer groups, the classroom and the school. When a student moves into a
new school, one of the key priorities for that student is making adjustments. This
emphasis on adjustment results in less available time for learning. Fowler-Finn (2001)
writes:
Each withdrawal and each entry takes a toll on the student who is moving, on the
students who remain, on teachers, on support staff, on the office and on parents –
schools spend a lot of time on activities that impede direct uninterrupted
instruction. (P. 36)
There is a profound impact of frequent mobility on student academic achievement
in the early years of a child’s school experience. The impact of transiency begins early in
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
13
a child’s education. Reynolds (1990) reported that in a study of pre-kindergarten and
kindergarten programs, mobility had a negative effect on achievement. This may be
attributed to the interruption of learning at a time in which the acquisition of key skills is
vital (Franco, 2013). Krenicki (1999) examined student results related to the New Jersey
Early Warning Test and found that student mobility negatively impacted student scores
and reading and mathematics. Kerbow et al. (2003) found that the academic growth of
highly mobile students is less than the growth of stable students with similar
characteristics. Gamble (2004) examined the effect of student mobility on student
achievement under Tennessee’s school accountability system. Gamble found that student
mobility was shown to affect student achievement in both reading and mathematics.
Correlational analyses indicate that high levels of school mobility are significantly related
to poor academic performance (Felner et al, 1981).
Kariuki & Nash (1999) found that students who experience mobility several times
in their school tenure suffer even greater achievement loss. Researchers found a statistical
difference between groups of students with one move and those that made multiple
moves. Students removed three or more times were often eligible for special education.
Mobility affects attendance, impacting achievement.
Mobility affects attendance rates as well. For every day that a student does not
attend school, the student misses additional knowledge and important contact with peers
and teachers. Support for school attendance is important for all students, especially those
who are transient. Mobile students are at great risk for falling behind academically and
developmentally, resulting in the students falling even further behind, exasperating the
situation (Hinz & Snapp, 2003). As students fall behind, they become frustrated and this
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
14
results in greater absenteeism. In one study, researchers found that mobility seemed to
have a slightly greater impact on attendance then on achievement (Parke & Kanyongo,
2012). Rumberger et al. (1998) found that in a study of California students, children who
made even one school change between grade 8 and 12 were less likely to graduate from
high school than students who remain stable in the same school. A recent analysis of
student mobility versus graduation rate in the state New Jersey found a statistically
significant variable that negatively influenced graduation rate. Schools that have high
mobility rates tend to have low graduation rates (Ross, 2014).
Mobility’s effect on the system.
Student mobility also takes a toll on school systems. Sanderson (2003) reported
that urban schools faced with high mobility rates are often forced to commit large blocks
of time towards the paperwork related to intake and outflow of transient students.
Schools must collect a tremendous amount of information to enter into a student
information system. Demographic information, household information medical forms,
and media releases represent just some of the paperwork that must be completed. Schools
must also dedicate time and effort to administering district required assessments when
students enter school. For example, if a school utilizes a diagnostic assessment for
planning and instruction purposes, school personnel must administer this assessment to
the new student. This process takes additional staff time and can be quite burdensome
and a school district with high transiency. Additionally, records are sometimes lost in the
shuffle, presenting a challenge for the new school, as staff must communicate with a
student prior school in an attempt to obtain school records. This challenge often results
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
15
in additional testing and evaluation of the new student, further taxing the system in terms
of personnel and finances.
Schafft (2003) reported that the effect of school mobility is even more
pronounced in smaller, limited resource districts. In these districts, mobility resulted in
increased administrative costs, and great unpredictability in planning and budgeting.
Small districts often do not have room to absorb additional costs for testing or salary time
spent; personnel in small districts often have multiple roles and do not have time in their
schedules to accommodate assessment and intake work with new students. Kerbow
(1996) found that in some schools, class rosters changed frequently. This resulted in
making planning difficult. Some students may move into the classroom in the middle of
the unit and would be lacking necessary prerequisite skills. Not only is it difficult to a
reverse course and offer remediation, this also makes assessment of the content more
difficult. Teachers reported less time to collaborate with peers, less time to truly focus on
the student learning, and less time to innovative in their planning and instruction. These
classrooms became more focused on reviewing contents rather than introducing new
skills and knowledge. This resulted in slowing the pace of the class for all students,
mobile and stable.
Theoretical Foundations Impacting Mobility
Self-concept theory.
Some research shows that there is a connection between moving between schools
and self-concept. The self-concept theory relates to the beliefs, opinions, and attitudes
towards our existence. Self-concept controls what we think about ourselves and how we
think and behave throughout our lives. Long (1972) suggests that mobility causes an
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
16
interruption and a smooth flow of peers, teachers, curricular and teaching materials, and
general social and academic support systems. When a student moves from a school in
which they have valued friendships with peers and trusted relationships with adults, to a
new school, the absence of these things impacts their perception of the world. This
hypothesis aligns with other work supporting the impact of stressful life events on
children. In adjusting to a school transfer, mobile students are forced to adapt to new
peers and to new academic and behavioral standards (Jason et al., 1992). What is
considered a norm in one classroom may not be a norm in another. Teacher expectations
may vary. Different modalities of learning may be incorporated from one classroom to
the next. For example, a student may move into a new classroom in which that teacher
expects quality cooperative learning work when that student never received any modeling
or instruction on what effective groupwork entails. If a student fails to work in adherence
to norms of the new classroom, that student may experience frustration and a lack of
confidence.
A student’s self-concept is a factor that determines success of the outcome of the
move. Hendershott (1989) reported that social support attenuates a negative effect of
mobility on measures of self-concept. As students continue to struggle to connect
socially and academically, they become frustrated, and their self-esteem suffers. This in
turn leads to problem behaviors, which consequently, causes academics to erode even
more. Attending a new school in conjunction with the pressure of forging new
friendships and fitting in may negatively impact children’s self-esteem and their
perception of their own existence.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
17
Self-actualization theory.
Much of Maslow’s work is a conceptual model that is impacted by mobility.
Self-actualization derives from being able to leverage one’s abilities and resources to
reach their potential. Maslow’s hierarchy of needs is made up of physiological, safety,
love, self-esteem, and self-actualization. Figure 1 shows Maslow’s pyramid of needs.
Beginning at the bottom, each level needs to be taken care of before one can address the
needs at the next level. Maslow connects the role of motivation in learning, theorizing
that people follow each of these levels of need in sequence, and that learning is dependent
on the foundational components of this hierarchy. The bottom tier in this hierarchy
involves basic physiological needs: food, water, and shelter. As mobile students tend to
hail from families who are struggling financially, these students often lack the basic
physiological and safety needs of the first two levels of the foundation (Kerbow, 1996).
Mobile families often have limited access to food and healthcare, and often include nontraditional living arrangements that sometimes pose safety issues (Kerbow, 1996; Schafft,
2006). Even if moving to a new school does not impact physiological or safety needs, it
often does impact the third tier –love and belonging. This is the tier in which the
importance of connections to peers and friendships is realized. New students lack peer
and teacher relationships, and this takes time and effort to develop. Such relationships
lead to students feeling accepted and belonging; the absence of these impacts learning.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
18
Figure 1
Maslow’s hierarchy of needs. Adapted from “Maslow’s hierarchy of needs”, by J.
Finkelstein, 2006.
https://commons.wikimedia.org/wiki/File:Maslow%27s_hierarchy_of_needs.png
One of the biggest concerns of mobile students is making friends and fitting in. The third
tier of Maslow’s pyramid involves feeling loved and accepted. It relates to our need to
feel as if we belong to a specific social group. It involves both feeling loved and feeling
love towards others. Rhodes (2008) found that students experience emotional anxiety
related to this, and an inability to focus on their studies until they felt secure in their
social setting. This aligns to Maslow’s hierarchy of needs, of which safety represents the
third tier (Maslow, 1987).
The fourth tier focuses on self-esteem. This is associated with a student feeling
confident and respected by others (Maslow, 1987). A student cannot demonstrate
confidence until the first three tiers are experienced. The self-worth that comes from
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
19
feeling safe and secure and belonging enhances the environment in which learning can
take place.
Constructivism.
The concept of constructivism can be used to explain the impact of mobility on
student achievement. Active learning occurs during the transition to a new school.
Students learn about their own inner beliefs, strengths and challenges, and they learn
about those around them, including peers, school staff, and families (Rhodes, 2008). The
experiences they face help them to develop the ability to cope and assimilate into a new
culture; unfortunately, some students are unable to construct a proper framework for
assimilating and experience social, emotional, and academic issues. When students
struggle to maintain a proper structure in which they can interact with course materials
and grow, learning is impacted.
Psychological theory.
In the absence of conditions conducive to personal growth, mobile students can
suffer. The adjustment of being a transfer student can impact a student’s psychological
well-being, social and academic competence and behaviors, and eventually achievement.
Mobile students face many challenges in assimilating to a new school, including the
psychological challenge of coping with a new school environment (Holland, 1974), and
adjusting to new standards and classroom routines (Jason et al., 1992).
Developmental-ecological theory.
Developmental ecological theory goes a step further in that it acknowledges not
only the impact of mobility on mobile children, but also how mobility affects teachers
and peers in the classroom as well. The needs of mobile children can negatively affect
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
20
instruction for other students and cause a general disruption to learning (Bronfenbrenner,
2005). This has been confirmed by additional research, finding that when teachers adjust
their routines to accommodate mobile students this leads to changes or repetition in
lesson plans (GAO, 1994). This theory also suggests that there are impactful transactions
that occur between a student and his or her peers and teachers, and over time, this creates
important pathways to social, emotional, and academic development. If a child has a
history of success in developing connections with peers and teachers, this can be built
upon in the future, and the child has an advantage. Mobile students often do not have the
luxury of developing such connections, and this unsuccessful history of social
transactions breeds future difficulty with adjustment.
At a workshop convened by the National Research Council in June 2009, one
paper examined the consequences of student transiency from a developmental perspective
(Beatty 2010):
Children’s body function, brain development, capacities for dealing with stress,
and behavior change over time, and these variations may make them more or less
vulnerable to—or able to withstand—the effects of mobility. Parents as well as
children may perceive and handle a move differently depending on the child’s
developmental stage...Disruptions in this development can have a snowball effect,
which explains how mobility has the potential to harm children...Specifically,
mobility (particularly repeated mobility) can disrupt children’s routines, the
consistency of their care and health care, and their relationships, as well as
learning routines, relationships with teachers and peers, and the curriculum to
which they are exposed. (p.6)
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
21
In other words, mobility is detrimental to a student’s emotional and academic growth,
and this causes gaps in their development. Subsequent moves only magnify gaps that
develop in these foundational developmental milestones.
Social-cultural theory.
Researchers have commonly identified sociocultural theory as a foundation for
understanding the impact of mobility on educational outcomes. Coleman (1998) posits
that social capital theory argues that children build vital connections with their peers and
teachers which are critical for their own personal development and success, and mobility
removes the opportunity to build these connections. Developing connections and
friendships with peers takes time. Stable students have the advantage of benefiting from
already established relationships with peers and are at an advantage. Vygotskiĭ’s (1978)
socio-cultural theory explains that success in school is highly dependent on social success
and cultural relevance. When students move into a new setting, they struggle to connect
with peers; for some, these connections never develop. It is difficult for some students to
succeed in an environment in which they do not yet understand the culture.
Relational framework.
In an examination of mobility of students in schools across the US, Spencer
(2017) examined existing literature and presented a framework that defines student
mobility. Spencer’s framework also outlines the relationships between the causes and
effects of mobility within several different contexts. Figure 2 highlights the types,
motivators and consequences of student mobility. Considering all of these variables is
important when interpreting the results of student mobility studies, as they are
interrelated. This framework displays the different types of mobility, and how they are
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
22
caused by different motivators. These types of mobility include structural, structural,
voluntary, non-voluntary, reactive, and strategic. In addition, each of these types of
mobility results in varying consequences. Spencer’s (2017) framework also highlights
additional factors that must be considered in mobility studies, such as the relationship
between motivators and distal outcomes of mobility. The presence of variables that may
be correlated with motivators, type, and consequences of mobility must also be
considered. Finally, the potential impacts of operational considerations must be
considered as well.
Figure 2
Relational framework for student mobility. Adapted from “An examination of student
mobility in U.S. public schools”, by K. Spencer, 2018.
https://repository.upenn.edu/cgi/viewcontent.cgi?article=4377&context=edissertations
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
23
Policy and Practice
Systems of accountability.
School accountability is a prime topic these days, from local parent teacher
organization meetings to the halls of legislators. In accordance with the Every Student
Succeeds Act (ESSA), states are accountable for creating an evaluation system for
schools and determining a way for focusing resources on low performing schools and
traditionally underserved students demonstrate low achievement. States are mandated to
establish long term goals for student achievement growth, graduation rates, and English
language proficiency. States must also select several additional measures upon which
schools can be evaluated. As part of this process, states must identify schools in need of
improvement based on the performance of all students, and of student subgroups (U.S.
Department of Education, 2019).
Pennsylvania’s system of accountability.
Pennsylvania has created a system for measuring the success of schools using
multiple measures. A new reporting system, the Future Ready PA Index, features a
dashboard approach to school and student group performance. The Future Ready PA
Index illustrates student and school success on eleven indicators using a color-coded
system (Pennsylvania Department of Education, 2019). Six of these indicators are used
in the process for identifying schools in need of school improvement.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
These indicators are as follows (federal accountability school improvement
indicators denoted with an *):
•
Percent Proficient or Advanced on Pennsylvania State Assessments*
•
Meeting Annual Growth Expectations*
•
Percent Advanced on Pennsylvania State Assessments
•
English Language Growth and Attainment*
•
Regular Attendance*
•
Grade 3 ELA and Grade 7 Math Early Indicators of Performance
•
Career Standards Benchmark*
•
High School Graduation Rate*
•
Industry-Based Learning
•
Rigorous Courses of Study
•
Post-Secondary Transition to School, Military, or Work
School improvement identification in Pennsylvania.
In a process termed annual meaningful differentiation by federal statute, states
must designate schools, at least every three years, into three designations:
•
Comprehensive Support and Improvement (CSI): Schools facing
significant challenges in achievement, growth, and any of the other four
areas highlighted above
24
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
•
25
Additional Targeted Support and Improvement (A-TSI): schools
experiencing poor performance by one or more student groups belong a
specified threshold
•
Targeted Support and Improvement (TSI): schools experiencing poor
performance by one or more student groups in danger of approaching a
specified threshold
Schools are identified for one of the levels of school improvement if they have
both low achievement scores and low growth profiles (below statewide minimum values)
and poor performance on additional ESSA-required indicators. If mobility impacts
student achievement and growth as well as graduation rates, can a high mobility rate lead
to a school improvement designation?
Stakeholder perceptions.
Parents place high value in published accountability ratings. Research
surrounding parent perceptions of state school accountability reporting show that 80% of
parents place value in reported test score summaries (Owens & Peltier, 2002).
Unfortunately for school systems with high student transiency rates, while it is easy for a
parent to view a website and see a number, it’s not as simple to understand factors that
influence that number. It is often common practice for external stakeholders, including
the media, to compare the values assigned to an indicator for two separate schools.
Without context, it could appear that the school with a higher value is the better school;
however, one needs to take into account a variety of factors including mobility. When
parents review these school accountability ratings without context, parents in a school
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
26
district with high mobility may decide to leave the district for a district for another that is
perceived to be better in serving students.
There are numerous factors that the state should keep in the forefront when
designing an accountability system. An accountability system must evaluate each school
in terms of its own context (Sirotnik, 1999). Such systems must go beyond test scores to
include a variety of additional factors. Sewell et al. (1982) found that mobility is a very
important intervening variable in achievement and must be controlled during
interpretation of achievement progress for reporting and decision-making purposes.
Educational accountability systems across the nation.
Currently, only about half of all states collect data on mobile students or post such
data (Blashe et al. 2018). The information that is collected is not consistent, which
makes state by state comparisons very difficult. While federal mandates require schools
to identify students with some extenuating circumstances, such as homelessness, the
federal government does not define how transient students would be viewed, nor does it
mandate that they be tracked. Some states count only students who switch mid-year,
while others include students who move outside of the academic school year. Florida, for
example, tracks students who move between the months of October and February.
Massachusetts defines mobile students as ones who move between October and June.
Texas is perhaps the closest to define incomplete mobility. Students in a school for less
than 83% of the school year are referred to as mobile. Figure 3 identifies the twenty-nine
states that track student turnover by any means. Not all of these states publish the results.
