effect of socioeconomic status on middle school …

Running Head: Effect of SES on Attendance and MAP Scores 1

EFFECT OF SOCIOECONOMIC STATUS ON MIDDLE SCHOOL STUDENTS’

ATTENDANCE RATES AND MISSOURI ACHIEVEMENT PROGRAM

COMMUNICATION ARTS AND MATHEMATICS SCORES

By

Bob Willis

Submitted to

The faculty of the Educational Specialist Program

Northwest Missouri State University

Department of Educational Leadership

College of Education and Human Services

Maryville, MO 64468

Field Study Committee Members

Dr. Timothy J. Wall

Submitted in Fulfillment of Graduation Requirements for

61-723 WRITING & INTERPRETING EDUCATIONAL LITERATURE AND STATISTICS

AND 61-724 FIELD STUDY

Effect of SES on Attendance and MAP Scores 2

ABSTRACT

This study investigated the effect of socio-economic status (SES) on students’ attendance and

students’ achievement as measured by the communication arts and mathematics sections of the

Missouri Assessment Program (MAP) test. This study addressed existing data on current

seventh and eighth grade students at the middle school level in suburban Kansas City, Missouri.

This study used a causal-comparative research design to examine existing data on two groups of

students, based on their Free and Reduced Lunch (FRL) status. In this study, FRL status was

used as the determinant for SES. The students who were on FRL had statistically significant

(p=.000-.002) lower mean attendance rates and lower mean communication arts and mathematics

scale scores on the MAP test than their non-FRL peers. In addition, students’ attendance and

students’ achievement on the MAP test was shown to have a statistically significant (p=.000-

.029), negligible to weak positive relationship.


TABLE OF CONTENTS

ABSTRACT .........................................................................................................................2

LIST OF TABLES ...............................................................................................................7

CHAPTER ONE: INTRODUCTION TO THE STUDY ...................................................8

Background

Conceptual Underpinnings

Statement of the Problem

Purpose of the Study

Research Questions

Null Hypotheses

Limitations of the Study

Delimitations of the Study

Definition of Terms

Summary

CHAPTER TWO: REVIEW OF RELATED LITERATURE ............................................16

Overview


History of the National School Lunch Program

Student Certification for Free and Reduced Lunch

The Use of Free and Reduced Lunch as a Socio-Economic Status Determinant

Socio-Economic Status and Attendance

Socio-Economic Status and Achievement

The Relationship of Attendance and Achievement

Summary of the Literature Review

CHAPTER THREE: RESEARCH METHODOLOGY ...................................................28

Problem and Purpose of the Study

Study Group

Research Design

Variables Used in the Study

Research Questions

Null Hypotheses

Instrumentation and Data Collection

Data Analysis Strategies

Summary


CHAPTER FOUR: PRESENTATION AND ANALYSIS OF DATA ............................35

Overview

Statement of the Research Questions

Results and Discussion for Research Question One

T-Test for Statistical Significance Between SES and Attendance

Results and Discussion for Research Question Two

T-Test for Statistical Significance Between SES and MAP Scores

Results and Discussion for Research Question Three

CHAPTER FIVE: OVERVIEW, FINDINGS AND RECOMMENDATIONS ...............45

Overview

Summary of Research Methods

Data Analysis

Discussion of Findings

Conclusions

Recommendations

APPENDIX A ....................................................................................................................53

APPENDIX B ....................................................................................................................54


REFERENCES ..................................................................................................................55


LIST OF TABLES

Table 1: The Relationship Between SES and Attendance (2011-2012) ...........................37

Table 2: The Relationship Between SES and Attendance (2012-2013) ...........................39

Table 3: The Relationship Between SES and MAP Scores for Current 7th

Graders ........41

Table 4: The Relationship Between SES and MAP Scores for Current 8th

Graders ........42

Table 5: The Relationship Between Attendance and Achievement for Current 7th

Graders

............................................................................................................................................44

Table 6. The Relationship Between Attendance and Achievement for Current 8th

Graders

............................................................................................................................................44


CHAPTER ONE

INTRODUCTION TO THE STUDY

Background

Numerous studies in the past have examined students’ socioeconomic status and the

effect it can have on achievement (Harwell and LeBeau, 2010;Sirin, 2005; Stull 2013). The

same can be said for studies attempting to determine the link between students’ absences and

achievement (Gottfried, 2009; Gottfried, 2010; Gottfried, 2011; Ready, 2010; Morissey,

Hutchinson and Winsler, 2013). Because students’ achievement is of great importance for all

parties involved in the educational process, any factor affecting achievement should be closely

examined so that achievement can be maximized.

With the passage of the No Child Left Behind act (NCLB) in 2001, assessment and

accountability for student achievement became even more important to school districts (Braden

and Schroeder, 2004). For schools failing to meet adequate progress, federal funding can be

withheld (Braden and Schroeder, 2004). Because K-12 assessment is often measured through

standardized testing, it is important for educators to understand the factors which can affect test

scores.

In 2011, it was announced that states could apply for a waiver in order to free them of

some of the requirements of NCLB. As of September 2013, 42 states had been granted waivers

(U.S. Department of Education, 2013). Missouri is one of these states (Missouri Department of

Elementary and Secondary Education, 2012; Missouri Gets No Child Left Behind Waiver,


2012). One of the requirements for receiving a waiver from NCLB is that states improve their

teacher evaluation systems, to include student growth and achievement as part of teacher

evaluations (Missouri Department of Elementary and Secondary Education, 2013; U.S.

Department of Education, 2013;). Because the Missouri Assessment Program (MAP) test is the

primary assessment tool for the state of Missouri (Missouri Department of Elementary and

Secondary Education, 2012), the measurement of student growth and achievement in Missouri

could possibly include student scores on the Missouri Assessment Program (MAP) Test. Under

the new Missouri Educator Evaluation System, student scores are now a part of a teacher’s

evaluation and can carry weight in any personnel and employment decisions a school might

make (Bock, 2012; Missouri Department of Elementary and Secondary Education, 2013). In

other words, student performance will help to determine a teacher’s proficiency level, and could

bear weight on whether or not a teacher is retained or let go (Missouri Department of Elementary

and Secondary Education, 2013).

Due to current legislation and the way in which Missouri Educators will be evaluated,

student achievement as measured by the MAP test is not only important for the student, but also

for teachers and administrators. While student achievement and success is the ultimate goal for

educators, the new evaluation system must also be taken into account. It is for these reasons that

all factors affecting student achievement should be examined in hopes of improving

achievement. (Bock, 2012; Missouri Department of Elementary and Secondary Education,

2013).

This study will examine student achievement as measured by the Missouri Assessment

Program in two middle schools in Suburban Kansas City, Missouri. The study will attempt to

determine if socio-economic status has an effect on student attendance and achievement, while


attempting to gauge the level of relationship, if any, between attendance and performance on the

communication arts and mathematics portions of the MAP test.

Conceptual Underpinnings

In numerous studies, socio-economic status (SES) has been shown to be one of the

strongest correlates of student achievement (Barry, 2006; Sirin, 2005; Stull, 2013). In many of

these studies, student eligibility for free and reduced lunch (FRL) has been the determinant for

grouping students as low SES (Abbott and Joireman, 2001; Harwell and LeBeau, 2010; Sirin,

2005). While being eligible for FRL is not a fully descriptive determinant of SES (Harwell and

LeBeau, 2010; Lubienski and Crane, 2010; Sirin, 2005), it is a measure that is often used in

research because it is available for every student, is linked to government guidelines, and is easy

to obtain (Harwell and LeBeau 2010).

Student attendance has been shown to be positively correlated with student achievement

in past studies (Gottfried, 2009; Gottfried, 2010; Gottfried, 2011; Jones, 2006; Roby, 2004).

