THE EFFECTS OF HIGH SCHOOL ATHLETIC PARTICIPATION
ON STUDENT ACHIEVEMENT, ATTENDANCE,
AND DISCIPLINE
A Thesis Presented to the Faculty
of
California State University, Stanislaus
In Partial Fulfillment
of the Requirements for the Degree
of Master of Arts in Education
By
Talmage Allen
May 2014
CERTIFICATION OF APPROVAL
THE EFFECTS OF HIGH SCHOOL ATHLETIC PARTICIPATION ON
STUDENT ACHIEVEMENT, ATTENDANCE,
AND DISCIPLINE
by
Talmage Allen
Signed Certification of Approval Page is
on file with the University Library
Dr. John Borba
Professor of School Administration
Date
Dr. Chet Jensen
Professor of Education
Date
DEDICATION
This work is dedicated to my family and a teacher who inspired me. First and
foremost I dedicate this thesis to my wife, who has been willing to sacrifice time to
allow me to pursue my master’s degree and has supported me in my goals and
professional career choices. Words cannot describe the help that she has been in my
life. To my children, Grant, Mackenzie, and Tyler, for their understanding of their
dad who sometimes had to step away from family activities to get his homework
done. To my parents Brad and Dantzelle, who have helped, guided, and supported me
in my education and were always encouraging me to “do your best.” You were
always there to help me throughout the educational challenges that I faced and
overcame. You taught me how to work hard, and without that lesson, I would have
never gotten this far.
Lastly I dedicate this work to my fifth grade teacher, Sandra Hodge, who
ultimately inspired me to go into education. Her dedicated time and talents inspired
me to have the confidence to take on any task at hand. I have learned that with
dedication and encouragement, I can accomplish anything I put my mind to.
iii
ACKNOWLEDGEMENTS
I would like to thank Dr. John Borba for his guidance in seeing me through
the completion of this project. I could not have done it without your help, insight and
direction. To Dr. Chet Jensen: it was because of your instruction that I realized I
could take on this task and be successful at it.
To Lori Lippincott: thank you for your time and talents to help me compile the
data needed for this study. Also to Maria Pires: thanks for your help in collecting the
student information needed for this study.
iv
TABLE OF CONTENTS
PAGE
Dedication ...............................................................................................................
iii
Acknowledgements .................................................................................................
iv
List of Tables ..........................................................................................................
vii
Abstract ................................................................................................................... viii
CHAPTER
I.
Introduction ...........................................................................................
1
Statement of the Problem ..........................................................
Research Question ....................................................................
Hypotheses ................................................................................
Significance of the Study ..........................................................
Limitations and Delimitations...................................................
Definitions of Terms .................................................................
Summary ...................................................................................
3
3
4
4
4
5
6
Review of the Literature .......................................................................
7
Introduction ...............................................................................
GPA...........................................................................................
Attendance ................................................................................
Discipline ..................................................................................
Summary ...................................................................................
7
7
11
14
18
Methodology .........................................................................................
19
Introduction ...............................................................................
Sample Population ....................................................................
Treatment Group .......................................................................
Control Group ...........................................................................
Instrumentation .........................................................................
Statistical Analysis ....................................................................
Summary ...................................................................................
19
19
20
20
20
21
21
Results of the Study ..............................................................................
22
Introduction ...............................................................................
22
II.
III.
IV.
v
Description of the Sample .........................................................
Findings Related to H1 ..............................................................
Findings Related to H2 ..............................................................
Findings Related to H3 ..............................................................
Summary ...................................................................................
22
23
24
24
25
Summary, Conclusions, and Recommendations ...................................
26
Introduction ...............................................................................
Summary ...................................................................................
GPA...........................................................................................
Attendance ................................................................................
Discipline ..................................................................................
Conclusions ...............................................................................
Recommendations for Further Research ...................................
26
26
27
27
28
28
29
References ...............................................................................................................
32
V.
vi
LIST OF TABLES
TABLE
PAGE
1. GPA of Athletes and Nonathletes .....................................................................
24
2. Attendance of Athletes and Nonathletes ...........................................................
24
3. Referrals of Athletes and Nonathletes ..............................................................
25
vii
ABSTRACT
During tough financial times, school districts are continuing to look for ways to save
money by cutting programs. Some school districts look to the cost of athletics as a
way to save money. Educators who consider this option may wish to consider the
effects of athletics on the academic achievement, attendance, and discipline of student
participation. This study involved one high school in the Central Valley of California
and compared the athletes to the nonathletes in regard to their GPA, days in
attendance at school, and the number of disciplinary referrals. Students were
identified as athletes, if they participated in any of the fourteen sports offered at the
school. Students were identified as nonathletes if they did not participate in any sports
at the school. The sample number selected for both the athletes and nonathletes was
fifty and they were selected randomly. After the students were identified, they were
listed alphabetically. Every seventh student athlete was selected from a list of 355
students for this study and every ninth student nonathlete was selected from a list of
459 students for this study. A t-test of independent samples was used to analyze the
data at the .05 level. The data that were collected and analyzed suggest athletes have a
significantly better GPA and attendance record than nonathletes. Also, the results
suggest that the number of disciplinary referrals between athletes and nonathletes was
not significantly different.
