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School-based interventions for chronically absent students in poverty

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School-based interventions for chronically absent students in poverty

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School-Based Interventions for Chronically Absent Students in Poverty
by
Jennifer Ann Chapman

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

May 2021

© Copyright 2021 by Jennifer Ann Chapman
All Rights Reserved

The Committee for Jennifer Ann Chapman certifies the approval of this Dissertation

Alison Muraszewski
Kathy Stowe
Courtney Malloy, Committee Chair

Rossier School of Education
University of Southern California
2021
iv
Abstract
This study investigates promising practices at Alpha High School for attendance interventions
which decrease chronic absenteeism for students in poverty. The study applies Bronfenbrenner’s
Ecological Model framework (Bronfenbrenner, 1979) to a mixed-methods analysis. The
quantitative focus entailed an analysis of student attendance and intervention data to compare the
frequency of access of interventions to final chronic absenteeism rates across subgroups. The
qualitative design involved interviewing five members of the attendance team at Alpha High
School to determine perceptions of intervention impacts. The study determined that changes
made to the intervention process during the 2018-2019 school year, including additional
attendance team staffing and implementation of the No Credit Status intervention with students,
resulted in a decrease in chronic absenteeism across all subgroups. Perceptions of stakeholders
shared that building relationships, increased accountability, and increased capacity and resources
were also contributing factors to the decrease in absenteeism. Based on study findings, in
conjunction with a literature review, this study suggests recommendations focused on increasing
student accountability and providing additional school-based supports and credit recovery
options for students experiencing significant absenteeism.

v
Dedication
This dissertation would in no way be complete without sending so much gratitude to my
incredible husband, Kevin Chapman. I would not have applied to this program without your
consistent encouragement and a bit of bullying. And I am certain that I never would have
completed this program or this study without your tremendous amounts of patience, joining me
on audiobooks, listening to me stress and complain, and spending hours and hours with our
daughter so I could work. I love you and honestly believe this degree is just as much yours as it
is mine.

vi
Acknowledgements
Without the encouragement and support of a select group of individuals, I would never
have completed this undertaking. First, I would like to send an incredible amount of gratitude to
my interview participants, the staff at Alpha High School and all of the district employees who
spent countless hours pulling data for me. Their dedication to always doing what is best for
students and their openness to experiment with new ideas and to share outcomes not only make
significant contributions to this study but to the entire field of education.
Additional thanks are owed to my incredibly unique cohort and the fantastic faculty,
particularly Dr. Muraszewski for helping me start strong and Dr. Datta for helping me finish
strong, at the University of Southern California, Rossier School of Education. Particularly, many
thanks go to my incredible “Reading Group of Awesomeness!” Balancing the many aspects of
this program along with a growing family has not always been an easy task, but the camaraderie,
reading notes, and continuing laughs were always there to get me through the rocky spots. I
would never have finished this dissertation without the support, both academically and
personally, from each one of you. Additional acknowledgements go to my twelfth grade English
Teacher, Mr. Cooper, for incessantly encouraging me to be more concise with my writing and to
my amazing editor Susan Gilpin for pulling my APA game together reinforcing that conciseness.
I would lastly like to thank my committee, Dr. Courtney Malloy, Dr. Alison
Muraszewski, and Dr. Kathy Stowe as well as my Capstone assistant, Dr. Carey Regur. Serving
on a committee requires committing a significant amount of time and thought, all to support
someone else’s vision. I cannot thank each of you enough for the tremendous amounts of
feedback, insight, and patience you contributed to my constantly evolving study.

vii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables .................................................................................................................................. x
List of Figures ................................................................................................................................ xi
Chapter One: Overview of the Study .............................................................................................. 1
Context and Background of the Problem ........................................................................ 2
Purpose of the Project and Research Questions .............................................................. 4
Importance of the Study .................................................................................................. 4
Overview of Theoretical Framework and Methodology ................................................ 6
Definitions....................................................................................................................... 7
Organization of the Dissertation ..................................................................................... 8
Chapter Two: Literature Review .................................................................................................... 9
History of Chronic Absenteeism ..................................................................................... 9
Contributors of Chronic Absenteeism .......................................................................... 13
Impact of Chronic Absenteeism.................................................................................... 18
Bronfenbrenner’s Ecological Model Conceptual Framework ...................................... 20
Summary ....................................................................................................................... 26
Chapter Three: Methodology ........................................................................................................ 28
Research Questions ....................................................................................................... 28
viii
Overview of Design ...................................................................................................... 28
Research Setting............................................................................................................ 29
The Researcher.............................................................................................................. 30
Data Sources ................................................................................................................. 31
Validity and Reliability ................................................................................................. 35
Ethics............................................................................................................................. 36
Chapter Four: Findings ................................................................................................................. 39
Participating Stakeholders ............................................................................................ 39
Interview Participants ................................................................................................... 42
Results and Findings ..................................................................................................... 43
Research Question 1 ..................................................................................................... 43
Research Question 2 ..................................................................................................... 57
Research Question 3 ..................................................................................................... 74
Summary ....................................................................................................................... 82
Chapter Five: Recommendations .................................................................................................. 84
Discussion of Findings and Results .............................................................................. 84
Recommendations for Practice ..................................................................................... 89
Limitations and Delimitations ....................................................................................... 97
Recommendations for Future Research ........................................................................ 98
Conclusion .................................................................................................................... 99
ix

References ................................................................................................................................... 102
Appendix A: Interview Protocol ................................................................................................. 110

x
List of Tables
Table 1: Data Sources 29
Table 2: Student Demographic Data from 2015-2016 school year through
2018-2019 school year 40
Table 3: Attendance Team Member Demographics 43
Table 4: Mean and Median of Yearly Excused, Unexcused and Total Days
Absent and Absenteeism Rates 45
Table 5: 2015-2016 Through 2018-2019 Percentage of Students Chronically Absent 46
Table 6: 2015-2016 Percentage of Students Receiving Interventions and
Chronically Absent 51
Table 7: 2016-2017 Percentage of Students Receiving Interventions and
Chronically Absent 53
Table 8: 2017-2018 Percentage of Students Receiving Interventions and
Chronically Absent 54
Table 9: 2018-2019 Percentage of Students Receiving Interventions and
Chronically Absent 56
Table 10: Attendance Interventions at Alpha High School 73

xi
List of Figures
Figure 1: Attendance Interventions within Bronfenbrenner’s Ecological Model 26
Figure 2: Four Year Comparison of Chronically Absent Rates by Subgroup 47

1
Chapter One: Overview of the Study
In the last decade, chronic absenteeism has emerged as a critical problem nationwide.
From the 2013-2014 school year (National Center for Education Statistics, 2016) to the 2015-
2016 school year (Department of Education, 2019), when the federal government began
monitoring individual student absenteeism rates, national absenteeism rates of students increased
from 13% to 16%. Furthermore, among high school students, 21% of students were chronically
absent during the 2015-2016 school year (Department of Education, 2019). Once the
absenteeism trend was discovered nationally, many states began monitoring their own chronic
absenteeism rates on state, district, and school levels. Chronic absenteeism is defined as 10% or
more missed school days during the academic year and includes both excused and unexcused
full-day absences (Attendance Works, 2018). The evidence further highlights that partial day
absences (with a majority at the beginning or end of the day) are three times as prevalent as full
day absences (Whitney & Liu, 2017), demonstrating a further problem. Due to growing trends of
absenteeism of students, attendance rates became a standard of school accreditation in 36 states
in the United States by the 2018-2019 school year (Department of Education, 2019). This
problem is important to address because consistent daily attendance is a key predictor of on-time
graduation (Allensworth, 2007; London, 2016; Oregon Department of Education, 2015), both
factors to support student success and school accreditation. As chronic absenteeism grows,
schools may not only risk facing accreditation failures for attendance rates, but also for falling
achievement rates that were impacted by declining attendance (Gottfried, 2011; Gottfried, 2014;
Oregon Department of Education, 2015).
Drawing from the literature, low socioeconomic students are more likely to be
chronically absent from school than more affluent peers due to diminished access to critical

2
resources (Balfanz & Byrnes, 2012; Chang & Romero, 2008; London, et. al., 2016). Balfanz and
Byrnes’ (2012) study examining state attendance data from six states showed consistently in all
states that impoverished students miss more school than peers not in poverty. Chang and Romero
(2008) found that compared to affluent families, families in poverty lack the same access to
healthcare, nutritious food, clothing, and reliable housing and transportation, which contribute to
increased absenteeism. The literature shares that students from poverty show higher levels of
absenteeism, thereby increasing their risk of becoming high school dropouts and demonstrating
their need for additional resources (Balfanz & Byrnes, 2012; Chang & Romero, 2008; London et
al., 2016).
Context and Background of the Problem
The state of Virginia released its own state and school level attendance data as of the
2016-2017 school year. During that period, the statewide chronic absenteeism rate in Virginia
was 12%, below the prior year’s national average (Virginia Department of Education, 2019d).
However, upon examining the absenteeism rate among subgroups, 18% of students in poverty in
Virginia were chronically absent, above the prior year’s national average (Virginia Department
of Education, 2019d). In order to mitigate chronic absenteeism of all students, the state of
Virginia, along with 35 other states (Department of Education, 2016), has added attendance
reporting as an accreditation factor for all public schools beginning in the 2018-2019 school year
(Virginia Department of Education, 2018). Specifically, in order to achieve a Level One
(highest) accreditation status, no more than 15% of the students at a school can qualify as
chronically absent by the end of the school year (Virginia Department of Education, 2018). The
addition of this accreditation factor now requires schools to develop, implement, and document
interventions for students specifically focused on increasing a student’s daily attendance.

3
In one particular Virginia school district, NOVA School District (pseudonym), only 10%
of high schools would have met the state standard for attendance accreditation based on data
from the 2017-18 school year (Virginia Department of Education, 2019c). By the end of the
2018-19 school year, 50% of NOVA District high schools were able to meet the accreditation
rating, but none of the schools with an economically disadvantaged population higher than 35%
met the accreditation standard (Virginia Department of Education, 2019c). However, one
economically disadvantaged school was able to make significant progress towards reducing
chronic absenteeism. Alpha High School (pseudonym) was able to decrease its chronic
absenteeism rate from 33.7% in 2017-18 to 19.2% in 2018-19 (Virginia Department of
Education, 2019a) the largest improvement in the entire district. While an absentee rate of 19%
still only qualifies as a Level Two attendance rate, the school did move out of the Level Three
range they fell in with a 34% absentee rate (Virginia Department of Education, 2018).
Alpha High School has a population of nearly 2400 students, over two-thirds of whom
are economically disadvantaged (Virginia Department of Education, 2019a). Alpha has
traditionally only implemented the attendance interventions required by the state of Virginia.
However, once attendance became an accreditation factor, Alpha adapted their processes to
increase the size of their attendance team, allowing for more individualized intervention
approaches, and also incorporated a new intervention requiring students to recover missed time
in class before earning a passing credit for the class. By further investigating attendance
monitoring and intervention practices at Alpha High School, this study intends to identify
promising supports and interventions that may lead to improved attendance rates among students
in poverty.

4
Purpose of the Project and Research Questions
The purpose of this study is to examine promising supports and interventions that can
help students in poverty overcome barriers and develop the same attendance habits as their non-
chronically absent peers.
Research questions guiding the study are:
1. What were the attendance patterns over time at Alpha High School?
2. What attendance interventions were offered at various levels of the system at Alpha
High School?
3. What were the perceptions of stakeholders at Alpha High School regarding the impact
of interventions?
Importance of the Study
Chronic absenteeism among students in poverty (Chang & Romero, 2008) has been
shown to negatively impact academic outcomes and the likelihood of on-time graduation
(Allensworth, 2007; London et al., 2016; Oregon Department of Education, 2015). An
examination of data from the Sioux Falls School District in South Dakota discovered a
significant negative correlation (0.379 for 2006 and 0.388 for 2007) between the number of days
absent and grade point average (GPA) (National Center for Education Statistics, 2009). The data
showed that as the number of absences increased, the percentage of students with a GPA over 3.0
decreased (National Center for Education Statistics, 2009). Specifically, less than 30% of
students with more than 15 absences (both excused and unexcused) had a GPA of 3.0 or higher
(National Center for Education Statistics, 2009). In the state of Virginia, from 2017 through
2019, students in poverty have shown a 13% deficit annually on the state reading exam and an
11% deficit on the state math exam, but a 6% higher rate of absenteeism (Virginia Department of

5
Education, 2019d). The evidence highlights that students in poverty miss up to three times as
much school as affluent peers (Balfanz & Byrnes, 2012). If students in poverty are already
academically behind (Virginia Department of Education, 2019d), but are also missing more
school compared to their peers, there is little hope to decrease the achievement gap.
Additionally, students who are chronically absent, even as early as middle school, show a
higher high school dropout rate (Alonso et al., 2011; Allensworth, 2007). A study of a
Philadelphian school district found that only 13% of students who missed 20% or more of school
during their 6th grade year graduated on time, and only an additional 4% graduated one year late
(Balfanz et al., 2007). In Virginia in 2019, the federal graduation indicator for economically
disadvantaged students was 8% lower than all students (Virginia Department of Education,
2019d). Considering the same students are also missing more school than their peers, the
likelihood of closing the graduation gap is also low.
Further negative outcomes of chronic absenteeism among adolescents can stretch into
adulthood, including increased likelihood of unemployment, incarceration, and dependency upon
welfare (Christenson et al., 2001) as well as involvement in crime, drug use, gang involvement,
theft, and violence (Onder, 2017). For Alpha High School, an added community consequence of
losing full accreditation exists if the school fails to improve and sustain chronic absenteeism
rates as they are accredited yearly. Neglecting to address negative student attendance patterns not
only results in negative outcomes for the students, but also impacts outcomes for the entire
school and ultimately society. By investigating and identifying interventions that lead to
improvements in student attendance, schools can implement practices that not only improve their
absenteeism rates, but also support their students’ academic achievement (Gottfried, 2011;

6
Gottfried, 2014; Oregon Department of Education, 2015) and likelihood of on-time graduation
(Allensworth, 2007; London et al., 2016; Oregon Department of Education, 2015).
Overview of Theoretical Framework and Methodology
The problem of practice was examined through Bronfenbrenner’s Ecological Systems
Model (Bronfenbrenner, 1979) with a lens on student attendance (school policies and structures,
external forces in the community, and cultural beliefs of families). Bronfenbrenner’s model
examines the impacts of the microsystem (immediate environment), mesosystem (environments
containing the person), exosystem (social structures), and macrosystem (social and cultural
values) on an individual’s development and decision making (Bronfenbrenner, 1979). In order to
decrease the student chronic absenteeism rate at Alpha High School, the personal and societal
structures and policies that impact student attendance were explored. By examining the
environmental factors which impact a student’s development, specifically a student’s decision to
attend school, procedures can be developed within schools to support more consistent
attendance. Interventions were examined on macro (state accreditation requirements), exo
(school monitoring and reporting of attendance), meso (family engagement and education around
attendance), and micro (student engagement and education) levels to determine which ones most
significantly promote positive, sustained attendance habits.
The study entailed a mixed-methods approach which both examined student attendance
data and investigated the practices implemented by attendance teams at schools. Student data
were analyzed to discover attendance trends of students receiving specific attendance
interventions. Additionally, members of the school’s attendance team were interviewed to
determine the practices in place to address students with poor attendance patterns and the

7
perceived outcomes of those practices. Both investigative paths were utilized to determine
specific interventions that positively impacted student attendance.
Definitions
The following definitions clarify key factors in the study of chronic absenteeism of
students in poverty.
• Accredited refers to schools whose quality indicators in overall student achievement
in English, mathematics and science, achievement gaps in English and mathematics,
and student engagement are all rated as near, making sufficient progress, meeting, or
exceeding the state standard or schools that have received a waiver from the General
Assembly (Virginia Department of Education, 2019b).
• Chronic Absenteeism means 10% or more missed school days during the academic
year, including both excused and unexcused full-day absences (Attendance Works,
2018).
• Economically Disadvantaged refers to students whose household meets the income
eligibility guidelines (less than or equal to 185% of Federal Poverty Guidelines) for
free or reduced-price school meals (Virginia Department of Education, 2019b).
• Federal Graduation Indicator is a graduation rate reported to the U.S. Department of
Education only counting students who earned Advanced Studies or Standard
Diplomas (Virginia Department of Education, 2019b).
• School Accreditation is a process to evaluate the educational performance of public
schools (Virginia Department of Education, 2019b).
• Truant is to being absent without parental permission (Bruner et al., 2011).

8
Organization of the Dissertation
This dissertation is organized into five chapters. Chapter 1 provides the reader with the
key concepts and terminology commonly found in a discussion about chronic absenteeism of
adolescents, particularly of those in poverty. The organization’s background and stakeholders, as
well as a review of the evaluation framework and the study’s guiding questions are provided.
Chapter 2 provides a review of current literature surrounding the scope of the study. Topics of
historical monitoring and intervention practices, contributors and impacts of chronic
absenteeism, and the evaluating framework are addressed. Chapter 3 details the methodological
choices surrounding participants, data collection, and analysis. In Chapter 4 the data and results
are described and analyzed. Chapter 5 provides context-specific recommendations based on data
and literature for improving chronic absenteeism among adolescents in poverty.