Figure 4 displays the twenty-four states who post such data. As Figure 5 highlights, only
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
27
twenty-one states post district-level mobility data. At the school-level, this statistic is
even smaller. Figure 6 identifies the seventeen states that display school level mobility
data. Pennsylvania is currently not one of the states that posts or even collects data on
student mobility.
Figure 3
Tracking turnover across the country: states that track student turnover [graphic].
(2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
Figure 4
Tracking turnover across the country: turnover data is posted [graphic]. (2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
28
Figure 5
Tracking turnover across the country: district level data is posted [graphic]. (2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
Figure 6
Tracking turnover across the country: school level data is posted [graphic]. (2018).
https://projects.jsonline.com/news/2018/10/9/student-mobility-numbers-not-tracked-bymany-states.html
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
29
Staff practice and attitudes towards mobile students.
Controlling for outside factors, the single biggest impact on student success is the
teacher. Staff practice and attitudes towards mobile students can have a significant impact
on their success. From a teacher’s perspective, student mobility can be disruptive (Lash
& Kirkpatrick, 1990). Not only do such students require immediate attention, but they
must learn the rules and routines of the new school and classroom, which put a strain on
teachers. School days do not have extra transition time built-in to assist mobile students
with transition; instead, teachers must take time away from their already short class
periods to help acclimate new students to classroom culture. Teachers in classrooms with
multiple mobile students often end up reviewing old material instead of introducing new
material, which impacts the stable students in the class (Rothstein, 2004). This slowing
down of the pacing of the classroom impacts academic growth of stable students as well.
Pennsylvania’s value-added assessment system measures students against their past
growth. If a classroom teacher slowed the pace of instruction to reteach material to new
students, the existing students in the class would likely not achieve as high as statistical
modeling would expect, and this would result in potentially poor growth values assigned
to this classroom and also to its teacher.
Rumberger et al. (1999) suggest the teachers should review the cumulative
records of new students to assess grades, attendance, and important background
information. Contacting the prior teacher is an effective way to learn more about that
student and the background the student brings (Kerbow, 1996). It is difficult to plan
instruction when a teacher does not know what academic knowledge a new student
brings. Because of this, assessments are a necessary part of the intake process. Hartman
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
30
(2006) reports that not knowing the academic abilities of new students negatively impacts
a teacher’s planning and instruction process and puts an overall strain on the system and
its resources.
Chow (2014) found that teachers should prioritize fostering supportive
relationships with mobile students and their parents as a means to promote their success.
When teachers have more contact with parents, they can learn more about the student’s
needs and home environment and provide necessary structure in the classroom to meet
those needs. Parents can also learn about teacher expectations, as well as classroom and
school culture. Strong teacher-parent connections lead to meaningful and productive
conversations, which will better help the transient student in the adjustment period.
Cloer (2015) studied teachers at an elementary school and their perception
towards mobile students. The goal of the project was to solicit teacher perceptions about
the success or failure of mobile students. Teachers indicated that upon the arrival of a
new student, they would examine initial enrollment paperwork and learn about the new
student through talking. Examining cumulative records was another action undertaken by
teachers, but this sometimes requires dedicated time. Sadly, even though all teachers
interviewed placed value in talking with parents of a new student, they indicated that
parents do not always make themselves available to meet. All teachers agreed that the
presence of mobile students significantly impacts planning and instruction, and that it is
difficult to plan without knowing what background the student brings. Teachers also
agreed that placing students in groups is difficult without knowledge of a student’s prior
experience with group work. All teachers found it was important to assign the new
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
31
student a friend or a buddy to guide them around the school. The important role of
counselors in this process was also mentioned as a vital support to new students.
Cloer (2015) also found that teachers expressed concern for increased behavior
issues. New students do not understand class procedures and routines, and thus, may
interrupt the flow of the class. Mobile students often demonstrate poor adjustments and
experience increased behavioral issues resulting in less time on task and less stability
(Rumberger et al., 1999).
Administrative practice towards mobility.
Procedures put in place by administration, as well as general administrative
support directly affects the achievement of mobile students. Just as a teacher is the single
biggest factor in the success of a classroom, an administrator is the single biggest factor
in the success of a school. In a study of student mobility, high rankings of school
leadership and usefulness of its professional development programs was found to
correlate positively with performance (Heywood & Thomas, 1997). Franke et al. (2003)
describe an informal intake process at one school in which an informal family history and
child academic assessment take place. It is during such informal intake meetings that
school staff may ‘get to know’ student. Even if all of the prior school records have been
received by the new school, personal meetings often provide richer information and
context, beyond that which can be found in student academic files. At the same school,
front desk staff are sensitive to the issues of new and transient students and are respectful
of their circumstances. This is important because the front office is often seen as the first
contact points for communications, questions, and concerns.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
32
System-level practices impacting mobility.
Filipelli & Jason (1992) suggest that as part of a child’s transition to a new school,
educators and perhaps mental health professionals should assess stressful life events in
the lives of transfer students. This way, schools might be able to identify potential
roadblocks to transition. Adults might be ignorant to the primary concerns of the
children themselves; while adults may be interested in making sure the student is
properly scheduled and has a bus stop, the child may be more concerned immediately
where to sit for lunch and dress code. Students may also come with adverse childhood
experiences affecting their ability to transition. Identifying these experiences and their
impact on the present can help social workers design an effective transition plan for the
student. Huffman (2013) writes about the value of school social workers who can work
with at-risk students to build attendance plans, and work with parents to overcome
barriers.
Smith et al. (2008) highlighted that a commitment to screening students
immediately upon enrollment, using intentional placement, instituting progress
monitoring, and adjusting as necessary provides mobile students with a great opportunity
to succeed in school. This suggests a shift from a reactive approach to students moving
in, to a more proactive approach, one that has been carefully considered and planned
beforehand, and implemented in a system in which transient students do not fall through
the cracks. This involves providing diagnostic screenings, such as those in math and
reading, to identify not only needs but also strengths. The screenings will help inform
class placement and planning for instruction. The progress monitoring of mobile students
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
33
provided the school with a means of evaluating the success of a student’s assimilation,
and an early warning of potential roadblocks.
Fisher & Matthews (1999) conducted a qualitative study examining factors that
lead to increased school stability for mobile students. The most effective measure schools
took was supporting families with wraparound services. The researchers found that
students benefit from increased interaction with staff who exhibited a caring demeanor
and high expectations. The stability of consistent programming and clear guidelines and
policies helped address the academic and social needs of the students. Effective programs
placed high value on the creation of positive relationships with families. Increased
school stability was supported by school administration in their shared leadership,
demand of high levels of collegiality, and their continued evaluation of the program with
an emphasis on continuous improvement.
One way of reducing student mobility might be if schools provide information to
parents about the harmful effects of changing schools. Kerbow (1996) suggests that if
parents were made more aware of the value of stable environments for children, mobility
will be reduced, and additionally, relationships with families may be more firmly
established. Many urban schools have high levels of mobility. Some of these schools
make many attempts to implement programs and practices to help families (Nakagawa et
al., 2002). However, it was found that these attempts did not result in greater
involvement from the families.
Policy that impacts mobility.
Unfortunately, researchers have found that student mobility has not received
much attention from policymakers. One reason is that transiency is often seen as
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
34
inevitable and out of the school’s control (Rumberger & Larson, 1998). Pupil mobility
has implications for many policy areas, including school funding and goal-setting
(Demie, 2002). State and local policies can have a considerable impact on the success of
mobile students. Rural, chronically mobile students have escaped the attention of schools
and public policymakers (Schafft, 2006). This often goes unrecognized, in part because
the numbers of students entering and exiting schools usually balance out, so the net
enrollment changes are not noticeable. Nationally, the lack of attention paid to transiency
is likely because the students don’t fit into federal subgroup categories, and thus escape
from being under the lens of federal and state accountability.
It is difficult to hold schools accountable when indicators are based on factors
outside of the schools control, such as transiency (Delong, 2002). Student mobility poses
unique problems. Administrators at high mobility schools should be given fund
allocations to create new programs and learning opportunities specifically targeting
mobile students (Williams, 2003). Even the US General Accounting Office has proposed
that policymakers focus greater attention on the needs of mobile students. GAO’s (1994)
report suggested that the US Department of Education can play a role in helping mobile
children by ensuring that they have access to federally funded education programs and
encouraging states to implement more effective student record transfer systems, and to
support local education agencies in accommodating mobile students. Wasserman (2001)
suggests that achievement test results for schools need to be interpreted taking variation
in student mobility into consideration. School choice advocates often point to school
choice as a way to reduce the impact of student mobility (Coleman-Weathersbee, 2018).
If states allow school choice programs, then students may not have to change schools
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
35
when their place of residence changes. Rumberger (2016) suggested that school districts
might also be flexible with school boundaries and provide transportation and support to
families considering moving.
Gamble (2004) recommends that states have an obligation to collaborate with
school systems intensively, to ensure that all stakeholders are informed of the needs of
mobile students. It is also important that the presence and plight of mobile students be
made visible and understood by all. Better informed staff are better prepared to meet the
needs of transient students.
Policymakers should shift their focus from assigning numerical ratings to schools,
towards more socially desirable educational outcomes, such as whether students learn
what they need to learn and whether these learning outcomes are equally distributed
(Longanecker & Blanco, 2003). Housing and community development policy should
focus on investment in low income communities, which would result in less families
leaving, and thus lower student mobility (Metzger, Fowler, Anderson & Lindsay, 2016).
Overwhelming evidence shows that most school mobility is a function of involuntary
residential moves, and a governmental program to increase the supply of affordable
housing can help stem transiency (Hartman, 2006). This type of investment would
enhance social capital and assets within the community. Heinlin & Shinn (2000)
proposed that school systems can work with community groups to reduce disruptive
moves. Once such program studied involved parents, educators, landlords, social
workers, and politicians and led to a 38% reduction in transiency.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
36
Summary
School accountability is an important issue in education today. Schools are being
identified as in need of school improvement based on academic and behavioral indicators
of success. These indicators of success are negatively impacted by student mobility. The
goal of this literature review was to define mobility, identify its connections to indicators
of achievement and success, and review how student mobility is factored into statewide
school accountability models. Descriptions of student mobility were highlighted in an
effort to develop an operational definition of mobility for the purpose of this action
research project. Most popular definitions of student mobility defined mobile students as
those who have moved within the current school year, though there exists some evidence
that suggests that mobility impacts student achievement beyond just the year in which the
student experienced a move. Theoretical frameworks related to student mobility were
reviewed, suggesting how transiency can have a negative impact on student achievement.
Transiency impacts students at a deep level, resulting in developmental, social, emotional
and academic deficits. Much of this relates to Maslow’s hierarchy of needs. Finally, a
review of state and federal accountability models was conducted, finding that there is
disparity from one state to another in terms of whether or not student mobility is factored
into indicators of school success.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
37
CHAPTER 3
Methodology
The purpose of this chapter is twofold: it will introduce the research methodology
for this action research project, and it will discuss its various implications. A
comprehensive review of the literature shows that research supports a correlation
between student mobility and indicators of school success. There also exists a great
disparity between districts and sometimes schools within districts related to levels of
student transiency. Additionally, Pennsylvania’s system of school accountability
provides a report of student success in a number of federally-mandated areas, but it does
not consider levels of student mobility.
This chapter will first re-introduce and develop the research questions. The
methodology selected will be highlighted, including a justification for the research design
as well as a detailed description of the statistical data analysis. Background information
on the researcher and participants will be provided. Data collection, procedures and data
analysis will be described. Finally, threats to validity, trustworthiness, ethical concerns,
and fiscal implications will be reviewed.
Purpose
This action research project examined the impact of student mobility on school
accountability indicators. A causal comparative research design was utilized, as the
researcher’s intent was to conclude a cause and effect correlation between student
mobility and overall score accountability indicators.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
38
Problem.
Many of the schools designated for school improvement also experience high
student mobility. Decades of research show there is a correlation between student
mobility and success in school; kids who move more generally perform worse. If school
improvement designations are based on factors affected by student mobility, are school
districts with a high percentage of student mobility more likely to be designated for
school improvement?
Research questions.
This action research project was initiated to answer two questions. Is there a
significant relationship between student mobility and a school’s accountability
indicators? How do schools fare in Pennsylvania’s school accountability system when
controlling for levels of student mobility?
Setting and Participants
The school districts taking part in the research project were selected as they
represented various levels of student mobility, and ones in which district leaders
indicated great interest in the results of the study. In order to examine the impact of
mobility, the research required subjects (schools) with significant levels of transiency, in
order to examine correlation. One school district chosen has been identified for school
improvement by the state, based on school accountability indicators. The other school
district has not been designated for school improvement, but some within the school
district have voiced concerns relating to the challenges posed by the levels of student
mobility they face. Both school districts chosen are led by superintendents who have
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
39
great interest in the results of the study, as intend to use the work to inform decisions
relating to fiscal and human capital resources.
Each school district is unique in its composition and community, but both school
districts experience a significant student mobility rate. In an effort to maintain
confidentiality of the data, the school districts will be referred to as school district X and
school district Y.
District X is located in a suburb in western Pennsylvania. In the past, the district
has received a number of awards celebrating its academic success, including a Blue
Ribbon Schools award. The district serves over 3000 students with a staff of over 500.
Over the past 10 years, the communities that comprise the district have experienced a
shift in businesses and housing. Transitional housing has become more readily available
in the district, which results in greater migration of students. District X has not been
designated for school improvement yet, but the administration continues to pay close
attention to indicators of academic success of all students, and is committed to adjusting
programs and offerings as needed.
District Y is a smaller suburban school district located in a city with a high
poverty rate. It is ranked in the bottom 5% in numerous state and national school
rankings. The communities that comprise this district have experienced a sharp decline in
longtime residents, and the district currently experiences a very high rate of student
mobility. The school district receives a high percentage of annual revenue from the state,
placing it among districts receiving the highest state funding in Pennsylvania. A
tremendous amount of financial resources are being funneled into improving academic
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
40
achievement for students in this district, and the superintendent is committed to utilizing
these resources efficiently.
Schools were recruited using a variety of strategies. The opportunity to discuss
partnering was mentioned at a role-alike meeting of western Pennsylvania schools. The
researcher also targeted schools by reaching out to superintendents and asking them to
consider participation in the study.
There were several unsuccessful attempts in the process to solicit partners for this
project. Several school districts indicated interest initially, but declined to participate as
the study involved student data. Two superintendents mentioned to the researcher that
they would be concerned if the research showed that there is a little correlation between
student mobility and indicators of academic success; this may cause some to infer that a
district is doing a disservice to all students, whether or not those students are
continuously enrolled. Two cyber-charter schools indicated interest early in the process,
but later backed out prior to granting final permission to participate. While the schools
did not provide a reason, between initial interest and final agreement, legislation was
introduced in the states which would drastically impact cyber charter schools. It is
speculated on the part of the researcher that the schools decided not to participate due to
the timing of this potential legislation that may drastically impact this type of school in
the future. A study that had a potential to show any deficiencies in a school may be
frowned upon when the school may likely be under increased public scrutiny.
Intervention and Research Plan
Positivism gives rise to quantitative methodology (Mukherji & Albon, 2015). This
research was approached with a positivism epistemology (Age, 2011), as it uses a
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
41
systematic, scientific approach to the way the research is conducted, and results
examined. Because positivism is grounded in objectivity and discrete data sets, it
supports quantitative methodology. In examining the role a positivist methodology plays
in quantitative research, Mukherji & Albon (2015) posit that “correlational studies are
used in situations when it is difficult or impossible to use experiments, but the researcher
wants to see if there is a relationship between two variables”. This describes a limiting
factor of studying student mobility, as a researcher cannot use an experimental approach
to examine student mobility. The role of the researcher in this case was limited to data
collection, data analysis, and interpretation in an objective manner. Using extant
accountability data provides quantifiable observations. These observations led to a
statistical analysis that is judged only by logic and free from subjectivity and
interpretation. This approach was selected by the researcher as it is a scientific approach
to examining data that leads to results that can be often generalized across a field. In
alignment to the researcher’s own beliefs regarding the importance of an objective,
impartial examination of data, positivist research is likely conducted to establish
correlational or causal relationships that can be generalized and shown to be objective
(Paré, 2004).
Hendricks (2017) explains that through the action research process, practitioners
use the knowledge generated through their research to inform practice as well as guide
and improve systems at a higher level. As the researcher has spent several years
embedded in school improvement work, action research provides a systemic approach to
pinpointing challenges to school improvement.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
42
The approach also allows valuable fiscal resources earmarked for school
improvement to be redirected towards research-identified solutions. As an action
researcher, the author will be able to ground future work in the results of this project.