viii
CHAPTER I
INTRODUCTION
On any given autumn Friday night in the Central Valley of California, one can
drive from community to community just following the lights of high school football
stadiums. In some communities, the entire town almost closes down for the weekly
football game. This tradition, which occurs throughout the Central Valley, is observed
all over the country and not just with football. Some communities will even close for
basketball games, wrestling matches, baseball games, or other athletic events. These
activities bring pride to students, teachers, parents, administrators, and communities.
High school athletics is a common topic of discussion around the community. For
many, high school athletics is a big part of their lives.
Although embedded in the culture and a way of life in many communities,
athletic programs are considered for reduction or elimination when cutting budgets in
difficult economic times. Frequently, sports are dropped in order for a district to save
money. In response, communities flip the tables and restore funding cuts by raising
money for athletic programs (Staples, 2009). High schools are not the only
educational institutions that make cuts to their athletic programs. Universities have
taken similar actions. For example, the University of California at Berkeley decided
to cut athletic programs in 2010 to save money. In response, the University of
California at Berkeley alumni raised money to restore the cuts (Associated Press,
2011).
1
2
Little is known about the origin of organized high school athletics, but it is
known that in the state of Connecticut in 1875, Norwich Free Academy and New
London High School began a rivalry in football, the oldest in the United States, which
continues to this day. During the late 1800s and on the heels of the popular new sport,
states quickly learned there was a need to form a governing body of high school
athletics to provide safety for athletes, rule enforcement, officiating, and champions.
In 1895, the first state to create a unified federation was Wisconsin (Wisconsin
Interscholastic Athletic Association, 2011). The purpose of the federation was to
create rules of competition by which all association members would abide. Many
states followed this model of a unified system. In 1920, the National Federation of
State High School Associations was formed as a governing body of public and most
private school athletics in the United States. The national association has a
membership of more than 18,500 schools (National Federation of State High School
Associations, 2011).
Clearly, high school athletics has a history and plays an important role in
communities. But what role does athletics play in the lives of the student athletes
themselves? How does it affect the lives of students and their performance in specific
areas? When schools are looking at cutting athletic programs as a means to save
money, they may want to first consider the effects that athletics have on their
students. If the student athletes are better than their nonathlete peers on the basis of
GPA, attendance, and discipline, would schools want to cut their athletic programs?
3
This study will determine if there is a difference between high school athletes and
nonathletes in the following three areas: GPA, school attendance, and discipline.
Statement of the Problem
Public education is in a budget crisis. Because of poor choices by multiple
parties, education is at a risk. School districts in California are trying to figure out
how they can balance a budget during these times. Districts have to do more with
less, be creative with spending, and cut departments and student activities. One area is
high school athletic programs.
Many parents cry foul when school districts even mention dropping athletics
and react by threatening to take their children to another school district or private
school. Before school districts make this decision, it is important that educators,
students, policy makers and community members know the effects of high school
athletics on students. This study may give some insight to this topic of interest.
The purpose of this study is to examine the difference between high school
student athletes and nonathletes in terms of grades, school attendance and discipline.
Such information may be helpful to educational leaders and policy makers as they
contemplate cuts to athletic programs in public schools.
Research Question
Is there a difference in grades, school attendance, and discipline between high
school student athletes and nonathletes?
4
Hypotheses
H1: There is no significant difference in the mean GPA between students who
participate in athletics and students who do not participate in athletics.
H2: There is no significant difference in the mean number days of attendance
between students who participate in athletics and students who do not participate in
athletics.
H3: There is no significant difference in the mean number of discipline referrals
between students who participate in athletics and students who do not participate in
athletics.
Significance of the Study
Hopefully, this study will provide teachers, administrators, and community
members with useful information regarding the effects of athletics in the high school
environment. This author will determine if the GPA, attendance, and discipline of
athletes are different than nonathletes at one high school located in the central valley
of California. This study may encourage those who make critical decisions regarding
school finance to consider some of the positive and negative consequences of
reducing athletic programs.
Limitations and Delimitations
The following limitations and delimitations are presented to assist the reader
in understanding the results of this study and to moderate the generalizations one
might assume:
5
Limitations
This study is limited to student athletes and students who are nonathletes at
one 9–12 high school in Central California during one school year.