Some research has also been conducted in an attempt to find a relationship between SES and

attendance. Romero and Lee (2007) state that children from poor families are more likely to be

chronically absent than those with higher incomes. In their follow up to the 2007 study, Romero

and Lee (2008) examined maternal and family risk factors linked with student absences and

found that “children living in poverty, and to some extent low income children” (p. 3) were more

likely to be exposed to multiple risk factors than their higher income peers. In their study, the

authors found that children exposed to more risks were more likely to miss school than their

counterparts facing less risks (Romero and Lee, 2008).


Research has shown both SES and attendance to have an effect on student achievement.

In this study, the researcher will continue to investigate these two variables and their possible

effect on achievement, but also investigate the possible relationship between SES and

attendance.

Statement of the Problem

As a result of the importance of standardized testing, it is imperative that educators are

aware of any and all factors that may affect student achievement. While there is existing

evidence from past studies about the relationship of SES and student attendance and SES and

student achievement, much of it has focused on school-level data from the primary grades. This

study will add to the body of knowledge by investigating this relationship using student level

data at the middle school level, which is an extremely important transitional period for students.

Purpose of the Study

This study will attempt to determine if there is a difference in attendance rates or MAP

scores of two groups: students who are eligible for free and reduced lunch, and students who are

not eligible for free and reduced lunch. One purpose of this study is to determine if there is a

difference between students’ attendance rates based on their SES grouping. This study will also

attempt to determine if there is difference between students’ achievement level as measured by

the communication arts and mathematics sections of the Missouri Assessment Program (MAP)

test based on their SES grouping. Finally, this study will investigate whether or not there is a

relationship between students’ attendance rate and students’ communication arts and

mathematics MAP scores.


Research Questions

RQ1. Is there a significant difference in attendance rate at a suburban Kansas City,

Missouri school district when considering students from low SES backgrounds and those not

from low SES backgrounds?

RQ2. Is there a significant difference in communication arts and mathematics MAP

scores at a suburban Kansas City, Missouri school district when considering students from low

SES backgrounds and those not from low SES backgrounds?

RQ3. Is there a significant relationship between students’ attendance rate and students’

communication arts and mathematics MAP scores at a suburban Kansas City, Missouri school

district?

Null Hypotheses

Ho1: There is no significant difference in attendance rate at a suburban Kansas City,


from low SES backgrounds.

Ho2: There is no significant difference in communication arts and mathematics MAP


SES backgrounds and those not from low SES backgrounds.

Ho3: There is no significant relationship between students’ attendance rate and students’


district.


Limitations of the Study

1. No student data were gathered to establish a baseline for this study. Students’

incoming abilities were not considered.

2. Students were grouped according to SES based on their free and reduced lunch status.

While FRL status is a good indicator of SES, it is not the only determinant of SES and students

may be affected by other factors.

Delimitations of the Study

1. This study only included currently enrolled 7th

and 8th

graders from two middle

schools in Suburban Kansas City, Missouri during the 2013-2014 school year.

Definition of Terms

The following terms and definitions were used by this study.

Attendance: For the purpose of this study, the term attendance will be defined as the

percentage of school days present in the school year.

Free and Reduced Lunch (FRL): A student is eligible for a free lunch if family income is

at or below 130% of the federal poverty rate. For a family of four, this would mean annual

income is at or less than $30,615 per year for the 2013-2014 school year. A student is eligible

for a reduced price lunch if family income is between 131% and 185% of the federal poverty

rate. For a family of four, this would me annual income of between $30,616 and $43,568 (United

States Department of Agriculture, 2013).


Missouri Assessment Program test (MAP test): The standardized test used by the State of

Missouri to measure students’ progress in meeting the Show-Me Standards and GLE strands.

This test includes the assessments in communication arts, mathematics, and science. At the time

of this study, testing was required in communication arts and math in grades 3-8, and in grades 5

and 8 for science. Students’ correct responses on the test are given a MAP scale score, and these

scale scores are further broken down into four different achievement levels: Below Basic, Basic,

Proficient, and Advanced. (Missouri Department of Elementary and Secondary Education,

2012).

Missouri Department of Elementary and Secondary Education (DESE): The regulatory

agency for public education in Missouri grades K-12 . (Missouri Department of Elementary and

Secondary Education, 2012).

Socio-Economic Status: For the purpose of this study, FRL designation will be the

determinant of SES. Students currently on FRL will be considered to be of low-SES, while

students not on FRL will be considered to be of higher-SES.

Summary

The results of standardized tests such as the MAP test are of the utmost importance to

teachers and administrators. Therefore, it is important for all involved with education to

understand any factors that could affect these results. Past studies have examined the

relationship between SES and test scores as well as SES and attendance (Baxter, Royer, Hardin,

Guinn, and Devlin, 2011; Lamdin, 2001). Studies by Gottfried (2009, 2010, 2011) and others

have also examined the relationship between attendance and achievement. This study will build

on the knowledge of others and determine if there is a statistically significant difference between


those students who are on FRL and those students who are not on FRL in attendance rate. This

study will also determine if there is a statistically significant difference between those students

who are on FRL and those who are not on FRL and MAP Communication Arts and Mathematics

scores. Finally, this study will determine if there is a relationship between students’ attendance

and students’ MAP Communication Arts and Mathematics scores. The results of this study will

give insight into how and where SES affects attendance and achievement and also how

attendance is related to achievement. Giving teachers and administrators this knowledge will

help them to understand factors related to attendance and achievement, and assist them in

developing new ways of thinking or policies to improve both student attendance and student

achievement.


CHAPTER TWO

REVIEW OF LITERATURE

Overview

This chapter will present literature related to student socio-economic status, student

attendance, and student achievement, and relationships that literature suggests to exist amongst

the three. Sections on the history of the national school lunch program, Student certification for

free and reduced lunch, The use of free and reduced lunch as an SES determinant, Socio-

economic status and attendance, Socio-economic status and achievement, and the relationship of

attendance and achievement will be discussed.

Student achievement is important to all involved in the education process. The ultimate

goal of teachers and administrators is student success in school and in life. While in school, one

measure of student success is through standardized tests. Standardized testing became

supremely important to schools and teachers with the passage of the No Child Left Behind act of

2001 (Arce, Luna, Borjian, and Conrad, 2005; Braden and Schroeder, 2004). Although Missouri

has been granted an exemption from some of the requirements of NCLB, standardized testing is

still very important to school districts and teachers as the MAP test is used to compare school

districts and may be used in the new Missouri Educator Evaluation System (Missouri

Department of Elementary and Secondary Education, 2012).

Socio-economic status has been shown to adversely affect students’ lives in multiple

aspects, including school achievement (Morissey et al., 2013; Sirin, 2005). Students’ attendance

has also been shown to have an effect on student achievement (Gottfried 2009, 2010, 2011; Roby

2004). It is for these reasons the researcher chose to investigate whether students in a suburban


Kansas City, Missouri school district on FRL score differently on the MAP test from their peers

not on FRL as well as whether the two groups’ attendance rates displayed a significantly

significant difference.

History of the National School Lunch Program

The National School Lunch Program (NSLP) became a permanently subsidized federal

program with the passage of the National School Lunch act of 1946 (Hinrichs, 2010). The act

was seen as a measure of national security. Schools have the option of participating in the

program. In exchange for federal subsidies, schools have to agree to a set of rules including

serving school lunches on a free or reduced basis to children whose families cannot afford the

full cost of a lunch (Gunderson, n.d.).

Student Certification for Free and Reduced Lunch

Today, a student is eligible for a free lunch if family income is at or below 130% of the

federal poverty rate. For a family of four, this would mean annual income is at or less than

$30,615 per year for the 2013-2014 school year (United States Department of Agriculture, 2013).

A student is eligible for a reduced price lunch if family income is between 131% and 185% of

the federal poverty rate. For a family of four, this would mean annual income of between

$30,616 and $43,568 (United States Department of Agriculture, 2013). Harwell and LeBeau

(2010) explain that students can be certified to receive FRL in two ways: through information

provided by the family, or through direct certification, “based on whether a household receives

food stamps…or participates in at least one federally funded assistance program…(p. 122). If

certification is done by the family, they simply fill out paperwork containing information on

household income and turn it in to the district. Certification that occurs through direct means is


usually handled by a social service agency (Bass, 2010; Harwell and LeBeau, 2010). The goal of

the FRL program is to provide adequate nutrition to lower SES students in order to help them be

successful in school.