9
Chapter Two: Literature Review
Chapter 2 reviews possible factors that contribute to chronic absenteeism among
adolescents and the corresponding interventions to combat those factors. The first section
examines the history of attendance monitoring and intervention practices. The second section
focuses on the contributing factors to chronic absenteeism, including early attendance patterns,
socioeconomic status, student interest, engagement and acceptance, and student self-efficacy and
emotional control. The third section reviews the impacts of chronic absenteeism, examining
academic achievement, drop-out rates, and societal burdens. The final section explores
Bronfenbrenner’s Ecological Model (1979) as a framework for examining chronic absenteeism
causes and interventions.
History of Chronic Absenteeism
Chronic absenteeism of American students has not only been growing, increasing from
13% to 16% just from 2014 to 2016 as a group (National Center for Education Statistics, 2016;
Department of Education, 2019), but also worsens on an individual basis as students progress
through their K-12 education (National Center for Educational Statistics, 2009). As of 2016, 21%
of high school students missed at least 10% of the school year (Department of Education, 2019).
Attendance issues often develop well before high school. Hickman et al. (2008) showed that
while much educational legislation is focused only on compulsory education of students in high
school, the study participants who dropped out of school showed an average of 124 missed
school days in K-8 grades. Their research further shows that the absenteeism gap between high
school dropouts and graduates widens throughout a student’s educational career (Hickman et al.,
2008). The research on absenteeism is still immature, most having only occurred in the last 15

10
years, and narrow, primarily focused only on daily attendance rates or students with unexcused
absences.
Monitoring
Prior to establishment of the Every Student Succeeds Act in 2015 (US Department of
Education, 2020), methods of attendance monitoring in schools, which have not focused on
individual student records, have allowed students with excessive excused or partial day absences,
and even some with excessive unexcused absences, to continue detrimental attendance habits
without intervention. Bruner et al. (2011) highlighted that if a school is not monitoring the
specific students who are consistently absent, solely monitoring average daily attendance figures
can make a 95% daily attendance rate mask the prevalence of chronic absenteeism. The same
study further shared that attendance monitoring missteps occur when schools only focus on
truancy monitoring, a requirement from the No Child Left Behind legislation, and neglect all
other forms of absences (Bruner et al., 2011). A student who misses school without the
permission of an adult is considered truant; however, by only monitoring truant students, the
large group of “excused absence” students, who are still consistently missing 10% or more of
school with adult permission, are missing out on attendance interventions (Bruner et al., 2011).
In order to account for all chronically absent students, traditional attendance monitoring methods
needed to change. Due to the prior failed attendance tracking systems, chronic absenteeism is
now a standard of school accreditation in 36 states in the US (Department of Education, 2019)
and even a student level graduation requirement in one state (Education Commission of the
States, 2019). As a result, many schools must change their procedures to monitor and intervene
with students who are chronically absent to school to support their students’ academic
achievement, socio-emotional needs, and the likelihood of on-time graduation.

11
Interventions
Just as attendance monitoring procedures have morphed over time, attendance
intervention procedures have grown as well. Prior to 2015, during the No Child Left Behind
(NCLB) standards when attendance reporting was required only for elementary and middle
schools (Harris, 2003), state level attendance interventions focused mainly on truant (unexcused
absence) students. In Virginia, Adequate Yearly Progress (AYP) for school accreditation was
solely focused on graduation rates in high school and only required attendance reporting from
elementary schools (Harris, 2003), thereby minimizing the need for formal attendance
interventions. An alternative state example from the Pennsylvania Compulsory Attendance and
Truancy Elimination Plan, developed under NCLB regulations, was more inclusive of attendance
interventions and required the employment of an “attendance officer” or “home and school
visitor” for most school districts to enforce compulsory attendance school code (Pennsylvania
Board of Education, 2006). School based interventions suggested by the Pennsylvania plan
included sending a notice to parents through certified mail, hosting a parent conference to
develop a truancy elimination plan, referring students to a county-based youth agency, or filing a
citation with the local district judge for habitual truancy (Pennsylvania Board of Education,
2006). The only excused focused intervention suggested by the Pennsylvania Board of Education
(2006) was requiring students in excess of ten excused absences to provide a doctor’s note.
With the adoption of the Every Student Succeeds Act in 2015, attendance monitoring
adaptations also prompted new attendance intervention practices nationally. State level
interventions incorporated chronic absenteeism rates into school accreditation standards
(Department of Education, 2019) and student graduation requirements (Education Commission
of the States, 2019). Due to the accreditation standard, school intervention practices are now

12
encouraged to take a school-wide approach through a tiered system of support focused on all
students (Attendance Works, 2017). Kearney and Graczyk (2013) elaborate on a “Response to
Intervention” approach to combating attendance problems by promoting attendance for all
students (Tier 1), providing targeted interventions for at-risk students (Tier 2), and providing
intense and personalized interventions for all students reaching chronically absent levels (Tier 3).
When focusing on chronic absenteeism as a whole, and not just truancy, school level
interventions across tiers include recognizing students for improved attendance, building
relationships with students and families, developing personalized plans to address barriers to
attendance, pairing students with mentors, and, in extreme circumstances, seeking legal support
(Attendance Works, 2017).
Within the last ten years, studies have begun to examine the effectiveness of individual
attendance interventions internationally. In a Dutch pilot program, the intervention strategy of
increasing home visits of at-risk youth through the utilization of mentors, teachers, case
managers, social workers, and compulsory education age consultants showed a -1.4% impact on
dropout rates among the lowest track of students (Cabus & DeWitte, 2015). A Kenyan study
found an increase in elementary school attendance rates by schools that provided a nutritious
snack to students before recess (Omwami et al., 2011). A qualitative study out of England
asserted that adapting the school context (reduced schedules, virtual instruction, and home
visits), providing emotional support (building resilience skills and increasing mental health
supports), and building two-way relationships with parents were all effective interventions for
schools experiencing attendance problems (Finning et al., 2017). Finally, the Freeman et al.
study (2016) across 37 American states examined the link between School-Wide Positive
Behavior Interventions and Supports (SWPBIS) and student academics, attendance, and

13
behavior. The study found that schools that did not implement SWPBIS strategies showed a
0.07% improvement in attendance rates per year. However, schools that were implementing
SWPBIS with fidelity showed a 0.51% improvement, while schools with implementation levels
approaching fidelity showed a 0.3% improvement (Freeman et al., 2016). The study further
found that while schools with higher levels of poverty had lower attendance rates, their rate of
change over time was similar to schools not in poverty (Freeman et al., 2016). Just as attendance
monitoring practices shifted from focusing on truant students to focusing on all students,
attendance intervention practices have shifted to a whole school approach.
Contributors of Chronic Absenteeism
Multiple factors contribute to chronic absenteeism of high school students on historical,
societal, school, and student levels. Historical components explore early indicators for high
school dropouts (Ansari & Pianta, 2019; Hickman et al., 2008; Lehr et al., 2004). Societal
aspects examine how the socioeconomic status of students impacts attendance (Balfanz &
Byrnes, 2012; Chang & Romero, 2008; London et al., 2016). School level factors review the
influences from interest, engagement, and social acceptance of students (Gase et al., 2016;
Gnambs & Hanfstingl, 2016; Gottfried, 2011; Luciana et al., 2012; Onder, 2017; Raufelder et al.,
2016; Whitney & Liu, 2017), while student focuses explore students’ self-efficacy and emotional
control skills (Caprara et al., 2013; Dembo & Eaton, 2000; Diaz-Herrero et al., 2018; Green et
al., 2012). Each of these factors can contribute independently or in conjunction with other factors
to mold attendance habits of high school students.
Early Indicators for High School Dropouts
Research highlights that chronic absenteeism attendance patterns of high school dropouts
first develop in elementary and middle school. School systems can identify poor attendance of

14
high school dropouts as early as kindergarten and first grade. In the Hickman et al. (2008)
longitudinal study of attendance patterns of high school dropouts, poor attendance was seen as
early as kindergarten; by first grade the number of days absent for dropouts compared to
graduates was statistically significant. Additional research supports that elementary students with
poor attendance patterns are likely to maintain similar or worse attendance in later grades. In a
study of a school district identified with a large amount of low-income students, Lehr et al.
(2004) determined that early attendance patterns showed that dropouts had twice as many
absences in the fifth grade and three times as many absences in the ninth grade compared to their
graduate peers. Ansari and Pianta (2019) found not only was elementary absenteeism indicative
of absenteeism in school in later years, but it was also indicative of academic and social-
behavioral struggles by the time a student was 15 years old. Because patterns of chronic
absenteeism are visible as early as kindergarten, schools can identify potential high school
dropout candidates well before high school. Chronic absenteeism can also have more significant
impacts on students of low socio-economic status.
Low Socio-economic Status
Drawing from the literature, students of low socioeconomic status are more likely to be
chronically absent from school than more affluent peers due to diminished access to critical
resources. Research shows elementary students who are economically disadvantaged have an
increased likelihood of chronic absenteeism. A longitudinal study in a San Francisco school
district found that participation in Free/Reduced Price Lunch showed the second highest positive
correlation with chronic absenteeism in elementary students (London et al., 2016). Furthermore,
chronic absenteeism has been shown to increase in middle and high school for students in
poverty. Balfanz and Byrnes’ (2012) study examining state attendance data from six states

15
showed consistently in all states that impoverished students miss more school than peers not in
poverty. Specifically, data from Maryland showed that elementary school students in poverty had
two times higher rates of chronic absenteeism, while poor middle and high school students had
three times higher rates of chronic absenteeism (Balfanz & Byrnes, 2012). Additional research
indicates that families in poverty are not as equipped as affluent families to support consistent
attendance. Chang and Romero (2008) found that compared to affluent families, families in
poverty lack the same access to healthcare, nutritious food, clothing, and reliable housing and
transportation, which contribute to increased absenteeism. They additionally found that parents
in poverty do not always understand the importance or formalities of developing good attendance
habits in kindergarten (Chang & Romero, 2008). This collection of literature demonstrates
students from poverty show higher levels of absenteeism, thereby increasing their risk of
negative academic outcomes, including becoming high school dropouts. Poverty, however, is not
the only contributor to chronic absenteeism.
Lack of Student Interest, Engagement, and Social Acceptance
Student interest and engagement is a main motivation in students’ decisions to attend
school (Gase et al., 2016; Whitney & Liu, 2017). When examining partial day absences, students
are most likely to be absent from a math class and least likely to be absent from a social studies
class, which parallels the national survey on engagement showing the lowest student engagement
levels in math classes and the highest levels in social studies classes (Whitney & Liu, 2017). The
Gase et al. (2016) study identified either not liking the subject or not finding the subject useful as
a primary reason students were unmotivated to attend class. Attendance not only increases when
students are interested in school, but also when they feel engaged at school.

16
An engaging school environment supports positive attendance habits (Gase et al., 2016;
Gnambs & Hanfstingl, 2016; Onder, 2017). Onder (2017) found that some causes of absenteeism
included a non-engaging school environment. Gase et al. (2016) found that engaging
relationships with teachers and other adults in the building were a main indicator of why students
choose to attend certain classes. Additionally, Gnambs and Hanfstingl (2016) analyzed factors
that contribute to a decrease in intrinsic academic motivation. Self- determination theory persists
that individuals gain more personal satisfaction and motivation due to intrinsic factors over
external factors (Ryan & Deci, 2004). The Gnambs and Hanfstingl (2016) study, examining self-
determination theory, found failure to meet any of the three basic needs of autonomy,
competence, and relatedness results in a decline in intrinsic academic motivation among
adolescents. Specifically, the study showed that children from ages 11 to 16 experience a natural
decrease in intrinsic motivation, mean slope (M = -.14). However, controlling for relatedness
(M = .03), competence (M = .15), and autonomy (M = .04) all showed a positive mean slope
indicating a growth in intrinsic motivation (Gnambs & Hanfstingl, 2016). Essentially, if
students’ cognitive, emotional, and social needs are not being met by the school, students lose
the motivation to actively engage in school (Gase et al., 2016; Gnambs & Hanfstingl, 2016;
Onder, 2017).
Social acceptance is an additional factor which supports school engagement and
attendance. Onder (2017) cited the lack of ability to make friends as a main contributor of
absenteeism, while Gottfried (2011) additionally found that many students can feel alienated
trying to return to school after an attendance gap. Further evidence highlights that compared to
people in early childhood and later adulthood, adolescents show the highest responsivity towards
social acceptance and affiliation as a behavioral motivator (Luciana et al., 2012) which could

17
promote better school attendance. Similarly, a study by Raufelder et al. (2016) out of Germany
found that self-determination (which predicted higher levels of school engagement) was higher
among students experiencing strong interpersonal relationships with their teachers and peers at
school. Along with acceptance, interest, and engagement, students’ self-efficacy and emotional
control can contribute to the decision to attend school regularly.
Student Self-Efficacy and Emotional Control
Students’ self-perceptions are a primary facet of emotional self-control capabilities that
significantly promote consistent school attendance (Caprara et al., 2013; Diaz-Herrero et al.,
2018; Green et. al, 2012). The Diaz-Herrero et al. (2018) study examining varying profiles of
emotional intelligence in relation to school refusal found that students with decreased emotional
regulation capabilities are more likely to engage in school refusal behaviors. A similar study
examined 198 students’ development from age 15 to 21 to determine if correlations existed
between students’ self-efficacy in expressing positive emotions, self-efficacy in managing
negative emotions, and emotional stability (Caprara et al., 2013). The study found a correlation
that students who did not perceive themselves as being highly self-efficacious in regulating their
negative emotions also showed lower levels of emotional stability, but no correlation between
either of those two factors and a student’s ability to regulate positive emotions (Caprara et al.,
2013).
Self-efficacy skills promote the development of sustained, self-regulating behaviors such
as consistent attendance (Caprara et al., 2013; Green et al., 2012). Dembo and Eaton (2000)
found that adolescents have generally poor time management and self-regulation abilities. In
turn, developing higher levels of self-efficacy in adolescents is a key strategy when trying to
change or sustain particular behavior traits such as consistent attendance (Caprara et al., 2013).

18
Green et. al. (2012) found that the combination of high academic motivation and self-concept in
high school students was the main predictor of developing positive attitudes towards school,
which subsequently decreased the amount of absenteeism among students. While it is important
to analyze the many factors that contribute to developing patterns of chronic absenteeism in
students, the ultimate impacts of chronic absenteeism must also be considered.
Impact of Chronic Absenteeism
The impact of unaddressed student absenteeism starts while a student is still enrolled in a
K-12 school but continues well beyond their graduation date. Significant impacts to consider
include low academic achievement while still in school, increased likelihood of dropping out of
school, and future negative impacts post high school. Repercussions from absenteeism not only
impact students but can also be a detriment to society as a whole.
Low Academic Achievement of Students
Research reveals chronically absent students have an increased likelihood of experiencing
academic difficulties, including low academic achievement and low standardized test scores,
which become contributing factors to dropping out of high school. As absenteeism increases,
achievement decreases (Gottfried, 2011; Gottfried, 2014; Oregon Department of Education,
2015). Specifically, chronic absenteeism is predictive of low levels of achievement on
standardized assessments. A review of elementary student achievement spanning six years in a
Philadelphia school district showed that on both math (effect size of -0.08) and reading (effect
size of -0.07) standardized assessments, absenteeism was correlated negatively to achievement
(Gottfried, 2011). Likewise, chronic absenteeism leads to lower achievement on state-mandated
standardized tests, further supporting an increased likelihood of dropping out of high school. In a
similar study, the Oregon Department of Education (2015) found that, compared to regularly

19
attending peers, fewer chronically absent students met the state standard level of achievement on
both math (20% fewer) and reading (12% fewer) examinations. In Gottfried’s 2014 study,
students with moderate levels of chronic absenteeism showed lower achievement in math and
reading than peers who were not chronically absent, and students with strong chronic
absenteeism showed the lowest achievement of all three groups. Low academic achievement and
low standardized test scores are not only correlated to chronic absenteeism, but also to dropping
out of high school.
Increased Dropout Rate of Students
As absenteeism increases, the likelihood of on-time graduation decreases. Based on a
study of the graduating cohorts of 2007 and 2015 in Baltimore city schools, a group in which
over 75% of students are in poverty, data showed that students who had ten or fewer absences in
the sixth grade were 70% likely to graduate on time compared to students who missed 20 or
more days of school, dropping to a 28.6% likelihood of on-time graduation (Alonso et al., 2011).
A similar study by the Oregon Department of Education (2015) found the graduation rate of
chronically absent students to be 16% lower than peers. Another study found that specifically
students from poverty have a heightened probability of dropping out of high school (Christenson
et al., 2001). Chronic absenteeism, if not addressed early, not only impacts students’ futures
academically, but can also have deleterious impacts on society.
Increased Societal Burden as Adults
There are significant societal implications for chronically absent students and high school
dropouts. Bray (2006) discovered that students of low socioeconomic status are impacted more
detrimentally by missing time with a teacher than affluent peers. Additionally, Aydin (2003),
Barlow and Fleischer (2011), and Mueller and Giacomazzi (2006) all revealed that significant

20
correlations exist between absenteeism and future negative behaviors, including drug use, crime,
gang involvement, and violence. Another study found that students from poverty have a
heightened probability of dropping out of high school, a path that leads to an increased likelihood
of future unemployment, incarceration, and utilization of government support (Christenson et al.,
2001). Improving attendance rates of K-12 students in poverty is not just critical for each
student’s future success, but for the success and flourishment of society as a whole.
Bronfenbrenner’s Ecological Model Conceptual Framework
The problem of practice was examined through Bronfenbrenner’s Ecological Systems
Model (Bronfenbrenner, 1979) with a lens on student attendance and interventions (school
policies and structures, external forces in the community, and cultural beliefs of families).
Bronfenbrenner (1979) claims that different environmental settings, from an immediate to an
extended level and the interplay between settings and an individual, impact one’s human
development. Bronfenbrenner’s model examines the impacts of the microsystem (immediate
environment), mesosystem (environments containing the person), exosystem (social structures),
and macrosystem (social and cultural values) on an individual’s development and decision-
making (Bronfenbrenner, 1979). By examining the environmental factors which impact a
student’s development, specifically their decision to attend school, procedures can be developed
within schools to support more consistent attendance. Each level of Bronfenbrenner’s Model was
investigated to determine the factors and interventions that influence attendance. While each
level indicated certain factors within that particular environment that influence attendance, it is
important to remember that each of those factors can be influenced by components from other
environments. There is a constantly connected and evolving interplay of influences that both lead
to student absenteeism and support consistent daily attendance.