Delimitations
For the purpose of this study, the following will not be taken into
consideration: gender, ethnicity, socioeconomic status, athletic team success, and
individual student athletic success.
Definitions of Terms
For the purpose of clarification, the following definitions are included:
Student Athlete. A student who participates as a member of a team in at least
one sport in an academic year. The three levels of competition that were selected for
this study are all sponsored by the high school at the varsity, junior varsity or
freshman level. The sports that were selected for this study are as follows:
Fall: Coed Football, Girls’ Volleyball, Boys’ Soccer, Girls’ Golf and Coed Cross
Country.
Winter: Boys’ Basketball, Girls’ Basketball, and Coed Wrestling.
Spring: Boy’s Baseball, Girls’ Softball, Coed Tennis, Girls’ Soccer, Boys’ Golf and
Coed Track and Field.
Nonathlete. A student who chooses not to participate in high school athletics.
Grade Point Average (GPA). A measure of academic achievement for
students in high school. Letter grades are converted using the following scale: (A = 4;
6
B = 3; C = 2; D = 1; and F = 0). Each numeric grade is multiplied by credits per
course. The total number of grade points is divided by the total credits.
Attendance. Student presence or absence during the school day. Students in
class are marked as present. Students who are not present are marked absent.
Discipline. Any infraction that results in a referral. Disciplinary referrals result
in formal action by building administrators. An action may include a consequence
such as a formal warning, detention, Saturday school, in-school suspension, out-ofschool suspension, or recommendation for expulsion.
Summary
In these tough economic times, it is easy for school districts to cut programs.
In Chapter I, the rich history of high school athletics was discussed. Is there a
difference between athletes and nonathletes regarding attendance, behavior, and
academic achievement? This study will attempt to answer this question by comparing
the GPAs, attendance, and discipline of student athletes and nonathletes.
Chapter II will review and examine related literature on the topics of this
study: GPA, attendance, and discipline.
CHAPTER II
REVIEW OF THE LITERATURE
Introduction
This study will determine if there is a difference between high school athletes
and nonathletes in the following three areas: Grade Point Average (GPA), school
attendance, and discipline. This chapter will review studies related to student athletes
and nonathletes regarding GPA, discipline and attendance.
GPA
In the state of Nebraska, Dick (2010) examined the differences between
students who participated in extracurricular activities which included athletics and
those who did not. He selected a midsized western Nebraska community of
approximately 14,800 people. Enrollment at the high school was about 850 students.
A t-test was used to analyze the difference in GPA between students who
participated in extracurricular activities and those who did not. He found that the
students who participated in extracurricular activities had a mean GPA of 3.06 with a
standard deviation of .789. During the same school year, the students who did not
participate in extracurricular activities had a mean GPA of 2.39 with a standard
deviation of .789. There was a significant difference in the GPA in favor of students
who participated in extracurricular activities (t(273) = -6.940, p < .001).
Streb (2009) investigated the GPA of 492 graduating seniors and surveyed
them about their participation in after school programs. A t-test was used to see if
7
8
there was a significant difference. The students participating in the study were from a
large midwestern school district.
Streb found that students who participated in after school, extracurricular
activities had a higher GPA than those who did not participate. The mean GPA of
students in extracurricular activities was 3.14 with a standard deviation of 0.61. The
students who did not participate had a mean GPA of 2.52 with a standard deviation of
0.76. There was a significant difference in GPA in favor of students who participated
in extracurricular activities. The difference was determined at the .05 level of
significance.
Stephens and Schaben (2002) studied students in grade eight during the 1998–
1999 academic year at an urban middle school in Omaha, Nebraska. The athletes
were classified as playing one or more sports during that school year. Of the 136
students who participated in the study, 73 were athletes and 63 were nonathletes.
Also, the authors made comparisons based on gender that involved an equal number
of male and female participants (68).
The authors found that the mean GPA of athletes was 3.151 with a standard
deviation of 0.807. The nonathletes had a mean GPA of 2.400 with a standard
deviation of 1.010. The mean GPA of the female athletes was 3.400 and the males
was 2.967. The female nonathletes had a mean GPA of 2.453 and the male
nonathletes had a mean of 2.310. The analysis showed that GPA of male and female
athletes was significantly higher than the GPA of nonathletes. The difference was
determined at the .05 level of significance.
9
Rombokas, Heritage, and West (1995) investigated the effects of high school
athletics and the relationship to their college academic performance. There were 292
college students who participated in the study. Participation in extracurricular
activities was assessed by a questionnaire. All questionnaires were anonymous,
voluntary, and self-administered. The university is located near a large metropolitan
area in the mid-South. Out of the 292 participants, 172 were female and 120 were
male.