Having a local, regional, and state role in school improvement efforts, the findings will
be acted upon in a manner that should directly impact students, staff, and administrators
in the state. As action research, the project will inform the ethics of school improvement
efforts based on objective work. This effort will also connect existing research with
systemic practices and thinking.
Connection to fiscal implications.
The research design will result in findings that will have several fiscal
implications, both locally, as well as at a state and national level. The process outlined in
this research project is one that could be replicated at no cost in any Pennsylvania school.
Schools may wish to audit their success with transient students by using the same files to
examine the academic success of mobile students. As the process would be free, it would
not require payment to any outside firm and thus would be a fiscally responsible
commitment on the part of district leaders.
Also, at a school level, schools may redirect taxpayer money from content
specific expenses to supports for transient students. Schools have only a finite amount of
money to spend and targeting the groups of students most in need would provide the most
success from the resources they have.
At a state level, over two million dollars will be spent over the next few years on
school improvement efforts. At the time, the system as it is currently organized provides
content-specific advisers to schools in school improvement at a great cost. The results of
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
43
this study may inform the state in making changes to its school improvement staffing,
providing more transition coordinators to schools to help those students most in need.
Research Design, Methods & Data Collection
This research was designed as a quantitative correlational study. The goal of the
study is to describe the relationship between transiency rate and school accountability
indicator values, and also to establish a relationship between these two factors. As such,
the project uses a causal comparative design (Schenker & Rumrill, 2004), intended to
identify relationships between independent and dependent variables. A hallmark of this
type of design is that it examines data after actions have occurred. The researcher hopes
to determine whether or not the school accountability indicators, as independent
variables, are affected by student mobility, as a dependent variable. Causal comparative
research design is an effective way to examine relationships between variables when it is
not possible to manipulate the actual variables themselves. As it would the impossible
and unethical to intentionally move students between schools, this type of design allows a
researcher to examine the effect of such actions outside of the experimental procedures.
While other means of research may result in more compelling recommendations based on
causation, the research questions associated with this project would be difficult to
examine with other methods.
Multiple forms of data.
There are seven key sources of data required as part of this action research
project. It is important to note that all data files identified students by PAsecureID,
which is a statewide, randomly assigned identification number for students in the state of
Pennsylvania. At no point were student names shared with the researcher.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
44
The first source of data examined was the school accountability values posted on
Pennsylvania’s Future Ready PA Index website at https://futurereadypa.org. This site is
updated each fall to reflect the success of Pennsylvania schools during the previous
school year. It is an aggregate of school progress measures relate to academic success and
college and career readiness. As viewed in Figure 7, this index includes assessment
measures, on-track measures and readiness indicators.
Figure 7
Future Ready PA Index. School Performance ã 2020. Retrieved April 23, 2020 from
https://futurereadypa.org. Screenshot by author.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
45
This website evaluate scores on 11 indicators. Six of these are federally-mandated and are
the measures used to designate schools for school improvement. Those six federally
mandated measures are academic achievement, academic growth, attendance, graduation
rate, English learner proficiency, and career readiness benchmarks. Future Ready PA
Index values in each of the six areas were noted for each of the schools involved in the
study. The values posted on the website will be compared to the adjusted values
determined by the researcher when controlling for percentage of transient students.
Pennsylvania assessments in grades three through eight are administered each
spring. High school assessments in the state can be administered throughout the year with
a cycle beginning in the summer and ending each spring. The results of these assessments
are provided to districts in a single file known as the district accountability file. This file
is made available to district superintendents each year in June, through a restricted access
site known as PA eDirect (https://www.drcedirect.com/). This file contains state
assessment results for all students in the district. The file also contains information
related to whether or not each student was attributed to a school for reporting purposes or
not. It is this file that was obtained from each participating district that allows the
researcher to identify which students would be included in achievement and growth
reporting.
The other reports necessary for completion of this project were all pulled from
each district’s student information system. Several of these are part of the process of data
submissions to the state known as PIMS submission. The Pennsylvania Information
Management System (PIMS) is the means by which the state aggregates data from
schools for reporting and analysis. One such required file is a report known as the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
46
student-career standards benchmark report, which is uploaded at the end of the school
year and contains all of the information necessary for calculating career readiness
percentages.
Another necessary data source is known as the student calendar fact template.
This report provides necessary information to calculate attendance rates. Attendance is
reported on the Future Ready PA Index as a lagging indicator, meaning that the number
reported on the website is the value from not the previous school year but the year prior
to that. A lagging indicator is necessary when a variety of circumstances result in an
inability to be able to aggregate final information related to a given indicator in a timely
fashion. Another data source is known as the frozen graduate cohort data, which is also a
lagging indicator. This report would identify students in the prior year enrolled in high
school for four years who graduated. This data will assist the researcher in determining
graduation rates.
There is a sixth federally-mandated indicator of success that factors into the
Future Ready PA Index, but was not necessary to gather from the participating schools.
The percent of English language learners who achieve proficiency is also reported on the
system, but is only reported for schools with a minimum N-count of 20. None of the
schools participating in this project had an enrollment of English learners at that level,
and thus, that data is not available nor reported on the website.
One final piece of data collected from each of the districts identified enrollment
dates of students. For the purpose of this research, mobile students were defined as those
not continuously enrolled for at least one year. This enrollment information was used to
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
47
flag mobile students in the system, and to be used when creating adjusted student groups
as detailed in the procedure section that follows.
All of this data was obtained through each of the school district’s PIMS
administrators. (The Pennsylvania Information Management System, or PIMS, is a
statewide, longitudinal information management system designed to assist schools in
submitting timely data in a consistent format.) The researcher worked with each
superintendent to collaborate with this data administrator to pull the necessary reports
from their student information system for use in the project. One strategy that proved
helpful was accessing the PIMS manuals on the PIMS website and determining the
specific names of the reports needed. Entering into meetings with data administrators,
knowing the specific names of the reports needed helped to streamline the process, and
the data administrators expressed appreciation for the succinct specificity.
Data files were downloaded to a local, password-protected laptop, and saved in a
password-protected folder. Only the researcher maintained access and password to this
laptop. At the conclusion of the project, all files in this folder were permanently deleted.
Timing of the data collection.
The timing of the data collection was based upon the extant data required for
analysis. State accountability indicators are posted to a public website in the fall,
reflecting the prior year’s results. Data factoring into these results is drawn from a series
of data uploads initiated by the school district, through the summer just prior to the fall
release of school accountability indicators. Because of this, all available data for
examining a prior year’s success is available for collection by mid-summer. The data for
this research project was collected during February 2020, reflecting performance during
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
48
the 2018-2019 school year, with the exception of two lagging indicators, attendance and
graduation.
Choices and organization of the data.
The data collected and analyzed was classified into four categories. The data was
obtained from the source that informs Pennsylvania’s school accountability system and
the same attribution rules were applied. It is important to note that the state created
specific rules as to which students are attributed to a school and which students cannot be
attributed to a school. The rationale for the creation of attribution roles is based on the
fact that there are some students who are enrolled in a school for a minimal amount of
time that would not likely allow the organization enough time to make an academic
impact.
Achievement.
This indicator represents the percentage of students who scored proficient or
advanced on a state assessment. The Pennsylvania System of School Assessment (PSSA)
exam is administered to students in grades three through eight for mathematics and
English language arts, and grades four and eight for science. Additionally, students are
administered tests in Algebra, Biology, and Literature in high school, but this action
research study examined state assessments in grades three through eight only, as
reporting at the high school is more complex and obtaining the high school assessment
data in a format that would allow for validity may prove challenging. These state
assessments rank students in four proficiency levels – below basic, basic, proficient, and
advanced. Two groups of students do not factor into state calculations: students enrolled
after October 1, and first year English language learners. As the Future Ready PA Index
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
49
reports achievement at a subject specific, building-wide level, sample groups will be
defined by building, separated by content area.
Growth.
This indicator represents how a given group of students has grown from an
academic standpoint relative to their entering achievement. The same attribution rules
that are applied to achievement are also applied to growth. As the Future Ready PA
Index reports growth at a subject-specific, building-wide level, sample groups will be
defined by building, separated by content area.
Attendance Rate.
Attendance is defined as the percentage of students enrolled in a school for 90
school days or more, who are present for 90% or more of the days. This measure is a
lagging indicator. A lagging indicator is one that is the value from not the school year of
interest but the year before that. (The reason for this is that the complete data set that
comprises some indicators, such as attendance, cannot be fully collected by state for a
considerable length of time after the school year ends.) As the Future Ready PA Index
reports attendance at a building-wide level, sample groups will be defined by building.
Graduation Rate.
This represents the percentage of students who graduated from a school in a fouryear cohort. This measurement is also a lagging indicator. As the Future Ready PA Index
reports graduation at a twelfth grade building level, sample groups will by building
cohort.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
50
Career Readiness Benchmark.
This represents the percent of students who have satisfied requirements related to
career education as mandated by the state. This is reported by grade span, with reporting
occurring at the end of grade 5, grade 8, and grade 11. Accordingly, sample groups will
be aggregated based on these reporting rules.
English Language Learner Proficiency.
This indicator provides a measure of English learner growth and attainment of
English language proficiency. This is evaluated through the use of a state mandated
assessment known as ACCESS for ELLs.
Procedures for aggregating and examining the data.
After obtaining agreement to participate from superintendents, and then obtaining
the necessary data from the school district PIMS administrators, the process began with
flagging transient students in each of the files.
Flagging students in files.
As none of these files or submissions require a specially defined transiency field,
the researcher had to manually flag each transient student in each file. This was
accomplished by sorting each file by PAsecureID, then creating a column labeled
transient and placing an indicator in this column for each student who had not been
continuously enrolled in the school for at least one year.
Identifying students factoring into achievement and growth.
Each district’s district accountability file was manipulated to remove all students
who were not attributed to a school, remove all students enrolled after October 1, and
remove all students who were flagged as first year English language learner students.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
51
These students are not factored into the values on the Future Ready PA Index. The
remaining data was manipulated to determine the percent proficient/advanced for each
score and this number was compared to its value on the Future Ready PA Index site to
ensure fidelity. Once it was verified that the remaining data is the data that factored into
school accountability, then an adjusted cohort was created for each school, based on a
nationwide regional transiency rate of 8%. If a school had a rate of transiency at higher
than 8%, then the transient students would be removed, and through a process of random
selection, only 8% would be added back to the file (see process that follows). Finally,
proficient/advanced values were calculated again using this adjusted cohort.
Process of random selection.
When the number of transient students exceeded 8%, those students were pulled
out of a file and placed into a separate spreadsheet. The students were first sorted in
ascending order by PAsecureID. Each student was assigned a number beginning with the
number one. A random number generator (https://www.calculator.net/) was used to
randomly select a quantity of numbers that would equal 8% of the total student
population. These randomly selected students were then added back to the day to file.
This new group of students was identified as the adjusted group.
Identifying students factoring into the additional indicators.
For the additional indicators (career readiness, graduation, and attendance) a
similar procedure was followed. Students not attributed to a school were removed and
transient students were identified. If a school exceeded the 8% threshold of transient
students, they were removed and 8% selected for a random sampling and added back to
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
52
the group to form an adjusted cohort. Each of these adjusted groups were compared to
the formal group in the data analysis phase of the project.
Data analysis.
The data analysis phase began immediately following the creation of adjusted
cohort groups to compare to the formal cohort groups. Raw data files were manipulated
to isolate students attributed for school accountability. Transient students were flagged in
the files. Indicator values were calculated at the all student group level, a stable student
only level, and if applicable, and adjusted group controlled to 8% transient students
determined through random sampling. SPSS software was used to conduct a correlation
analysis on the data.
Statistical analysis.
The statistical analysis took place using SPSS software. This software, produced
by IBM, is the leading platform for statistical analysis in higher education, and is widely
used in industry. SPSS software was selected as it provides an effective way to manage
and analyze data, and a wide range of options to view the results.
The study examined the data in two ways. First, indicators were compared to
percent of mobile students in the sample group. Second, the concentration of mobile
students was compared to the change in each indicator’s value between the all student
group and the stable student group.
SPSS software was used to determine correlation and statistical significance of
the results. A bivariate measures of correlation analysis was utilized. Bivariate
correlation analysis is conducted to examine the relationship between two different
variables. The analysis produces a value that represents the relationship between a
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
53
change in A when there is a change in B. As the focus of this action research project is
an examination of the empirical relationship between student mobility and school
accountability factors, a bivariate correlation analysis will help examine the hypotheses
of association between the multiple sets of data.
The process for completing a bivariate correlation test using SPPS software
entails selecting the analyze function, then correlate. In the bivariate correlation option
menu, the two variables to be tested (i.e. % transient and math growth score) were pulled
into the test box. The following items were also selected: Pearson correlation coefficients,
two-tailed significance, and flag significant correlations. Following this setup, the test
process was run. (See Figure 8.)
Figure 8
SPSS Software. Bivariate correlations menu ã2015 IBM. Screenshot by author
Institutional Review Board (IRB).
To ensure that no district felt coerced to participate, the researcher held numerous
conversations with each participating district superintendent, providing not only the
purpose and rationale for the project, but also a detailed description of the methodology
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
54
and data analysis. Each superintendent was also provided with a copy of the IRB review
request, on which the researcher committed to maintaining confidentiality. As part of this
IRB review request, and in subsequent emails, each superintendent was assured of and
acknowledged the fact that they retained the right to withdraw from participation at any
time. Consent forms to participate were signed by each superintendent.
In adherence to university policy, an IRB request was submitted to the IRB
Review Board in November. 2019 (Appendix A). The IRB proposal was approved on
November 14, 2019 (Appendix B).
In order to make sure that the data collected was handled and stored in a
confidential manner, the researcher requested data files without name association. No
personally identifiable information was shared. This anonymous data was saved on a
local password-protected computer in a password-protected folder and the data was
deleted at the end of the project. There is no risk of bias in this study, as students were
not identified by name, and adjusted school accountability indicators were calculated
using district-provided files.
Validity
The purpose of this research was to determine the effect of transiency on school
accountability ratings. In research it is important to consider if observed variation can be
attributable to other causes aside from changes in the independent variable. When
considering threats to the internal validity, or credibility, of the results, history and
maturation, two common internal validity threats were not present in the study. Another
common internal validity threat is selection, and this was negated by the random
sampling methods used by the researcher.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
55
It is also important examine external validity or transferability, which relates to
how the results of a study can be generalized across subjects and settings. While the
experimental process did provide ecological validity, it is possible that the design led to a
small threat in population validity. While the researcher took many steps to solicit
partners for the project, only two school districts would participate. As the
Commonwealth has 499 school districts, it is possible that the two school district selected
are not completely representative of the majority, which might impact the ability to
generalize the conclusions across the Commonwealth.
Finally, the researcher made all efforts to ensure objectivity in this study. The
data that was collected followed a strict format aligned to state data-collection protocols
and consistent among all school districts. Random sampling took place using a wellaccepted process utilized in research around the globe. Student names were not shared,
nor did the researcher and superintendents have any discussion regarding expected
outcome of the analysis.
As the project was limited to analyzing extant data, no human subjects were
involved. The only potential discomfort to a school would be if the data showed that
regardless of student mobility all students are underachieving; this would serve as a
discomfort as it would be a sign of an ineffective system.
Summary
The purpose of this chapter was to explain the methodology used to answer the
action research questions. A discussion of the methodology, participants, data collection,
procedures, and data analysis followed. An empirical methodology of philosophical
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
56
positivism was used to develop the research, which examined the effect of transient
populations on school accountability indicators.
A quantitative data analysis was conducted utilizing information provided to
school districts through the Pennsylvania school accountability system. The method of
research was to examine the six school accountability indicators that factor into school
improvement designation. The process for examining these and their impact on mobility
involved isolating the transient students from the stable students, then conducting a
statistical analysis to look for a relationship between the percentage of transient students
in a school and its accountability values. The accountability values from eight schools in
Pennsylvania were examined. The schools exhibited diversity in terms of socioeconomic
composition.
The methodology proved to be internally valid and faced only a small threat in
external validity, in terms of population validity. The researcher ensured that the project
was completed in an ethical manner, and that no human subjects were involved, and no
personally-identifiable information was provided. Proper protocol was followed in
adherence to the institutions IRB policy. Chapter 4 will outline results of the study and
demonstrate in action the methodology described in this chapter.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
57
CHAPTER 4
Data Analysis and Results
The purpose of this chapter is to present the results of the statistical testing and
analysis. A grounded theory methodology of positivism was used to answer the research
questions. For each of the two research questions, the data analysis and associated
descriptive correlations will be shared, along with supporting methodology to allow the
study to be replicated. The processes used to filter the raw accountability files to isolate
attributed students as well as to flag transient students will be shared, as well as the
calculations that led to the indicators that were studied. Included in this chapter will be
graphics and tables used to visually display and emphasize the results of the study. The
chapter will conclude with a reflection on each research question and concluding answers
drawn from the data. This action research project sought to find answers to two questions.