The Use of Free and Reduced Lunch as a Socio-Economic Status Determinant

Harwell and LeBeau (2010) extensively discuss the use of FRL status as an SES

determinant in their examination of past educational studies. The authors point out several faults

in using just FRL status when conducting research. One of the main problems for researchers is

to define just what constitutes SES. The authors state that “there is no widely agreed-upon

definition of SES or consensus on whether SES consists of a relatively modest number of

discrete classes or is best represented as a semi-continuous variable with possibly hundreds of

classes” (p. 122). The authors also argue that there is “compelling evidence that a significant

percentage of students are incorrectly certified as eligible or not eligible” (p. 124). This view

was also shared by Bass (2010) who argued that fraud was rampant in the program. Bass pointed

out that no verification of income is required when parents apply for FRL. While school districts

are required to attempt to verify a small portion of their participants each year, it has been shown

that “a high proportion of those asked to provide proof of income could not or would not

comply” (Bass, 2010, p.69). In addition, Bass stated that because schools receive more federal

assistance for each student on FRL, “local school districts have a clear incentive to register as

many students in NSLP as possible” (p. 68). Bass also argues that school districts often fail to

attempt to verify students’ eligibility for FRL (2010). Despite the shortcomings of using FRL

status as the determinant of SES in educational studies, Harwell and LeBeau (2010) state that:


…the FRL variable is consistently defined because of its link to the government’s

poverty guidelines, is available for every student, is nonintrusive, is simple (eligible, not

eligible), and can be obtained relatively cheaply because information is taken directly

from school records. (p. 126)

While some studies did attempt to define and measure SES through a composite of

factors (Barry, 2005; Duncan and Magnuson, 2005; Milne and Plourde, 2006; Stull, 2013), the

majority of the studies, papers, and presentations the researcher found used FRL participation as

a determinant for SES (Brtik, 2013; Bulach, Malone and Castleman, 1995; Gottfried, 2009 and

2011; Jones, 2006; Morissey et al., 2013; Pennington, 2013). Baxter et al. (2011) maintain that

“SES can be difficult to collect at the individual child level because of parental privacy and

confidentiality concerns” (p. 419). Therefore, many researchers use FRL data in their studies

due to it being more readily available than other options (Harwell and LeBeau, 2010).

In their 2012 report, the Omaha Public School District (2012) state:

Although not the most precise indicator of poverty, student participation in the Free and

Reduced-Price Lunch program is the only indicator of socioeconomic status universally

available to public schools across the nation. (p. 1)

The use of FRL as the determinant for SES was also defended in a 2001 study for the

Washington School Research Center, where Abbott and Joireman state that:

While the percentage of students in a given school on free/reduced lunch is not a direct

measure of low income, it is at present the best existing measure, and it is used

extensively throughout comparable research literature. (p.5)


Whereas the researcher realizes that FRL status is not the only possible determinant of

family SES, the researcher has chosen to use FRL as the determinant for SES because it is tied to

government standards and programs and because it is the data that is readily available.

Socio-economic Status and Attendance

The relationship between students’ SES and their school attendance was examined in

several studies. Hinrichs (2010) stated that “receiving a subsidized lunch may raise incentives to

attend school” (p. 2). However, his study did not examine attendance. Thottungal, Kern, Key,

and Sherman (2013) tell us that “Students who participate in the School Breakfast Program

(SBP) attend 1.5 more days of school annually…” (p. 4). While this statistic alone does not

suggest a relationship between SES and attendance, the authors suggest that making the SBP and

alternative breakfast programs more widespread would result in more low-income students to

participate, and in turn, raise their attendance rates (Thottungal et al., 2013).

Schagen and Benton (2006) found in their study of student attendance that “schools with

higher free school meal eligibility showed higher levels of absence (p. 30). Furthermore, in their

study attempting to link income, attendance, and achievement, Morissey et al. (2013) found

“very small but significant associations between the receipt of free or reduced-price lunch and

greater absences and tardies” (p. 7). Additional confirmation of the relationship between SES

and attendance was also found in 2010, when Ready noted the relationship between SES and

student attendance. Ready found that students of lower SES missed more school, but also that

other factors such as single parent homes and speaking a language other than English at home

contribute to absences (Ready, 2010). The case for the relationship between SES and attendance

was also strengthened with the results from a 2007 study by Romero and Lee. Using data from


the Early Childhood Longitudinal Study, the authors found that “In all grades, the lower family

income, the higher the absenteeism rates” (p. 1).

While many studies did find a relationship between SES and attendance, in a 2011 study

conducted to determine the relationship between school absenteeism, body mass index, academic

achievement, and socioeconomic status, Baxter et al. investigated the effect of socioeconomic

status as determined by FRL status on student attendance and found that “These analyses fail to

support…the inverse relationship between absenteeism and SES that was expected and has been

found by other researchers (p. 422).

In summary, students’ SES and attendance rate has been studied by multiple researchers.

Many, but not all, have found a positive relationship to occur between these two variables.

Generally speaking, these studies suggest that as SES goes up, attendance rate also goes up.

Conversely, these studies suggest that as SES goes down, absences go up.

Socio-economic Status and Achievement

Numerous studies were found which explored the relationship between students’ socio-

economic status and achievement. Specific to Missouri, the Nation’s Report Card shows that in

2011, students in grade 8 who were on FRL scored 23 points lower than students not on FRL.

Similar results were seen for the same year in grade four, as students on FRL scored 22 points

lower than their peers not on FRL (U.S. Department of Education, 2011). The Nation’s Report

Card utilizes the NAEP mathematics assessment which is designed to “present a broad view of

what our nation’s students know and can do in mathematics” (National Center for Education

Statistics, More About NAEP Mathematics section, para. 1, 2012). Scores can range from 0-500


on this test, which is given to a representative sample of students from all 50 states (National

Center for Education Statistics, 2012).

In 2013, Judith Stull used data from the Early Childhood Longitudinal Study to

investigate the effect of SES on achievement. She used a composite including income,

education, and occupation to determine SES. On a standardized general knowledge test, Stull

found that as family SES went up, so did the child’s achievement score. She also investigated

other possible variables such as type of school (public or private), teacher’s age, and child’s

gender but found that “family SES was always the most strongly related variable and was always

positive…” (p. 63).

Shores, Shannon, and Smith (2009), conducted a study on the effect of individual learner

variables and their effect on fifth and sixth grade students mathematics scores. This study found

a statistically significant positive relationship between those students on FRL and anxiety when

taking a test. The study also found a statistically significant negative relationship between those

students on FRL and mathematics achievement.

In their 2001 technical report, Abbott and Joireman examined standardized test scores in

the state of Washington to determine if there was a relationship between test scores, students on

FRL, and the ethnicity of students. In this study, the authors use school-level data to investigate

these relationships and define low income “as the percentage of students in a given school who

were on free or reduced lunch” (p. 5). Achievement was measured using two standardized tests.

In their findings, the authors conclude low income has more of an effect on achievement than

does ethnicity.


Barry also investigated the relationship between SES and achievement in 2005. Data for

this study came from the 2002 Educational Longitudinal Study. The dependent variable in her

study was an NCES standardized test. Among her findings was that “SES, net of other factors is

at the .000 significance level and is the strongest predictor of test scores (.224)” (p. 20).

Furthermore, Barry pointed out that as SES goes down, so do test scores (Barry, 2005). Similar

findings occurred with school level data in the Pennington report for the Iowa department of

Education. Pennington found that as the percentage of students in a school district on FRL goes

down, average district scores in math, reading, and science go up (Pennington, 2013).