Students reported their high school and college GPA. Also, they identified the
high school activities for which they participated while in high school. Of the students
surveyed, 61.1% played a sport and had a GPA of 3.0 or higher in high school and
41.8% who participated in high school athletics, had a 3.0 or higher GPA in college.
The study revealed that almost half of the students who participated in high school
athletics maintained a GPA of 3.0 or above in college.
Lumpkin and Favor (2012) looked at all students in the state of Kansas who
participated in athletics and compared them with students who did not participate in
athletics in the 2008–2009 school year. Athletes were identified by using the Kansas
State High School Activities Association master roster. The researcher then used
academic data of participating students who were available from the Kansas State
Department of Education. This information included the results of the seniors who
took the ACT and results of the optional questionnaire in which students self-reported
their GPA.
10
Of the students who were identified as athletes, 9,347 self-reported their GPA
on the ACT. Of the students who were identified as nonathletes, 9,221 self-reported
their GPA on the ACT. The athletes (80.1%) reported a GPA of 3.0 or higher. The
nonathletes (70.5%) reported a GPA of 3.0 or higher. The GPA of the athletes was
9.6% higher. In addition, 58% of the athletes reported having a GPA of 3.5 or above.
Also, 39.8% of the nonathletes reported having a GPA of 3.5 or above. The GPA of
the athletes was 12% higher. Overall, the GPA of senior athletes was higher
compared to the nonathletes.
JacAngelo (2003) looked at 10 public high schools in the Miami-Dade County
School District. The 10 schools were randomly selected from the district’s 31 high
schools. The author collected data on 2,081 male and female students in total; 1,081
who were identified as athletes and 1000 as nonathletes. Students were in grades 9–
12.
The relationship between athletes and nonathletes was evaluated by an
analysis of variance (ANOVA). The study stated that both male and female grade
point averages of athletes were significantly higher than nonathletes. The male
athletes had a mean GPA of 2.64 and the male nonathletes had a mean GPA of 1.87.
The female athletes had a mean GPA of 2.89 and the female nonathletes had a mean
GPA of 2.04. The cumulative mean GPA for athletes was 2.74 and the cumulative
mean GPA for nonathletes was 1.95 with a standard deviation of .43 for athletes and
.51 for nonathletes. The mean GPA difference of 0.79 was significant.
11
Attendance
In a study conducted by McCarthy (2000), 17 of the largest schools in
Colorado participated in a survey. The number of students who completed the survey
was 19,543. Of the 17 schools, 10 reported attendance records. One purpose of the
study was to determine if there was a difference in attendance between high school
students who were participants in athletics and those who were non participants.
The results of the survey were reported descriptively. Information was
collected from 10 high schools in Colorado. The mean daily absentee rate per student
was 15.1057 days per school year. The nonparticipant group (56.9%) had a mean
daily absentee rate per student of 19.3798 days per school year. The participants in
athletics (43.1%) had a mean daily absentee rate per student of 9.7736 days per
school year. The students who participated in athletics were absent almost half as
many days as nonparticipants.
In 1988, the National Center for Education Statistics conducted a survey of
25,000 eighth graders, their parents, teachers, and principals across the country to
determine if student participation in extracurricular activities is related to student
success in school. In 1992, the center conducted a follow up survey of the same
students who were in their senior year. Extracurricular activity of high school seniors
was an item that was addressed in the survey. O’Brien and Rollefson (1995) reported
the findings descriptively. They found that 50.4% of participants and 36.2% of
nonparticipants had no unexcused absences during the first semester of their senior
12
year. In this same survey, 50.7% of participants and 42.3% nonparticipants never
skipped classes during the first semester of their senior year.
Diaz (2005) surveyed 2,069 students at 14 high schools in Southwest
Minnesota. The region is overwhelmingly rural with farms and small towns. An
ANOVA was used to analyze the data. Diaz determined a positive relationship
existed between extracurricular activity participation and student attachment to the
school (p < 0.05). With the increased level of attachment came an increased level of
how much the students were enjoying school. Also the study showed a decline in the
desire to change schools as participation increased.
Whitley (1995) conducted a study that included 133 of the 321 high schools in
North Carolina. All participant schools were members of the North Carolina High
School Athletic Association (NCHSAA). The subjects of this study were students in
grades 9-12 during the 1994–95 school year. They randomly selected athletes and
nonathletes from each school to participate in a survey. The NCHSAA collected the
surveys and the respondents were classified as athletes and nonathletes. Whitley also
used a state reporting program to determine the attendance rates of students.