Is there a significant relationship between student mobility and a school’s accountability
indicators? How do schools fare in Pennsylvania’s school accountability system when
controlling for levels of student mobility?
Data Analysis
For the purpose of the study, mobility and transiency will appear interchangeable.
Mobility will be defined as students who have not been continuously enrolled in the same
school for twelve months. An average student mobility rate of 8% was utilized as
reported in the Current Population Survey Annual Social and Economic Supplement
posted on the census.gov website (“Geographical Mobility”, 2018). Based on research
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
58
that indicates that transiency impacts academic achievement and school success, the
researcher assumed that the presence of mobile students in a school would adversely
affect state accountability indicators. Based on this assumption, the researcher also
speculated that when controlling for the number of mobile students in a group, the
school’s accountability numbers would likely experience an increase, perhaps high
enough to prevent a school improvement designation. Will the data analysis support these
hypotheses?
Key terms and definitions referenced in the process.
Before presenting the process by which the researcher analyzed the data, it is
important to provide the reader with an explanation of key terms and definitions
referenced in the process. A description of these key terms follows.
Pennsylvania’s system of school accountability.
The data analysis created modified students groups (controlled for transiency rate)
which were then compared to numbers publicly posted on Pennsylvania’s Department of
Education website. Pennsylvania has created a system for measuring the success of
schools using multiple measures. This system, the Future Ready PA Index, features a
dashboard approach to school and student group performance. The Future Ready PA
Index illustrates student and school success on eleven indicators using a color-coded
system (Pennsylvania Department of Education, 2019). Per federal guidelines, six of the
eleven indicators are used in the process of identifying schools in need of school
improvement (U.S. Department of Education, 2019). Since this action research examined
the impact of transiency on school improvement, these six indicators were examined in
each of the three analyses as part of this project.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
59
These indicators are as follows (the six federal accountability school improvement
indicators examined in the project identified with an *):
•
Percent Proficient or Advanced on Pennsylvania State Assessments*
•
Meeting Annual Growth Expectations*
•
Percent Advanced on Pennsylvania State Assessments
•
English Language Growth and Attainment*
•
Regular Attendance*
•
Grade 3 ELA and Grade 7 Math Early Indicators of Performance
•
Career Standards Benchmark*
•
High School Graduation Rate*
•
Industry-Based Learning
•
Rigorous Courses of Study
•
Post-Secondary Transition to School, Military, or Work
Descriptions of the six indicators examined.
Achievement.
This indicator represents the percentage of students who scored proficient or
advanced on a state assessment. The Pennsylvania System of School Assessment (PSSA)
exam is administered to students in grades three through eight for mathematics and
English language arts, and grades four and eight for science. Additionally, students are
administered tests in Algebra, Biology, and Literature in high school, but this action
research study examined state assessments in grades three through eight only, as
reporting at the high school is more complex and obtaining the high school assessment
data in a format that would allow for validity may prove challenging. These state
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
60
assessments rank students in four proficiency levels – below basic, basic, proficient, and
advanced. Two groups of students do not factor into state calculations: students enrolled
after October 1, and first year English language learners. As the Future Ready PA Index
reports achievement at a subject specific, building wide level, sample groups will be
defined by building, separated by content area.
Growth.
This indicator represents how a given group of students has grown from an
academic standpoint relative to their entering achievement. The same attribution rules
that are applied to achievement are also applied to growth. As the Future Ready PA
Index reports growth at a subject-specific, building-wide level, sample groups will be
defined by building, separated by content area.
Attendance Rate.
Attendance is defined as the percentage of students enrolled in a school for 90
school days or more, who are present for 90% or more of the days. This measure is a
lagging indicator. A lagging indicator is one that is the value from not the school year of
interest but the year before that. (The reason for this is that the complete data set that
comprises some indicators, such as attendance, cannot be fully collected by state for a
considerable length of time after the school year ends.) As the Future Ready PA Index
reports attendance at a building-wide level, sample groups will be defined by building.
Graduation Rate.
This represents the percentage of students who graduated from a school in a fouryear cohort. This measurement is also a lagging indicator. While eight schools
participated in this project, only one of these schools was a high school; therefore the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
61
researcher did not examine graduation rate as an n-count of one would not provide
statistical significance.
Career Readiness Benchmark.
This represents the percent of students who have satisfied requirements related to
career education as mandated by the state. This is reported by grade span, with reporting
occurring at the end of grade 5, grade 8, and grade 11. Accordingly, sample groups will
be aggregated based on these reporting rules.
English Language Learner Proficiency.
This indicator provides a measure of English learner growth and attainment of
English language proficiency. This is evaluated through the use of a state-mandated
assessment known as ACCESS for ELLs. This indicator is only reported for schools that
have a minimum student group of 20 English learners; none of the schools participating
in this project met this requirement, thus the researcher omitted this indicator from the
correlation analysis.
Definition of transient.
As examined in the review of the literature, there is little common language for
both measuring and defining mobility. It has been found in previous research that the
recency of mobility matters. The more recent the move to a new school, the greater it’s
possible effect on student achievement and assimilation (Green & Daughtry, 1961). In
the first year in which a student moves to a different school, progress on learning
experiences the most severe loss. This negative impact on achievement continues at a
lesser rate in subsequent years. During this initial transition year, transient students also
encounter the most difficulty with settling into a new culture and making social
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
62
connections. Additionally, the Current Population Survey Annual Social and Economic
Supplement (CPS-ASEC), posted on the census.gov website, shows a mobility rate for
2017-2018 of 8% in the northeast United States and defines mobility as those who have
moved ‘within the past twelve months’(“Geographical Mobility”, 2018). For these
reasons, for the purpose of this action research, transient students will be defined as
students who have not been continuously enrolled in the same school for 12 months.
School improvement identification.
In a process termed annual meaningful differentiation by federal statute, states
must designate schools, at least every three years, into three designations:
•
Comprehensive Support and Improvement (CSI): Schools facing
significant challenges in achievement, growth, and any of the other four
areas highlighted above
•
Additional Targeted Support and Improvement (A-TSI): schools
experiencing poor performance by one or more student groups belong a
specified threshold
•
Targeted Support and Improvement (TSI): schools experiencing poor
performance by one or more student groups in danger of approaching a
specified threshold
Schools are identified for one of the levels of school improvement if they have
both low achievement scores and low growth profiles (below statewide minimum values)
and poor performance on additional ESSA-required indicators. If mobility impacts
student achievement and growth as well as graduation rates, can a high mobility rate lead
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
63
to a school improvement designation? With this key background developed and defined,
collection of the data began.
Collecting the sample data.
The first step in this process was to collect the data that would be examined. This
study examined student accountability data from eight Pennsylvania schools. Four of
these schools are elementary buildings with a K-4 configuration. The economically
disadvantaged rate at the schools ranges from a low of 40% through a high of 68%. One
school is a K-6 building configuration with a 74% economically disadvantaged rate. Two
schools are middle schools, one 5-6 building and one 7-8 building, with economically
disadvantaged rates of 53% and 60% respectively. The eighth building examined in this
study is a high school with an economically disadvantaged rate of 47%. With the
exception of the 7-8 and high school buildings, all of the other buildings have been
federally-designated as Title I.
Once permission to participate was obtained from superintendents of districts
involved in this study, the researcher identified the state mandated uniform data file
submissions that factor into state accountability indicators. Each district’s data manager
exported the requested files from the district’s student information management system,
removing student names as an added layer of confidentiality. These files were shared
with the researcher. In addition, the district data managers also provided a file containing
student enrollment information from June 1, 2016 through May 31, 2019. This
information was used to flag transient students in the accountability files. With these
files in hand, the next step was to determine which students in these files are factored into
(attributed) to school accountability values.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
64
Identifying attributed students and triangulating data.
Upon receipt of the accountability files, the next step in the process was to
identify which students in the files are attributed to the schools. This was necessary
because there are some students who may be enrolled in school, but due to
Pennsylvania’s school accountability attribution business rules, the students do not factor
into calculations. For achievement and growth, the district accountability file was filtered,
removing students who were not attributed to any district school. Additionally, first year
English language learners, as well as those students enrolled after October 1, were
removed. In order to confirm the accuracy of the filtering and to ensure the triangulation
of data, proficiency rates were calculated for each school and compared to those
published on the Future Ready PA Index website.
For career readiness benchmarks, the exported file contains all students to be
attributed, and thus, no additional filtering of exempt students was necessary. Care only
had to be taken to filter for each school and create separate groups as such. The file
necessary for calculating attendance contains all student attendance data including those
who attended for only a partial year. The researcher had to apply the business rules of
selecting only those students who attended for 90 or more days. Finally, the file necessary
for calculating graduation rate required students attributed to other schools to be filtered
from it. As with the attendance and growth files, these files were triangulated to ensure
that the starting indicator values matched those on the Future Ready PA Index website.
Now that the researcher identified which students ‘count’ towards accountability, the next
step was to determine which of those students could be considered transient.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
65
Identifying and flagging transient students.
After the data from the accountability files was filtered for accuracy in matching
the state report and values, the next step was to identify and flag transient students in the
file. For the purpose of this action research project, transient students are defined as
those students who have not been continuously enrolled for at least one year prior to the
start of a given school year. This project focused on school accountability indicators from
the 2018-2019 school year, with attendance and graduation being lagging indicators,
reporting from the 2017-2018 school year. As such, it was necessary to obtain enrollment
information from June 1, 2016 through May 31, 2019. Once the accountability files were
filtered for attributed students and accuracy checked, transient students could be flagged
in the files.
In flagging students in the achievement, growth and career readiness files, the
researcher identified students who enrolled on or after August 24, 2017. These students
would be flagged in the files. The PAsecureIDs of transient students were pasted into
each accountability file, and a conditional highlighting rule was applied which helped to
quickly identify transient students in the file. A column was added to denote this
attribute. The same process took place for the attendance and graduation accountability
files; however, as these two indicators are lagging, students who are enrolled on or after
August 24, 2016 were defined as transient. Once transient students were identified, this
allowed for transiency rates to be calculated for each group for each indicator.
Calculating the rate of transiency in each group for each indicator.
As each accountability indicator has its own attribution rules, and the exports
from student information management systems are specific to the report, there is
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
66
variation between transiency rates for a given school for each indicator. A rate of
transiency was calculated for each school for each indicator. The rate was calculated by
comparing the number of transient students in a group to the total number of students in
the group. The transiency rate was defined by the percentage of transient students in the
group. This was used in two ways. The first was to identify if a school had a transiency
rate higher than the 8% national average. If so, the school was assigned an adjusted
cohort controlled to 8%. The other key aspect in identifying the transiency rate is for use
in the correlation analysis that follows.
Creating stable and adjusted groups.
The data in the original files obtained from participating districts contained the
information that resulted in the indicators posted on the Future Ready PA Index website,
and this included all stable and mobile students. As this action research project examined
whether the inclusion of mobile students impacts the indicator values, it was important to
create two separate groups for each school and indicator. These two groups would be
compared in the analysis to determine the impact that the addition of transient students
has on a school’s accountability values. The first additional group set was defined as
only stable students, and did not include any mobile students. This was pertinent as it
provided an overall indicator value for a group if it did not include any transient students.
For schools and indicators that had a mobility rate higher than 8%, an adjusted group was
created as well. This adjusted group was important as it was used to examine whether or
not a school’s accountability values are lower when the percentage of mobile students is
higher than average.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
67
The process for creating the adjusted group began with removing the transient
students from the file. Random numbers were then assigned to this list of transient
students, and a random number generator was used to select students to add back to the
file. Students were randomly selected and added back to the accountability file until the
transiency rate for the group was calculated at 8%. This became the adjusted group.
These three sets of sampling groups – all, stable, and adjusted – were then analyzed for
correlation.
Bivariate measures of correlation.
This study sought to examine the effect of transiency on achievement indicators
and focused on exploring the correlation between two different sets of variables: the
relationship between transiency and change in indicator value, and the relationship
between transiency and the actual value. Bivariate analysis was selected as a means of
answering the problem statement, as this analysis provides an effective method to show
whether or not there is any association between transiency and accountability indicators.
Bivariate correlation analysis is one that examines the relationship between two different
variables. The analysis produces a value that represents the relationship between a
change in A when there is a change in B. For example, a bivariate analysis could be
used to examine the percentage of electric vehicles in a community compared to the
number of charging stations; it might also be used to examine the relationship between
the number of web browser ads displayed for face masks and the number of online mask
purchases. In the case of this action research project, the researcher was examining the
relationship between two variables: the rate of transiency and each of the indicator
values. Bivariate analysis is an effective way to solve this problem, as it shows the
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
68
researcher the relationship between transiency and indicator values. If the levels of
transiency are known, it might be easier to predict the indicator value. Data analyses
results that show a strong correlation between transiency rates and school accountability
indicators will provide an answer to the researcher’s problem examining whether high
transiency rates affect school improvement designation.
Pearson correlation.
A bivariate correlation analysis produces a Pearson correlation coefficient that can
be used to identify the strength of a relationship. Additionally, this analysis also
identifies whether there is statistical significance with the relationship. One important
limitation of this analysis to note is that a bivariate Pearson correlation does not identify
causation, but rather correlation or association between sets of variables.
A bivariate Pearson correlation begins with a null hypothesis H0 that assumes a
true correlation value p0 of 0. An alternative hypothesis HA represents the actual
correlation as p1, with an assumed value not equal to 0. This can be represented as:
If H0 holds a p0 of 0, no correlation exists;
If HA holds a p0 not equal to 0, some correlation exists
This analysis examines what, if any, correlation exists supporting an HA with a p0 not
equal to 0. The correlation coefficient of the sample is identified as r, and is calculated
(using the SPSS software) as:
rab =
cov(a,b)
var(a) • var(b)
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
69
with (a,b) representing the variables in consideration, cov(a,b) is the covariance between
a and b, and var(a) and var(b) representing the sample variance of a and b, respectively.
Adhering to Cohen (1988), the strength of the correlation is defined by:
strong correlation
|r|>.5
moderate correlation .3<|r|<.5
weak correlation
.1<|r|<.3
As Pearson Correlation values can be positive or negative, absolute values are used in
considering strength of relationship. The value in the use of a Pearson Correlation
analysis in this project is that its results will show the strength of the relationship between
the rate of student transiency and the school accountability values. A challenge in
conducting a Pearson Correlation analysis is the mathematical computations necessary;
using software that automates the process, including reporting, mitigates this challenge.
SPSS software.
Conducting multiple correlation analyses by hand can be very time-consuming,
and thus, a commercial software package was utilized for this purpose. This software
allows the researcher to more easily input data from the school accountability files, and
quickly view automated correlation analysis results. Statistical Package for Social
Sciences (SPSS) is a software package published by IBM that allows complex statistical
data analysis. This software is one of the leading data analysis tools used by social
scientists, researchers, educators, and many others in higher education. It offers a
familiar interface for inputting data, and powerful tools for conducting regression and
correlation analysis, as well as producing visualizations. SPSS was used in this study’s
correlation analysis. The software provided the researcher with a statistical correlation
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
70
between each experimental group and each of the accountability indicators. This was then
used by the researcher to identify whether or not a significant correlation existed, as well
as to prepare recommendations for future action and research. With accountability files
obtained, attributed and transient student identified, and transiency rates calculated, the
correlation analyses could begin.
Examining change in school indicators caused by transiency rate.
Is there a significant relationship between a school’s rate of student mobility and
its school accountability indicators? Can a correlation be made between the percentage
of transient students in a school group’s student composition and the impact that
subgroup has on the schools indicator value? In order to address this, a correlation
analysis was conducted examining the relationship between change in indicator value at
each school when comparing the all-student group with the stable-only student group. In
other words, can a connection be made between how many transient students are in a
school population and how this affects its indictor value? The researcher was looking for
how significant of an impact that transiency rate has on a school accountability values
(and thus, on its ‘effectiveness’, as reported on the Future Ready PA Index). The
following analyses were conducted using the bivariate correlation analysis tool in SPSS:
•
Change in Math Growth Indicator vs. Transiency Rate
•
Change in Attendance Indicator vs. Transiency Rate
•
Change in ELA Achievement Indicator vs. Transiency Rate
•
Change in Math Achievement Indicator vs. Transiency Rate
•
Change in Career Readiness Indicator vs. Transiency Rate
•
Change in ELA Growth Indicator vs. Transiency Rate
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
71
Examining relationship between levels of transiency and reported indicators.