21
Microsystem
The environmental factors that most immediately impact an individual compose the
microsystem (Bronfenbrenner, 1979). This includes people (family, friends) and environments
(home, school) that an individual interacts with personally. For example, children develop
language skills by watching and hearing the conversations of those around them and by
interacting personally in conversations (Bronfenbrenner, 1979). Their immediate environment is
influencing how, when, and to what extent they learn to talk. In the school attendance realm,
students may develop their own attendance habits by viewing the habits of older siblings
(Hickman et at., 2008) or by talking with parents about the importance of attending school
(Chang & Romero, 2008).
Other immediate factors that could impact a student’s ability to attend school include
transportation, personal or family health issues, and student social relationships. Attendance
intervention factors on a microsystem level are considered Tier 3 level supports as they are
individualized to meet specific needs of the student (Attendance Works, 2017). Sample
microsystem interventions could include a walk to school or an attendance buddy, who can
check in with students daily to confirm they are heading to school or join them on their walk if
there is a safety concern or connecting a student or family with a specific community agency to
help support an access need (Attendance Works, 2014). Microsystem interventions from this
study included initial meetings and interagency meetings with students and school staff to review
student attendance and the no-credit status that students experienced when accruing too many
absences. While microsystem-based interventions target the specific, immediate need of the
student, considerations must be made regarding factors in the meso-, exo-, or macrosystems that
are influencing that need in order to develop effective interventions.

22
Mesosystem
The mesosystem consists of the interactions between multiple settings (Bronfenbrenner,
1979), for example, a student’s school athletic schedule influencing the time he or she eats
dinner with family at home and the time that student has left to complete homework.
Bronfenbrenner’s (1979) mesosystic elements may take a variety of forms, including people
similar to both settings, communications between settings, and attitudes and information in one
setting but about the other. From an attendance perspective, communications between schools
and parents about attendance policies, feelings of alienation when transitioning from home to
school (Gottfried, 2011), and school outreach and engagement factors to welcome students to the
school environment (Onder, 2017) all fall within the mesosystem.
Mesosystem interventions can include providing engaging extracurricular activities at
schools to encourage student involvement (Attendance Works, 2017) or creating specific systems
of communication between the school and parents to keep families informed about student
attendance patterns and available supports (Attendance Works, 2014). Interventions specific to
this study that fall within the mesosystem include teacher and counselor contact with parents,
school sponsored parent-student-staff meetings, and academic and attendance support programs,
including Saturday school and extended school days, that are programed by the school.
Mesosystic interventions focus on creating supports in tangentially connected environments that
impact the student’s immediate environment. For example, increasing a parent’s knowledge at an
interagency meeting about the legal attendance requirements and the academic supports offered
at the school, could increase the pressure a student receives at home to adopt more positive
attendance habits. And just like microsystem interventions, mesosystic interventions are both
influenced by and can make influences on factors in the other three systems.

23
Exosystem
The exosystem examines settings that do not specifically include the individual, but
indirectly impact an individual due to their influence on primary settings (Bronfenbrenner,
1979). Examples of exosystem settings include the school a parent attended, or the policies set
on a district level and their impacts on the individual student. Attendance connections made in
the exosystem include socioeconomic factors of parents that impact a student’s access to school
(Balfanz & Byrnes, 2012; Chang & Romero, 2008) or the influence of attendance monitoring
and reporting requirements on a school or district level on interventions offered to students
(London et al., 2016).
Exosystem level attendance interventions focus on connecting with social services and
health supports available in communities to increase access and service for families in order to
decrease subsequent causes of absences (Attendance Works, 2014). Study specific exosystemic
interventions include the gamut of support services that families could be connected to after
interagency meetings or meetings with an intervention specialist as well as the referral of student
attendance cases to juvenile intake. Exosystemic interventions focus on how a change in an
environment that does not directly contain the student can trickle down to an environment that
does directly contain the student. For example, by connecting a family to health support services
for a sick parent, a student may be freed to attend more school instead of caring for that parent.
Again, the impact of interventions in the ecosystem is dependent on the connection between the
systems.
Macrosystem
The macrosystem develops from consistencies, belief systems, and ideologies prevalent
throughout the lower systems that influence the culture of a society (Bronfenbrenner, 1979).

24
Macrosystem examples include cultural beliefs about the importance of education or ideas such
as “No Child Left Behind.” Attendance influences from regulatory macrosystem components
include state and national regulations such as required attendance monitoring in No Child Left
Behind (NCLB) and the Every Student Succeeds Act (Conry & Richards, 2018). Additional
influences from a cultural level encompass societal beliefs about future crime (Onder, 2017) or
unemployment (Christenson et al., 2001) of persons who were chronically absent while in the
public schools system.
Macrosystemic interventions would focus on state and nationally mandated attendance
monitoring and reporting which impacts school accreditation (Department of Education, 2019)
and subsequently a school’s development of attendance intervention practices. Macrosystemic
interventions connected to this study included increasing funding provided to school to
implement additional attendance interventions. Macrosystem interventions focus on influencing
the beliefs in society that could impact personal understandings about the importance of
attendance. These beliefs radiate through each subsequent level of the ecological system and
influence the development of sub-interventions. Similarly, beliefs developed at the macrosystem
level are influenced by the trends and behaviors present at the sub-levels. For example,
increasing funding for attendance interventions federally allows states, districts, and schools
more flexibility to design attendance interventions better suited to meet their individual students’
needs. Each level of Bronfenbrenner’s Ecological System is constantly impacting and being
impacted by all other levels.
Interrelation of Systems
Factors from each level of Bronfenbrenner’s model and the interrelations between those
factors influence the personal development of the individual, specifically, their attitudes and

25
behaviors around school attendance. In American society, national attendance reporting
requirements exist (Department of Education, 2019) in order to influence the individual
attendance support offered at a school level.
• Macrosystem. The United States Department of Education develops policies to ensure
that Every Student Succeeds (U.S. Department of Education, 2020).
• Exosystem. Individual schools develop policies and procedures to encourage and
monitor school attendance and to identify students who are struggling.
• Mesosytem. Schools communicate with parents about the importance of consistent
attendance and interventions available to support students with interrupted
attendance.
• Microsystem. Students engage in personalized interventions at school and talk with
parents about supported attendance monitoring at home.
• Individual. A student develops new personal beliefs about the value of attendance and
is better able to self-monitor their attendance-based habits.
Similarly, a student’s choice to attend or not attend school influences a school’s decision
to respond to that student choice and allocate resources as needed. The re-allocation of resources
then has cascading effects on other students’ personal choices, as well as influences on the
district and state levels’ choices to support the needs of the school. Each layer of the attendance
intervention system is constantly influencing the opportunities in other layers. Figure 1 visually
represents the multiple levels of factors at play regarding student attendance interventions
throughout Bronfenbrenner’s Model.

26
Figure 1
Attendance Interventions within Bronfenbrenner’s Ecological Model

Summary
Addressing the history, contributing factors, and future implications of chronic
absenteeism of students in poverty is critical to the long-term success of students. The research
of Hickman et al. (2008) stressed the importance of educational regulations starting in primary
school, citing the widening absenteeism gap throughout a student’s educational career (Hickman
et. al, 2008). Additional researchers focused on the societal implications for chronically absent
students and high school dropouts. Bray (2006) identified the heightened impact of missing

27
school on students from low socioeconomic backgrounds, while other researchers expressed the
long-term societal impacts of habits of chronic absenteeism, including increased crime (Aydin,
2003; Barlow & Fleischer, 2011; Mueller & Giacomazzi, 2006) and government dependency
(Christenson et al., 2001). By examining the literature regarding the history, contributing factors,
and implications of chronic absenteeism and framing that research within Bronfenbrenner’s
Ecological Model, determinations on the best interventions that influence student attendance
habits can be made.

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Chapter Three: Methodology
The following sections describe the design and methods behind this study on chronic
absenteeism. The purpose of this study was to determine school-based interventions that promote
improved attendance habits of students in poverty. The study utilized two methods of data
collection to answer the three posed research questions. The methodology report begins with an
overview of the study design, information on the research setting and researcher, and the data
sources being utilized. It then discusses the validity and reliability of the data sources, followed
by discussion on the ethical implications of this research.
Research Questions
1. What were the attendance patterns over time at Alpha High School?
2. What attendance interventions were offered at various levels of the system at Alpha
High School?
3. What were the perceptions of stakeholders at Alpha High School regarding the impact
of interventions?
Overview of Design
This study utilized a mixed-methods design. Quantitative data were applied by analyzing
the attendance data of students during the 2015-2016, 2016-2017, 2017-2018, and 2018-2019
school years to examine the attendance focused interventions at Alpha High School, with an
attention to year-to-year changes in data compared to changes in intervention practices.
Additionally, qualitative data were collected via attendance team interviews. The qualitative
focus involved interviewing adult members of the school’s attendance team to determine the
interventions implemented with chronically absent students and the perceived outcomes of those
interventions. Table 1 offers an overview of the data sources by research question.

29
Table 1
Data Sources
Research Questions Attendance and
Intervention Data
Analysis
Attendance Team
Interviews
RQ1: What were the attendance patterns over
time at Alpha High School?
X X
RQ2: What attendance interventions are
offered at various levels of the system at
Alpha High School?
X X
RQ3: What are the perceptions of
stakeholders at Alpha High School
regarding the impact of interventions?
X X

Research Setting
The study took place at an ethnically diverse northern Virginia high school of over 2400
students (Virginia Department of Education, 2019a). The student population was approximately
60% Hispanic, 20% Black, and less than 10% each of White, Asian, and other ethnicities
(Virginia Department of Education, 2019a). Almost 30% of the students were classified as
English language learners; just over 10% were students with disabilities; and approximately two-
thirds of the students were economically disadvantaged (Virginia Department of Education,
2019a). The school, included in a school system with over ten other high schools, had one of the

30
largest populations of students living in poverty, but was able to make the largest improvement
in attendance in the entire system during the 2018-2019 school year (Virginia Department of
Education, 2019c). Despite maintaining a 34% chronic absenteeism rate during the 2016-2017
and 2017-2018 school years, Alpha High School was able to drop the rate to just 19% for the
2018-2019 school year by implementing new interventions with its chronically absent students
(Virginia Department of Education, 2019a). Because of this dramatic improvement in attendance
of students in poverty, Alpha High School was the ideal setting to investigate attendance
promoting interventions.
Interview participants in the study included selected staff at the school during the studied
school years. Five specific members of the school attendance team were included in the
interview phase. These staff members were selected because they helped to develop the
attendance policies at the school and were the primary administrators of interventions. They also
analyzed a majority of the school attendance data on a regular basis and were generally the most
knowledgeable at the school about attendance practices of students. In addition to interviews,
existing student data, including daily attendance records and intervention participation, were
examined.
The Researcher
I am an Assistant Principal at a fellow high school in the same school system as Alpha. I
have worked in educational settings in three different school systems over the last 14 years and
have been analyzing attendance data and experimenting with attendance interventions for
students over the last four years while a member of attendance teams in two different school
systems. While I do not work directly at the school being studied, I am an employee in the same

31
school district and have professional relationships with multiple colleagues who do work at the
school in question.
My previous attendance work, professional relationships, as well as my upper middle-
class upbringing in a predominantly white school system could all have contributed to
assumptions and biases in the study. These biases could have negatively impacted the study by
developing prior assumptions regarding reasons students are absent from school and
interventions that may or may not work, and therefore reviewing the study results from a biased
perspective. In order to mitigate these potential assumptions and biases, I shared the conclusions
from the interviews and data analysis with the attendance team being interviewed to perform
member checking (Merriam & Tisdell, 2016) and assure that the conclusions being drawn were
consistent with the information provided from participants.
Data Sources
Two data sources were utilized in this study. Initially, five members of the attendance
team at Alpha High School were interviewed to determine attendance perceptions and
intervention practices. Then, the attendance data of student records from the 2015-2016 school
year through the 2018-2019 school year were analyzed to determine trends between continued
absenteeism and attendance-based student interventions.
Attendance Team Interviews
The first data source involved interviews of select members of the attendance team at
Alpha High School.
Participants
The attendance team at Alpha High School primarily consisted of six people, including
the principal, one assistant principal, two teachers on special assignment (TOSA), one counselor,

32
and one truancy officer. Each team member was selected to serve a specific purpose on the team,
including data analysis, student support, community outreach, and state reporting. The five most
active members of the attendance team were interviewed. The two TOSAs were the primary
implementers of student interventions and were interview participants. Additionally, the assistant
principal who oversees the attendance team was interviewed as well as the counselor who
returned from retirement to join the team and the intervention specialist who was added to the
team as a special assignment. A purposeful network sampling method (Merriam & Tisdell, 2016)
was utilized by identifying the participants currently situated on the attendance team who can
speak to attendance interventions being implemented (the assistant principal and TOSAs) and
then recruiting additional participants (the counselor and intervention specialist) after feedback
from interviewees regarding team members who have significant interaction with attendance
data or interventions at the school.
Instrumentation
The interview protocol was designed as a qualitative standardized open-ended interview
(Johnson & Christenson, 2015) with open-ended questions developed ahead of time which were
consistently asked of all participants. This approach allowed for analysis of the same sets of
procedures from the viewpoints of multiple stakeholders who helped to develop them. The
interview included 19 questions, which included basic information about each participant’s
position on the attendance team, the prior and current attendance monitoring procedures at the
school, the current interventions implemented at the school, and the perceived effectiveness of
those interventions.
Interviews were recorded, with participants’ permission, to allow for a review of the
transcript afterwards. Even though interviews were recorded, I also took small supplementary

33
notes during interviews to highlight key topics to focus on in the recordings and to express
engagement with the participant’s contribution (Bogdan & Biklen, 2007). The interview strategy
was to make participants comfortable by previewing topics with them ahead of time so they
could feel prepared and by focusing on their individual role and contributions on the attendance
team during each interview.
Data Collection Procedures
The logistical procedures for collecting data started with an initial meeting with the
principal at the school to preview the study. This meeting was scheduled early in the school year.
This time frame gave the principal the time to analyze their own data and procedures from the
focused school years so they could confidently talk about them and make suggestions for critical
members of the attendance team to connect with.
After meeting with the principal, individual interviews with the five primary team
members were scheduled at the convenience of participants. Interviews occurred via Zoom at the
preferred time of the interviewee and lasted approximately one hour each. All but one (at the
request of the participant) of the interviews were recorded (audio and video) on a laptop. I also
requested an option for a follow-up interview if there were any remaining questions after
reviewing all the responses.
Data Analysis
After each interview, the recording was reviewed as well as any accompanying notes that
I took to create a transcript. Notes from the interviews were included with each question before
the transcript of responses to allow for easier location of important quotes and information from
the interviews as recommended by Patton (1987). Once the transcript was created, participant
responses were grouped in a table by question so multiple answers to each question could be

34
reviewed together. This allowed for triangulation of the data by reviewing multiple responses to
the same questions and comparing those responses to the results from the accompanying data set
analysis (Merriam & Tisdell, 2016). Review of transcripts looked for comments from
participants that were both aligned with the results from the data analysis and responses from
other interviewees. It also looked for perceptions of participants that were consistent among
interviews.
Attendance Student Records
The second data source examined was the analysis of secondary attendance data of all
students at Alpha High School during the 2015-2016, 2016-2017, 2017-2018 and 2018-2019
school years.
Data Collection Procedures
The student data were analyzed from 12 spreadsheets of raw data, three for each school
year. One spreadsheet for each year included the demographic de-identified data of each student,
including the number of days they were enrolled during that school year. The demographic data
included: grade, gender, ethnicity, English learner status, disability status, and Free and Reduced
Meal (FARM) status. The two additional sheets listed the specific days that each student was
absent, one listing only excused days and another listing only unexcused. Information was
included for all students at the school who were enrolled as of the last day of the school year.
The unexcused and excused spreadsheets were utilized to develop totals of absences for the full
year. All of these data were then analyzed to compare to the perceptions of stakeholders
regarding the impact of interventions.