The mean absence rate for athletes was 6.61 days per year and for nonathletes
was 12.58 days per year. The t-test was used to determine if a significant difference
existed between the two groups. The difference was significant as the nonathlete
group missed almost twice as many days per year as the athletes
t = 35.00, p < .0001).
13
Kaufmann (2002) attempted to determine if a relationship existed between
student achievement and participation in athletics. The author looked at high school
students in two suburban high schools from a major metropolitan area. The first
school referred to as School A had 377 records; the second school, referred to as
School B had 675 records. The schools together had 1,052 records that were used for
the study. The study looked at the students’ first 3 years of high school attendance,
which were grades 9-11. The period of the study was from 1994 to 1998.
An ANOVA was used to analyze the data (p < .01). The study showed student
absentee rates over the three year period. School A athletic participants were absent
an average of 18.451 days. The nonathletic participants were absent an average of
30.728 days. At School B, the participants in athletics were absent an average of
21.192 days. The nonathletic participants were absent 30.396 days. Similar results
were observed within each school. Together the two schools’ athletic participants
averaged 20.330 days absent in a three year period. This was compared to the
nonparticipants who averaged 30.489 days absent over the three year period. This
difference of just over 10 days was significant (p < .001).
Barden (2002) looked at four medium size high schools in eastern Georgia.
These four schools had approximately 4,530 students combined from grades 9–12.
The four school’s 600 students were randomly selected for the study. The study’s data
were collected for the 2000–2001 school year.
The study showed that the group of nonparticipants averaged 10.94 absences
per student for the school year. Those students who participated in athletics averaged
14
7.67 absences for the school year. The athlete group was present an average of 3 days
more per year than the nonparticipant group. The study showed that students who
participate in multiple activities such as athletics, school clubs, and music and the arts
average only 5.93 days absent per school year. The study used a statistical analysis to
generate the averages with a standard deviation of 12.73 for athletes and 11.46 for
nonparticipating group.
Discipline
Laughlin (1978) studied 243 athletes who wrestled in the San Francisco Bay
Area. The study focused on wrestlers who stayed on the team and those who quit. The
students came from seven high schools located in two school districts. The coaches
for each team met with Laughlin and reported the date of birth, year in school, and
weight classification of each athlete. Laughlin secured discipline information as well
as other data from the schools.
The wrestlers had a mean of .09 disciplinary referrals during their season, with
a standard deviation of .40. During the off season, they had a mean of .13 disciplinary
referrals with a standard deviation of .29. On the other hand, the wrestlers who quit
had a mean of .31 referrals with standard deviation of .58 for both in and out of
season. The wrestlers’ referrals were less during the wrestling season and higher
during the off season. The wrestlers who quit the team had almost three times the
number of referrals as those who stayed.
Overton (2001) performed a state wide study on athletic performance
comparing athletes to nonathletes in North Carolina. His study consisted of over
15
125,000 students in 131 high schools who were members of the North Carolina High
School Athletic Association. The schools that participated also used North Carolina’s
Student Information Management System, which allowed for the data to be analyzed.
A t-test was used to compare a random 117 athletes to 117 random
nonathletes. The study found that the mean average referral for athletes was 33.3%
and the mean average referral for nonathletes was 41.8%. The athletes had
significantly less referrals than the nonathletes by a mean difference of 8.5%. The
significance was p=.0012.
Rhea and Lantz (2004) compared aggressive behaviors of athletes and
nonathletes. The study consisted of 338 athletes and nonathletes from 4 rural high
schools in the Midwest. The participants included 234 high school athletes, 137 male
and 97 female. The nonathletes were comprised of 104 students, 64 males and 40
females. The Youth Risk Behavior Surveillance Survey was completed by the
students.
The authors used a chi square test to analysis the data collected from the
survey. The results showed that nonathletes reported higher levels of problematic
behaviors. They scored higher in the trouble in school category (χ² (1, 202) = 5.27, p
< .03). They also scored higher in the trouble with police category (χ² (1, 202) = 7.74,
p < .03). They also scored higher in the other three categories: drinking while driving
(χ² (1, 202) = 14.74, p < .0001), marijuana use (χ² (1, 202) = 13.53, p < .0001), and
cocaine use (χ² (1, 202) = 4.20, p < .05). The only category that was found not to have
any significant difference was property damage. The study suggested there are no
16
significant differences found between female athletes and female nonathletes for any
of the variables that were classified as violent. The male and female nonathletes in
most areas reported higher levels of behavior problems compared to those who
participated in athletics.
Ramsey (2010) conducted a study on Hispanic athletes and nonathletes. The
research was conducted in Northwest Georgia at Southeast Whitfield High School.