How do schools fare in Pennsylvania’s school accountability system when
controlling for levels of mobility? If a school with a higher than average level of transient
students had a level of student mobility as low as the national average, would its
accountability indicator values be higher? Can one infer that when a school has a higher
level of student transiency, its school accountability values will be correspondingly lower
and thus, the school would be more susceptible to school improvement designation? In
order to address this, two different correlation analyses were conducted. The first
analysis examined the relationship between indicator value when comparing the stableonly student group at each school and an adjusted group controlled for the national
average of 8% mobility. The analyses conducted using the bivariate correlation analysis
tool in SPSS were:
•
Career Readiness Indicator for all-student group vs. adjusted group
•
Math Achievement Indicator for all-student group vs. adjusted group
•
ELA Achievement Indicator for all-student group vs. adjusted group
The second analyses examined the percent of transient students in a school group
compared to its value reported on the Future Ready PA Index website. The following
analyses were conducted using the bivariate correlation analysis tool in SPSS:
•
Attendance Indicator vs. Transiency Rate
•
ELA Achievement Indicator vs. Transiency Rate
•
Math Achievement Indicator vs. Transiency Rate
•
Math Growth Indicator vs. Transiency Rate
•
Career Readiness Indicator vs. Transiency Rate
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
•
72
ELA Growth Indicator vs. Transiency Rate
The following section of this chapter will discuss the results of these analyses.
Results
Research question one - findings.
Is there a significant relationship between a school’s rate of student mobility and its
school accountability indicators? Table 1 displays the results of the analyses that were
conducted. For each set of variables examined, the correlation coefficient between the
variables as well as the significance of the relationship is displayed.
The key point to note in this table is the ‘Strength of Relationship’ column. Of
the six analyses conducted, it was found that four of the six show a strong relationship
between the rate of transiency and the change indicator value at that school; the
remaining two show a moderate relationship. This means that yes, there exists a
significant relationship between the rate of student mobility and indicator values.
Table 1
Bivariate correlation results between transiency rate and change in examined indicators
for each school.
Analysis
Change in Math Growth
Indicator vs. Transiency Rate
Change in Attendance
Indicator vs. Transiency Rate
Change in ELA Achievement
Indicator vs. Transiency Rate
Change in Math Achievement
Indicator vs. Transiency Rate
Change in Career Readiness
Indicator vs. Transiency Rate
Change in ELA Growth
Indicator vs. Transiency Rate
Pearson
Correlation (r)
-.982
Strength of
Relationship
Strong
Statistical
Significance(p)
.018
-.961
Strong
.002
-.635
Strong
.126
-.630
Strong
.130
-.450
Moderate
.703
-.356
Moderate
.557
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
73
Career readiness benchmarks.
Career readiness benchmarks are reported as the percentage of students who, by
the end of grades five, eight, and 11, have completed a mandated number of career
readiness artifacts. As seen in Table 1, a moderate correlation of -.450 was found
between the rate of transiency and the change in career readiness benchmark value. This
demonstrated that an increased rate of transiency results in a decreased career readiness
indicator value.
Attendance.
Attendance is defined as the percentage of students enrolled in a school for 90 or
more school days who were present for 90% or more of those school days. As seen in
Table 1, a strong correlation of -.961 with a statistical significance of .002 was found
between the rate of transiency and the change in attendance value. This demonstrated
strong evidence that an increased rate of transiency results in a decreased attendance
indicator value.
Math growth.
Academic growth in math will be defined using Pennsylvania’s PVAAS model of
growth, which examines the entering achievement for a group of students compared to
the exiting achievement of the same group of students. It will be calculated by creating
custom reports populated with the students in each examined goup. As seen in Table 1, a
strong correlation of -.982 with a statistical significance of .018 was found between the
rate of transiency and the math growth value. This demonstrated strong evidence that an
increased rate of transiency results in a decreased math growth indicator value.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
ELA growth.
Academic growth in ELA is defined in the same manner. As seen in Table 1, a
small correlation of -.356 was found between transiency rate and ELA growth value.
This demonstrated only small evidence that an increased rate of transiency results in a
decreased ELA growth indicator value.
Math achievement.
Achievement in math will be defined as the percentage of students who scored
proficient or advanced on the current year’s math state assessments (PSSA or Keystone
Exam). As seen in Table 1, a large correlation of -.630 was found between the rate of
transiency and the math achievement levels. This demonstrated strong evidence that an
increased rate of transiency results in a decreased math achievement indicator value.
ELA achievement.
Achievement in ELA will be defined in the same manner. As seen in Table 1, a
strong correlation of -.635 was found between the rate of transiency and the ELA
achievement levels. This demonstrated strong evidence that an increased rate of
transiency results in a decreased ELA achievement indicator value.
Graduation and EL proficiency.
English learner proficiency indicators were omitted from this analysis because
there was not an n-count to be reported on the Future Ready PA Index. The graduation
indicator was omitted as there was only one participating high school in this action
research project.
74
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
75
Research question two – findings.
How do you schools fare in Pennsylvania’s state school accountability system
when controlling for transiency? Table 2 displays the results of the analyses that were
conducted. For each set of variables examined, the correlation coefficient between the
variables as well as the significance of the relationship is displayed.
The key point to note in this table is the ‘Strength of Relationship’ column. Of
the three analyses conducted, it was found that all show a strong relationship between the
school indicator value for the all-student group and the group adjusted to 8%; this means
that decreasing the rate of transiency for each school does had a direct impact on all
values examined, increasing the school indicator values.
Table 2
Bivariate correlation results between cohorts adjusted to 8% transiency rate and change
in indicator value examined for each school.
Analysis
Career Readiness
Indicator vs. 8%
Transiency Rate
Math Achievement
Indicator vs. 8%
Transiency Rate
ELA Achievement
Indicator vs. 8%
Transiency Rate
Pearson Correlation
(r)
1
Strength of
Relationship
Strong
Statistical
Significance (p)
.000
1
Strong
.000
1
Strong
.000
How does transiency affect the indicators that factor into school improvement
designations? In order to examine the last research question, a correlation analysis
between transiency rate and absolute values of indicators was conducted. Table 3
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
76
displays the results from this analysis. For each set of variables examined, the correlation
coefficient between the variables as well as the significance of the relationship is
displayed.
The key point to note in this table is the ‘Strength of Relationship’ column. Of
the six analyses conducted, it was found that three of the six show a strong relationship
between the rate and transiency and the indicator value at that school; one of the
remaining three shows a moderate relationship. This means that an increased rate of
transiency in a school could have a negative impact on four of the six values examined as
reported on the Future Ready PA Index. If increased transiency rates lead to decreased
accountability values, this makes school with high mobility rates more susceptible to
being designated for school improvement.
Table 3
Bivariate correlation results between transiency rate for each school and the absolute
(reported) values of each indicator for that respective school
Analysis
Attendance Indicator
vs. Transiency Rate
ELA Achievement
Indicator vs.
Transiency Rate
Math Achievement
Indicator vs.
Transiency Rate
Math Growth
Indicator vs.
Transiency Rate
Career Readiness
Indicator vs.
Transiency Rate
ELA Growth Indicator
vs. Transiency Rate
Pearson Correlation
(r)
-.920
Strength of
Relationship
Strong
Statistical
Significance (p)
.009
-.779
Strong
.221
-.639
Strong
.361
-.414
Moderate
.586
-.270
Weak
.826
-.204
Weak
.742
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
77
Career readiness benchmarks.
As seen in Table 3, a small correlation of -.270 was found between the rate of
transiency and the absolute value of career readiness benchmarks. This demonstrated
only small evidence that an increased rate of transiency results in a decreased career
readiness indicator value, which could lead to greater likelihood of school improvement
designation.
Attendance.
As seen in Table 3, a large correlation of -.920 with a statistical significance of
.009 was found between the rate of transiency and the absolute value of attendance rate.
This demonstrated strong evidence that an increased rate of transiency results in a
decreased attendance indicator value, which could lead to greater likelihood of school
improvement designation.
Math growth.
As seen in Table 3, a moderate correlation of -.414 was found between the rate of
transiency and the absolute value of math growth. This demonstrated evidence that an
increased rate of transiency results in a decreased math growth indicator value, which
could lead to greater likelihood of school improvement designation.
ELA growth.
As seen in Table 3, a small correlation of -.204 was found between the rate of
transiency and the absolute value of ELA growth. This demonstrated only small
evidence that an increased rate of transiency results in a decreased ELA growth indicator
value, which could lead to greater likelihood of school improvement designation.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
78
Math achievement.
As seen in Table 3, a large correlation of -.639 was found between the rate of
transiency and the absolute value of math achievement. This demonstrated strong
evidence that an increased rate of transiency results in a decreased math achievement
indicator value, which could lead to greater likelihood of school improvement
designation.
ELA achievement.
As seen in Table 3, a large correlation of -.779 was found between the rate of
transiency and the absolute value of ELA achievement. This demonstrated strong
evidence that an increased rate of transiency results in a decreased ELA achievement
indicator value, which could lead to greater likelihood of school improvement
designation.
Graduation and EL proficiency.
English learner proficiency indicators were omitted from this analysis because
there was not an n-count to be reported on the Future Ready PA Index. The graduation
indicator was omitted as there was only one participating high school in this action
research project.
Discussion
This action research project examined two questions: is there a significant
relationship between a school’s rate of transiency and its accountability indictor? How to
schools fare in Pennsylvania’s school accountability system when controlling for
transiency? An interpretation of the analyses results will be discussed in the next section.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
79
Findings on the relationship between rate of transiency and indicator value.
Is there a significant relationship between a school’s rate of transiency and its
accountability indicator? It was assumed that there would be a strong relationship
between the percentage of transient students in a school population and its accountability
values. This was supported by the results of the project. Four of the six indicators
examined showed a strong relationship between the rate of transiency and the change
indicator value for the schools; the remaining two show a moderate relationship. This
provides statistical evidence that there is a significant relationship between the rate of
student mobility and each of the indicator values examined. The indicators with the
strongest relationship to rate of transiency were found to be math growth and attendance,
followed by ELA achievement and math achievement. ELA growth and career readiness
showed a moderate relationship.
There are implications of these results at several levels. At a school level, this is
important because it provides evidence of the need for support of mobile students, in all
of the six areas examined. At a student level, what interventions are in place to assist the
students? What supports do schools have in place to ensure that the unique needs of the
students are met? At a state level, this is important because it supports an existing body of
work relating to the challenges faced by students who move between districts. As the
state is committed to equity for all students, this often-marginalized group should be
provided with statewide assistance. The state is investing millions of dollars over the
next few years in school improvement efforts, and this supports the researcher’s belief
that research-based supports that address the challenge of student mobility be provided.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
80
Findings on the impact of transiency on school improvement indicators.
How do you schools fare in Pennsylvania’s school accountability system when
controlling for transiency? It was assumed that an increased percentage of mobile
students would lead to decreased school accountability indicators, and this in turn would
lead to a greater likelihood of school improvement designation for schools which
experience a high level of student mobility. The bivariate Pearson Correlation analysis of
the impact of transiency rate on the values of school accountability indicators found a
strong correlation for its impact on math and ELA achievement, as well as in attendance.
A moderate correlation was found to math growth; a small correlation was found for both
ELA growth and career readiness benchmark values. As a result, schools with a higher
level of transiency will likely experience accountability indicator numbers that are lower,
and it is reasonable to infer that these schools will more likely be identified for school
improvement. The results of this project showed that for schools with a greater than
average level of transiency, when this rate was reduced to the national average, their
school accountability values increased. This would make them less likely to be identified
for school improvement designation.
This is important for schools as a school improvement designation carries a
negative stigma. No school wants to be identified for school improvement. The results of
this research will inform not only the participant schools, but schools across the
Commonwealth that their levels of transient students do impact their accountability
scores; there is a significant correlation between the percentage of transient students and
the change in their value. In other words, the more transient students they have, the lower
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
81
their values will likely be. This in turn will make them more susceptible to being
identified for school improvement. Recommendations based on this will be provided in
the next chapter. This is also important for the state as it identifies a potential flaw in its
school improvement designation system. As mentioned earlier in this paper,
Pennsylvania’s accountability system does have some measures in place to ensure that
students with a short tenure at a school are not included for identification purposes, but
the research shows that these business rules do not consider all of the transient students.
Just as Pennsylvania recently passed legislation which will factor the poverty rate of a
school district into teacher and school leader evaluations, the state may wish to consider
factoring transiency rates into the process as well. Additionally, Pennsylvania is
investing significant money over the next few years in school improvement efforts, and
the research suggests that one subgroup of students not currently the subject of focused
effort – mobile students – could benefit from research-based supports.
Findings interpreted by indicator.
While each of the schools may experience variation among transient population,
stable student body, staffing and leadership, and other external factors, commonality was
found in the impact of mobile students on each building’s school accountability indicator
value.
Attendance.
The outcome of the analysis for attendance showed a large correlation, with high
statistical significance, between attendance values and transiency rates. This corresponds
with what can be found in a review of existing literature. Arriving at a new school,
students can feel frustrated in their current academic levels compared to those of their
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
82
peers, and this sometimes results in greater absenteeism. Parke and Kanyongo (2012)
found that student mobility has a profound impact on attendance, even greater than on
achievement. What this means in terms of the research problem is that when a school has
a high level of transient students, its attendance indicator value will likely be decreased,
and this makes it more likely that the school could be designated for school improvement.
Mathematics growth.
The results also showed large and moderate correlations between rates and
mathematics growth. The meaning of this in relation to the research problem is that
increased levels of student mobility result is a decrease in math growth values, and since
these values factor into school improvement designation, make the school more
susceptible to school improvement designation. This is likely due to the impact of lost
instruction or content not mastered. Growth calculations consider past academic
performance and predict or project where students are expected to score on the next
assessment, but they do not take into account a student’s history of mobility. This is
consistent with decades of research that show a detrimental effect of mobility on student
success in school. When mobile students are removed from a value-added growth
analysis, school scores increase (Williams, 2003). Without a business rule of removing
the scores of mobile students, the math growth indicators were negatively impacted.
ELA growth.
Interestingly, in contrast to math growth, the results of the correlation studies
showed only a small relationship between transiency and growth in English language
arts. What this means in terms of the research problem is that when a school has a high
level of transient students, there is only small evidence that its ELA growth indicator
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value will likely be decreased, which results in only a small effect on whether the school
could be designated for school improvement. The reason for this disparity between
content areas is not apparent in the results. The researcher speculates that it could be due
to the fact that mathematics is a more discrete subject and English language arts skills
extend across multiple curricular areas, the impact of missed instruction is greater in
mathematics. PA Core Standards for mathematics have a great variety of discrete topics
in each grade level, and the mastery of each is crucial for success in vertical progression
(K-12) through the subject area. Specific eligible content in a math course might be
addressed for two weeks in one grade, and not revisited until over an entire year later. If
as a result of a recent transition, a student fails to master eligible content in a specific
reporting category, or even worse, is not exposed to that content, an entire school year
might pass until the student has the opportunity to develop that content again. State core
standards for ELA represent an integrated model of literacy, one in which components
are closely connected (Common Core Standards Initiative, 2020). Skills are introduced
and embedded throughout a typical ELA curriculum, which allows for more opportunities
for students to interact with content. This more integrated design, with its more multiple
opportunities to revisit and refine skills, may explain why students tend to score closer to
their projected scores in ELA than in mathematics.
Math achievement.
The results of the study show a strong correlation between transiency and
mathematics achievement scores in all analyses. Across the board, mathematics
achievement scores were lower when the transiency rate was higher. The meaning of this
in relation to the research problem is that increased levels of student mobility result is a
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decrease in math achievement values, and since these values factor into school
improvement designation, make the school more susceptible to school improvement
designation. This aligns to the decades of research that show the detrimental impact of
transiency on student success in school. Shoho (2010) found a similar correlation in a
similar study examining Texas state math assessments. As curricula vary widely from
one district to another, this places transient students at a significant disadvantage when
they arrive at a new school, because they have not progressed through that particular
district’s vertically- and horizontally-aligned curricula.
ELA achievement.
The action research project results also demonstrated a large correlation between
transiency rate and ELA achievement values. What this means in terms of the research
problem is that when a school has a high level of transient students, its ELA achievement
indicator value will likely be decreased, and this makes it more likely that the school
could be designated for school improvement. A considerable body of research supports
this finding. A study of a New Jersey state exam found that student transiency negatively
impacted student scores in reading (Krenicki, 1999). California students experiencing
several moves, when administered the California achievement test in reading,
demonstrated reading scores that were 50% lower (The Family Housing Fund, 1998).
Career readiness benchmarks.