35
The raw data were provided by the school system. The data were merged, de-identified,
and analyzed to determine if the use of attendance interventions (and specifically which
interventions) improved the attendance of the student body.
Data Analysis
Data were analyzed by merging attendance data (total excused and unexcused days
missed) using a Vlookup to the spreadsheet with the demographic data to develop one working
spreadsheet per year. The data were then coded to indicate whether a student was likely to have
received each of the offered interventions at the school based on the number of absences they
had accrued as interview participants shared that each intervention was implemented when
students reached a specified number of unexcused absences. The total days absent compared to
total days enrolled was also used to determine a final rate of absenteeism for each student. Pivot
tables were then utilized to determine percentages of students in each subgroup accessing
interventions (teacher contact, initial meeting, referral to intervention specialist, counselor
contact, interagency meeting, referral to attendance officer, and qualification for No Credit
Status) as well as the percentages of students qualified as chronically absent by the end of the
school year. Additionally, the mean and median were calculated for the number of excused,
unexcused, and total absences for all students as well as the absenteeism rate for all students for
each school year.
Validity and Reliability
Multiple methods were employed to ensure validity and reliability of results in the study.
The main method to increase the validity of results was the use of triangulation, namely,
collecting data from multiple different sources to determine if similar results were present
(Creswell & Creswell, 2018). Internal validity, in particular, was established by comparing the

36
reality of the attendance team members’ perceptions to the data analysis comparing attendance
and interventions (Merriam & Tisdell, 2016). Additionally, member checking of the interviews
(Creswell & Creswell, 2018) was utilized when results from each interview were shared with the
interviewee before incorporating them into the study to confirm that the correct conclusions were
drawn. Finally, the findings from both data sources were reviewed for discrepant cases in the
analysis to determine if there were alternative explanations for the success of certain
interventions incurred by certain student groups (Merriam & Tisdell, 2016).
During the entire study, a key focus was to ensure that processes and procedures for each
of the data sources were tightly aligned with the research questions and conceptual framework.
Additionally, when developing each instrumentation and data analysis method, all data sources
were viewed through the lens of Bronfenbrenner’s Ecological Model (Bronfenbrenner, 1979).
The attendance data examined the resulting reality of the individual as well as the micro- and
mesosystems by focusing on the individual’s environments and experiences (interventions) that
may have influenced attendance patterns. Meanwhile, the attendance team interviews
investigated the exo- and macrosystems by investigating the school and societal level impacts on
the individual’s attendance.
Ethics
Multiple ethical dilemmas needed to be addressed when designing the study. A main
ethical consideration across both data sources involved maintaining the confidentiality of
participants and data records (Merriam & Tisdell, 2016). Each data source addressed this
concern separately. The attendance records analysis excluded any identifying information of
individuals in the results as data were de-identified at the district level before being provided to
me. No name, student ID, or personal demographic data were shared that could be traced back to

37
an individual student. Additionally, when a subgroup was so small (less than 0.5% of students)
that the combination of identifiers could indicate who is a member of the group, that group was
excluded from the shared results. In the attendance interviews, personal contact information was
only collected for the purpose of following up with participants in case clarity was needed or to
perform member checking. No identifying information was shared in the results of the study.
Furthermore, conclusions were only shared if they were developed from a whole group basis. If
individual opinions strayed from the group and were pertinent to the research, there was no
identifying information shared indicating which group member the aversion came from.
Individual name, demographics, or positional information was never released with interview
results. All confidentiality protection procedures were shared with all participants before
engaging in the processes.
Additionally, the purpose of the study and the manner of sharing results were presented
to each interview participant ahead of time (Merriam & Tisdell, 2016). All participation was
optional, and an informed consent statement was shared with each participant before engaging in
the process (Merriam & Tisdell, 2016). For the attendance interviews, the purpose of the study
was presented to the entire team before scheduling interviews and team members were given a
chance to ask any clarifying questions. Interviews were then scheduled individually, at the
convenience of the participant, if they elected to contribute. No repercussions, either personally
or school-based, were administered to those who elected not to participate or not to allow for
recording of their interview. Finally, at any point during the interviews if adults felt
uncomfortable and wanted to stop the process, they were allowed to end their participation and
the answers that they had provided before that time were destroyed and not used in the study. As
this study involved human subject research, a further layer of protections was applied by

38
submitting the study plans to the Institutional Review Board (IRB) at the University of Southern
California before implementing data collection procedures.

39
Chapter Four: Findings
This mixed-methods study sought to identify school attendance-based interventions that
positively impacted the attendance of students in poverty. The two methods implemented in the
study included a quantitative four-year review of attendance and intervention data and a qualitative
interview of the leaders of the attendance team at a school with improving attendance. This chapter
begins by identifying the organization and the participants in the study and then moves into the
findings and results. The research questions grounding the study were:
1. What were the attendance patterns over time at Alpha High School?
2. What attendance interventions were offered at various levels of the system at Alpha
High School?
3. What were the perceptions of stakeholders at Alpha High School regarding the impact
of interventions?
Participating Stakeholders
The study took place at Alpha High School, an ethnically diverse northern Virginia high
school of over 2400 students (Virginia Department of Education, 2019a). Alpha High School’s
student population was a majority of both minority and economically disadvantaged adolescents
(Virginia Department of Education, 2019a). Nearly 30% of the students were English Learners
and just over 10% were students with disabilities (Virginia Department of Education, 2019a).
Table 2 represents the full school and subgroup demographic data from 2015-2019.

40
Table 2
Student Demographic Data from 2015-2016 School Year through 2018-2019 School Year
Group 2015-2016 2016-2017 2017-2018 2018-2019
F % F % F % F %
All Students 2400 100 2446 100 2404 100 2259 100
2 or More
Races
124 5.2 104 4.3 79 3.3 79 3.5
American
Indian/
Alaska
Native
7 0.3 5 0.2 8 0.3 5 0.2
Asian 200 8.3 205 8.4 201 8.4 188 8.3
Black 592 24.7 565 23.1 515 21.4 466 20.6
Hispanic 1183 49.3 1296 53.0 1358 56.5 1320 58.4
Native
Hawaiian/
Other Pacific
2 0.1 2 0.1 4 0.2 3 0.1
White 292 12.2 269 11.0 239 9.9 198 8.8
Economically
Dis-
advantaged
1496 62.3 1584 64.8 1622 67.5 1541 68.2
Special
Education
268 11.2 271 11.1 260 10.8 240 10.6
English
Learner
617 25.7 798 32.6 784 32.6 687 30.4
17 Years Old + 860 38.1

Note. F = frequency; % = percentage

41
To preserve the anonymity of students, the subgroups American Indian/Alaska Native
and Native Hawaiian/Other Pacific were excluded from all data reviews as they represented less
than 0.5% of students. The 17-Year-Old + category included any student who was seventeen
years old at the first day of that school year. These students could receive a different intervention
path as of the 2018-2019 school year than students under the age of seventeen and, in turn, were
examined in their own subgroup.
Historically, Alpha High School had only been implementing the attendance
interventions for students who were state mandated. However, when chronic absenteeism
became a factor for school accreditation in 2018, Alpha revamped its intervention processes and
added additional school-based interventions. Prior to the 2018-2019 school year, the state of
Virginia adjusted its school accreditation standards to include chronic absenteeism as an
evaluative factor. Virginia set the standard that to be fully accredited at a Level One (highest)
rating, 15% or less of the student population could qualify as chronically absent by the end of the
school year (Virginia Department of Education, 2018). At that time, Alpha High School’s
chronically absent rate was 34% (Virginia Department of Education, 2019a). To prepare for the
new accreditation standard, Alpha implemented multiple changes to their current attendance
monitoring and intervention system, both budgetarily and systemically. Despite having one of
the largest populations of students living in poverty in their school system of over ten high
schools, Alpha was able to make the largest improvement in attendance in the entire system for
the 2018-2019 school year (Virginia Department of Education, 2019c).
For this study, the student level attendance and intervention data were compared from the
2015-2016 to the 2018-2019 school year to identify trends and changes in attendance data and
compare those adjustments to the qualitative data provided by the attendance team interviews.

42
Full school year data were compared each year from 2015-2016 through 2018-2019. Only partial
data were available for the 2019-2020 school year due to the abrupt end of attendance data
because of COVID-19 closures and was therefore not included in the study. As this study was
focused on identifying the interventions or systems of interventions resulting in positive
attendance changes with students, the three lead coordinators and two significant contributors of
the school’s attendance team were interviewed.
Interview Participants
Alpha High School boasted over 150 instructional staff members, nearly all of whom
contributed to some portion of the attendance intervention process, according to stakeholders
interviewed. For the purposes of this study, the stakeholders most involved in decisions related to
attendance—the school’s most active attendance team members—were interviewed. The
school’s attendance team normally consisted of the principal, an assistant principal, two teachers
on special assignment (TOSA), an intervention specialist, an attendance officer, and a part-time
counselor. The assistant principal and two TOSAs analyzed the school attendance data and
coordinated with the other team members and the different school departments to implement
necessary interventions when needed. These three lead members of the attendance team, along
with two of the main implementers of interventions, were the participants interviewed for this
study. Table 3 describes the following demographic features of the participants: participant
name, participant job title. number of years on attendance team, description of responsibilities on
team. All participants’ names are represented with a pseudonym to protect participant
confidentiality.

43
Table 3
Attendance Team Member Demographics
Name Job Title Years on
Team
Team Responsibilities
Mark Teacher on Special
Assignment
3 Implement initial meetings; coordinate with
students on No Credit Status; oversee
Saturday school
Kathy Teacher on Special
Assignment
3 Implement initial meetings; coordinate with
students on No Credit Status; oversee
extended day
Sharon Assistant Principal 5 Oversee attendance team and all attendance
processes; coordinate with administrators for
interagency meetings
Miles Intervention
Specialist
1 Meet with students aged 17-1/2 and older who
are referred; perform home visits for
students and families the school cannot
successfully contact
Dan Retired Counselor 3 Implement initial meetings; access student data
reports; follow up with student cohorts

Results and Findings
This section reports on the results and findings from the data analysis and interviews as
they related to the research questions and the conceptual framework, focused on
Bronfenbrenner’s Ecological Model. Findings from both methods as they related to each
research question will be presented, followed by a summary.
Research Question 1
Research Question 1 asked the following question: What were the attendance patterns
over time at Alpha High School? Student attendance data were analyzed over a four-year span to

44
identify patterns in attendance among student subgroups. Data were examined from the 2015-
2016 school year through the 2018-2019 school year.
Attendance Outcomes
Table 4 represents the mean and median of the number of excused absences, unexcused
absences, and total absences, as well as the absenteeism rate, for all students at the school from
the 2015-2016 to the 2018-2019 school year. When examining the mean and median of number
of absences per student and absenteeism rate per student across the four years, significant
changes could be noticed in the 2018-2019 school year compared to the prior three school years.
A reduction in both the mean and median days absent could be seen for excused, unexcused,
total absences, and absenteeism rates in the 2018-2019 school year. The mean and median
reductions both supported that a majority of students at the school showed reductions in all forms
of absenteeism. Across all four years the median for each measure was multiple points lower
than the mean. A lower median than mean indicated that over half of the students at the school
had better attendance than the average number of missed days (indicating a smaller group of
students with significant numbers of absences) and that the largest groups of students had the
least number of absences.

45
Table 4
Mean and Median of Yearly Excused, Unexcused, and Total Days Absent and Absenteeism Rates
Year Excused Unexcused Total % Days Absent
Mean Median Mean Median Mean Median Mean Median
2015-2016 4.5 4 12.5 7 15.2 10 9.5 5.9
2016-2017 5.6 4 12.5 8 15.8 11 9.4 6.2
2017-2018 4.9 3 10.3 6 15.3 11 9.5 6.4
2018-2019 2.2 1 8.4 6 10.6 8 6.6 4.7

Table 5 and Figure 2 show the four-year comparison of chronically absent rates by
subgroup. The table and figure illustrate the drop in chronic absenteeism across all subgroups
during the 2018-2019 school year.

46
Table 5
2015-2016 Through 2018-2019 Percentage of Students Chronically Absent
Group 2015-2016 2016-2017 2017-2018 2018-2019
All Students 32.5 32.2 30.9 16.4
2 or More Races 37.9 33.7 36.7 12.7
Asian 31.0 27.8 26.4 8.5
Black 26.5 23.9 23.7 14.6
Hispanic 36.4 36.0 34.0 18.0
White 27.7 34.2 31.4 19.7
Economically
Disadvantaged
35.1 34.5 33.2 17.6
Special Education 42.5 40.6 32.7 25.0
English Learner 34.7 34.1 33.5 17.5

47
Figure 2
Four Year Comparison of Chronically Absent Rates by Subgroup

Analysis of both individual student attendance totals as well as student absenteeism rates
across four years of data indicates a reduction in absenteeism during the 2018-2019 school year.
The mean and median of student excused, unexcused, and total absences all dropped in the
fourth school year. Additionally, the percentage of students deemed chronically absent, having
missed 10% or more of school, also dropped in every single subgroup in the student body.
Four Year Data Comparison by Subgroup
A quantitative data analysis was conducted on four years of individual student full-day
attendance data to investigate trends in student attendance patterns among the student body and

48
key subgroups at Alpha High School. A full year of data was available for the 2015-2016, 2016-
2017, 2017-2018, and 2018-2019 school years. While intervention practices continued during the
2019-2020 school year, a full year of data was not available as the mandatory attendance
requirement for students was removed beyond March 13, 2020 due to the COVID-19
interruption to in-person instruction. The 2019-2020 school year was therefore not included in
the analysis. Each examined data set was composed of all students who were still enrolled at
Alpha as of the last day of each school year. Data were examined to discover trends among the
entire student population and among student subgroups based on ethnicity, socioeconomic status,
special education status, and English learner status. The percentage of students in each subgroup,
as well as the percentage of students in the overall population, who accrued a certain number of
unexcused absences and were subsequently likely to receive each intervention was determined.
Additionally, each student’s final absenteeism rate was calculated to determine which students
were designated as chronically absent (having missed 10% or more school days).
Each attendance intervention was considered likely to be implemented after students
accrued a specific number of full-day unexcused absences or unexcused class period absences, as
indicated in Table 6. As class period attendance data were not available, students who attained
ten full days of unexcused absences were designated as students likely to have received the No
Credit Status intervention while students who attained three full days of unexcused absences
were designated as students likely to have received the teacher contact intervention. Some
students may have received the intervention before this point if they were also experiencing
partial day unexcused absences, however those data were not available.
Chronic absenteeism rates were determined based on students’ total days absent, both
excused and unexcused, compared to their individual total days enrolled at the school. While the

49
state accreditation standards only calculate chronic absenteeism for students who were enrolled
at your school by the 30th school day, this study included data of all students who were enrolled
in the school at the end of the year. As each of the four examined school years had a total of
between 170 to 178 school days, a student enrolled for the full year was considered chronically
absent after 17 absences, whether excused or unexcused, as that constitutes 10% of the school
year.
The percentages of students likely to access each intervention were then compared to the
percentage of students who finished the year classified as chronically absent. Additionally, the
subgroup percentages were determined based on the number of students in that subgroup likely
to have received an intervention compared to the total population in that subgroup, not the total
population in the school. The subgroup data were then compared to the overall school data to
determine which subgroups were likely to have accessed interventions more frequently than
other subgroups. Students were still included in intervention rates regardless of whether they
were determined to be chronically absent by the end of the year. Finally, frequencies of
intervention access and chronic absenteeism rates were compared across all four years of data to
identify changes in frequencies year to year.
2015-2016
Table 6 represents the full school and subgroup attendance and intervention data from the
2015-2016 school year. Table 6 shows the percentage of total students likely to have accessed
each intervention during the 2015-2016 school year as well as the percentage of students who
were determined chronically absent by the end of the year. For example, Table 6 shows that
75.4% of all students were likely to have received the teacher contact intervention, while 80.6%
of students of two or more races were likely to have received the same intervention. During the

50
2015-2016 school year, Alpha High School showed an overall chronic absenteeism rate of
32.5%. The subgroups of two or more races (37.9%), Hispanic (36.4%), Economically
Disadvantaged (35.1%), Special Education (42.5%), and English Learners (34.7%) all showed
chronically absent rates higher than the general school population. The population with the
lowest chronic absenteeism rate was Black students at 26.5%. The largest reduction between
interventions occurred between the teacher call (three unexcused) and the initial meeting (five
unexcused absences) with an overall drop of 14.9% (an average of 7.5% per accumulating
absence) and a subgroup drop ranging from a 12.9% (Hispanic students) drop to an 18.9%
(Black students) drop. The smallest reduction occurred between the interagency meetings and the
referral to the Attendance Officer with an 11.4% overall drop or a 3.8% drop per accumulated
absence for all students. There was a 42.9% drop among all students who likely received at least
one attendance intervention and students who were chronically absent by the end of the school
year, with the largest drop among Black students (47.5%) and smallest drop among Asian
students (33%). There was a 5.7% drop for overall students from the last implemented
intervention, referral to the Attendance officer, to the state of being chronically absent.