Only Hispanic students in the eleventh and twelfth grades participated. The school
was selected because it had a 50.8% Hispanic population. Participants consisted of
333 students, 165 female and 168 male of which 109 were athletes and 224 were
nonathletes.
A Wald chi-square was used to analyze the data that were provided by the
school, county, and coaches. One of the variables considered was discipline.
Information gathered through office referrals was analyzed. The results of the study
showed that disciplinary referrals were issued to participants less often than
nonathletes (p < .004).
Zaugg (1998) conducted a study at Magrath Junior/Senior High School in
Magrath, Alberta, a small rural farming town. The study took place during the 1996–
1997 school year. This study involved 134 high school students, 52 athletes and 82
nonathletes. The students, between the ages of 15 to 19, were in grades 10–12. The
athletes were on the basketball and volleyball teams. Of the athletes, 24 were male
and 28 were female. Of the nonathletes, 42 were male and 40 were female.
17
The study compared the athletes and nonathletes’ behavior according to the
number of office referrals for discipline. The school also has a demerit point system
for inappropriate behavior. Demerit points were assigned according to the severity of
the offense. The athletes consisted of 52 students, eight of whom were sent to the
office for discipline. Fifteen percent of the group with 11 disciplinary visits was
assigned a demerit point mean of 2.1. The nonathletes consisted of 82 students, 15 of
which were sent to the office for discipline. Twenty-one percent of the group with 39
disciplinary visits was assigned a demerit point mean of 5.5. The author did not find a
significant difference between the athletes and nonathletes with regard to disciplinary
visits or demerit points.
Cohen, Taylor, Zonta, Vestal, and Schuster (2007) looked at another form of
discipline by looking at the rates of juvenile arrests to determine if there was a
relationship with the availability of high school extracurricular sports. This study took
place in the Los Angeles County public high schools in 2002; 175 of the 198 high
schools were invited to participate. Schools were asked to fill out a survey on the
number of extracurricular sports programs offered as well as a percentage of students
who participated in those programs. This information was compared with the
community data on the rate of juvenile arrests in those same areas of participating
high schools in Los Angeles.
The data were evaluated with an ordinary least squares regression (OLS)
analysis. The schools that reported 13 or fewer sports programs had an average
juvenile arrest rate of 30.9 per 10,000 youth. The schools that offered 16 or more
18
sports programs had an average juvenile arrest rate of 1.7 per 10,000 youth. There
was a significant difference of over 29.2 juvenile arrests per 10,000 youth. The results
of the study suggested a positive relationship between sports programs and lower
juvenile arrests (p = 0.17).
Summary
Chapter II consisted of a review of the literature regarding the effects of
athletic participation on GPA, attendance, and discipline. Chapter III will present the
methodology and procedures used in this study.
CHAPTER III
METHODOLOGY
Introduction
This study attempted to determine if there is a difference between high school
athletes and nonathletes in the following three areas: GPA, school attendance, and
discipline. The methodology of this study is discussed in the following order:
(1) selection of the sample population and the identification of the treatment and
control groups, (2) instrumentation, and (3) statistical analysis.
Sample Population
This study was conducted using data from one high school located in the
Central Valley of California during the 2012–2013 academic year. This high school’s
population included students enrolled in grades 9, 10, 11, and 12. The total population
of the school was 863 students, which consisted of 435 (50.4%) males and 428
(49.6%) females. The ninth grade included 235 (27.2%) students. The tenth grade
included 231 (26.8%) students. The eleventh grade included 178 (20.6%) students.
The twelfth grade included 219 (25.4%) students.
The students who were eligible for this study were enrolled at the high school
for the entire school year (N=814). The students were identified as athletes if they
participated in at least one of the 14 sports offered at the high school and were
enrolled for the entire school year. The athletes consisted of 355 of the students in the
school and represented 44% of the student population. The students who were
19
20
identified as nonathletes did not participate in athletics in the 2012–2013 school year
and were enrolled for the entire academic year. The nonathletes consisted of 459 of
the students in the school and represented 56% of the student population.
This Central Valley high school is made up of mostly two ethnic groups:
white, non-Hispanic and Hispanic. The white, non-Hispanic population is 51%,
Hispanic population 43%, and Asian 2%. The school reported 1% or less in the
following ethnic groups: Two or more races, African American, Pacific Islander,
American Indian, and Filipino.
Treatment Group
The students in the Treatment Group (N=50) participated in athletics during
the 2012–2013 school year. Students were identified as athletes if they participated in
at least one of the 14 sports that were offered during the school year and were
enrolled for the entire academic year. This study examined all levels of athletes
including varsity, junior varsity, and freshman sports.
Control Group
The students in the Control Group (N=50) did not participate in athletics
during the 2012–2013 school year and were enrolled for the entire academic year.