Finally, the results of the study showed only a moderate correlation between
transiency rate and its impact on school indicator, and small correlation between the rate
and absolute value. The meaning of this in relation to the research problem is that
increased levels of student mobility only moderately impact this indicator, which
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demonstrates that it could have some impact on school improvement identification. Of
all in-school indicators examined, this is the one that schools can most readily help
students to accomplish, possibly due to the fact that career readiness work is exploratory
in nature and less dependent on mastery of a sequence of academic skills. Unlike the
sequential nature of math and ELA content, career and work standards are more universal
and subject to personal choice and teacher acceptance. Even if a transient student has
experienced gaps in academic learning in the past, or may be at a lower academic level
compared to his peers in the current school, helping the student provide evidence of
career awareness would likely be on affected by this. Helping students show evidence of
career awareness and preparation requires a less-intense level of effort than academic
content.
Summary
This chapter highlighted the results of the correlation analysis, linking the
research questions to the evidence that was found. The school accountability data for
eight schools was obtained and examined in an effort to understand the impact of student
mobility on school accountability indicators.
A bivariate Pearson correlation analysis was conducted, seeking to determine a
relationship between three sets of considerations: (a) transiency rate and change in
school indicator values, (b) school absolute values and values adjusted to 8% transiency,
and (c) transiency rates and absolute school values. Based on the strength of relationship
found between the rate of transiency and how that affected the indicator at the school, this
means that the addition of transient students to a group has a negative impact on
accountability values. Transiency rates had a statistically strong connection to math
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growth, attendance, ELA achievement, and math achievement. These rates had a
statistically moderate connection to career readiness and ELA growth.
The data analysis also found that when controlling the number of transient
students in a score to the national average of 8%, this had a direct impact on all
indicators, increasing their value, which demonstrated that the more transient students in
a group, the lower their accountability values. If increased transiency rates lead to
decreased accountability values, this makes schools with high mobility rates more
susceptible to being designated for school improvement. In summary, one research
question asked is there a significant relationship between student mobility and a schools
accountability indicators. The answer is yes; higher levels of transient students lead to
lower accountability values. The second question asked about the impact this might have
on school improvement designation. The answer is it could have a direct and negative
impact on this, as the resulting lower values put the score at greater risk for school
improvement status. Chapter 5 provides a critical analysis of the results, implications all
these results at a local and state level, and recommendations for further research.
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CHAPTER 5
Conclusions & Recommendations
This chapter provides a discussion of the findings to help answer the following
research questions: Is there a significant relationship between student mobility and a
school’s accountability indicators? How do schools fare in Pennsylvania’s school
accountability system when controlling for levels of student mobility?
This action research project was a study based on quantitative grounded theory.
The purpose of the project was to examine the role of student mobility on Pennsylvania’s
school accountability framework. This final chapter provides a discussion of the major
findings as they relate to impact on students and schools, the theoretical foundations
impacting student mobility, its impact on achievement and measures of success, and
practice and policy. The chapter also includes a discussion of fiscal implications, as well
as implications for theory and research, and practice. Recommendations for future
research will also be provided. The chapter concludes with future plans for work in the
researcher’s field informed by the findings.
Prior to embarking on this project, the researcher predicted that an increased
percentage of mobile students would negatively impact school accountability indicators.
The analysis indicated a strong correlation between transiency rate and achievement
scores and attendance. The theory that the addition of transient students to a school’s
population would impact school accountability indicators was supported by findings that
demonstrate a large correlation between transiency rates and math achievement scores,
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ELA achievement scores, math growth values, and attendance. This has significant
implications for the researcher as applied to his profession; further action related to the
findings will be addressed later in this chapter.
Conclusions
This section of the final chapter will discuss the effectiveness of the research, its
applicability and replicability, and the implications of the research.
Effectiveness.
When reflecting on the results of action research, it is important to consider both
the efficacy and the effectiveness of the project. Efficacy considers whether the project
worked in the experimental setting as designed. Effectiveness considers whether the
project will work in a real world setting.
When considering efficacy, it appears that the design of the project was
successful. The researcher was able to obtain the necessary data files from each school
district, as well as identify the school accountability indicators as defined by the state.
Using the data provided, and adhering to student confidentiality by using PAsecureIDs,
the researcher was also able to identify and isolate transient students in each population
group. The selected SPSS analyses were able to provide correlation data that could be
successfully used to either support or reject the hypotheses.
When considering effectiveness, one must consider the applicability of the
research design in a broader spectrum. Could the project be applied statewide in all
schools? Yes. This research would provide results with confidence due to the consistent
methods of data collection, reporting, and analysis at the school and state levels.
Pennsylvania requires every school district to collect consistent data in a statewide
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system in which every school district reports accountability information following a
defined set of standards. The implication of this is that a researcher could obtain the
necessary files from every school district in the state without exception. Additionally,
given that the information obtained would be in a consistent format from every school
district, conducting the analyses with a greater n-group would also be possible. Just as the
researcher was able to complete a bivariate correlation analysis comparing data from
eight schools, the same analysis could be completed comparing data from 2000 schools.
Another factor supporting the effectiveness of this research is the fact that school
accountability indicators values are compiled and reported following a standard protocol,
and reported on the state website. These accountability indicators are reported for every
school district in Pennsylvania, with only a few exceptions.
Application to researcher’s institutional setting.
The researcher’s intent related to action and communication based on the results
of this project was impacted by the COVID-19 crisis of 2020. The results of this study
would have been discussed at great length with district leaders of participating schools in
spring 2020. The results also would have been shared at a statewide level, for action and
discussion at the same time. In March 2020, the priority at both the district level and the
state level shifted to a very narrow focus on support of continuity of education; with that
said, discussions not directly impacting continuity of education or the reopening of
schools were sidelined.
The researcher has already briefly shared the results with the district leaders. Due
to a shift in focus in schools, a more comprehensive review of the results has been
delayed. At a later time, when planning for the reopening of schools subsides, the
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researcher will meet with leaders from each participating school to share the results. He
plans to engage the stakeholders in discussions involving the findings and
recommendations put forth in this paper.
As for application at a state level, the COVID-19 crisis has also sidelined many
discussions. Several planned school improvement protocol and policy meetings have
been canceled due to shifting priorities. It is the researcher’s intent to engage school
improvement leadership and statewide policy- and decision-makers in the findings and
recommendations learned as a result of this project.
On a personal level, the researcher has shared these findings with numerous
colleagues and peers in districts. Although the strong relationship between rates of
transiency and school accountability indicators have long been assumed by some in the
field, this project provides statistical evidence. Since completing the project, the
researcher has shared these findings and suggested policy change in multiple initiatives in
which he is involved, and he plans to intensify these efforts in the future.
Specific findings and interventions to be shared with participant schools.
•
In the analysis which included your school’s information, there was a strong
statistical correlation found between rate of transiency and accountability indicator
values. This means that the more transient student you have, the more likely you will
have lower indicator values.
•
Drawing off of this relationship, the lower your accountability indicators are, the
more likely you will be designated or re-designated for school improvement status.
•
The result of this project will provide you with statistical evidence that you might use
to embark on an effort to provide a more supportive environment for transient
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students, which would also reduce the chances that you will fall into school
improvement status.
•
The use of an action planning template created by the researcher as a result of this
project will be recommended. Appendix C displays the LEA Action Planning
Template for Transient Cohorts, based on the Council of Chief State School Officers
(2017) framework for improvement cycle. This framework is used by many states,
including Pennsylvania, to move from a compliance-based focus to an action-based
focus for school improvement.
•
While the procedure for this would vary from one school to another based on their
student information system vendor, the researcher will offer to work with each school
to examine the performance of transient students on additional, non-Future Ready
indicators of performance, such as grades, classroom and diagnostic assessments, and
discipline referrals.
•
Based on the results of this comprehensive examination, the school leaders will be
directed to local and state points of contact for assistance in building capacity based
on the needs that have been identified.
•
Finally, and not limited to participant schools, an additional resource will be shared.
Appendix D displays the Workflow for Comparing Transient Student Performance to
Stable Student Performance. This guide was created by the researcher as a means to
provide school districts with the ability to replicate this in part or in whole.
The following section discusses implications related to the study, and highlights actions
to impact change that the researcher plans to take based on the results.
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Implications.
The findings of this action research project result in numerous implications, both
fiscal implications, as well as policy and practice implications. These implications range
from actions that may be taken by the researcher to actions that must be considered at a
state-level.
Fiscal implications.
As school improvement efforts involve a considerable investment of money, both
at a local level and at the state level, the results of this project have numerous significant
fiscal implications. Decades of school improvement work have targeted low-performing
schools with considerable federal and state money to aid in improving academic
outcomes for students. These implications relate to how money is spent on staffing and
on resources.
Implication 1: Pennsylvania’s School Improvement System – New Positions.
Pennsylvania’s official system for school improvement is structured in alignment
with federal government education legislation. One aspect of the system involves
assigning personnel known as Core Team Members (CTM) to each underperforming
school. There are CTMs who specialize in general school improvement, math, ELA, and
data analysis. These core team members are funded by federal and state school
improvement money. The CTM’s engage in a process of data gathering, plan
development and implementation, and review following a school improvement cycle
designed by the state. Consideration for levels of mobile students and their needs is not
inherently part of this process. One fiscal implication that may result in substantial
positive results for underperforming schools would be shifting funding from existing
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CTM positions to create new core team members specializing in support for mobile
students. With a focus on the needs of not only mobile students, but the needs of their
teachers as well, consultants in this new position may be able to help mobile students
transition better. They may also be able to help schools develop a more substantial
support structure for mobile students, which should lead to better academic outcomes.
Having input into one aspect of school improvement leadership team for the state, the
researcher has already shared findings with several co-leads, and will continue to
advocate for this change within the sphere of his influence in the future.
Implication 2: Research-Based Practices.
Currently, Pennsylvania’s system for school improvement provides funding for
the purchase of research-based practices for school improvement. As this action research
project demonstrated, mobile students experience decreased academic success and
decreased attendance. Funds may be spent on the purchase of research-based products
and services that would improve teacher in-school practice towards mobile students. As
a state co-lead for school improvement as well as diagnostic assessment, the researcher
will apply this learning in the continued development of a research-based practices in
assessment portal.
Implication 3: A Shift in Local Expenditures.
School improvement money is often spent on purchasing new curriculum
packages for use with the whole student body. If transient students are the student
subgroup responsible for decreased accountability scores, then schools may wish to shift
funding from global curriculum packages to interventions and supports for mobile
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students. The researcher will recommend this shift to leadership of the schools who
participated in this project, as well as school leaders across the state.
Implication 4: Personnel.
School districts operate on very finely-tuned budgets, and staffing is often a
challenging task. Classroom teachers often struggle to accommodate the needs of mobile
students, while continuing to push stable students to higher achievement levels. Schools
may wish to shift funding to allow for personnel with an expertise in student transition to
assist buildings and teachers with this challenge. The researcher will use these findings
to recommend staffing changes in support of transient students. These recommendations
will be provided to central administration staff from the schools who participated in the
project.
Implication 5: Replication of this Project for Local Audits.
This project was completed at no cost using readily available data that is
aggregated and reported by every public school building in Pennsylvania. Schools who
wish to audit their success in engaging mobile students are able to replicate this process
at no cost to taxpayers. District leaders who initiated this analysis would demonstrate
fiscal responsibility in the management of district resources.
One means of modifying this project to allow for easier replication would be the
elimination of the statistical analysis using SPSS software. A district might still identify
transient students, flag the students as such in the districts accountability file, then create
modified accountability indicators examining the non-mobile group. While this
replication would not include a correlation analysis, since the results of this action
research already indicate that a correlation exists, the process of replication would help a
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district determine if the same pattern is present locally. The researcher plans to create a
document to be shared locally to help guide districts through replicating this process. Not
only would this provide another value-added service of the intermediate unit, but would
also provide a useful tool for schools to use.
Implications for practice and policy.
There are numerous implications for practice and policy informed by the results
of this action research project. Considerations related to student mobility can be
classified into: systems of accountability, school improvement identification, stakeholder
perceptions, staff practice and attitudes, building-level practice, system-level practice,
and policy.
Implication 6: Systems of Accountability.
In accordance with the Every Student Succeeds Act (ESSA), all states must create
a system for evaluating schools to determine a way for focusing resources on
underperforming schools as well as traditionally underserved students who demonstrate
low academic performance. Pennsylvania’s Future Ready PA Index is designed to
adhere to these federal regulations. There is a protocol in place for determining which
students are attributed to schools and which students are not. This does provide some
safeguards that prevent students who were enrolled for only a short period of time to
factor into school accountability ratings; however, even when considering those
exclusions, the inclusion of some students with a history of mobility into school ratings
does have a detrimental effect on these scores. Pennsylvania (and states with similar
protocols) may wish to revisit attribution roles and consider changes to better account for
student mobility between schools. For example, the state may wish to consider the
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exclusion of students who have not been continuously enrolled for one entire academic
year. While the researcher cannot take definitive action to change this accountability
system, he will share the results with decision-makers who might be able to impact
change.
Implication 7: School Improvement Identification.
Pennsylvania’s system for school improvement is based on a process defined in
federal statutes, known as annual meaningful differentiation. This process involves two
levels of examination. The first level considers building achievement and growth scores.
If a building demonstrates low values in both of these indicators, a second level of
consideration is given to for other factors, which include attendance, graduation, career
readiness benchmarks, and English learner proficiency. This action research project
demonstrated that mobility significantly impacts student achievement and growth as well
as attendance. As a result, as long as mobile students are still attributed to school
buildings in annual meaningful differentiation, then it stands to reason that buildings with
high mobility rates might more frequently be identified as in need of school
improvement. The state may wish to consider rate of student mobility when examining
the six indicators used to determine school improvement designation. The researcher
plans to meet with leaders within the Pennsylvania Department of Education to discuss
the results of this project.
It is important to note that in response to the COVID-19 pandemic of 2020, the
United States Department of Education granted a waiver to the state of Pennsylvania,
waiving it’s a requirement to identify schools in the 2020-2021 school year in one
category of school improvement, and it’s possible that identification in the other category
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as a school improvement might also be waived. This pause on designation provides a
unique opportunity for the state to consider the implications of this research, and conduct
a broader analysis, before reengaging in process several years down the line. This also
provides the participants school districts to consider the results of this project and put into
place structures to support the needs of transient students before the next round of school
improvement identification resumes. It is possible with a comprehensive action plan
informed by this research, a score may be able to avoid designation in the future.
Implication 8: Stakeholder Perceptions.
Many parents place a high value in the accountability ratings published on state
school effectiveness websites. Owens and Peltier (2002) found that 80% of parents place
value on reported school summaries. As there is a strong correlation between student
mobility and many of the indicators put it on the future ready index, it stands to reason
that schools with high mobility rates may be perceived by parents as failing a significant
majority of students, when in reality, the numbers are low in large part due to the
transient population. While the state does publish a page of demographic information for
each school, mobility rates are not defined or identified. Pennsylvania may wish to adopt
a policy of reporting mobility rates by school. The state may even wish to use a visual
reporting, for example a scatterplot, to identify schools who are high-performing despite
their rate of student mobility. Additionally, it is often common practice for the media to
compare values assigned to indicators between schools. Without context, it may appear
that a school with a higher value is a better school, while in reality, one of the schools
may have a higher rate of student transiency. The state may wish to create and release
documents addressing the importance of considering mobility when evaluating a school’s
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accountability indicators. The researcher plans to share the results of this project with
consultants with the Pennsylvania Training and Technical Assistance Network
(PaTTAN), to bolster their current efforts in this realm.
Implication 9: Staff Practice and Attitudes.
The implications of this study’s results on staff practices prove challenging. From
a teacher’s perspective, student mobility can be disruptive. Mobile students require
immediate and ongoing attention. In addition to the need for getting caught up, the
students also need to learn the rules and routines of their new school and classroom.
These tasks put an extra burden on teachers who already have limited time to provide
appropriate instruction for large numbers of students. As the results of this study showed
a significant correlation between student mobility and academic success, teachers may
wish to consider the following actions to help minimize the impact of mobility on both
the transient students themselves, as well as the rest of the class:
•
Reviewing the cumulative records of new students to assess grades, attendance,
and important background information
•
Administering diagnostic intake assessments to identify student academic
strengths and weaknesses
•
Fostering supportive relationships with mobile students and their parents
•
Ensuring that students understand behavior expectations, procedures and routines,
in order to limit behavioral issues
The researcher is responsible for designing and facilitating professional development for
hundreds of teachers in the region. He will continue to share the results of this research in
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an effort to change teacher perceptions related to this challenge. Additionally, this will be
shared with participating districts so they may better inform their own staff.