51
Table 6
2015-2016 Percentage of Students Receiving Interventions and Chronically Absent
3 Class
Absences
5 Full-
Day
Absences
6 Full-Day
Absences
7 Full-Day
Absences
10 Full-
Day
Absences
Absent
10% of
School
Year
a

Group Teacher
Call
Initial
Meeting/
Letter
Counselor
Call

Interagency
Meeting

Referral to
Attendance
Officer
Determined
Chronically
Absent
All Students 75.4 60.5 55.0 49.6 38.2 32.5
2 or More
Races
80.6 66.1 60.5 53.2 44.4 37.9
Asian 64.0 49.5 46.0 42.0 34.5 31.0
Black 74.0 55.1 48.1 42.1 30.2 26.5
Hispanic 79.3 66.4 61.5 56.2 44.2 36.4
White 67.8 52.7 45.9 41.4 29.5 27.7
Economically
Disadvantaged
78.6 63.8 58.8 53.3 42.2 35.1
Special
Education
82.5 69.4 64.9 56.7 42.9 42.5
English
Learner
76.5 62.9 57.4 52.5 42.5 34.7

a
17 absences if enrolled for full school year.

2016-2017 and 2017-2018
Attendance trends similar to those that occurred during the 2015-2016 school year
continued through the 2016-2017 and 2017-2018 school years. Table 7 represents the full school

52
and subgroup attendance and intervention data from the 2016-2017 school year, while Table 8
represents the full school and subgroup attendance and intervention data from the 2017-2018
school year.
During the 2016-2017 school year, Alpha High School showed an overall chronic
absenteeism rate of 32.2%, a minimal drop from the previous year. During the 2017-2018 school
year, Alpha High School showed an overall chronic absenteeism rate of 30.9%, an additional
1.3% drop from the previous year. The same subgroups from the 2015-2016 year, with the
addition of White students, all continued to show chronically absent rates higher than the general
school population through both subsequent school years. Of those populations with chronic
absenteeism rates higher than the overall, each group showed a reduction from the prior year,
with the exception of White students, who showed a 6.5% increase in 2016-2017, and students of
two or more races, who showed a 3% increase in 2017-2018. The population with the lowest
chronic absenteeism rate continued to be Black students, who continued to show small
improvements through both subsequent years. The largest reduction between interventions
continued to occur between the teacher call (three unexcused) and the initial meeting (five
unexcused absences), while the smallest reduction continued between the interagency meetings
and the referral to the Attendance Officer. There were similar drops (49.5% in 2016-2017 and
45.6% in 2017-2018) among all students who were likely to have received at least one
attendance intervention and students who were chronically absent by the end of the school year.
Additionally, there were drops (7.8% in 2016-2017 and 3.1% in 2017-2018) similar to 2015-
2016 for overall students from the last implemented intervention, referral to the Attendance
officer, to the state of being chronically absent. Overall, there were small changes in attendance

53
data between the 2015-2016, 2016-2017, and 2017-2018 school years, but most trends remained
consistent.

Table 7
2016-2017 Percentage of Students Receiving Interventions and Chronically Absent
3 Class
Absences
5 Full-
Day
Absences
6 Full-Day
Absences
7 Full-Day
Absences
10 Full-
Day
Absences
Absent
10% of
School
Year
a

Group Teacher
Call
Initial
Meeting/
Letter
Counselor
Call

Interagency
Meeting

Referral to
Attendance
Officer
Determined
Chronically
Absent
All Students 81.7 66.7 60.5 54.0 40.0 32.2
2 or More
Races
86.5 76.0 71.2 59.6 42.3 33.7
Asian 70.2 54.6 50.2 43.4 33.7 27.8
Black 77.9 59.5 52.0 46.0 31.9 23.9
Hispanic 86.3 72.4 66.4 60.1 45.8 36.0
White 75.1 60.2 53.2 47.6 32.7 34.2
Economically
Disadvantaged
84.3 69.7 63.7 57.2 43.6 34.5
Special
Education
88.2 75.6 69.7 64.2 52.4 40.6
English
Learner
84.2 69.4 65.2 58.6 45.7 34.1
a
17 absences if enrolled for full school year.

54
Table 8
2017-2018 Percentage of Students Receiving Interventions and Chronically Absent
3 Class
Absences
5 Full-
Day
Absences
6 Full-Day
Absences
7 Full-Day
Absences
10 Full-
Day
Absences
Absent
10% of
School
Year
a

Group Teacher
Call
Initial
Meeting/
Letter
Counselor
Call

Interagency
Meeting

Referral to
Attendance
Officer
Determined
Chronically
Absent
All Students 76.5 62.1 55.6 49.7 34.0 30.9
2 or More
Races
69.9 59.9 57.0 51.9 38.0 36.7
Asian 61.2 44.8 40.3 37.3 20.9 26.4
Black 73.8 57.3 50.7 44.3 28.9 23.7
Hispanic 81.0 67.2 60.3 54.5 39.0 34.0
White 73.6 60.7 52.7 45.2 27.6 31.4
Economically
Disadvantaged
78.6 64.5 58.6 53.1 37.0 33.2
Special
Education
80.4 66.9 60.4 53.8 38.8 32.7
English
Learner
80.0 65.9 59.2 54.0 38.8 33.5

a
17 absences if enrolled for full school year.

2018-2019
Table 9 represents the full school and subgroup attendance and intervention data from the
2018-2019 school year. During the 2018-2019 school year, Alpha High School showed an
overall chronic absenteeism rate of 16.4%, a 14.5% drop from the previous year and significant

55
improvement from all prior years. The subgroups of Hispanic (18.0%), White (19.7%),
Economically Disadvantaged (17.6%), Special Education (25.0%), and English Learners (17.5%)
all still showed chronically absent rates higher than the general school population; however, in
the 2018-2019 school year, every subgroup showed a reduction from the prior year, with all but
two groups (Black and Special Education) showing a decrease of over 10%. The most significant
decrease of 24% came from students of two or more races. The population with the lowest
chronic absenteeism rate was Asian students at 8.5%.
The largest improvement between interventions again occurred between the teacher call
(three unexcused) and the initial meeting (five unexcused absences), with an overall drop of
15.5% (an average of 7.8% per accumulating absence) and a subgroup drop ranging from a
12.6% (White students) drop to a 21.6% (students of two or more races) drop. The smallest
reduction occurred between the interagency meetings and the referral to the Attendance Officer,
with a 16.2% overall drop or a 5.4% drop per accumulated absence for all students. There was a
51.9% drop among all students who were likely to have received at least one attendance
intervention and students who were chronically absent by the end of the school year, with the
largest drop among students of two or more races (55.4%) and smallest drop among Special
Education students (42.6%). There was an 11.8% drop, a 4% improvement compared to the next
highest year, for overall students from the last implemented intervention, referral to the
Attendance Officer and eligibility for No Credit Status, to the state of being chronically absent.
This was also the first year that students aged 17 and older could be referred to the Intervention
Specialist. Of the 25.1% of students who were likely to have received this intervention, 20.7%
were chronically absent by the end of the year, a 4.4% reduction.

56
Table 9
2018-2019 Percentage of Students Receiving Interventions and Chronically Absent
3 CA
a
5 FDA
b
5 FDA
b
6 FDA
b
7 FDA
b
10 FDA
b
Absent
10% of
School
Year
c

Group Teache
r Call
Initial
Meeting/
Letter
Referral
to Inter-
vention
Special-
ist
d

Coun-
selor
Call
Inter-
agency
Meet-ing
Referral
to Atten-
dance
Officer &
No Credit
Status
e

Deter-
mined
Chron-
ically
Absent
All Students 72.6 57.1 25.1 50.4 44.4 28.2 16.4
2 or More
Races
68.4 46.8 12.7 41.8 41.8 29.1 12.7
Asian 60.6 45.2 24.5 38.8 27.7 15.4 8.5
Black 68.9 52.4 24.7 45.1 40.3 23.2 14.6
Hispanic 76.4 61.4 25.8 54.3 48.1 31.3 18.0
White 69.2 56.6 28.8 52.0 47.0 32.3 19.7
Economically
Dis-
advantaged
74.6 60.0 25.2 53.1 47.0 29.7 17.6
Special
Education
73.3 57.9 23.3 50.8 47.5 32.9 25.0
English
Learner
73.2 59.0 28.1 51.7 45.3 30.6 17.5

a
Class absences.
b
Full-day absences.
c
17 absences if enrolled for full school year.
d
Added
2018-2019 school year.
e
Added 2018-2019 school year and occurs at 10 class period absences.

57
Summary
The four-year analysis of attendance and intervention data of students at Alpha High
School revealed consistent attendance patterns during the first three years and significant
decreases in absenteeism during the fourth (2018-2019) school year. Decreases were apparent
across all subgroups at the school. Larger reductions were also observed during the 2018-2019
school year from the last implemented intervention (referral to attendance officer during the first
three years, but referral to the attendance officer paired with No Credit Status during the final
year) and the final chronic absenteeism rate. The three changes to interventions included in the
2018-2019 school year were the addition of the intervention specialist, the increase of staff
members involved in the interagency meeting, and the inclusion in the No Credit Status program.
All interventions across all four school years are examined in more depth in the following
section.
Research Question 2
Research Question 2 asked the following question: What attendance interventions are
offered a at various levels of the system at Alpha High School? Interviewees shared that multiple
interventions were offered at Alpha High School over a four-year period, including both state-
mandated, district-supported, and school-developed interventions. Specific interventions
discussed include teacher home contact, initial meetings with students, letters home, meetings
with an intervention specialist, counselor home contact, interagency meetings with students and
parents, referral to attendance officers, No Credit Status, and referral to juvenile intake.
State-Mandated Interventions
All five interview participants shared the list of the same four attendance interventions
required by the state of Virginia for accrued unexcused absences. Interventions include the initial

58
meeting, the interagency meeting, the referral to an attendance officer, and the referral to intake.
Interviewees shared that all state interventions were based solely on full-day unexcused
absences. While the state does not provide specific requirements regarding how and to what
extent each intervention is implemented, they do provide minimum guidelines under the Code of
Virginia 8VAC20-730-20 “Unexcused Absences Intervention Process and Responsibilities”
(Virginia’s Legislative Information System, 2021a). Both the school and state interpretation of
each level of intervention are summarized in the next section.
Initial Meeting
Other than the requirement to mark a student as “excused” or “unexcused” any time they
are absent from school and to request an explanation from the parent regarding the absence
(Virginia’s Legislative Information System, 2021a), the initial meeting is the first state-mandated
attendance intervention for accrued unexcused absences. The Virginia Code indicates,
When a student has received five unexcused absences, the school principal or
designee or the attendance officer shall make a reasonable effort to ensure that
direct contact is made with the parent. The parent shall be contacted in a face-to-
face conference, by telephone, or through the use of other communication
devices. During the direct contact with the parent and the student (if appropriate),
reasons for nonattendance shall be documented and the consequences of
nonattendance explained. An attendance plan shall be made with the student and
parent or parents to resolve the nonattendance issues. The student and parent may
be referred to a school-based multi-disciplinary team for assistance implementing
the attendance plan and case management. (Virginia’s Legislative Information
System, 2021a, C2)

59
At Alpha High School, prior to the 2018-2019 school year, Sharon shared that one staff
member, herself, monitored and implemented all initial meetings at the school. That staff
member would meet with any student accruing five unexcused absences and develop an
attendance plan. While the initial meeting only included the student, it was paired with the
school-sponsored intervention of the letter home to notify parents of the absences. Due to the
exorbitant number of students requiring initial meetings and the limited staffing to implement,
Assistant Principal Sharon shared that it “felt like we were just checking a box” to complete the
meetings. Because the attendance team was not confident that initial meetings were implemented
with fidelity and making an impact with students, they determined there was a need to change.
Alpha was able to begin changing their process for initial meetings in 2018.
During the 2018-2019 school year, multiple participants shared that Alpha increased its
staffing for initial meetings. They revealed that a retired counselor was hired to work two days a
week at the school focusing solely on the students requiring an initial meeting. Additionally,
Sharon elaborated that a school staff member who was heavily involved with the school sports
teams was assigned to help with initial meetings as part of their duty period and the two TOSAs
were available to assist when extra hands were needed as well. The initial meeting team was
divided to focus on specific student subgroups. The retired counselor worked primarily with
students aged 17 and older, many of whom he had already built strong relationships with. One
member explained that most of these students were not likely to qualify for referral to a court
case due to aging out of compulsory attendance laws so the counselor focused on motivational
factors more relevant to their life, including graduating and their future job search. Dan shared
that with the older kids he “would run a transcript for them and talk about graduation” and that
the meeting was “more in-depth.” He shared that “once they made a connection, they’d come

60
back and say, ‘When are you going to be here next week?’” Dan continued that he tried to
implement initial meetings as efficiently as possible in order to limit the time students spent
pulled out of class. He would pull a report of students, grades, transcripts, and previous
conferences to bring along to his meetings. While attendance was the primary reason for the
meeting, he wanted to hit on anything that was a concern for the student, allowing him to have a
more in-depth conversation and gain more rapport with the students. He also would pull students
briefly out of their classes to meet, instead of waiting for them to get a pass and then meet in the
office. He wanted to disrupt their time in class as little as possible, as these were students who
needed to spend more time in class.
Meanwhile, the teacher and the TOSAs were charged to work with the younger students
who may have needed very different levels of support and could present a long-term attendance
need. The TOSAs explained that the initial meeting process for younger students was very
similar to the process for older students except that there was more focus on the legal obligation
to attend school. At initial meetings, each team member was able to develop a student-specific
attendance plan indicating the unique supports required by that student. Miles shared that this
initial meeting,
…is just calling out the student from the classroom to let them know what’s going
on, that it’s a requirement by law to be in school. It’s not optional to put in place
the plan. To see if there are health problems or mental health problems or
connectivity problems to refer those to the staff.
Sharon additionally elaborated about the importance of developing a plan for each
student, sharing that,

61
they have a sheet that they have to fill out of what is your plan for this student
after talking to them. What are the supports that they need and if it’s something
they reach out to the counselor after the initial meetings now and say ‘hey this kid
has to put their elementary school sister on the bus, that’s why they’ve missed
first period’...and then that helps when the teacher has that background and they
realize well, yeah, be flexible with how I work with them, too, knowing what the
kid’s facing.
Plans were documented on a school form and in the school’s student information system,
so it is available to view by other staff members and carries with the students from year to year.
Attendance team members could also use the initial meeting to connect students with outside
supports, such as the school counselor or social worker, if a need presented itself. The counselor,
teacher, and TOSAs would then follow up with students on their caseload throughout the year to
monitor progress on their attendance plan. Dan shared that initial meetings were “kind of
checking their temperature and then we can determine from there what the best approach is. You
have to peel back the layers a little bit to find that out.” All participants agreed that the initial
meeting was a critical step in beginning the relationship building process with students which
they considered to be a major contributor to attendance improvements.
Interagency Meeting
If a student continues to accrue unexcused absences after completing the initial meeting,
an interagency meeting would be scheduled at the school. The Code of Virginia requires:
The school principal or designee or the attendance officer shall schedule a face-to-
face attendance conference, or an interaction that is conducted through the use of
communication technology, within 10 school days from the date of the student's

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sixth unexcused absence for the school year. The attendance conference must be
held within 15 school days from the date of the sixth unexcused absence. The
conference shall include the parent, student, and school personnel (which may be
a representative or representatives from the multi-disciplinary team) and may
include community service providers. (Virginia’s Legislative Information System,
2021a, C3)
The interview participants indicated that at Alpha High School the interagency meetings
were scheduled once a student accrued seven full-day unexcused absences. Prior to 2018-2019,
all interagency meetings were run by the same staff member who completed the initial meetings.
One interviewee described that interagency meetings required a face-to-face meeting with the
student and all efforts were made to include the parent either in person or via phone. After
adapting interventions in 2018-2019, the interagency meetings were split equally among the
administrative staff at the school and included an assistant principal, the student, parent, and
truancy officer. Additional staff, including parent liaisons, a counselor, the social worker, the
school resource officer, intervention specialist or the community-based therapist liaison, would
also be invited to meetings where students may have presented unique attendance needs. Sharon
alluded to the impact of the new interagency system by sharing that
we could have seven, eight people in that meeting, and so when the parent walked
in, they were so thankful that everybody took that time, that basically whatever
we needed they were there to support us, too, because they realized at that point it
was a team.
Interagency meetings would be utilized to review the current attendance plan in place and
offer additional supports and adjustments to better support the student. Students and parents

63
would also be informed of the future outcomes of continued absenteeism, including the potential
for court charges. Miles shared that,
if a kid keeps being absent, then the interagency has to be put in place. The school
has to call the parents and the meeting has to be held with the parents and the
students to deal in a supportive way to understand what’s going on and offer
support and to let the parents understand that if absences keep coming, then the
court could be asked to intervene and there’s a process by law that we have to do
if we don’t see a change in their absence.
Interagency meetings were also documented in the school information system. Similar to
initial meetings, participants considered the student and family relationship building that
occurred in interagency meetings as a crucial contributor to improving attendance.
Referral to Attendance Officer
For students continuing to accrue unexcused absences beyond the interagency meeting,
the next intervention step is the referral to the attendance officer. The Virginia Code indicates
The school principal or designee shall notify the attendance officer or division
superintendent of the student's seventh unexcused absence for the school year.
The division superintendent or designee shall contact the Juvenile and Domestic
Relations Court intake to file a complaint alleging the student is a child in need of
supervision (CHINSup) or to institute proceedings against the parent. In addition
to documentation of compliance with the notice provisions of § 22.1-258 of the
Code of Virginia, all records of intervention regarding the student's unexcused
absences, such as copies of the conference meeting notes, attendance plan, and