In 2005, Sirin investigated a large body of journal articles published from 1990-2000

which were all investigating the effect of SES on academic achievement. In this study, Sirin

discussed the many ways this relationship could be differently explored with a few of the

differences being: determinants of SES, level of data (school or district level vs. student level),

grade level, and the way academic achievement was measured. As a result of the study, Sirin

determined that “Of all the factors examined in the meta-analytic literature, family SES at the

student level is one of the strongest correlates of academic performance” (p. 438). The author

also states that the differences in classifying SES can alter the relationship between SES and

achievement.

In this section, several studies demonstrated the relationship between SES and student

achievement. These studies measured SES and achievement in multiple ways and came to

similar conclusions: SES and student achievement are related at the student, building, and

district level.


The Relationship of Attendance and Achievement

The relationship of attendance to student achievement has been dissected in numerous

studies in the past, as well as in recent years. A few of the recent studies have been conducted by

Michael Gottfried (2009, 2010, 2011). In his 2009 study, Gottfried sought to investigate how

different absence types (excused, unexcused) might affect achievement. Using data from the

School District of Philadelphia, the 2000 Census, and results from the Stanford Achievement

Test – Ninth Edition (SAT-9), Gottfried determined that “increasing the number of total days

absent from school is related negatively to academic performance regardless of excused or

unexcused delineations” (p. 405). Of the relationship between SES and achievement, Gottfried

also found that “…the coefficients on being a special education student, English-language

learner, free lunch recipient…are negative and statistically significant” (p. 406). In other words,

students on FRL have lower average scores on the SAT-9 test than students not on FRL, and

students who have more absences also score lower on the SAT-9 test.

In the 2010 study, Gottfried sought to examine the relationship between attendance,

GPA, and standardized test performance at the individual student level. In this study, Gottfried

attempted to account for incoming differences in student ability by developing a baseline model

of student achievement. Among Gottfried’s findings was that “the relationship between

attendance and GPA is positive and significant and that this relationship becomes slightly

stronger for middle school students” (p. 448). Gottfried also found a statistically significant,

positive relationship between attendance and students’ scores on the SAT 9 test. This is

important, as it shows that as attendance rate goes up, so does test scores.


Gottfried attempted to determine the relationship between attendance and achievement in

2011 in a study which included siblings in the Philadelphia School District. Consistent with his

earlier research, Gottfried found a significantly significant negative relationship between student

absences and student achievement on the SAT 9 test even when accounting for several student,

neighborhood, classroom, and teacher characteristics. Once again, as absences go up,

achievement goes down.

Looking beyond Gottfried, in 2001, Lamdin found that attendance was “positively and

significantly related to standardized achievement test performance” (p. 155). This study utilized

school level data from 107 elementary schools in Baltimore, Maryland. Lamdin’s study also

found a “strong positive correlation between no free lunch and attendance” (p. 157). This tells us

that as the number of students not on FRL goes up, attendance rates also go up. In 2004, Roby

also examined the effect of attendance on standardized testing in Ohio. Roby found a

statistically significant, positive relationship between attendance and the Ohio Proficiency Test at

the 4th

, 6th

, 9th

, and 12th

grade level. This data was also investigated at the building level.

Romero and Lee build upon this relationship in their study with data from the Early Childhood

Longitudinal study which suggests that “Greater absenteeism in kindergarten was associated

with lower achievement in reading, math, and general knowledge at the end of first grade” (p. 3).

In this section on the relationship between attendance and achievement, numerous studies

were cited which demonstrated the positive relationship between attendance and achievement.

As attendance goes up, so does achievement. Studies in this section also tied into the previous

section of this paper and again confirmed the positive relationship between SES and attendance.

Typically, higher SES has been shown to manifest itself in higher attendance rates when

compared to lower SES.


Summary of the Literature Review

This chapter presented literature related to student socio-economic status, student

attendance, and student achievement, and relationships that have been proven to exist amongst

the three. Sections on the history of the national school lunch program, Student certification for

free and reduced lunch, The use of free and reduced lunch as an SES determinant, Socio-

economic status and attendance, Socio-economic status and achievement, and the relationship of

attendance and achievement were discussed.

To summarize this review of literature, students’ SES and attendance rate has been

studied by multiple researchers. Many, but not all, have found a relationship to occur between

these two variables. Generally speaking, students of lower SES have lower attendance rates than

those of higher SES. In addition, several studies demonstrated the positive relationship between

SES and student achievement. These studies measured SES and achievement in multiple ways

and came to similar conclusions: SES and student achievement are positively related at the

student, building, and district level. As a final point, numerous studies were cited which

demonstrated the positive relationship between attendance and achievement. As attendance goes

up, so does achievement. Through this literature review, links have been revealed between SES

and attendance, SES and achievement, and attendance and achievement.






CHAPTER THREE

RESEARCH METHODOLOGY

Problem and Purposes of the Study









not eligible for free and reduced lunch. The purpose of this study is to determine if there is a



the Missouri Assessment Program (MAP) test based on their SES grouping. Finally, this study

will investigate whether or not there is a relationship between students’ attendance rate and

students’ MAP scores.

Study Group

This study group consisted of 7th

and 8th

grade students currently enrolled at two separate

middle schools in Suburban Kansas City, Missouri. The group consisted of 418 seventh graders,

and 418 eighth graders.


This study group included students designated as receiving FRL benefits from the school,

and students not receiving FRL benefits from the school. In this study, 72 seventh graders

(17.2%) and 83 eighth graders (19.9%) were categorized as being eligible for FRL.

Research Design

This study utilized a causal-comparative research design. The causal-comparative design

was selected because neither the independent variables, nor the dependent variables were

manipulated because they had already occurred (Lunenburg and Irby, 2008).

Variables Used in the Study

This study utilized multiple independent (IV) and dependent (DV) variables in order to

examine the relationships between SES, attendance, and achievement. According to Kranzler

(2011):

An independent variable is a variable that is manipulated to determine its effect on

another variable. A dependent variable is the focus of most statistical analyses, because it

is the variable that is measured in response to manipulation of the independent variable.

(p. 31)

For RQ1: Is there a significant difference in attendance rate at a suburban Kansas City,


from low SES backgrounds? The IV is SES status and the DV is attendance rate.

For RQ2: Is there a significant difference in MAP communication arts and mathematics



SES backgrounds and those not from low SES backgrounds? The IV is SES status and the DV is

MAP communication arts and mathematics scores.

For RQ3: Is there a significant relationship between students’ attendance rate and

students’ MAP communication arts and mathematics scores at a suburban Kansas City, Missouri

school district? The IV is students’ attendance rate and the DV is students’ MAP

communication arts and mathematics scores.

Research Questions




RQ2. Is there a significant difference in MAP communication arts and mathematics




MAP communication arts and mathematics scores at a suburban Kansas City, Missouri school

district?

Null Hypotheses

Ho1: There is no significant difference in attendance rate at a suburban Kansas City,


from low SES backgrounds.


Ho2: There is no significant difference in MAP communication arts and mathematics


SES backgrounds and those not from low SES backgrounds.

Ho3: There is no significant relationship between students’ attendance rate and students’

MAP communication arts and mathematics scores at a suburban Kansas City, Missouri school

district.

Instrumentation and Data Collection

Data for this study was collected with the assistance of school central office personnel

(See Appendix A). Prior to the collection of data, Institutional Review Board approval was

obtained (See Appendix B). Because this study involved existing data and the subjects remained

anonymous to the researcher, exempt status was granted.

Prior to the researcher’s receipt of the data, any identifying characteristics of students

were removed. Upon receipt of the data, the researcher separated the data into two categories:

Students who were receiving FRL and students who were not receiving FRL. Due to grade-level

differences in MAP index scores, students were also separated by current grade level: seventh or

eighth. For example, when in grade seven, the possible MAP communication arts scale score

range is 515-865, but in sixth grade, the possible range is a slightly different 505-855 (Missouri

Department of Elementary and Secondary Education, 2012). Because of these differences, the

researcher made the decision to separate data for students in seventh grade and students in eighth

grade.