Implication 10: Building-Level Practices.
School accountability indicators reflect on building administrators. As a
significant percentages of mobile students can negatively impact these values,
administrators may wish to employ several strategies to help mitigate the challenges
posed by transient students:
•
Implement high-quality professional development programs aimed at increasing
teacher awareness of the challenges faced by mobile students
•
Design a formal intake process in which an informal family history and child
academic assessment can take place
•
Conduct personal meetings with new students and their parents
•
Ensure that front desk staff are sensitive to the issues of transient students and
respectful of the challenges they face
The researcher plans to meet with building and central administrators from participating
school districts to share the results and these recommendations.
Implication 11: System-Level Practices.
As transiency tends to affect entire school systems and is not limited at a building
level, there are a number of district-level implications as well. These implications
include:
•
Designing districtwide student mobility awareness programs and building
capacity in all adults who come in contact with children, from bus drivers to
cafeteria aides to teachers
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Providing access to mental health professionals to help assess stressful life events
in the lives of the students
•
Tasking social workers with building assimilation and attendance plans, and
working with parents
•
Instituting screening in progress monitoring plans to ensure that mobile students
quickly acclimate and experience success
The researcher plans to meet with building and central administrators from participating
school districts to share the results and these recommendations.
Implication 12: Policy.
As student mobility is a challenge faced by schools nationwide, from rural
schools to urban schools, an emphasis on policy may help. Based on the results of this
action research project, implications for policy include:
•
State and federal education legislation that mandates a new federal reporting
subgroup comprised of mobile students
•
Fund allocations earmarked to create new programs and learning opportunities
targeting this group
•
School choice programs and/or flexible district boundary programs may reduce
transiency and result in better academic success for students
Future Directions for Research (Recommendations)
Future plans
As a result of completing this action research project, the researcher has identified
five areas in which lessons learned will be applied. These actions fall into two categories:
state-level actions and local actions.
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State-level actions.
The researcher holds leadership positions on several Pennsylvania state
educational initiatives. From this scope of influence, the results of this action research
will be applied at a high-level through three projects.
Pennsylvania School Improvement Identification and Planning.
Pennsylvania’s state system of school improvement identification examines
school performance in six areas: academic achievement, academic growth, attendance,
graduation, career readiness benchmarks, and English language learner proficiency rate.
The system does not currently factor student mobility rates into identification. As a
member of the leadership team tasked with designing and implementing some aspects of
the school improvement process in the state, the researcher will share the findings of this
project and propose a revised set of procedures for school improvement identification that
will factor in school mobility rate, or somehow otherwise consider the levels of transient
students. Additionally, it will be recommended that the school improvement program
establish core team member positions with a focus on student mobility and other out of
school challenges. As the project showed that there is a correlation between student
mobility rate and accountability indicator values, and these values are used to identify
schools for school improvement, then an assumption can be made that schools receiving
school improvement services might benefit from supports for transient students.
Classroom Diagnostic Tools.
The researcher is also a state co-lead for a diagnostic assessment known as the
Classroom Diagnostic Tools (CDT). The CDT is offered at no cost to all Pennsylvania
schools, and is a computer adaptive diagnostic assessment that can be administered in
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grades three through 12, in all state assessment tested subject areas. At this time,
approximately 60% of schools in the state of Pennsylvania utilize the CDT. One of the
biggest challenges facing teachers when a new student enrolls in their classroom is
quickly identifying gaps in that student’s content knowledge and understanding. The
CDT is a powerful tool that can be used to provide a detailed report of student
comprehension aligned to Pennsylvania academic eligible content. As part of ongoing
promotion of the tool, marketing materials will be created and distributed to schools
across Pennsylvania promoting the value of administering the CDT to newly-enrolled
students. Schools will be encouraged to embed the use of the CDT into a formal intake
process for mobile students. Once the results of the test are available, teachers of the
students will be able to examine vertical learning progressions and will be able to quickly
identify gaps in learning.
Pennsylvania Intermediate Unit Leadership.
As a state role-alike lead for curriculum and instruction consultants across
Pennsylvania’s twenty-nine intermediate units, the researcher plans to share the results of
this research with peers across the state. Statewide, all intermediate units retain
consultants to work with local school districts in various school improvement efforts, and
the impact of student mobility on various school effectiveness indicators would be key
information to inform this work.
Local-level actions.
The researcher currently holds the position of Program Director in the Teaching
and Learning division of a regional education agency (known as intermediate units in
Pennsylvania). In this position, he routinely provides consultation and professional
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development to local district and school administrators and teachers. He is also
responsible for assisting in the development of additional services and professional
development, based on district needs, research, and best practice. The results of this
action research project will inform local work in four areas.
Communicating Results to District Administrators.
Results of this project will be shared with district administrators through rolealike meetings with superintendents and curriculum directors. Districts will be surveyed
as to the formal and informal processes in place to assist transition for mobile students.
As the researcher has a high interest in not only the academic success of mobile students,
but also the overall success of schools, assistance will be offered to local districts with an
interest in developing or refining programs to improve transition for mobile students.
Informing Local Consultation.
The researcher routinely meets with administrators and teachers from 42 local
school districts. These consultations often focus on root cause analysis and strategic
planning. Informed by the results of this action research project, levels of mobile students
and the supports in place to assist them will now be considered in these consultations.
When analyses take place examining student academic and organizational success by
subgroup, when possible, a ‘transient’ student subgroup will now be included in the study
and subsequent discussion and planning.
Promoting Supports for Transient Students in Remote Learning.
In response to the COVID-19 crisis of 2020, the researcher’s institution has
recently received several rounds of grant funding to offer professional learning
opportunities to western Pennsylvania educators related to remote learning. As a co-lead
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for the Reimaging and Reinventing Education project, he is responsible for developing
and implementing professional development focusing on building teacher capacity to
more effectively offer remote learning. One of the strands of best practices is flexibility
for learners with diverse needs. The researcher has already begun crafting a professional
development module aimed at communicating the results of this research and providing
strategies for schools and teachers to welcome and accommodate students who may have
moved into the district but due to remote learning, are visiting their new classroom for the
first time in only a remote setting.
Building Additional Services and Supports.
The researcher plans to work with the program director for Teaching and
Consultation (TAC) to further refine and expand on existing professional development in
consulting related to transient students. The TAC staff routinely provide assistance to
schools in the support of underserved populations of students. It will be recommended
that services specializing in mobile students be substantially enhanced. This updated
strand of services and professional development will serve to help schools design formal
intake processes for transient students, and to build systemic supports to aid the students
in the transition. Additionally, these services would offer professional development to
teachers to build their capacity in helping mobile students to acclimate to a new
classroom, and to quickly experience academic success.
Recommendations for future research.
Informed by the results of this action research project, research may be conducted
to examine the impact of student mobility on school accountability through additional
lenses. Building on a limitation previously addressed, future research might study this
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
105
issue by examining a larger sample size of at least 330, representing a minimum of 10%
of the schools in the state. While similar studies have been completed in other states
examining the impact of student mobility on accountability indicators, additional research
might focus on the impact of those students on school improvement designation in those
states as well. It is also possible that the implications for policy and practice apply on a
national level.
As some schools already have existing programs in place to screen transient
students and to provide necessary support, additional research could examine this
relationship in these schools to determine whether or not the interventions put in place
result in reducing the impact of mobility on accountability indicators. Comparisons
could be drawn between schools with transient-focused interventions in place and schools
without, and analyses conducted to examine the effectiveness of those interventions.
As there are multiple external factors that affect student performance, future
research might focus on out-of-school conditions that impact the academic performance
of mobile students. Such research might examine number of moves, locations, family
background, and community supports. Finally, additional action research might be
conducted to examine the impact of transient students at the teacher-level, classroomlevel and system-level. What burdens are placed on teachers as a result of students
moving in? What are the implications on classroom instruction when a teacher must help
a student socially and academically assimilate? What are the system-level challenges that
impact a district’s ability to effectively help mobile students transition and experience
academic success?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
106
Summary
Decades of research have shown the negative impact of mobility on student
academic and behavioral success. Building on that research, this action research project
found that the impact of that correlation also affects most Pennsylvania school
accountability indicators.
The results of the study suggested a strong correlation between transiency rate and
change in school accountability indicators for attendance, math growth, math
achievement, and ELA achievement, and a moderate correlation with career readiness
benchmarks. Of all the school accountability factors examined, the only factor with
which student mobility had a small correlation was ELA growth.
While Pennsylvania’s Future Ready PA Index does report success on federally
mandated indicators by subgroup, mobile students are not considered. This marginalized
group can be difficult to identify and label, and their progress or lack thereof may not be
as evident as that of other groups of students with stable residence, but it is the
responsibility of the state and our school systems to provide supports. The results of the
study showed that mobile students negatively impact accountability indicators utilized for
school improvement designation. Hopefully, the funds set aside for improving
underperforming schools might be utilized for providing services and supports for this
group of students that often goes unnoticed.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
107
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THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
APPENDICES
121
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122
APPENDIX A
Proposal Number
IRB Review Request
Date Received
IRB Review Request
Institutional Review Board (IRB) approval is required before beginning any research and/or
data collection involving human subjects
Submit this form to instreviewboard@calu.edu or Campus Box #109
Project Title:
The Impact of Student Mobility on School Ratings in Pennsylvania’s School Accountability System
Researcher/Project Director
Brian Stamford
Phone #. 724-989-8983
E-mail Address. STA0255@calu.edu
Faculty Sponsor (if researcher is a student)
Dr. Kevin Lordon
lordon@calu.edu
Department Department of Secondary Education and Administrative Leadership
Anticipated Project Dates. September 1, 2019
to May 31, 2020
Sponsoring Agent (if applicable)
Project to be Conducted at
Project Purpose:
Allegheny Intermediate Unit, Homestead, PA
Thesis
Research
Class Project
Other
Keep a copy of this form for your records.
Required IRB Training
All researchers must complete an approved Human Participants Protection training course. The training requirement can
be satisfied by completing the CITI (Collaborative Institutional Training Initiative) online course at
http://www.citiprogram.org New users should affiliate with “California University of Pennsylvania” and select the “All
Researchers Applying for IRB Approval”course option. A copy of your certification of training must be attached to this IRB
Protocol. If you have completed the training within the past 3 years and have already provided documentation to the IRB,
please provide the following:
Previous Project Title
Date of Previous Project IRB Approval
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
123
Please attach a typed, detailed summary of your project AND complete items 2
through 6.
1. Provide an overview of your project-proposal describing what you plan to do and how you
will go about doing it. Include any hypothesis(ses)or research questions that might be
involved and explain how the information you gather will be analyzed. All items in the
Review Request Checklist, (see below) must be addressed.
In accordance with federal education accountability regulations, the Pennsylvania Department of
Education recently designated hundreds of schools in the state as in need of school improvement.
Many of these schools have a higher rate of poverty than their peers, and research shows that with
increased poverty comes increased student mobility. Student mobility negatively impacts student
achievement and academic success. A quantitative correlational study is needed to investigate the
impact that high populations of mobile students have on a school’s school improvement
designation. The results of this study will inform all schools) as to the importance of providing
proper academic supports for mobile students, as well as offer evidence to support a change in
Pennsylvania’s school accountability system to take into consideration the rates of student
mobility.
2. Section 46.11 of the Federal Regulations state that research proposals involving human
subjects must satisfy certain requirements before the IRB can grant approval. You should
describe in detail how the following requirements will be satisfied. Be sure to address each
area separately.
(text boxes will expand to fit responses)
a.
How will you insure that any risks to subjects are minimized? If there are
potential risks, describe what will be done to minimize these risks. If there are risks,
describe why the risks to participants are reasonable in relation to the anticipated
benefits.
There is no risk of any kind, since the project is limited to analyzing extant data; no
human subjects will be involved. Only potential discomfort to the schools I work with
would be the data showing that regardless of student mobility, most students are under
achieving; this would serve as a discomfort as it would be a sign of an ineffective
system.
b.
How will you insure that the selection of subjects is equitable? Take into account
your purpose(s). Be sure you address research problems involving vulnerable
populations such as children, prisoners, pregnant women, mentally disabled persons, and
economically or educationally disadvantaged persons. If this is an in-class project
describe how you will minimize the possibility that students will feel coerced.
One suburban and one urban school were approached to partner on this research; the
schools represents typical schools in the state. Participation is voluntary and the
schools are enthusiastic to participate.
c.
How will you obtain informed consent from each participant or the subject’s
legally authorized representative and ensure that all consent forms are appropriately
documented? Be sure to attach a copy of your consent form to the project summary.
A consent form will explain the process and will require each school’s signature to
participate. A copy of the consent form is attached to this request. Consent is required
and was obtained from each school’s superintendent (attached).
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124
d.
Show that the research plan makes provisions to monitor the data collected to
insure the safety of all subjects. This includes the privacy of subjects’ responses and
provisions for maintaining the security and confidentiality of the data.
All data will be provided to me without name association; no personally identifiable
information will be shared with me; this anonymous data will be saved on my local
computer and will be deleted at the end of the project. The principal researcher will
have access to this data. Based on criteria provided by the researcher, the LEAs Will
separate accountability data into two groups of students based on those defined as
mobile and those defined as stable residence. The school districts will then remove
student names and PA Secure IDs from the dealer before providing it to the
researcher. There will be no identifying information in these accountability files. Each
school’s provided data will contain the following six school success indicators as
identified by federal accountability regulations: math/ELA achievement, math/ELA
growth, attendance, graduation rate, career benchmark completion, and EL
proficiency. These measures can be found reported at: https://futurereadypa.org
3. Check the appropriate box(es) that describe the subjects you plan to target.
Adult volunteers
Mentally Disabled People
CAL University Students
Economically Disadvantaged People
Other Students
Educationally Disadvantaged People
Prisoners
Fetuses or fetal material
Pregnant Women
Children Under 18
Physically Handicapped People
Neonates
4. Is remuneration involved in your project?
5. Is this project part of a grant?
Yes or
Yes or
No
No. If yes, Explain here.
If yes, provide the following information:
Title of the Grant Proposal
Name of the Funding Agency
Dates of the Project Period
6.
Does your project involve the debriefing of those who participated?
Yes or
No
If Yes, explain the debriefing process here.
7. If your project involves a questionnaire or interview, ensure that it meets the requirements
indicated in the Survey/Interview/Questionnaire checklist.
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125
California University of Pennsylvania Institutional Review Board
Survey/Interview/Questionnaire Consent Checklist (v021209)
This form MUST accompany all IRB review requests
Does your research involve ONLY a survey, interview or questionnaire?
YES—Complete this form
NO—You MUST complete the “Informed Consent Checklist”—skip the remainder of this form
Does your survey/interview/questionnaire cover letter or explanatory statement include:
[_] (1) Statement about the general nature of the survey and how the data will be
used?
[_] (2) Statement as to who the primary researcher is, including name, phone, and
email address?
[_] (3) FOR ALL STUDENTS: Is the faculty advisor’s name and contact information
provided?
[_] (4) Statement that participation is voluntary?
[_] (5) Statement that participation may be discontinued at any time without penalty
and all data discarded?
[_] (6) Statement that the results are confidential?
[_] (7) Statement that results are anonymous?
[_] (8) Statement as to level of risk anticipated or that minimal risk is anticipated?
(NOTE: If more than minimal risk is anticipated, a full consent form is required—and
the Informed Consent Checklist must be completed)
[_] (9) Statement that returning the survey is an indication of consent to use the data?
[_] (10) Who to contact regarding the project and how to contact this person?
[_] (11) Statement as to where the results will be housed and how maintained? (unless
otherwise approved by the IRB, must be a secure location on University premises)
[_] (12) Is there text equivalent to: “Approved by the California University of
Pennsylvania Institutional Review Board. This approval is effective nn/nn/nn and
expires mm/mm/mm”? (the actual dates will be specified in the approval notice from
the IRB)?
[_] (13) FOR ELECTRONIC/WEBSITE SURVEYS: Does the text of the cover letter
or
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
126
explanatory statement appear before any data is requested from the participant?
[_] (14) FOR ELECTONIC/WEBSITE SURVEYS: Can the participant discontinue
participation at any point in the process and all data is immediately discarded?
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127
California University of Pennsylvania Institutional Review Board
Informed Consent Checklist (v021209)
This form MUST accompany all IRB review requests
Does your research involve ONLY a survey, interview, or questionnaire?
YES—DO NOT complete this form. You MUST complete the
“Survey/Interview/Questionnaire Consent Checklist” instead.
NO—Complete the remainder of this form.
1. Introduction (check each)
[x_] (1.1) Is there a statement that the study involves research?
[x_] (1.2) Is there an explanation of the purpose of the research?