64
supports shall be presented to the intake worker (Virginia’s Legislative
Information System, 2021a, C4).
At Alpha High School, the implementation of each of these interventions occurs on a
slightly different timeline. At ten full-day unexcused absences, students are officially referred to
the attendance officer; however, the attendance officer has usually already been invited to the
prior interagency meeting and is familiar with the student. Dan shared that the “attendance
officers got involved for the severe cases.” The attendance officer will then meet with the student
and family, either in school or at a home-visit, and determine, with input from the school,
whether the case needs to proceed to the court systems. The school-based attendance officer will
traditionally only work on cases of students under 17.5 years of age, as the older students will
not qualify for court. Mark shared that at “ten [absences students] are referred to the attendance
officer. If 17.5 and below they go to the officer who proceeds through the court process; if above
they go to the intervention specialist.” At Alpha, students who are 17.5 and older are instead
referred to the intervention specialist, a district-hired attendance officer who specifically focuses
on supports and interventions to encourage adult students to continue their education.
Referral to Intake
If a student continues to accrue absences after being referred to the attendance officer, the
school has the option to refer the student to intake to potentially begin court proceedings. During
the initial meeting, the interagency meeting, and the attendance officer referral, the school
consistently makes sure to remind students and parents that it is their legal obligation to attend
school and that failure to do so can result in legal actions. When a student has reached the intake
process, the school must file documentation of all of the prior attendance interventions that have
been implemented with the intake officer. Sharon shared that “when we go to intake, we have to

65
show we’ve done everything at the school possible.” The intake offer then has a meeting with the
student, parent, and school representative to review the case and either develop an attendance
plan for the student or refer the case to a judge to start the formal court process. Miles elaborated
that for the “intake process, we have to file documents and a meeting with the intake officer. He
tries to put in place a plan; if not, he will refer the case to the judge and then the formal process
starts.” If a plan is developed, the intake officer will review the plan after a designated time
frame to determine if the student is improving or if further action needs to be taken. If the student
is referred to a judge, Miles shared that possible actions include the parents being fined up to
$2,500.00, the student being placed in a shelter for up to ten days or even the student being
placed in the juvenile detention center.
Summary
During the entire four years of examined data, Alpha High School consistently
implemented all attendance interventions mandated by state law. However, when they felt that
interventions were not making a significant impact with students, they enhanced the state level
interventions to more specifically focus on individual student needs by adapting interventions at
the school level. The Alpha High School attendance team specifically tried to work to make
initial meetings and interagency meetings most effective by adding members to the team to assist
with both meetings allowing meeting facilitators to focus more time on individual students and
families. Additional intervention support from the school district further supported this initiative.
District-Sponsored Interventions
According to interviewees, the district largely provided consultation to schools and
assistance with analyzing data. However, for the small group of schools who were not on track to

66
meet their attendance-based accreditation goal, the district provided an additional support
employee to work with each school, referred to as an intervention specialist.
Intervention Specialist
Alpha High School received their first intervention specialist during the 2018-2019
school year. Participants explained that the intervention specialist is a district employee housed
under the student services umbrella. While a standard attendance officer is funded by the district
and typically shared between a high, middle, and elementary school, an intervention specialist is
an attendance officer assigned to work exclusively with one school and designated to work
specifically with students who were on track to be chronically absent and were also 17.5 years or
older. One interviewee expressed that adult students are a particularly difficult age group to
apply attendance interventions with as there are no legal repercussions for a student failing to
attend school once they turn 18. In the state of Virginia, the compulsory attendance law states
that
Except as otherwise provided in this article, every parent, guardian, or other
person in the Commonwealth having control or charge of any child who will have
reached the fifth birthday on or before September 30 of any school year and who
has not passed the eighteenth birthday shall, during the period of each year the
public schools are in session and for the same number of days and hours per day
as the public schools, cause such child to attend a public school or a private,
denominational, or parochial school or have such child taught by a tutor or teacher
of qualifications prescribed by the Board of Education and approved by the
division superintendent, or provide for home instruction of such child as described
in § 22.1-254.1. (Virginia’s Legislative Information System, 2021b)

67
As a result, students who are over 18 or approaching the age of 18 do not qualify for the
referral to intake as a possible intervention. Interviewees elaborated that the role of the
intervention specialist was to work with each student to identify individual barriers to attendance
and connect them with supports that would either overcome those barriers or motivate them to
commit to graduating. Kathy expanded that the intervention specialist “could be an attendance
officer who works mostly with seniors or students 17.5 and above who would not be bound by
the court system. They look at more creative ways to help these kids.” Like an attendance
officer, the intervention specialist could make home visits for students and families who are
difficult to reach. They would work closely with the school social worker to connect students and
families to additional supports, including access to health care for physical and mental health
issues. Milton shared that the intervention specialist would “work with 17.5 and older, special
ones with other problems like homebound, pregnancies, dropouts and those kinds of students
who were not able to take to court because they are already legal age and not required to attend
school.” He also shared that each year they attend a conference in the area to specifically connect
with community agencies that can provide support for families. The intervention specialist could
also, in extreme cases, identify programs outside of the school system, such as Job Corps, to
support students in attaining their high school diploma or GED. Participants felt that the family
relationship building and support provided from the intervention specialist contributed to
positive changes in attendance patterns for many students.
Summary
The only district-offered intervention was the assignment of an intervention specialist to
assist the attendance team at Alpha High School as needed. Interview participants all shared that
additional interventions were needed beyond those mandated by the state and supported by the

68
district, therefore Alpha High School also developed additional interventions specific to their
school.
School-Sponsored Interventions
In addition to the state-mandated attendance interventions and the district-sponsored
intervention specialist, Alpha High School has developed a set of school-based interventions.
According to interviewees, while the school-based interventions do target students with
unexcused absences, they are not limited to those with full-day absences like the interventions
mandated by the state. Some school-based interventions at Alpha High School focus on class-by-
class absences to identify students who are still consistently absent but may not be identified by
the state mandated monitoring procedures.
Four specific school-based interventions were identified by interviewees, including 1)
teacher contact; 2) letters home; 3) counselor contact; and 4) No Credit Status. Additionally,
Alpha reallocated school-based funding to further support all levels of interventions.
Teacher Contact
The Teacher Contact intervention is a teacher-instigated intervention that is applied any
time a student has accrued three or more unexcused absences in an individual teacher’s class.
One participant stated that at the point when that occurs, teachers are required to contact the
parent or legal guardian of the student to inform them of the absences and discuss a recovery
plan, if needed, for work that was missed. Each time a student is absent beyond the third,
teachers are then expected to continue to contact the parents. Kathy explained that by
implementing the teacher contact intervention, the school was also able to “start involving
[parents] in the process” and expanded that teachers should also be calling parents when students
accrue multiple tardies or when a student is going to be assigned to “No Credit Status,” an

69
intervention discussed later. Participants felt that by establishing the requirement of
communication between the parents and students, parents should be aware of a developing
attendance issue before a student reaches a more significant intervention level. The teacher
contact intervention has been a standard intervention practice in place for at least the last five
years at Alpha.
Letter Home
The Letter Home intervention occurs once a student has achieved five days of unexcused
full-day absences. A certified letter is sent through the mail and includes the students’ attendance
records and the school policies and procedures for attendance monitoring and reporting. The
letter is prepared by a school secretary and serves as an additional parent notification strategy to
help ensure that parents are still notified of the attendance issue even if they were not able to be
contacted for the initial meeting. The letters are also available in multiple languages and a
translated form is included if the family has indicated a home language other than English. The
letter home was first incorporated during the 2018-2019 school year when attendance associated
responsibilities were dispersed among more staff members.
Counselor Contact
The Counselor Contact is set to occur at some point after the state-mandated initial
conference but before a student would qualify for an interagency meeting. Most often,
counselors will call home when the student has earned their sixth full day absence. Counselors
are then able to discuss with parents about academic concerns the student may be experiencing in
addition to the attendance concerns. One team member shared that the counselor contact is used
to ensure that parents have been notified of the attendance concerns before more extreme
interventions are applied. Again, participants felt this was a critical contributor to building

70
relationships with families. The counselor contact intervention has been a standard intervention
in place for at least the last five years.
No Credit Status
No Credit Status is a teacher-initiated intervention that was newly developed at Alpha
High School for the 2018-2019 school year and has been continually adapted ever since.
Interviewees shared that initially, teachers could refer a student for No Credit Status once that
student had missed their class, unexcused, ten times. Once in No Credit Status, a student’s grade
would be changed to a 59%, a failing grade in this school system, until he or she had completed
the recovery time for that class. Once a student has completed their recovery time, their grade
would be adjusted back to the percentage they had earned from assessments. One participant
explained that students would need to make up 60 minutes for every missed 90-minute class
period. Students referred to No Credit Status would be required to meet with one of the two
school TOSAs to schedule the number of hours they needed for recovery. Mark expanded that
students were able to recover time in three ways: a personally scheduled session after school
with their teacher, attendance at the two-hour after school extended day session, or attendance at
the three-hour Saturday school session. If students attended the extended day session, their
teacher was supposed to identify work that the students should be focusing on while there. If
students attended the Saturday session, four teachers, one in each core content area of math,
English, science, and social studies, were paid to offer on-the-spot support to students in the
subject area of their choosing. Kathy explained that students could go in and out of No Credit
Status at multiple points during the school year and could also be in No Credit Status for
multiple classes at one time. If a student failed to complete their recovery time, they would fail
the class for the school year.

71
No Credit Status was a school wide initiative that required all teachers to engage.
Multiple participants commented that teachers needed to be trained regarding how to monitor
their students’ cumulative attendance as well as how to submit a referral, track make-up time
through the school year, and make the necessary grade changes. The system also required the
two TOSAs to meet with each student who was referred to the program, monitor the students’
make-up time, report back to teachers, and supervise extended day and Saturday school sessions.
A further change was made to the No Credit Status program during the 2019-2020 school year
when it implemented a tardy tracking system as well. The adapted system now accounted for the
idea that eight class tardies would equal one day of a No Credit Status absence. The change
added the additional monitoring requirement for teachers to maintain a tardy log on top of the
absence log. Interviewees explained that implementing all of these changes required a significant
level of buy-in and training from staff building wide. Regardless, they unanimously commented
that No Credit Status was considered the largest contributor to changes in attendance patterns at
Alpha High School.
Summary
Teacher contact, letters home, counselor contact, and No Credit Status were all
interventions developed specifically at Alpha High School to supplement the state-mandated and
district-supported interventions already in place. In order to support the multiple adaptations to
interventions practices, significant budgetary decisions needed to be made.
Budget Reallocation
One of the largest changes for the 2018-2019 school year, supported at both the school
and district level, was the reallocation of budgeting to support increased staffing for the
attendance team. The district was able to provide one full-time additional support employee, the

72
intervention specialist, to work exclusively with absent students at a cost of just over $90,000.00.
Additionally, the school supported the funding for one part-time counselor, an approximately
$37,000.00 cost, exclusively dedicated to attendance and two teachers on special assignment
with an additional cost of $5,000.00. During the 2019-2020 school year, the school additionally
decreased the teaching load of both TOSAs from five sections to three sections, so they had
additional time during the day to complete attendance duties. This required the school to provide
stipends to other staff to pick up the additional instructional sections at a further cost of
$52,000.00 to the school. As part of the No Credit Status initiative, the school needed to further
provide funding to support the four weekly teachers and one supervisor staffing Saturday school
as well as the one teacher running the daily extended day sessions at a weekly cost of just under
$1000.00 for 30 weeks. Between the school and district additional staffing, over $200,000.00 per
school year was reallocated to attendance. Participates identified that the largest impacts from the
increased funding supported the increased staffing to implement initial meetings, interagency
meetings, and the No Credit Status initiative. Significant fiscal resources were required to
implement the newly developed intervention practices.
Summary of Interventions
Alpha High School has been able to develop an extensive and unique attendance
monitoring and intervention system for its students. Table 10 provides a list of interventions
supported by state, district, and school levels, when they were implemented, and what
stakeholders were included in implementation.

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Table 10
Attendance Interventions at Alpha High School
Intervention Years Utilized When Implemented Stakeholder Involvement
Teacher Contact 2015-2016 to
2019-2020
3+ class period
unexcused absences
Teacher, student, parent
Letter Home 2015-2016 to
2019-2020
5 full-day unexcused
absences
Secretary, parent
Initial Meeting 2015-2016 to
2019-2020
5 full-day unexcused
absences
Attendance team member
(TOSA or counselor),
student
Referral to
Intervention
Specialist
2018-2019 to
2019-2020
5+ full-day unexcused
absences
Intervention specialist,
student, parent
Counselor Contact 2015-2016 to
2019-2020
6 full-day unexcused
absences
Counselor, student, parent
Interagency
Meeting
2015-2016 to
2017-2018
7 full-day unexcused
absences
Admin, student, parent,
attendance officer
Interagency
Meeting
2018-2019 to
2019-2020
7 full-day unexcused
absences
Admin, counselor, student,
parent, attendance officer
Optional: parent liaison,
social worker, community
therapist, school resource
officer, nurse
Referral to
Attendance
Officer
2015-2016 to
2019-2020
10 full-day unexcused
absences
Attendance officer, student,
parent
Referral to Intake 2015-2016 to
2019-2020
Varies beyond 10 full-
day unexcused
absences
Admin, attendance officer,
student, parent, intake
officer
Potential: judge
No Credit Status 2018-2019 to
2019-2020
10 class period
unexcused absences
TOSA, teacher, student,
parent, teacher academic
support staff

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Alpha utilized a blend of state-mandated, district-supported, and school-specific
interventions to build their comprehensive intervention system. The intervention system was
designed to build as students accrue additional absences in either the full-day or class period
tracks so students progress through each checkpoint instead of being randomly assigned
interventions. The intervention system additionally relied on the support from 100% of the
instructional staff at the school and comprised a stakeholder group of students, parents, teachers,
administrators, counselors, secretaries, and other school specialist personnel.
Research Question 3
Research Question 3 asked the following question: What are the perceptions of
stakeholders at Alpha High School regarding the impact of interventions? In interviews,
interviewees shared their perceptions regarding the impact of interventions on student
attendance, student grades, and executive functioning skills of students. Furthermore, interviews
participants were able to share personal perceptions regarding the contributing factors to the
changes in attendance patterns, including the importance of relationship building, personal
accountability, and school and stakeholder capacity. Each perception is explored more in-depth
in the following sections.
Primary Improvements
All interview participants shared a perceived improvement in attendance during the 2018-
2019 school year. Mark immediately shared that “data wise, our chronic absenteeism rate went
from 31.3% to 19%” and referred to it as a “dramatic drop.” Sharon shared that the changes in
the 2018-2019 school year had a “very good impact” on attendance and that teachers were
motivated to engage in the interventions because they saw personal attendance issues “almost cut
in half.” Participants further expanded that No Credit Status was the most prominent and

75
impactful addition to the intervention protocols. Kathy specifically shared when asked which
interventions were most helpful that “No Credit Status is the obvious one and part of No Credit
Status is a reflection piece.” Mark similarly answered, “No Credit Status, building relationships,
well a combination of interventions so having the meeting, while in the meeting, building
relationships, and then having interaction with the students at extended day and Saturday
school.” The quantitative data further support the perception of an attendance improvement
occurring during the 2018-2019 school year and indicated the specific changes during that school
year as addition of an intervention specialist and referral to the No Credit Status program.
Secondary Improvements
Interview participants shared multiple perspectives regarding other noticeable
improvements with students outside of the attendance realm that they felt were tied to the
changes in interventions, including grades and executive functioning. The most prominent
change was the perception that student grades were improving. Sharon shared that the staff at
Alpha realized that “attendance was one thing, but the grades were connected. So, even after we
got the kids back in the building, they were so behind we had to do something to support them.”
Realizing the connection between attendance and achievement, the Alpha attendance team felt it
was important to provide an intervention that helped students relearn the material missed during
their absences. Prior interventions focused on addressing the attendance-based behavior and
making a plan to improve attendance in the future, but did not always address the material deficit
that the student encountered during the absences. The No Credit Status recovery options each
focused on providing students with the time and a support to help them boost their academic
performance while building more positive attendance habits. Mark felt that students were
beginning to make time up with teachers after absences but before qualifying for No Credit

76
Status and, as a result, improved their performance in the class due to the extra remediation time.
Sharon specifically shared,
I think we had started seeing improved grades, too, for kids who had figured out
that it was going to catch up to them eventually, and they started to figure, let me
just get it done the first time and come to class.
She continued to share that No Credit Status served as a particularly strong motivator.
She explained,
…motivator right there and honestly probably also one of the connectors to why
the kids’ grades were better, because they were making up stuff in real time
versus like, oh, I now have to make up somehow and recover my grade from six
months ago.
In addition to the grade improvements, interview participants felt there were other
benefits in the development of student skills. All interview participants shared that as a result of
the implementation of No Credit Status, they felt that the entire student body began to improve
their executive functioning skills. After a few months of implementing the program, students
began seeking out the TOSAs to schedule their hours on their own before teachers had even
submitted the referrals. Mark shared that “they knew where they were and they knew how many
hours they needed to make up and by the end, they were scheduling their own time.” Participants
also elaborated that some students became proactive with their teachers and would schedule
make-up time after each absence that they could bank in case they ever accrued enough absences
to put them in No Credit Status. While the banking of make-up time does not positively support
improved attendance habits, it does support the associated improvements of increased academic
achievement. Kathy discussed that students who attended the recovery opportunities increased

77
their advocacy skills by self-selecting to attend certain remediation groups, even if that is not the
class that landed them in No Credit Status. There were even a few experiences of students who
had recovered all of their required time and they requested to continue attending sessions to
access the academic resources.
The student self-regulation with the tardy system is just another example of increased
executive functioning skills developed within the student body. When the No Credit Status
intervention began incorporating tardies into the equation, Kathy commented that
kids who before were like, whatever, about tardies; they don’t want to be on No
Credit Status, they don’t want to have to make that time up, so they would start
getting to class, so they make the effort to get there.
Additionally, all interview participants felt that after the student body had completed one
year of the No Credit Status system, the majority of students were far more cognizant about their
absences and tardies in the next school year. While some students may have been skeptical that
the program would actually be implemented and not just threatened, the follow-up from the staff
and attendance team and the significant communications that went out to the community helped
solidify the confidence that students would have to face the consequences of No Credit Status.
Interview participants shared that in the 2019-2020 school year, far fewer students waited until
the end of the year to make up their time to recover from No Credit Status and were instead
participating in the recovery opportunities as they were assigned, yet another improvement in
self-regulation. From the perceptions of the attendance team stakeholders, the implementation of
No Credit Status not only improved the chronic absenteeism rate for the school but also
improved multiple secondary skills of students. Stakeholders shared additional perceptions
regarding the contributing factors to the success of the program.