Data to be examined include: FRL status, communication arts and mathematics MAP

test scores for the previous two years, and attendance rate for the previous two years. For FRL


status, there are two possibilities: students who are on FRL, and students who are not on FRL.

The communication and mathematics MAP test scores for the current seventh graders are for

tests taken during their fifth and sixth grade years; scores for the current eighth graders are for

tests taken during their sixth and seventh grade years. Finally, attendance rate was defined as the

percentage of school days present in the school year.

This study used FRL status as the determinant for SES. For the purpose of this study,

SES data would be characterized as being on the nominal scale as students are assigned a

category based on their eligibility for FRL (Kranzler, 2011). This study also used the results

from the communication arts and mathematics portion of the MAP test. MAP test data was

collected at the interval level as the scale has equal units of measurement, but no absolute zero

(Kranzler 2011). MAP scale scores on the communication arts portion of the MAP test can

range from 485-865 over the fifth, sixth and seventh grade tests which are used in this study

(Missouri Department of Elementary and Secondary Education, 2012). MAP scale scores on the

mathematics portion of the MAP test can range from480-860 over the fifth, sixth and seventh

grade tests which are used in this study (Missouri Department of Elementary and Secondary

Education, 2012). While this scale score has equal units of measurement, there is no absolute

zero. Lastly, attendance data collected represented a percentage of school days a student was

present for the school year. This data would be considered to be on the ratio scale as it has a true

zero point and equal units of measurement (Kranzler, 2011).

Data Analysis Strategies

Data was analyzed using descriptive and inferential statistics. After receiving the data,

the researcher organized all data into Microsoft Excel and performed statistical calculations


using EZ Analyze software. As part of this analysis, the mean, median, and mode were

calculated for students’ attendance rates and communication arts and mathematics MAP scores.

For research questions one and two, independent t-tests were calculated with an a priori

alpha level of α = .05 to determine if there was a significant difference between groups

attendance rates and MAP test scores (Lunenberg and Irby, 2008).







For research question three, the product-moment correlation coefficient (Pearson’s r) was

used because the question merely investigates a relationship between two groups, and data is on

the interval and ratio scale (Lunenberg and Irby, 2008). Pearson’s r was calculated with an a

priori alpha level of α = .05 to determine if there was a statistically significant relationship

between students’ attendance rates and students’ achievement on the MAP test.



district?


Summary

This chapter presented the Problem and purposes of the study, Study group, Research

design, Variables used in the study, Research questions, Null hypotheses, Instrumentation and

data collection, and Data analysis strategies.



not eligible for free and reduced lunch. One purpose of this study is to determine if there is a



the Missouri Assessment Program (MAP) test based on their SES grouping. Finally, this study

will investigate whether or not there is a relationship between students’ attendance rate and

students’ MAP scores. Data from the district which includes information on the SES, attendance

rate, and MAP test scores was obtained and input into Microsoft Excel in order to investigate

these variables. Any differences or relationships will be determined through the use of

independent t-tests and Pearson’s r.


CHAPTER 4

PRESENTATION AND ANALYSIS OF DATA

Overview

The purpose of this study was to determine if there is a difference in attendance

rates or MAP scores of two groups: students who are eligible for free and reduced lunch, and

students who are not eligible for free and reduced lunch. One purpose of this study was to

determine if there is a difference between students’ attendance rates based on their SES

grouping. This study will also determine if there is difference between students’ achievement

level as measured by the communication arts and mathematics sections of the Missouri

Assessment Program (MAP) test based on their SES grouping. Finally, this study will determine

whether or not there is a relationship between students’ attendance rate and students’

communication arts and mathematics MAP scores.

Statement of the Research Questions

This study addressed the following research questions:










district?

Results and Discussion for Research Question One

Research question one sought to determine if there was a difference in attendance rates

between students receiving FRL and students not receiving FRL. Attendance rates were

investigated for current seventh and eighth graders for the two previous school years (2011-2012

and 2012-2013). For the seventh graders, this would include their fifth and sixth grade years,

and for the eighth graders, their sixth and seventh grade years.

T-Test for Statistical Significance Between SES and Attendance

A t-test was applied to the data to determine if there was a statistically significant

difference in attendance rate in the 2011-2012 school year of students receiving FRL and

students not receiving FRL (see table 1). An a priori alpha level of .05 was established for this

study. The resultant significance level (p=.000) showed a statistically significant difference

between the groups, regardless of whether students were grouped together, or separated by grade

level. In both the seventh and eighth grade groups, students who were on FRL had a lower

average attendance rate than students who were not on FRL. The mean differences of the groups

(seventh grade – 1.781%, eighth grade 2.269%) may not appear to be a large difference on the

surface, but calculate out to 3 and 3.9 missed school days in a 174 day school year. This would

equate to students on FRL missing 18-23.4 more hours of instruction than their peers not on

FRL. For a group already known to have challenges, this could be substantial.


Based on this independent t-test of difference between groups (FRL and no FRL),

information suggests a statistically significant difference between attendance rates of the groups

in the 2011-2012 school year. Alpha level was set by the researcher at (0.05); the observed

result was 0.000. Because the observed error was less than alpha, the researcher rejected the null

hypotheses which stated, “There is no significant difference in attendance rate at a suburban

Kansas City, Missouri school district when considering students from low SES backgrounds and

those not from low SES background” and accepted the alternative. Further research and

analysis should be conducted.

Table 1

The Relationship Between SES and Attendance (2011-2012)

Current 7th

& 8th

Graders Combined Current 7th

Graders Current 8th

Graders

F & R

Status

1=yes, 2=no Yes No Yes No Yes

No

Mean: 93.893% 95.929% 94.072% 95.853% 93.738% 96.007%

Std. Dev: 5.831 3.546 5.527 3.263 6.116 3.819

N: 142 649 66 329 76 320

Mean

Difference: 2.036%

1.781%

2.269%

T-Score: 5.426 3.537 4.088

Eta Squared: .036 .031 .040

P: .000 .000 .000

A second t-test was applied to the data to determine if there was a statistically

significant difference in attendance rate in the 2012-2013 school year of students receiving FRL

and students not receiving FRL (see table 2). An a priori alpha level of .05 was established for

this study. The resultant significance level (p=.000) showed a statistically significant difference


between the groups, regardless of whether students were grouped together, or separated by grade

level. In both the seventh and eighth grade groups, students who were on FRL had a lower

average attendance rate than students who were not on FRL. The mean differences of the groups

(seventh grade – 2.160%, eighth grade 2.342%) may not appear to be a large difference at first,

but in this school year, these percentages calculate out to even more missed school time – 3.75

missed days for current 7th

graders, and 4.08 missed school days for current eighth graders in a

174 day school year. This would equate to students on FRL missing 22.5-24.48 more hours of

instruction than their peers not on FRL. If we look to the information gathered in the literature

review concerning attendance and achievement, we know that these missed instruction hours

could be detrimental to achievement (Gottfried, 2010; Lamdin, 2001; Ready, 2010; Roby, 2004).

Based on this independent t-test of difference between groups (FRL and no FRL),

information suggests a statistically significant difference between attendance rates of the groups

in the 2012-2013 school year. Alpha level was set by the researcher at (0.05); the observed

result was 0.000. Because the observed error was less than alpha, the researcher rejected the null

hypotheses which stated, “There is no significant difference in attendance rate at a suburban

Kansas City, Missouri school district when considering students from low SES backgrounds and

those not from low SES background” and accepted the alternative. Further research and

analysis should be conducted.