Instrumentation
The data were collected by the use of the district’s student information system
which is called Aeries. Students were identified as an athlete or nonathlete by using
the team rosters that were produced for each sports team. Aeries was used in this
study to retrieve the number of days students were presents, grade point average, and
21
number of documented referrals in the discipline record. After students were
identified as either athletes or nonathletes, 50 students were randomly selected to
create the data for this study. After the athletes were identified, their names were
listed alphabetically and every seventh athlete from a list of 355 students was selected
for this study. The same process was completed for the nonathletes and every ninth
nonathlete from a list of 459 students was selected for the study.
Statistical Analysis
The Statistical Program for Social Sciences 20.0 (SPSS) was used to analyze
the data. A t-test for independent samples was used to determine if there is a
significant difference in the means between high school athletes and nonathletes in
the following three areas: GPA, school attendance, and discipline. The alpha level
was set at the .05 level of significance.
Summary
Chapter III presented and discussed the sample, instrumentation, and the
statistical analyses to be used. Results of this study will be reported and described in
Chapter IV.
CHAPTER IV
RESULTS OF THE STUDY
Introduction
The purpose of this study was to examine the difference between high school
student athletes and nonathletes in terms of grades, school attendance and discipline.
The results from the tests will be discussed in the following order: (1) description of
the sample, (2) findings related to each hypothesis, and (3) summary.
Description of the Sample
This study was conducted using data from one high school located in the
Central Valley of California during the 2012–2013 academic year. This high school’s
population included students enrolled in grades 9, 10, 11, and 12. The total population
of the school was 863 students, which consisted of 435 (50.4%) males and 428
(49.6%) females. The ninth grade included 235 (27.2%) students. The tenth grade
included 231 (26.8%) students. The eleventh grade included 178 (20.6%) students.
The twelfth grade included 219 (25.4%) students.
The students who were eligible for this study were enrolled at the high school
for the entire school year (N=814). The students were identified as athletes if they
participated in at least one of the 14 sports offered at the high school and were
enrolled for the entire school year. The athletes consisted of 355 of the students in the
school and represented 44% of the student population. The students who were
identified as nonathletes did not participate in athletics in the 2012–2013 school year
22
23
and were enrolled for the entire academic year. The nonathletes consisted of 459 of
the students in the school and represented 56% of the student population.
After the athletes were identified, they were compiled on a list alphabetically
and every 7th athlete on the list was selected for this study. The same process was
completed for the nonathletes and every 9th nonathlete was selected for the study.
The treatment group consisted of 50 randomly selected students who were identified
as athletes. The control group consisted of 50 randomly selected students who were
identified as nonathletes.
Findings Related to H1
H1: There is no significant difference in GPA between students who
participate in athletics and students who do not participate in athletics.
An independent t-test analysis was used to determine if a difference exists
between the treatment and the control groups. For this analysis, significance was set
at p < .05. Results indicated that there was a significant difference in GPA between
the athlete group and the nonathlete group (see Table 1). Hence, the null hypothesis
was rejected.
Table 1
GPA of Athletes and Nonathletes
Variable
Nonathletes
Athletes
N
50
50
M
2.5442
2.9350
SD
.74022
.57558
p
.004*
*p < .05
The results suggest that the athlete group has a significantly better GPA than
the nonathlete group (p = .004).
24
Findings Related to H2
H2: There is no significant difference in attendance between students who
participate in athletics and students who do not participate in athletics.
An independent t-test analysis was used to determine if a difference exists
between the treatment and the control groups. For this analysis, significance was set
at p < .05. Results indicated that there was a significant difference in the days present
at school between the athlete and the nonathlete group (see Table 2). Hence, the null
hypothesis was rejected.
Table 2
Attendance of Athletes and Nonathletes
Variable
Nonathletes
Athletes
N
50
50
M
167.20
170.24
SD
7.279
4.732
p
.015*
*p < .05
The results suggest that the athlete group has a significantly better attendance
record than the nonathlete group, with regard to the amount of days present at school
(p = .015).
Findings Related to H3
H3: There is no significant difference in discipline problems between students
who participate in athletics and students who do not participate in athletics.
An independent t-test analysis was used to determine if a difference exists
between the treatment and the control groups. For this analysis, significance was set
at p < .05. Results indicated that there was no significant difference in the number of
25
discipline referrals between the athlete group and the nonathlete group (see Table 3).
Hence, the null hypothesis was accepted.
Table 3
Referrals of Athletes and Nonathletes
Variable
Nonathletes
Athletes
N
50
50
M
1.94
0.94
SD
3.467
1.570
p
.066
The results suggest that the discipline records of students in both groups were
similar. There is no significant difference in the mean number of discipline referrals
between the athlete group and the nonathlete group.