78
Contributing Factors
While all interview participants reported a perception that the implementation of the No
Credit Status intervention was a significant factor contributing to the improvement of the
absenteeism rate at the school, they expanded to share about the specific attributes of the
program that they felt influenced the change. The three biggest factors discussed were
relationship building, increased accountability, and increased capacity. Each of the three factors
is explored in the following section.
Relationships
Relationship building was reported from all interview participants as the largest
contributor to improved attendance for students. Mark summed it up when he stated,
Personal relationships are involved there, too, because you’re not just sending
kids a slip but you’re getting to know them, getting to know what are their issues.
That’s a big part because you remember their names, you know them, you know
what’s going on. Building relationships, that was probably the biggest thing that
happened whenever we started improving our data. Improving our numbers was
because of the relationship building with the kids because the kids actually knew
that we were invested in them so they would actually show up.
He further shared the students “need somebody to talk to so sometimes we’re the ones
that they have to talk to or they want to just release on. Sometimes we’re the one that they feel
comfortable with for giving us information we didn’t have.” Dan expanded that
Attendance has always been a detriment to the kids’ success. We’re just trying to
get the kids in school...A lot of time kids, because no one will listen to them, they
just stop coming...You make that connection, a lot of kids are afraid to take that

79
first step. I don’t feel like I was enabling; some of these kids need their hand held
through this stuff….I tried to have a little more personal care.
Kathy provided similar sentiments when she said, “I think that’s what it really comes
down to at the end is that relationship. You have a relationship with someone, they want to do
it.” Sharon elaborated that it was not just the relationships with the students that influenced the
positive change. The focus on building relationships with families also played a role. She shared
that in interagency meetings
we could have seven, eight people in that meeting and so when the parent walked
in, they were so thankful that everybody took that time, that basically whatever
we needed, they were there to support us, too, because they realized at that point it
was a team.
She further explained that the impact from involving the parents early and often
throughout the entire process helped solidify the trust with the families that the school was there
to support them. Throughout all levels of interventions, a focus for all stakeholders at Alpha
High School has been presenting opportunities for support and growth, not judgement. Miles
specifically shared that meetings with parents and students had to be held “to deal in a supportive
way, to understand what’s going on and offer support” and continued that “when we see students
have huge problems with attendance, it should be a meeting together to help the student and
family.”
This mentality has helped build stronger relationships between the school, students, and
parents which fosters the perception that relationships at all levels of the system are a main
contributing factor to developing positive attendance habits in students.

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Accountability
Interview participants also felt that the added level of student and staff accountability was
an additional contributing factor to the decrease in chronic absenteeism. The attendance team
shared that students no longer had a vague link between attendance and achievement. The new
system made it very clear that they had to attend class, or they would fail the class. Mark
expressed that it made
students accountable just because they knew where they were at, they knew how
many hours they needed to make up and by the end they were scheduling their
own time with us. They’re coming saying, ‘I need to make up four hours, I need
to come to Saturday school,’ or, for example, ‘I need extended day today and
Thursday to make up four hours because I need that or I’m going to fail.’ So, it
made the kids accountable. It gave them a piece.
Dan corroborated that “it really got the attention of the kid.” While the state focused on
accountability for the school, Alpha moved a portion of that accountability to its students.
Attendance was now owned not only by the administration or by the school staff, but it was also
owned by all of the school stakeholders, including parents and students. Teachers were
accountable for tracking their students’ attendance, contacting parents, and referring students for
support, the attendance team was accountable for implementing the interventions and connecting
students and families to supports or risk losing accreditation, and students and parents were
accountable for engaging in those interventions or risk failing classes or even legal action.
Sharon shared,
We communicated a lot because we wanted to make sure that parents knew
exactly where we stood every step of the way. Even at the end of the year, the

81
principal sent out a letter saying don’t forget No Credit Status, your child needs to
make up these hours. And I think at the end, to be honest with you, we had one
kid, I think, that did not make the time up and we did something to help them
make that time up because we made sure that they did.
The attendance team not only became accountable for checking the boxes required for
state accreditation, but they also became accountable to support each student to succeed in the
program that they created for them. That level of accountability in committing to student success
is believed to be a main factor supporting the success of the program.
Capacity
Even with a strong focus on building relationships and stakeholder accountability, all
interview participants felt the program would not have been nearly as successful without the
resources and staff buy-in to implement the program with fidelity. Alpha High School budgeted
for multiple additional staffing positions to allow for the personalized meetings and staffing of
No Credit Status recovery time. They expanded the size of their attendance team from one
person, an assistant principal, to seven people—an assistant principal plus a counselor, three
teachers, an intervention specialist, and an attendance officer. They expanded the role of all
teachers in the building, developed a monitoring and reporting system, and trained the whole
staff on implementation of the new system. Sharon shared the importance
to have the staff, the people that will put in the work, because I created
relationships that first year when I did it by myself, but it was so much that I
couldn’t do as one person. You’re never going to touch as many people as the
whole team doing it, that teamwork is important.

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She continued to touch on not only the importance of the human support, but also the
importance of the budgetary support and was honest in sharing that “we spend a lot of money on
our attendance team.” Miles additionally shared about the need to be knowledgeable about the
resources and supports available to families when you are meeting with them. It is not only the
resources needed to implement the school interventions that are important, but school personnel
also need connections to community, mental health, and physical health programs to be able to
pair students with the appropriate support. Having the conversation with the family is important,
but being able to act on that conversation is what makes changes. Miles shared the importance of
having the staff to do home visits when he said, “home visits, it’s a good resource because you
really see how the families are doing” and continued that it is a “huge help speaking Spanish
with families. When you speak to a person in a language they understand, that goes to the heart.”
He felt that his capacity to connect with families and connect them to the resources they need has
been a significant help for many students. Alpha High School’s attendance team perceived that
building capacity in their staff and having the resources to implement the attendance
interventions thoroughly and consistently allowed them to build relationships with students and
families and hold students accountable for their attendance actions, all resulting in positive
attendance outcomes for the whole school.
Summary
Alpha High School is a large northern Virginia high school with a majority of the
population of students living in poverty. When the state of Virginia incorporated attendance as
an accreditation factor in 2018, Alpha made changes to their school and district-based
intervention practices to try to improve their chronic absenteeism rate. In 2018-2019 the school
added an intervention specialist, three additional staff members to address attendance needs, and

83
incorporated the process of “No Credit Status” to the intervention processes that they were
already employing, including teacher contact, initial student meetings, parent letters, counselor
contact, interagency meetings including parents, and referrals to attendance officers and the court
systems.
A data analysis of the attendance and intervention data of all students at Alpha over a
four-year period was performed. The data were reviewed for the full school year for four years,
2015-2016, 2016-2017, 2017-2018, and 2018-2019. The data analysis showed that the year that
Alpha implemented the new intervention processes was the year with the lowest rates of chronic
absenteeism.
Five members of the school attendance team were also interviewed to gain information
regarding the perceptions of stakeholders about the impact of interventions at Alpha High
School. Interview participants shared that they felt there were improvements in student
attendance, grades, and executive functioning after the implementation of the new interventions.
They additionally expressed that they felt the focus on building relationships and increasing
accountability through the new interventions were key factors leading to the improvements.
Additionally, interview participants commented on the importance of having the capacity both
budgetarily and with staff buy-in as critical components of implementing the new interventions
successfully.

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Chapter Five: Recommendations
The purpose of this study is to determine attendance interventions that improve
attendance practices of students in poverty. This chapter contains a discussion of the results from
the quantitative analysis and the findings from the qualitative analysis and the implications of
those findings. Discussion compares the data trends with staff perceptions, identifies practices
suggested to support positive changes, and applies Bronfenbrenner’s Ecological Model
framework to attendance intervention practices. The chapter continues with recommendations for
practice related to implementing attendance interventions at the state, district, and school levels.
The chapter concludes with a discussion on limitations and delimitations related to the study
along with recommendations for future research.
Discussion of Findings and Results
Data from both the qualitative and quantitative analysis were compared to discover trends
in student attendance patterns and staff perceptions. A discussion of the findings uncovered in
Chapter 4 are included in the following section.
Data Trends and Staff Perceptions
Examination of the four full years of attendance data revealed a discernable drop in
chronic absenteeism for all subgroups of students during the 2018-2019 school year.
Specifically, when reviewing the data for all students, there was only a 1.6% range in chronic
absenteeism rates between the 2015-2016, 2016-2017, and 2017-2018 school years; however,
there was a 16.1% range when the 2018-2019 school year was added. Though fluctuating ranges
were noticeable across all of the subgroup data in the first three reviewed years, the same
significant drop was observed during the 2018-2019 school year for each student subgroup. The

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consistency in data trends across the subgroups indicated that there is some factor, unique to the
2018-2019 school year, that influences absenteeism rates.
Another notable data trend across the four years was the widening of the gap between the
yearly data examined across interventions. The initial intervention of a teacher call had a
difference of 9.1% of students receiving the intervention from the highest implemented year,
2016-2017, to the lowest year, 2018-2019. The following interventions showed similar
differences between the same two years with initial meeting at 9.6%, counselor call at 10.1%,
interagency meeting at 9.6%, and referral to the attendance officer at 11.8%. However, the range
for students chronically absent among the same two years was 15.8%, a 4.0% difference over the
next closest intervention. These trends again supported a factor contributing to changes in the
2018-2019 school year.
Furthermore, the difference between the percentage of students receiving an initial
intervention and the percentage of students deemed chronically absent at the end of the year
shows a related trend. During the 2015-2016 school year, there was a 42.9% drop from
intervention one to being chronically absent. In 2016-2017, there was a 49.5% drop and in 2017-
2018, there was a 45.6% drop, all comparable amounts. However, in 2018-2019 there was a
56.2% drop between students who received the first intervention and were chronically absent at
the end of the year. The 6.7% increase over the next closest year of data further indicated a
practice exclusive to 2018-2019 impacting the data.
Qualitative data also indicated an improvement in attendance during the 2018-2019
school year and identified potential contributing factors to that improvement. All interview
participants shared that they felt there was a significant improvement in student attendance by
the end of the 2018-2019 year. Additionally, they shared impressions that grades had also

86
improved overall. While no grade data were reviewed in this study, this perception is supported
by the literature. Research suggests that increased absenteeism is associated with decreased
academic achievement (Gottfried, 2011; Gottfried, 2014; Oregon Department of Education,
2015). Hence, an improvement in attendance similar to one seen at Alpha during the 2018-2019
school year could also support an improvement in academic performance.
Participants additionally shared perceptions regarding factors that positively impacted
attendance. The most often noted factor contributing to positive attendance changes was the
addition of the No Credit Status intervention during the 2018-2019 school year. Specifically,
participants shared that the increased focus on relationships as well as the focus on improving
student self-regulation associated with the intervention supported the improvements. Research
supports both assertions. Gase et al. (2016) shared that a main promoter of positive attendance
habits for students is having an engaging relationship with teachers and other adults in the
building. The No Credit Status intervention not only prompted a conversation about attendance
habits with the student and their teacher, but also connected each student with one of the two
TOSAs at the school who would conference with the student, make a plan, follow up with them,
and also see them at their recovery events. Each TOSA reported that many of the students on
their caseload would also seek them out to address both attendance and personal issues after that
relationship was established. Dembo and Eaton (2000) found that adolescents show deficits in
both time management and self-regulation abilities. Caprara et al. (2013) additionally shared that
developing higher self-efficacy in adolescents is a strategy to help change behavior traits such as
attendance. The No Credit Status intervention gave students a tangible connection between
attendance and achievement—if they do not go to class, they will not pass. Additionally, it
created an awareness for students about time management by either attending class the first time

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or needing to schedule make-up time. That accountability measure, paired with the increased
adult support to help students identify and practice better habits, could be a contributor to the
increased self-regulation in attendance habits perceived by interview participants and the
resulting improvements in attendance rates.
Bronfenbrenner’s Ecological Model Applied to Attendance Interventions
Bronfenbrenner’s Ecological Model examines the impact of environmental settings and
factors, and the interplay between those factors, on one’s human development (Bronfenbrenner,
1979). In the realm of student attendance interventions, schools would need to identify which
environmental factors, both within and outside of school control, have the strongest influence on
student attendance and then develop interventions that flow throughout the multiple
environmental settings impacting each student and counteract the negatively influencing factors.
From Bronfenbrenner’s perspective, influencing factors should not be viewed exclusively within
one environmental setting, but instead should be monitored to assess the impact and interaction
they have among the different layers of an individual’s environment and the ultimate impact on
the individual (Bronfenbrenner, 1979). From an attendance interventions perspective,
interventions should be developed to address the student, school, district, community, and state-
level influences, and how the combined influences affect the student in order to have the greatest
impact on the student.
Alpha has progressively been taking additional steps to adapt interventions to address the
whole student’s environment. Prior to the 2018-2019 school year, Alpha primarily focused
attendance interventions on the state requirements, limiting most interventions to the
macrosystem (Bronfenbrenner, 1979). Some of those interventions did filter down to lower
systems by requiring parent contact and student meetings and attendance plans (microsystem),

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but few focused on interventions that would address needs developed across the systems. The
decisions made in 2018-2019 to increase staffing and staff involvement at both the school and
district levels began making impacts at the exosystemic level (Bronfenbrenner, 1979) by
allowing the school to heighten parents’ understanding of the importance of attendance and
connecting families, especially those in poverty, to community supports to deal with other family
issues that may have a secondary impact on student attendance. The increased staffing then
trickled down to the mesosytem (Bronfenbrenner, 1979) by allowing for increased
communication between the school, parents, and students and increased access to academic
supports outside of the standard school day. Additionally, it fostered a greater school-wide focus
on building relationships between students and staff and the school and families, which
influences factors across Bronfenbrenner's systems. All of these intervention adjustments came
as a result of a change instigated in the macrosytem (Bronfenbrenner, 1979), including
attendance as an accrediting factor for schools. The change at the state level prompted the school
to make a process change, which changed the relationship the school developed with parents and
families and adjusted the relationship between staff and students. The combination of all of these
adjustments made an impact on individual students to adjust their personal attendance choices.
In order to address the problem of increased chronic absenteeism among students in
poverty, schools, school systems, and state governments should develop attendance-focused
interventions that target factors across multiple environments that negatively impact student
attendance by applying Bronfenbrenner’s Ecological Model framework to attendance
intervention practices. This process requires adapting practices at the school, district, and state
levels in order to make impacts at the individual student level. The next section addresses
specific recommendations to positively influence student attendance practices.