2. Is the participant. (check each)
[x_] (2.1) Given an invitation to participate?
[x_] (2.2) Told why he/she was selected.
[x_] (2.3) Told the expected duration of the participation.
[x_] (2.4) Informed that participation is voluntary?
[x_] (2.5) Informed that all records are confidential?
[x_] (2.6) Told that he/she may withdraw from the research at any time without
penalty or loss of benefits?
[x_] (2.7) 18 years of age or older? (if not, see Section #9, Special Considerations
below)
3. Procedures (check each).
[x_] (3.1) Are the procedures identified and explained?
[x_] (3.2) Are the procedures that are being investigated clearly identified?
[x_] (3.3) Are treatment conditions identified?
4. Risks and discomforts. (check each)
[x_] (4.1) Are foreseeable risks or discomforts identified?
[_] (4.2) Is the likelihood of any risks or discomforts identified?
[_] (4.3) Is there a description of the steps that will be taken to minimize any risks or
discomforts?
[_] (4.4) Is there an acknowledgement of potentially unforeseeable risks?
[_] (4.5) Is the participant informed about what treatment or follow up courses of
action are available should there be some physical, emotional, or psychological harm?
[x_] (4.6) Is there a description of the benefits, if any, to the participant or to others
that may be reasonably expected from the research and an estimate of the likelihood
of these benefits?
[_] (4.7) Is there a disclosure of any appropriate alternative procedures or courses of
treatment that might be advantageous to the participant?
5. Records and documentation. (check each)
[x_] (5.1) Is there a statement describing how records will be kept confidential?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
128
[x_] (5.2) Is there a statement as to where the records will be kept and that this is a
secure location?
[x_] (5.3) Is there a statement as to who will have access to the records?
6. For research involving more than minimal risk (check each),
[_] (6.1) Is there an explanation and description of any compensation and other
medical or counseling treatments that are available if the participants are injured
through participation?
[_] (6.2) Is there a statement where further information can be obtained regarding the
treatments?
[_] (6.3) Is there information regarding who to contact in the event of research-related
injury?
7. Contacts.(check each)
[x_] (7.1) Is the participant given a list of contacts for answers to questions about the
research and the participant’s rights?
[x_] (7.2) Is the principal researcher identified with name and phone number and
email address?
[x_] (7.3) FOR ALL STUDENTS: Is the faculty advisor’s name and contact
information provided?
8. General Considerations (check each)
[x_] (8.1) Is there a statement indicating that the participant is making a decision
whether or not to participate, and that his/her signature indicates that he/she has
decided to participate having read and discussed the information in the informed
consent?
[x_] (8.2) Are all technical terms fully explained to the participant?
[x_] (8.3) Is the informed consent written at a level that the participant can
understand?
[x_] (8.4) Is there text equivalent to: “Approved by the California University of
Pennsylvania Institutional Review Board. This approval is effective nn/nn/nn and
expires mm/mm/mm”? (the actual dates will be specified in the approval notice from
the IRB)
9. Specific Considerations (check as appropriate)
[_] (9.1) If the participant is or may become pregnant is there a statement that the
particular treatment or procedure may involve risks, foreseeable or currently
unforeseeable, to the participant or to the embryo or fetus?
[_] (9.2) Is there a statement specifying the circumstances in which the participation
may be terminated by the investigator without the participant’s consent?
[x_] (9.3) Are any costs to the participant clearly spelled out?
[x_] (9.4) If the participant desires to withdraw from the research, are procedures for
orderly termination spelled out?
[_] (9.5) Is there a statement that the Principal Investigator will inform the participant,
or any significant new findings developed during the research that may affect them
and influence their willingness to continue participation?
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[_] (9.6) Is the participant is less than 18 years of age? If so, a parent or guardian must
sign the consent form and assent must be obtained from the child
[_] Is the consent form written in such a manner that it is clear that the
parent/guardian is giving permission for their child to participate?
[_] Is a child assent form being used?
[_] Does the assent form (if used) clearly indicate that the child can freely refuse
to participate or discontinue participation at any time without penalty or coercion?
[x_] (9.7) Are all consent and assent forms written at a level that the intended
participant can understand? (generally, 8th grade level for adults, age-appropriate for
children)
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130
California University of Pennsylvania Institutional Review Board
Review Request Checklist
(v021209)
This form MUST accompany all IRB review requests.
Unless otherwise specified, ALL items must be present in your review request.
Have you:
[x_] (1.0) FOR ALL STUDIES: Completed ALL items on the Review Request
Form?
Pay particular attention to:
[x_] (1.1) Names and email addresses of all investigators
[x_] (1.1.1) FOR ALL STUDENTS: use only your CalU email
address)
[x_] (1.1.2) FOR ALL STUDENTS: Name and email address of
your faculty research advisor
[x_] (1.2) Project dates (must be in the future—no studies will be approved
which have already begun or scheduled to begin before final IRB approval—
NO EXCEPTIONS)
[x_] (1.3) Answered completely and in detail, the questions in items 2a
through 2d?
[x_] 2a: NOTE: No studies can have zero risk, the lowest risk is
“minimal risk”. If more than minimal risk is involved you MUST:
[x_] i. Delineate all anticipated risks in detail;
[x_] ii. Explain in detail how these risks will be minimized;
[x_] iii. Detail the procedures for dealing with adverse
outcomes due to these risks.
[x_] iv. Cite peer reviewed references in support of your
explanation.
[x_] 2b. Complete all items.
[x_] 2c. Describe informed consent procedures in detail.
[x_] 2d. NOTE: to maintain security and confidentiality of data, all
study records must be housed in a secure (locked) location ON
UNIVERSITY PREMISES. The actual location (department, office,
etc.) must be specified in your explanation and be listed on any
consent forms or cover letters.
[x_] (1.4) Checked all appropriate boxes in Section 3? If participants under
the age of 18 years are to be included (regardless of what the study involves)
you MUST:
[x_] (1.4.1) Obtain informed consent from the parent or guardian—
consent forms must be written so that it is clear that the
parent/guardian is giving permission for their child to participate.
[x_] (1.4.2) Document how you will obtain assent from the child—
This must be done in an age-appropriate manner. Regardless of
whether the parent/guardian has given permission, a child is
completely free to refuse to participate, so the investigator must
document how the child indicated agreement to participate
(“assent”).
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131
[x_] (1.5) Included all grant information in section 5?
[x_] (1.6) Included ALL signatures?
[x_] (2.0) FOR STUDIES INVOLVING MORE THAN JUST SURVEYS,
INTERVIEWS, OR QUESTIONNAIRES:
[x_] (2.1) Attached a copy of all consent form(s)?
[x_] (2.2) FOR STUDIES INVOLVING INDIVIDUALS LESS THAN 18
YEARS OF AGE: attached a copy of all assent forms (if such a form is used)?
[x_] (2.3) Completed and attached a copy of the Consent Form Checklist? (as
appropriate—see that checklist for instructions)
[x_] (3.0) FOR STUDIES INVOLVING ONLY SURVEYS, INTERVIEWS, OR
QUESTIONNAIRES:
[x_] (3.1) Attached a copy of the cover letter/information sheet?
[x_] (3.2) Completed and attached a copy of the
Survey/Interview/Questionnaire Consent Checklist? (see that checklist for
instructions)
[x_] (3.3) Attached a copy of the actual survey, interview, or questionnaire
questions in their final form?
[x_] (4.0) FOR ALL STUDENTS: Has your faculty research advisor:
[x_] (4.1) Thoroughly reviewed and approved your study?
[x_] (4.2) Thoroughly reviewed and approved your IRB paperwork?
including:
[x_] (4.2.1) Review request form,
[x_] (4.2.2) All consent forms, (if used)
[x_] (4.2.3) All assent forms (if used)
[x_] (4.2.4) All Survey/Interview/Questionnaire cover letters (if
used)
[x_] (4.2.5) All checklists
[x_] (4.3) IMPORTANT NOTE: Your advisor’s signature on the review
request form indicates that they have thoroughly reviewed your proposal and
verified that it meets all IRB and University requirements.
[x_] (5.0) Have you retained a copy of all submitted documentation for your records?
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Project Director’s Certification
Program Involving HUMAN SUBJECTS
The proposed investigation involves the use of human subjects and I am submitting the complete
application form and project description to the Institutional Review Board for Research Involving
Human Subjects.
I understand that Institutional Review Board (IRB) approval is required before beginning any
research and/or data collection involving human subjects. If the Board grants approval of this
application, I agree to:
1. Abide by any conditions or changes in the project required by the Board.
2. Report to the Board any change in the research plan that affects the method of using
human subjects before such change is instituted.
3. Report to the Board any problems that arise in connection with the use of human subjects.
4. Seek advice of the Board whenever I believe such advice is necessary or would be
helpful.
5. Secure the informed, written consent of all human subjects participating in the project.
6. Cooperate with the Board in its effort to provide a continuing review after investigations
have been initiated.
I have reviewed the Federal and State regulations concerning the use of human subjects in
research and training programs and the guidelines. I agree to abide by the regulations and
guidelines aforementioned and will adhere to policies and procedures described in my
application. I understand that changes to the research must be approved by the IRB before they
are implemented.
Professional (Faculty/Staff) Research
Project Director’s Signature
Student or Class Research
Student Researcher’s Signature
Supervising Faculty Member’s Signature
ACTION OF REVIEW BOARD (IRB use only)
The Institutional Review Board for Research Involving Human Subjects has reviewed this application to
ascertain whether or not the proposed project:
1.
2.
provides adequate safeguards of the rights and welfare of human subjects involved in the
investigations;
uses appropriate methods to obtain informed, written consent;
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
3.
4.
5.
133
indicates that the potential benefits of the investigation substantially outweigh the risk involved.
provides adequate debriefing of human participants.
provides adequate follow-up services to participants who may have incurred physical, mental, or
emotional harm.
Approved[_________________________________]
___________________________________________
_________________________
Chairperson, Institutional Review Board
Disapproved
Date
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
134
APPENDIX B
IRB Request Approval
Institutional Review Board
California University of Pennsylvania
Morgan Hall, 310
250 University Avenue
California, PA 15419
instreviewboard@calu.edu
Melissa Sovak, Ph.D.
Dear Brian,
Please consider this email as official notification that your proposal
titled “The Impact of Student Mobility on School Ratings in
Pennsylvania's School Accountability System” (Proposal #18-105)
has been approved by the California University of Pennsylvania
Institutional Review Board as amended.
The effective date of approval is 11/14/19 and the expiration date is
11/13/20. These dates must appear on the consent form.
Please note that Federal Policy requires that you notify the IRB
promptly regarding any of the following:
(1) Any additions or changes in procedures you might wish for your
study (additions or changes must be approved by the IRB before they
are implemented)
(2) Any events that affect the safety or well-being of subjects
(3) Any modifications of your study or other responses that are
necessitated by any events reported in (2).
(4) To continue your research beyond the approval expiration date of
11/13/20 you must file additional information to be considered for
continuing review. Please contact instreviewboard@calu.edu
Please notify the Board when data collection is complete.
Regards,
Melissa Sovak, PhD.
Chair, Institutional Review Board
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
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APPENDIX C
LEA Action Planning Template for Transient Cohorts - DRAFT
In order to improve a school’s support structure for transient students, it is
important to build a plan that incorporates effective practices that drive
change in practice. The Chief Council of State School Officers (CCSSO)
proposes the cycle of improvement below upon which school improvement
efforts can be built.
The template that follows provides suggestions for actions to be taken at
each stage in this cycle in order to provide a more comprehensive approach
to supporting populations of transient students in schools. Should a district
decide to formalize the steps in this template, the framework is aligned to
Pennsylvania’s Future Ready Comprehensive Planning Portal, which should
allow for easy transferability between this planning document and the site.
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
Step
Set the Direction
Assess Needs
Create Plan
Implement Plan
Monitor Work
Adjust Course
Action
136
Suggestions
Review historical performance
of transient students; establish a
guidance committee; set student
focused SMART goals
Conduct a comprehensive review
of the performance and
experience of transient students
in your school; examine
practices, processes and
routines that might be
inequitable to transient students;
conduct a root cause analysis as
to why transient students are
struggling in your school
Create a plan with
implementation indicators
related to your goals and based
on your needs assessment;
recommend the use of screening
and intake tools for mobile
students
Consider implementation at a
system, building, and classroom
level; how will you meet the
goals?
How will you monitor the work
and progress of transient
students? Might you create a
flag in your student information
system to allow easier
monitoring? How will progress
be reported?
As the monitoring occurs, how
will you adjust the course?
Might you consider focus groups
of transient students? Might you
consider including transient
students in the process?
THE IMPACT OF STUDENT MOBILITY ON SCHOOL RATINGS
137
APPENDIX D
Workflow for Comparing Transient Student
Performance to Stable Student Performance - DRAFT
Recent research has indicated a correlation between levels of student transiency and
Future Ready PA Index school accountability indicators (achievement, growth,
attendance, career readiness, graduation, and EL proficiency). Does the performance of
transient students in your school district align to this relationship? Use the process below
to disaggregate the results for students in your school. This document also includes an
optional section that allows for a correlational analysis examining data from multiple
schools. Note: as parts of this workflow involve a basic understanding of PIMS, it is
advised that this process is completed by or in cooperation with a district data manager.
STEP ONE: FILTER FOR ATTRIBUTED STUDENTS. All students who factor into
accountability can be found in the District Student Data File which is posted for
download on the pa.drcedirect.com website each June. District assessment coordinators
have access to download this file.
STEP TWO: FILTER FOR ATTRIBUTED STUDENTS. Not all the students in this file
factor into school accountability values. Remove the following students from this file
(see the column headers for titles):
• Students not attributed to the school code
• Students with a ‘Y’ in the ‘First Year ELL’ column
STEP THREE: VERIFY THAT THESE VALUES MATCH. Before proceeding, it is
important to verify that the content in this file matches the content that factored into
accountability indicators. To determine this, calculate proficiency or positive levels for
each of the sixth indicators using the data in this file and compare to those on the
futurereadypa.org website. If the values match, move on. If they do not, revisit step two.
Note: attendance and graduation are lagging indicators; therefore, those indicators would
come from data from the prior years’ District Student Data File
STEP FOUR: IDENTIFY TRANSIENT STUDENTS. In order to identify transient
students, complete a query of the student information management system to identify
students who enrolled within the past 12 months. Add a column to the District Student
Data File and flag the students as transient.
STEP FIVE: CALCULATE INDICATOR VALUES FOR THREE GROUPS. In order
to compare the performance of transient students to the all student body, you must create
three groups of students: all, stable (non-transient), and transient. Calculate the
accountability values for each of the six indicators for each of these three groups, then
move on to the questions for consideration portion of this document.
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138
QUESTIONS FOR CONSIDERATION: To examine the relationship between transient
students and stable students in your school, consider the questions below. Your response
to these questions will help guide school action planning related to transient students.
•
•
•
Is there a difference between the accountability values for the transient and nontransient groups? If so, what difference?
Do you notice any trends schoolwide or district-wide? Are these trends consistent
or is there variation between grades or schools?
Are there outliers? To what might you attribute this?
ROOT CAUSE ANALYSIS AND ACTION PLANNING: Now that you have identified
trends in your data it is time to action plan. Use the LEA Action Planning Template for
Transient Cohorts to create a plan for addressing the needs you have identified in your
district.
(OPTIONAL) CONDUCT A CORRELATIONAL ANALYSIS OF THE DATA: If you
are examining the data of multiple schools, you may wish to examine the correlation. Is
there a consistent relationship among those schools between transiency and
accountability indicators? One way to examine this is by conducting a bivariate
correlation test. While there are multiple ways to do this, one of the most popular
software packages for automating the process is IBM’s SPSS software. (If you are
unfamiliar with the software, it contains many useful tutorials.) In order to complete a
correlational analysis comparing the transiency rate at your schools and the school
accountability values, conduct a bivariate correlation test. In the bivariate correlation
option menu, pull the two variables to be tested into the test box, then select Pearson
correlation coefficient, two-tailed significance, and flag significant correlations.
In the example below, one would look for the Pearson correlation in the quadrant under
the opposing variable. Below you will note that the Pearson correlation is -.920.
Correlation is strong if this value is |p|>=.5
Correlations
AttendanceTra AttendanceAb
nsiencyRate
soluteValue
AttendanceTransiency Pearson
1
-.920**
Rate
Correlation (p)
Sig. (2-tailed)
.009
N
6
6
AttendanceAbsoluteVal Pearson
-.920**
1
ue
Correlation (p)
Sig. (2-tailed)
.009
N
6
6
**. Correlation is significant at the 0.01 level (2-tailed).