Summary
Chapter IV presented the results of the t-test that were used to accept or reject
the null hypotheses of this study. The results suggested that students who participate
in athletics have a better GPA and attendance record. Chapter V will present a
summary, conclusions, and recommendations for further research.
26
CHAPTER V
SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS
Introduction
The purpose of this study was to examine the difference between high school
student athletes and nonathletes in terms of grades, school attendance, and discipline.
A t-test for independence was utilized to determine whether there was a significant
difference between students who participate in athletics and those who do not
participate. Both groups represented in this study consisted of students from one high
school located in the Central Valley of California during the 2012–2013 academic
year.
Chapter V summarizes this study, presents conclusions, and provides
recommendations for further research.
Summary
Since the great recession, educators in many districts and schools have looked
at ways to save money. Some school districts are looking at cutting athletic programs
as a way to save money. The purpose of this study was to examine the difference
between high school student athletes and nonathletes in terms of grades, school
attendance, and discipline. Such information may be helpful to educational leaders
and policy makers if they should contemplate cuts to athletic programs in public
schools.
27
Data were gathered on GPA, attendance and the number of disciplinary
referrals per students. Students were identified as athletes if they participated in at
least one of the fourteen sports offered at the school. Students were identified as
nonathletes if they did not participate in any of the school sponsored sports. After
students were identified as either athletes or nonathletes, 50 from each group were
randomly selected for this study. After the athletes were identified they were
compiled on a list alphabetically and every seventh athlete on the list was selected for
this study. The same process was completed for the nonathletes and every ninth
nonathlete was selected for this study.
GPA
H1: There is no significant difference in GPA between students who
participate in athletics and students who do not participate in athletics.
Students’ grade point averages, computed on a 4.0 scale, were used in this
analysis. The students who participated in athletics were found to have a significantly
higher grade point average (M = 2.9350, SD = .57558) than the nonathletes (M =
2.5442, SD = .74022) (p =.004).
Attendance
H2: There is no significant difference in attendance between students who
participate in athletics and students who do not participate in athletics.
Students’ yearly attendance was used in this analysis. The total days in the
school year were 175. The students who participated in athletics were present
28
significantly more days (M = 170.24, SD = 4.732) than the nonathletes (M = 167.20,
SD = 7.279) (p = .015).
Discipline
H3: There is no significant difference in discipline problems between students
who participate in athletics and students who do not participate in athletics.
Student referrals were used in this analysis. The data showed no significant
difference in the mean number of discipline referrals between athletes and
nonathletes.
Conclusions
After analyzing the data, the study showed significant differences between
athletes and nonathletes in GPA and attendance. There was no significant difference
in regard to the number of discipline referrals.
This study is consistent with other studies across the nation. Dick (2010)
conducted a study with a similar school size in Nebraska. He found that the athletes
had a significantly better GPA. Similarly, JacAngelo (2003) studied 31 high schools
in the Miami-Dade School District in Florida. He found that the athletes’ GPAs were
significantly higher than nonathletes.
The results of this study on attendance were found to be consistent with other
studies that have been done. McCarthy (2000) examined schools in Colorado and also
found that athletes had significantly better attendance than the nonathletes. Also,
Barden (2002) concluded that athletes had better attendance by an average of 3 days
more per academic year.
29
This study suggests that discipline records of athletes are not better than those
of nonathletes. This is not consistent with the research on this topic. Overton (2001)
found that in a North Carolina study, athletes were found to have significantly lower
discipline referrals than nonathletes. Ramsey (2010) studied the disciplinary records
of Hispanic student athletes and Hispanic student nonathletes in Georgia and found
the athletes had significantly fewer disciplinary referrals.
This study validates the work of other researchers regarding the importance of
students participating in athletics as a valuable way to help students achieve a higher
GPA and better attendance per school year. As school districts face tough financial
decisions and look at programs to cut in order to save money, they need to first look
at this study and others before taking action that may curtail athletic programs. They
need to consider the potential effects on the GPA, attendance, and discipline of
students who participate in athletics. This study has shown educators the value of
athletic programs.
Recommendations for Further Research
Recommendations for continued studies in this area would include the
following:

Conduct research on a larger scale that would include regional, county, state
and national comparisons.

Conduct research to determine if differences exist between athletes and
nonathletes when school size is a variable.
30

Expand the research to other extracurricular activities outside of athletics;
examples include associated student body activities, clubs, band, choir, school
dance or cheer team, and drama.

Conduct research on athletes and see if their GPA, attendance, and discipline
are better before, during, and/or after the sports season.
REFERENCES
32
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