Table 2

The Relationship Between SES and Attendance (2012-2013)

Current 7th

& 8th

Graders Combined Current 7th

Graders Current 8th

Graders

F & R

Status

1=yes, 2=no Yes No Yes No Yes No

Mean: 93.577% 95.851% 93.867% 96.026% 93.326% 95.668%

Std. Dev: 6.244 3.625 6.379 3.344 6.152 3.891

N: 153 675 71 344 82 331

Mean

Difference: 2.274%

2.160%

2.342%

T-Score: 6.002 4.118 4.286

Eta Squared: .042 .039 .043

P: .000 .000 .000

Results and Discussion for Research Question Two

Research question two sought to determine if there was a difference in communication

arts and mathematics MAP test scores between students receiving FRL and students not

receiving FRL. MAP test scores in the areas of communication arts and mathematics were



and for the eighth graders, their sixth and seventh grade years.

T-Test for Statistical Significance Between SES and MAP Scores

A t-test was applied to the data to determine if there was a statistically significant

difference in MAP scores in 2012 and 2013 of current seventh graders when considering students

receiving FRL and students not receiving FRL (see table 3). An a priori alpha level of .05 was

established for this study. The resultant significance level (p=.000) showed a statistically


significant difference on both the communication arts and mathematics index score in both years

tested.

The mean difference in the current seventh graders’ scale scores for the communication

arts portion of the test was 21.015 in 2012 and 17.726 in 2013. The resultant differences in the

scale scores reveal a striking difference between the two groups. In both years, students on FRL

scored in the basic achievement level of the communication arts MAP test, while students not on

FRL scored in the proficient achievement level. For schools striving to get as many of their

students as possible into the proficient and advanced achievement-levels, this is huge.

The mean difference in the current seventh graders’ scale scores for the mathematics

portion of the test was 23.623 in 2012 and 21.927 in 2013. For the mathematics portion of the

test, the resultant differences in the scale scores demonstrate that both groups of students had

mean scores in the proficient achievement-level.


Table 3

The Relationship Between SES and MAP Scores for Current 7th

Graders

MAP

Communication

Arts 2012

MAP

Mathematics

2012

MAP

Communication

Arts 2013

MAP

Mathematics

2013

F & R

Status

1=yes,

2=no 1 2 1 2 1 2 1 2

Yes 670.180 691.195 674.145 697.768 671.657 689.383 688.143 710.070

Std. Dev: 25.161 28.457 32.090 38.846 23.043 25.462 29.289 35.270

N: 61 323 62 323 70 342 70 342

Mean

Difference: 21.015

23.623

17.726

21.927

T-Score: 5.383 4.501 5.390 4.868

Eta

Squared: .070 .050 .066 .054

P: .000 .000 .000 .000

A second t-test was applied to the data to determine if there was a statistically significant

difference in MAP scores in 2012 and 2013 of current eighth graders when considering students

receiving FRL and students not receiving FRL (see table 4). An a priori alpha level of .05 was

established for this study. The resultant significance level (p=.000-.002) showed a statistically

significant difference on both the communication arts and mathematics index score in both years

tested.

The mean difference in the current eighth graders’ scale scores for the communication

arts portion of the test was 8.463 in 2012 and 12.060 in 2013. In this case, the resultant

differences in the scale scores tell us that the mean communication arts scores of both groups of

students would fall into the proficient achievement-level.


The mean difference in the current eighth graders’ scale scores for the mathematics

portion of the test was 15.032 in 2012 and 13.893 in 2013. Again in this case, the resultant

differences in the mathematics scale scores tell us that the mean mathematics scores of both

groups of students would fall into the proficient achievement-level.

In each instance tested, there was a significantly significant difference in both

communication arts and mathematics scores on the MAP test between the two groups. While

this difference only resulted in a difference in achievement level in two tests (communication

arts scores of current seventh graders in 2012 and 2013), the fact that there was a statistically

significant difference in all areas is definitely something to examine further. Students who are

on FRL are scoring lower on the MAP test than students not on FRL in all cases, and as

educators, we need to examine ways to help close this gap.

Table 4

The Relationship Between SES and MAP Scores for Current 8th

Graders

MAP

Communication

Arts 2012

MAP

Mathematics

2012

MAP

Communication

Arts 2013

MAP

Mathematics

2013

F & R

Status

1=yes,

2=no 1 2 1 2 1 2 1 2

Mean: 678.547 687.009 690.427 705.459 682.463 694.523 698.684 712.578

Std. Dev: 26.208 26.585 35.121 32.406 35.253 30.792 34.138 34.675

N: 75 318 75 318 80 331 76 296

Mean

Difference: 8.463

15.032

12.060

13.893

T-Score: 2.486 3.555 3.053 3.126

Eta

Squared: .015 .031 .022 .026

P: .013 .000 .002 .002


Results and Discussion for Research Question Three

Research question three sought to determine if there was a relationship between

attendance and achievement based on MAP test scores. Attendance rates and MAP tests were



and for the eighth graders, their sixth and seventh grade years. This data was also split into

groups based on current grade level due to slight differences in the MAP scale scores.

Pearson’s r was used to determine if there was a relationship between students’

attendance rate and students’ scores on the communication arts and mathematics MAP tests. For

the current seventh graders, the results show a statistically significant, negligible to weak

positive relationship between attendance and all four tests with a p-value of .000 in all cases (see

table 5). The variance in the test scores that can be attributable to attendance ranges from a low

of 3.46% on the 2013 communication arts portion of the test to a high of 5.11% on the 2012

mathematics portion of the test. This means that roughly ninety-five to ninety-seven percent of

the variance in test scores could be attributable to factors other than attendance.

The current eighth grade tests also all show significantly significant, negligible to weak

positive relationship between attendance and all four tests (see table 6). All p-values for the

current 8th

graders test were statistically significant at the (p=.000) level except for the 2012

communication arts test which was still statistically significant at the (p=.029) level. The

variance in the test scores for current eighth graders that can be attributable to attendance ranges

from a low of 1.21% for the 2012 communication arts portion of the test to a high of 6.86% for

the 2013 mathematics section of the test. This means that roughly between ninety-three and


ninety-nine percent of the variance in test scores could be attributable to factors other than

attendance. While this is a negligible to weak relationship, it is still positive.

Table 5

The Relationship Between Attendance and Achievement for Current 7th

Graders

Current 7th

Graders

MAP

Communication

Arts 2012

MAP

Mathematics

2012

MAP

Communication

Arts 2013

MAP

Mathematics

2013

Pearson’s

Correlation: .207 .226 .186 .207

N: 384.000 385.000 412.000 412.000

P: .000 .000 .000 .000

Variance: .0428 .0511 .0346 .0428

Variance in test

scores

attributable to

attendance 4.28% 5.11% 3.46% 4.28%

Table 6

The Relationship Between Attendance and Achievement for Current 8th

Graders

Current 8th

Graders

MAP

Communication

Arts 2012

MAP

Mathematics

2012

MAP

Communication

Arts 2013

MAP

Mathematics

2013

Pearson’s

Correlation: .110 .213 .260 .262

N: 393.000 393.000 411.000 372.000

P: .029 .000 .000 .000

Variance: .0121 .0454 .0676 .0686

Variance in test

scores

attributable to

attendance 1.21% 4.54% 6.76% 6.86%


CHAPTER 5

OVERVIEW, FINDINGS, AND RECOMMENDATIONS

Overview

The purpose of this study was to determine if there is a difference in attendance

rates or MAP scores of two groups: students who are eligible for free and reduced lunch, and

students who are not eligible for free and reduced lunch. One purpose of this study was to

determine if there is a difference between students’ attendance rates based on their SES

grouping. This study will also determine if there is difference between students’ achievement

level as measured by the Missouri Assessment Program (MAP) test based on their SES grouping.

Finally, this study will determine whether or not there is a relationship between students’

attendance rate and students’ MAP scores. In this chapter, the study will be summarized, results

and additional findings discussed, conclusions will be presented, and recommendations will be

made.