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Recommendations for Practice
Multiple recommendations were developed framed by Bronfenbrenner’s Ecological
Model (Bronfenbrenner, 1979) to promote improvement of attendance habits for high school
students. The three recommendations are:
1. Policy Level Recommendation: Incorporate student-based graduation requirement
for attendance and develop a credit recovery program for students who are failing
or missing significant amounts of school.
2. State or District Level Recommendation: Fund a minimum of one full-time staff
member at each high school designated to solely address attendance interventions.
3. School Level Recommendation: Assign each student a staff mentor who will
monitor student academic progress, socio-emotional well-being, and attendance
while the student is enrolled at the school.
Each recommendation was founded in both findings from the study and previous research.
Recommendation 1
The first recommendation suggests incorporating student accountability measures at the
state level with a policy focused plan to incorporate a student-based graduation requirement for
attendance and develop a credit recovery program for students who are failing or missing
significant amounts of school. Currently in Virginia, there are academic-based graduation
requirements for all students in addition to passing the required number of classes. Students must
earn five verified credits (math, reading, writing, science, social studies) by passing the
associated state exam for at least one of their classes in each core area (Virginia Department of
Education, 2021b). The recommendation suggests adding a component that students must
complete at least 90% of the seat time requirement for each class to earn the course credit

90
towards graduation. If students do not meet the 90% requirement, they can recover the time by
engaging in a variety of alternative learning opportunities, including virtual credit recovery,
school-based credit recovery, completion of a personal skills course, or by applying for a waiver
for students with extenuating circumstances of excused absences. Like state waivers for testing
requirements, attendance waivers would only be available for students with significant health
concerns that prevent them from attending a comprehensive school regularly. In the state of
Virginia, students experiencing 15 consecutive days of absence, whether medical, excused, or
unexcused, are automatically unenrolled from their school and cannot access school resources or
services until they unenroll. The state waiver for attendance could help these students remain
enrolled with access to their school resources, while navigating their medical issues. By adding a
tangible attendance focus for students associated with each class, achievement in those classes is
likely to increase along with attendance.
Additionally, the student accountability measure should be paired with a resource to help
students recover when not meeting the standard, just as students are allowed to retest on state
required exams for graduation that they do not pass. The recovery focused recommendation
could be developed at a school, district, or state level and made available to students. The
recommendation involves developing a credit recovery program allowing students to recover
time or content from previously taught concepts in a class. Schools could utilize web-based
curriculum programs for students to access independently or develop their own set of recovery
curricular materials. Either way, students should be provided additional time outside of the
standard school day to engage in learning targets that they have not yet shown mastery in or that
they were not present to learn initially.

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Research supports that chronically absent students score lower on standardized tests than
their peers (Gottfried, 2011; Gottried, 2014; Oregon Department of Education, 2015). If students
are able to improve their attendance, their likelihood of passing the required standardized tests
for graduation and achieving higher grades in their courses required for graduation increases.
Gnambs and Hanfstingl (2016) shared that adolescents naturally experience a decrease in
intrinsic motivation, while Dembo and Eaton (2000) found that adolescents struggle with time
management and self-regulation. Given the developmental concerns of students in this age range,
providing a structured, extrinsic stimulus to attend school could be a helpful strategy to develop
positive attendance habits for students.
This recommendation is supported by the findings of this study regarding the No Credit
Status interventions. While that was a school-based intervention, it followed the same principles
as this state-based recommendation. Students had a personal accountability measure that was tied
toward passing a class, which is ultimately tied toward graduation. The intervention instigated
improvements in the development of student self- regulation skills and ultimately their
attendance. Like the No Credit Status intervention, a critical component of this recommendation
would be providing opportunities for students to recover missed class time after they are absent.
While No Credit Status gave the students the chance to recover time either after school or on a
Saturday, the state could offer a virtual credit recovery option and schools could offer site-based
recovery opportunities to help students both recover the missed time and improve course grades.
Qualitative data from this study further supported the benefits of students being provided with
time to focus on specific content missed in classes during absences or in classes that they were
struggling in. Sharon shared:

92
We noticed that attendance was one thing, but the grades were connected so we
had to, even after we got the kids back in the building, they were so behind, we
had to do something to support them, especially in classes like your math classes
where it builds up, so that was a huge thing that we did.
All participants shared a perceived increase in student achievement as a result of
implementing the No Credit Status intervention. The addition of a credit recovery program at
each school would not only enable students to recover missed school time, but it would also
enable them to recover missed content.
For students who are academically achieving in the class but still missing the time, an
alternative option could be available to recover time in a personal skills class that focuses on
increasing student executive functioning abilities. Lastly, just as there are waivers available for
state testing in extreme circumstances, students experiencing significant medical issues could
apply for the waiver to be exempt from the seat time requirement and connected with a program
that will better support learning based on their personal schedule.
Research supports that chronically absent students also experience difficulties with
academic achievement (Gottfried, 2011; Gottfried, 2014; Oregon Department of Education,
2015). Attendance interventions that only focus on getting students back into school may help
students with future achievement, but they do not address the missed learning opportunities from
previous absences. By helping students recover academically, students can experience increased
engagement levels at school which actually promotes future positive attendance and learning
habits (Gase et al., 2016; Gnambs & Hanfstingl, 2016; Onder, 2017).
Moving this support to a macrosystemic (Bronfenbrenner, 1979) level would also create
ripple effects in each of the other environments for the student, prompting all schools in the state

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to revisit their attendance intervention procedures and examine best practices in the area. Just as
the No Credit Status intervention was effective due to a combination of student accountability
and staff support, additional interventions would need to be implemented at the district and
school level to ensure schools had the capacity to implement the seat time requirement with
fidelity. Recommendations to support school and district-based attendance interventions are
found next.
Recommendation 2
The second recommendation for practice incorporates attendance intervention support
funded at the state or district level but implemented at the school level. Recommendation two
suggests funding a minimum of one full-time staff member at each high school designated to
solely address attendance interventions. While many high schools in Virginia have a designated
truancy officer with whom they work, these officers are often split between multiple schools in
the area. Recommendation 3 suggests that each high school in a district should have a minimum
of one district-funded employee designated to work with the school exclusively on attendance.
Further research should be performed to determine the student enrollment threshold for adding
additional attendance support employees. The composition of the student population should also
be taken into account. As the study showed that economically disadvantaged, special education,
and English Learner students have more chronic absenteeism than other subgroups, additional
staffing should be allocated to support the high need students in individual schools. A final
requirement of the recommendation would be for at least one of the attendance employees to
come from a counseling or social service-based background.
One major takeaway from this study was the importance of having the capacity to
implement interventions with fidelity considering the size and need of the student body. A major

94
issue at Alpha for many years was the lack of staffing supporting the attendance program. One
employee was responsible for implementing interventions for over 2000 students. The year that
additional budgeting was allocated at both a district and school level to increase attendance
focused staffing was the year with the largest gains in attendance. This exosystemic
(Bronfenbrenner, 1979) level intervention would provide the support schools need to adapt their
individual attendance intervention systems to meet their own specific needs instead of relying
solely on the implementation of state-mandated interventions.
Multiple organizational change theories highlight the importance of having the right
capacity and resources to implement change as a critical component. Clark and Estes (2008)
identify examining organizational processes and material solutions that need to be implemented
as a key step in identifying the gaps within an organization. McKinsey’s 7S framework shares
the importance of having the right staff, structures, and skills required to achieve organizational
objectives effectively (Singh, 2013). Additionally, Kotter’s Eight Step Process for Leading
Changes highlights the importance of enlisting the necessary volunteers to support the change
and removing barriers prohibiting the change (Wheeler & Holmes, 2017). Each of these change
models support the need for districts to provide their schools with the necessary resources to
implement the interventions needed to spark change in attendance patterns of students.
Recommendation 3
The final recommendation would be executed at a school-based level and suggests
assigning each student a staff mentor who will monitor student academic progress, socio-
emotional well-being, and attendance while the student is enrolled at the school. This
recommendation suggests that a school should develop a mentoring program which pairs all
school staff members with a small group of students with whom they work closely throughout

95
their entire time in high school. This program would have the same mentors move with cohorts
of students throughout their four years of high school. Time would be embedded into the school
schedule for mentors to meet with their student groups at least monthly, but preferably weekly.
Meetings would focus on building relationships with students and developing students’ executive
functioning skills. Mentors would also monitor student academic progress, attendance, and
general socio-emotional wellbeing and would be the first to make a referral for support when
they notice negative patterns developing in any of the three areas.
All of the interview participants shared the importance of relationships as a key factor for
building positive attendance habits with students. They further shared the importance of having
multiple staff members who were able to connect with students and their families to establish an
environment of support, not judgement. Developing a mentoring program at each high school
would give each student and their parents at least one adult in the building each year to whom
they could go for support and advice when needed. It would also make sure that there was
always a staff member in the building monitoring student habits and connecting students with
supports before negative habits significantly increased. The mentorship program would provide
each student with a microsytemic (Bronfenbrenner, 1979) level support that could directly
monitor and respond to the influencing factors in each student’s environment.
Research supports that an engaging school environment where students can build
personal relationships and feel connected is a main support of positive school attendance (Gase
et al., 2016; Gnambs & Hanfstingl, 2016; Onder, 2017). Gase et al. (2016) specifically shared
that engaging relationships with teachers and other adults in the building was a main indicator of
students choosing to attend school. Onder (2017) found that many students cite the lack of an
engaging environment as a reason to not attend school. Furthermore, Gnambs and Hanfstingl

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(2016) spoke about the importance of students feeling relatedness to spark their intrinsic
motivation and, in turn, supporting consistent daily attendance. Creating a mentoring structure
for all students can assure schools that each student is connected to the school and is being
supported based on their individual needs.
Limitations and Delimitations
Despite all preparations made for this study, multiple limitations and delimitations still
existed. The truthfulness of respondents is a main limitation. Though many precautions are put in
place to ensure confidentiality of responses, participants may feel uncomfortable sharing certain
information if it could reflect negatively on themselves. This may be an issue as adults may feel
as if they were not doing jobs correctly if they have to share negative results and hence do not
share them openly and honestly.
Another main limitation was the lack of necessary data. Full-year attendance data were
not available for the 2019-2020 school year due to the early in-person closure because of
COVID-19. After the first 120 days of school, all attendance was optional for students for the
remainder of the year, so all attendance intervention practices ceased. Therefore, data from 2019-
2020 were not able to be included. Data on student mobility, drop-outs, and transfers was also
not available. The enrollment from the beginning of the 2018-2019 school year to the end
dropped by 163 students, however information on where those students relocated could have
provided additional information on effectiveness of interventions. Additionally, due to the
district-wide navigation over to a new student information system, all class period level
attendance data were erased for all years prior to 2019-2020. Considering that partial day
absences can also be a significant problem for schools, having that data to examine both student
group trends and to more accurately place certain interventions would have been helpful.

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Another limitation occurred based on the timing of administration for each data source.
Due to the interrupted school year during 2019-2020 because of COVID-19, full year student
data could only be examined from the 2015-2016 through the 2018-2019 school years; however,
interviews and surveys did not take place until the 2020-2021 school year. This gap in timing
may have resulted in less accurate recall by participants. A major delimitation of the study was
the choice to analyze the attendance intervention procedures from multiple school years, some of
which include old intervention procedures while others include new procedures developed after
the state accreditation standards were changed but before the interruption to the school year due
to COVID-19 closures. The processes and procedures developed for each data source also
contribute to certain delimitations. Interview participants were specifically selected due to their
knowledge of attendance intervention implementation and impacts at the school while the data
study specifically focused on students who had received at least one attendance intervention
throughout the analyzed school year.
An additional limitation occurred based on the lack of specific intervention records at the
school. While all interview participants shared that students who accrued certain absences would
have received interventions, when working with over 2000 students, there is also a likelihood
that some students would have been missed. Since the school only kept paper records for
attendance plans, which were destroyed after one full school year, there was no specific method
to confirm whether or not a student actually received an intervention. While interview
participants were confident that all required interventions were implemented, a paper or digital
log was not available to confirm.
A specific delimitation of the study was only focusing on interventions for unexcused
students. As chronic absenteeism accounts for both excused and unexcused absences,

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interventions for students in both domains should have been examined to provide more accurate
data regarding effective interventions. Expanding the study to examine all attendance-based
interventions at a school would create a more representative picture of effective school-based
practices.
Recommendations for Future Research
Multiple opportunities for future research arose from this study. Two attendance-specific
areas to further explore include investigating the impact of full-day excused absences and partial
day absences on students. Chronic absenteeism is a result of the combination of both excused
and unexcused absences. There are students who qualify as chronically absent who may not have
a single unexcused absence and are hence missing out on many school-based attendance
interventions. Exploring the causes, impact, and interventions for excused absences could
contribute valuable insight into supporting student attendance. Similarly, many students who
experience partial day absences may be experiencing disciplinary action at their schools, but will
not always qualify for attendance-focused interventions. Expanding the research to analyze the
attendance impacts for these students could also be helpful.
Further examining the practices and processes of implementation for interventions, and
how those processes vary from school to school, could be another area for research. Investigating
what specifically schools do to build relationships with students and families or the variety of
ways they institute student accountability measures and the impacts of each could refine
interventions focused on increasing relationship or accountability practices. Research in both
areas could more specifically identify which factors most significantly contribute to attendance
improvements.

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Additionally, a focus of future research could examine longitudinal data of individual
students. Most schools are subject to varying mobility rates of their students throughout the year.
Whether students move to a new school, a specialized program, earn their GED or simply drop
out of school, examining the long-term path and practices of students could provide more in-
depth detail to interventions that show a long-term impact on students.
Another focus for future research involves investigating the academic implications for
students who are chronically absent and for students receiving certain attendance interventions.
While some interventions may not be changing attendance habits, they may still be valuable if
they are supporting student academic achievement. Additionally, research on non-traditional
learning opportunities that incorporate flexible schedules, asynchronous learning opportunities,
and non-traditional school access could provide insight to support students who are struggling to
engage with the traditional school day and setting. Many students with significant attendance
issues could benefit from opportunities that can more creatively adapt to their learning styles and
needs outside of the traditional school building.
Conclusion
Students who are chronically absent are at increased risk to struggle academically
(National Center for Education Statistics, 2009), to drop out of high school (Allensworth, 2007;
Alonso et al., 2011), and to face potential future unemployment, incarceration, and dependency
upon welfare systems (Christenson et al., 2001). These risks are especially prevalent for students
in poverty, as these students miss up to three times as much school as their peers (Balfanz &
Byrnes, 2012). This study used Bronfenbrenner’s Ecological Model framework (Bronfenbrenner,
1979) to identify school-based attendance interventions that impact student attendance at Alpha
High School, a large northern Virginia high school with a majority of students living in poverty.

100
Based on detailed findings collected from interviews with the school attendance team and a five-
year attendance data analysis, specific recommendations were proposed at varying levels of
Bronfenbrenner’s Model to improve student attendance.
The study was able to identify a specific school year indicating dramatic improvements in
student chronic absenteeism rates. Findings suggested that a new school-based intervention
process known as No Credit Status, paired with an increase in staffing to improve
implementation of existing interventions, influenced the changes in attendance habits during the
2018-2019 school year. Findings further supported that the increased focus on building
relationships with students and increasing the student accountability factors for attendance were
also contributors to the positive change. Recommendations focused on processes that could be
implemented at school, district, and state levels to increase the capacity for schools to implement
relationship and accountability-based attendance interventions practices.
Given that one in five high school students were deemed chronically absent as of the
2015-2016 school year, states, districts, and schools need to prioritize implementing attendance
intervention practices to prevent these students from facing the academic and adulthood
challenges associated with continued patterns of chronic absenteeism. As chronic absenteeism
rates are even higher among students in poverty (Balfanz & Byrnes, 2012), failing to address
negative attendance patterns of these students will only widen the already prevalent achievement
gap (Virginia Department of Education, 2019d). By implementing attendance intervention
practices that support positive attendance habits of all students, schools can increase achievement
levels for all students (Gottfried, 2011; Gottfried, 2014; Oregon Department of Education, 2015),
giving their students an advantage when they leave the school support behind and join the adult
world.

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%20Matters%20Final.pdf
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D. (2011). Destination graduation: Sixth grade early warning indicators for Baltimore city
schools their prevalence and impact. Baltimore Education Research Consortium.
http://www.baltimore-berc.org/pdfs/SixthGradeEWIFullReport.pdf
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Appendix A: Interview Protocol
1. Describe your position on the attendance team.
2. What attendance requirements are recommended at the state level?
3. What attendance requirements are dictated at the school level?
4. What were the attendance intervention procedures in place prior to the 2018-2019 school
year?
5. Were any changes made to attendance interventions due to the new state accreditation
standards? If so, walk me through that process.
6. What were the attendance intervention identification procedures for the 2018-2019 school
year?
7. What were the school-based attendance interventions?
8. In what ways were school staff involved in the attendance interventions?
9. In what ways were district staff involved in the attendance interventions?
10. What were the community-based attendance interventions?
11. In what ways were parents involved in the attendance interventions?
12. How do you determine which interventions to implement?
13. How are attendance interventions related or not related to one another?
14. What changes in student behavior/data trends have you witnessed since implementing the
new procedures?
15. What interventions or combination of interventions have you found to be the most helpful
in changing behaviors?
16. What interventions have you found to be the least helpful in changing behaviors?
17. What challenges were faced as you were working to implement interventions?

111
18. Is there anything you wish you would have done differently during the past school year?
19. Are there any interventions that are needed but are not currently able to be implemented?

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“Going up the river”: the consequence of response & the assumptions that underlie, support, and justify the practices of educational leaders for chronically absent youth

Asset Metadata

Creator Chapman, Jennifer Ann (author)

Core Title School-based interventions for chronically absent students in poverty

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Publication Date 04/28/2021

Defense Date 04/15/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Adolescent,attendance,chronic absenteeism,High School,interventions,OAI-PMH Harvest,Poverty,student,truant

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Malloy, Courtney (committee chair), Muraszewski, Alison (committee member), Stowe, Kathy (committee member)

Creator Email curryj@usc.edu,jencurry84@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-456609

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Legacy Identifier etd-ChapmanJen-9560.pdf

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