Summary of Research Methods

This study used existing district data on students from two middle schools in suburban

Kansas City, Missouri. The data encompassed the 2011-2012 and 2012-2013 school years and

the study group consisted of 418 students currently in 7th

grade and 418 students currently in

eighth grade. Because the data was already in existence, a causal-comparative research design

was used. The Institutional Review Board granted exempt status to this study because the data

already existed and the researcher would not know the identities of the students in the study

group. With the assistance of school administration, data was collected and separated into two

categories: Students who were receiving FRL and students who were not receiving FRL. Due to


grade-level differences in MAP index scores, students were also separated by current grade level:

seventh or eighth.

Data Analysis

Data was analyzed using descriptive and inferential statistics. After receiving the data,

the researcher organized all data into Microsoft Excel and performed statistical calculations

using EZ Analyze software. As part of this analysis, the mean, median, and mode were

calculated for students’ attendance rates and communication arts and mathematics MAP scores.

Research questions one and two investigated the possibility of a statistically significant

difference between students’ attendance rates and communication arts and mathematics scores

on the MAP test when taking into consideration students’ SES. For research questions one and

two, independent t-tests were calculated with an a priori alpha level of α = .05 to determine if

there was a significant difference between groups attendance rates and MAP test scores

(Lunenberg and Irby, 2008).

Research question three sought to determine if there was a relationship between

attendance and achievement based on communication arts and mathematics MAP test scores.

Pearson’s r (α = .05) was used to determine if there was a relationship between students’

attendance rate and students’ scores on the communication arts and mathematics MAP tests.

Attendance rates and MAP tests were investigated for current seventh and eighth graders for the

two previous school years (2011-2012 and 2012-2013).


Discussion of Findings

The results of this study suggest that in all cases investigated, there is a statistically

significant difference between SES and attendance, as well as SES and achievement. This

finding is consistent with findings of previous researchers, as discussed in the review of literature

(Abbott and Joireman, 2001; Barry, 2006; Jones, 2006; Lamdin, 2001 Romero and Lee, 2008).

This study adds to the body of knowledge suggesting that SES is a factor which affects students

in multiple ways.

The relationship between SES and attendance was demonstrated in the differences

exhibited by students at a middle school in suburban Kansas City, Missouri in the 2011-2012

school year, as well as in the 2012-2013 school year. This study demonstrated that students on

FRL had lower mean attendance rates than those not on FRL. These differences were all

statistically significant and were all found at a p-value of (p=.000). Although there is a

statistically significant difference, the researcher would consider both groups’ mean attendance

rates to be good. The students on FRL had mean attendance rates of 93.89% in 2011-2012, and

93.577% in 2012 and 2013 as compared to the 95.929% and 95.851% displayed be their non

FRL peers. However, when one looks at actual instruction time missed by students on FRL

when comparing to those students not on FRL, it is evident that even a small mean difference can

affect the student. The mean differences of current seventh and eighth graders were 2.036% in

2011-2012 and 2.274% in 2012-2013. This would equate to 3.54 and 3.96 more missed days of

school, respectively. This is an important finding for educators to be aware of. Making up

missed work and learning concepts that may have been missed while absent is a hard thing for

many middle school students to do, regardless of SES grouping. It often requires obtaining a

ride to or from school to get additional help beyond regular school hours. For a lower-SES


family, this could be more difficult than for those from a higher SES family. For some of these

students, their only means of transportation may be the school bus. Therefore, any make-up

work or learning of missed concepts either does not happen, or it has to happen during the school

day, often at the expense of learning new or current concepts that other students may have

already moved on to. For a low SES student, this loss of instructional time can accumulate and

take weeks for them to get caught up when missing just one or two days. Missing more school

can put these kids who are on FRL in a perpetual state of lagging behind the rest of the class and

struggling to catch up, which in turn, may affect their achievement levels in class and on

standardized tests, such as the MAP.

When investigating the differences between students’ SES and students’ scale scores on

the communication arts and mathematics portion of the MAP test, the researcher found that

among both current seventh and eighth graders, in both school years, students who are on FRL

had lower mean MAP test scores than students not on FRL in both the communication arts and

mathematics sections of the test. For the current seventh graders, the difference was statistically

significant at the (p=.000) level in all cases. For the current eighth graders, the difference was

statistically significant with p-values ranging from (p=.000-.002). The fact that this study

suggests that student of lower SES have lower mean MAP test scores than their higher SES peers

is important. It adds to the existing body of knowledge linking SES and achievement, but at the

middle school level with student level data.

In addition to students on FRL mean scores being lower than their non-FRL peers, one

very striking difference was found. In the case of the current seventh graders, mean

communication arts test scores in both the 2011-2012 and 2012-2013 school years were far

enough apart to put the FRL group into a different MAP achievement level than the non-FRL


group. In 2012, current seventh graders on FRL had a mean score of 670.18 on the

communication arts portion of the MAP test, while students not on FRL had a mean score of

691.195. In 2013, the FRL group had a mean score of 671.657, while the non-FRL group’s

mean score was 689.383. For these two tests, the FRL group scored in the basic achievement

level, while the non-FRL group scored in the proficient achievement level. As schools attempt

to move all of their students to proficient levels, this is a huge finding. This group (current

seventh graders on FRL) could be more closely examined in an effort to determine other factors

that may contribute to this difference in order to formulate a plan to help improve student

achievement. This is a group that could be helped to move up an achievement level, as their

scores were only four points away from the next achievement level in both years tested.

This discussion has already demonstrated the effect of SES on attendance and

achievement as related to research questions one and two. This study suggests that students of

lower SES as determined by FRL status have more absences and score lower on the

communication arts and mathematics sections of the MAP test than do their higher SES peers.

Research question three attempted to investigate the level of relationship, if any, between

attendance and performance on the communication arts and mathematics portion of the MAP

test. A product-moment correlation coefficient (Pearson’s r) was used to gauge this relationship.

In both school years investigated, at both grade levels, across all test sections considered, the

relationship was negligible to weak, and positive. This relationship was shown to be statistically

significant at the (p=.000) level in all cases except for the current eighth graders’ 2010

communication arts test, which was still statistically significant and had a value of (p=.029).

While the relationship is weak, and the variances in the test scores show us that over ninety

percent of the variance could be attributed to other factors, the positive relationship is still there.


Attendance and achievement on the communication arts and mathematics portion of the MAP

test are positively related. The magnitude of this relationship may have been affected by the fact

that both groups’ attendance rates, despite being statistically significantly different, were both

high (93.893% and 93.577% for FRL, 95.929% and 95.851% for non-FRL). These attendance

rates may differ in other buildings or in other districts, which could change the relationship.

The results of this study are of interest to educators for a number of reasons. Although

this study failed to establish a strong correlation between attendance and achievement as has

been demonstrated in previous studies, this study has shown that low SES can negatively affect

both attendance and test scores. With this knowledge, educators can begin to investigate

possible strategies to assist those who are of lower SES to improve both their attendance and

achievement. In all cases, further research is needed.

Conclusions

1. Students in a suburban Kansas City, Missouri school district who are of lower SES

background score lower on the communication arts and mathematics sections of the

MAP test than their peers who are of higher SES.

2. Students in a suburban Kansas City, Missouri school district who are of lower SES

have more absences than their peers who are of higher SES.

3. Attendance and achievement are positively related, but at negligible to weak levels at

a suburban Kansas City, Missouri school district.

Recommendations

Upon completion of the study, the following recommendations are presented.


Recommendation One. This study could and should be replicated by many other teachers

and administrators. Through the information gathered and data analyzed, plans could be

formulated to help improve student attendance and achievement. This data and the resultant

plans should be shared with other educators for the benefit of all. Further studies are needed.

Recommendation Two. While this study presented interesting and useful data and

statistically significant results, the researcher believes that the factors that go into determining

SES should be further explored. Several more variables could be taken into account besides FRL

designation which could bring to light other SES factors that may affect students’ attendance and

achievement (Harwell and LeBeau, 2010; Sirin, 2005). By using these combinations of

variables, a truer picture of SES might be achieved. Further studies are needed.

Recommendation Three. After examining the results of the data regarding attendance

between the two groups and discussing the reasons it may be hard for lower SES students to get

caught up after missing school, the researcher suggests that the school goes back to offering a

“late bus” a few nights a week after school. This bus would allow students who need to make up

work or spend extra time with a teacher to do so after school, while still having transportation.

Recommendation Four. This data should be shared with the communication arts teachers

of this class of current seventh graders. While personally identifying characteristics of lower

SES students could not be shared, communication arts teachers could attempt to find areas of

weakness for all students in an attempt to bring the low SES group’s mean communication arts

MAP scores up to the proficient level.

Recommendation Five: All involved in the education process of young people should

become familiar with factors that can affect attendance and achievement. Because SES has been


shown to be a factor that strongly affects both, educators should take the time to learn about the

challenges faced by those of lower SES. Armed with this knowledge, programs could be

implemented to aid all students in the hopes of improving not only their school attendance and

achievement, but also their lives. There is time available in the current school day that could be

used to aid all students. Time spent in advisory and sustained silent reading could and should be

used to help students who need it.


APPENDIX A

Data Collection Table

Students’ FRL Status, MAP Scores, and Attendance Rates

Student Name

F & R Status

1=yes, 2=no

Grade Level

2013-14

MAP Comm

Arts 2012

MAP Comm

Arts 2013

MAP Math

2012

MAP Math

2013

Attendance

Rate 2011-12

Full Year

Attendance

Rate 2012-13

Full Year


APPENDIX B

Institutional Review Board Approval


REFERENCES

Abbott, M. L., & Joireman, J. (2001, July). The relationships among achievement, low

income, and ethnicity across six groups of Washington state students (Report No. 1). Lynwood,

WA: Washington School Research Center.

Augustine-Thottungla, R., Kern, J., Key, J., & Sherman, B. (2013). Ending childhood

hunger: A social impact anlysis. Washington, DC: Deloitte.

Barry, J. (2006). The effect of socio-economic status on academic achievement

(Unpublished master's thesis). Wichita State University, Wichita, KS.

Bartik, T. J. (2013, January). Family income, student achievement, and educational costs.

Upjohn.

Baxter, S. D., Royer, J. A., Hardin, J. W., Guinn, C. H., & Devlin, C. M. (2011). The

relationship of school absenteeism with body mass index, academic achievement, and

socioeconomic status among fourth-grade children. Journal of School Health, 81(7), 417-423.

Bock, J. (2012, January 19). Missouri teachers could be evaluated on student progress.

Retrieved from St. Louis Post-Dispatch website: http://www.stltoday.com

Bulach, C. R., Malone, B., & Castleman, C. (1995). An investigation of variables related

to student achievement. Mid-Western Educational Researcher, 8(2), 23-29.

Downey, D. B., von Hippel, P. T., & Broh, B. (2004). Are schools the great equalizer?

School and non-school sources of inequality in cognitive skills. American Sociological Review,

69(5), 613-635.


Fraenkel, J., & Wallen, N. (n.d.). [The nature of causal-comparative type research].

Retrieved September 18, 2013, from How to Design and Evaluate Research in Education

website: http://highered.mcgraw-hill.com/sites/0073525960/student_view0/

Gottfried, M. A. (2009). Excused versus unexcused: How student absences in elementary

school affect academic achievement. Educational Evaluation and Policy Analysis, 31(4), 392-

415.

Gottfried, M. A. (2010). Evaluating the relationship between student attendance and

achievement in urban elementary and middle schools: An instrumental variables approach.

American Educational Research Journal, 47(2), 434-465.

Gottfried, M. A. (2011). The detrimental effects of missing school: Evidence from urban

siblings. American Journal of Education, (117), 147-182.

Gunderson, G. W. (n.d.). National school lunch program. Retrieved November 6, 2013,

from United States Department of Agriculture, Food and Nutrition Service website:

http://www.fns.usda.gov/nslp/history

Harwell, M., & LeBeau, B. (2010). Student eligibility for a free lunch as an SES measure

in education research. Educational Researcher, 39(2), 120-131.

Hinrichs, P. (2010). The effects of the national school lunch program on education and

health. Journal of Policy Analysis and Management, 29(3), 479-505.

Income eligibility guidelines. (n.d.). Retrieved November 6, 2013, from United States

Department of Agriculture, Food and Nutrition Services website:

http://www.fns.usda.gov/cnd/Governance/notices/iegs/iegs.htm


Jones, D. J. (2006). The impact of student attendance, socio-economic status and mobility

on student achievement of third grade students in title I schools (Unpublished doctoral

dissertation). Virginia Polytechnic Institute, Blacksburg, VA.

Kranzler, J. H. (2011). Statistics for the terrified (5th ed.). Upper Saddle River, NJ:

Prentice Hall.

Lamdin, D. J. (1996). Evidence of student attendance as an independent variable in

education production functions. The Journal of Education Research, 89(3), 155-162.

Lubienski, S. T., & Crane, C. C. (2010). Beyond free lunch: Which family background

measures matter? Education Policy Analysis Archives, 18(11), 1-43.

Lunenburg, F. C., & Irby, B. J. (2008). Writing a successful thesis or dissertation: Tips

and strategies for students in the social and behavioral science. Thousand Oaks, CA: Corwin

Press.

Milne, A., & Plourde, L. A. (2006). Factors on a low-SES household: What aids

academic achievement? Journal of Instructional Psychology, 33(3), 183-193.

Missouri assessment program grade-level assessments (Missouri Department of

Elementary and Secondary Education, Comp.) [Brochure]. (2012). Monterey, CA: CTB/McGraw

Hill.

Missouri educator evaluation system. (n.d.). Retrieved from Missouri Department of

Elementary and Secondary Education website: http://dese.mo.gov/eq/ees.htm

Missouri gets no child left behind waiver. (2012, June 29). Retrieved from

http://www.columbiatribune.com


Missouri's educator evaluation system. (n.d.). Retrieved from Missouri Department of

Elementary and Secondary Education website: http://dese.mo.gov/eq/ees.htm

Morrissey, T. W., Hutchinson, L., & Winsler, A. (2013). Family income, school

attendance, and academic achievement in elementary school. Developmental Psychology, 1-13.

National assessment of educational progress: More about NAEP mathematics. (2012,

August 1). Retrieved November 6, 2013, from National Center for Education Statistics website:

http://nces.ed.gov/nationsreportcard/mathematics/moreabout.aspx

Noerrlinger, C. (2012, December). District free and reduced-price lunch report. Omaha,

NE: Omaha Public Schools.

Pennington, J. (2013, June). District characteristics: What factors impact student

achievement. Des Moines, IA: Iowa Department of Education.

Ready, D. D. (2010). Socioeconomic desadvantage, school attendance, and early

cognitive development: The detrimental effects of school exposure. Sociology of Education,

83(4), 271-286.

Roby, D. E. (2004). Research on school attendance and student achievement: A study of

Ohio schools. Educational Reseach Quarterly, 28(1), 3-14.

Romero, M., & Lee, Y.-S. (2007, October). A national portrait of chronic absenteeism in

the early grades. New York, NY: National Center for Children in Poverty.

Romero, M., & Lee, Y.-S. (2008, January). The influence of maternal and family risk on

chronic absenteeism in early schooling. New York, NY: National Center for Children in Poverty.


Schagen, I., & Benton, T. (2006). Don't judge schools purely on raw attendance data or

examination results. Education, (96), 30-31.

Shores, M. L., Shannon, D. M., & Smith, T. G. (2010). Individual learner variables and

their effect on mathematics achievement as students advance from fifth to sixth grade. Journal of

Research in Childhood Education, (24), 187-194.

Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic

review of research. Review of Educational Research, 75(3), 417-453.

Stull, J. C. (2013). Family socioeconomic status, parent expectations, and a child's

achievement. Research in Education, (90), 53-67.

U.S. Department of Education. (2011). The nation's report card: Mathematics 2011 state

snapshot report. Institute of Education Sciences.

effect of socioeconomic status on middle school …

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