Research

Difference in GPA Between Working and Non Working Students 1
Difference in GPA Between Working and Non Working College Students
Karina Bitman

Abstract
College is always an expensive time in a young person’s life. The new experiences and
challenges also bring financial difficulties. Even students who receive government aid
might not be meeting all their financial needs. College tuition isn’t the only expense
students deal with; they must pay books, supplies, and housing if necessary. It is common
for college students to work to offset some of the expenses. As the economy shifts, and
tuition prices constantly go up every several years, it’s interesting to see if working
directly affects GPA. GPA is a major indicator of the academic performance for most
schools. Being able to understand the factors contributing to GPA is only beneficial to
both the student and the school. I used the six step hypothesis test to understand if there is
a difference in GPA between working and non-working students. I conducted the
Independent T test to compare the two samples.

Attending college is a unique and challenging time for any young adult. Students are
introduced to a different way of learning, a new culture, and a new set of expectations.
This transition period also includes new stressors that the student might not have had to
deal with before. While in college, a major stressor is money. While some students
receive financial aid in the form of grants and scholarships, that might not cover all the
expenses. Regardless, if a student lives alone or with their parents, college is a big
expense. To offset some of the expenses, a majority of students choose to work part or
full time to make the situation more manageable. Interestingly enough, in the 1960’s,
most universities in California were either low-cost or free. As we can see, that is no
longer true in our day and age. University costs are constantly going up. According to
Kate Pickert, an editor of Time magazine, “In recent decades, the state has decreased the
share of overall public higher education costs it pays for and the system has become
increasingly dependent on student contributions, among other sources, for the difference
(Pickert, 2014).” This could be an explanation of why more students have decided to
work.. A similar study submitted to the International Journal of Business Administration
in 2014, looked to see if work was a factor in lower GPA. The research showed that when
students work more than 11 hours per week there is a small decline in GPA (Tessema,
Ready, Astani, 2014). A study done in Cal State Marcos on “Factors Affecting GPA”
looked at multiple factors in a student’s life, such as: commute, work, motivation, and
time spent studying. They concluded that the most significant factor to GPA was the
amount of time spent studying (Legpasi, Perez, Remigio, Sengsourya, 2008). As a
college student myself, I have always worked full-time and went to school full-time. It is
very challenging as both require large time commitments. I am able to maintain a “B”

average in terms of my GPA. I always wondered if work was a contributor to overall
GPA. This is what sparked my question and curiosity to explore this further. GPA stands
for grade point average and is a student’s overall performance in their college. A lot of
schools value this information as it is an indicator of the college’s performance
academically. It is important to understand the changing landscape to better understand
students.
1) ResearchQuestion: On average, is there difference in GPA between working and
non working LACC college students.
2) Hypothesis:
H0: µ1-µ2=0 (µ1=µ2)
H1: µ1-µ2≠0 (µ1 ≠µ2)
Methods:
When looking to obtain a sample to answer my research question, I utilized my network
at Los Angeles City College. I had a friend of mine post a flyer in her Microbiology class
with the online link to my survey. She took the time to explain to the students how to
access the survey and reassured them it was anonymous. This allowed the students to
answer my questions without worrying about their name being identified; which allowed
them to be more honest in their responses. I bought candy for her to hand out to the
students as an incentive. She encouraged everyone to apply so I can choose from a larger
sample. I ended up using a sample of twelve students; six working and six non working.

When creating my questionnaire, I decided to go with SurveyMonkey.com. It is an
online website that allows you to create free surveys that you can link to your social
media or directly e-mail to people. It’s also completely anonymous for the user. I made
sure my questions were simple and concise; I wanted the person taking the survey to be
able to finish it in under a few minutes. I decided to use the Independent Sample T test to
conduct my research. I chose this because I am comparing two different groups of people.
Questionnaire:
1) What is your age?
2) What is your gender?
3) Please describe your race/ethnicity?
4) Are you a CSUN student?
5) Are you currently employed?
6)What is your current GPA?
3) Reject Ho at = 0.05 with 10 df when t exceeds +/_ 2.228
Results:
According to my results, I decided to retain my null hypothesis. When looking at my
data, I did not notice a difference in GPA between students who work and students who
don’t work at LACC. The calculated T value came out to .000; this does not exceed the
critical T value of +/- 2.228. The standard error difference came out to 1.01653 between
the groups. We are 95% confident that the average mean difference is between -
2.26497, 2.26497. Since there is a 0 in between my confidence interval, this is yet
another indicator to retain. The probability of calculating the observed test statistic, if null

is true, is p = 1.000. My means for both groups came out to 4.50. The standard deviation
came out to 1.679.
The graphs below provide a detailed visual representation of the data collected. It helps
to visually see all the information in the form of tables to understand the interpretation of
the results.
Group Statistics
work N Mean Std. Deviation Std. Error Mean
gpa yes 6 4.5000 1.97484 .80623
no 6 4.5000 1.51658 .61914
Independent Samples Test
t-test for Equality of Means
Sig. (2-tailed) Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower
gpa Equal variances assumed 1.000 .00000 1.01653 -2.26497
Equal variances not
assumed
1.000 .00000 1.01653 -2.28558
t-test for Equality of Means
95% Confidence Interval of the
Difference
Upper
gpa Equal variances assumed 2.26497
Equal variances not assumed 2.28558
Levene's Test for Equality of
Variances
t-test for Equality of
Means

F Sig. t df
gpa Equal variances assumed 1.216 .296 .000 10
Equal variances not
assumed
.000 9.376
Discussion:
On average, there is no difference in GPA between working and non working LACC
college students. According to the study done by the International Journal of Business
Administration, mentioned in my Introduction, my findings are not consistent. The study
reflected on the fact that once a student works more than 11 hours per week, there is a
small decline in GPA (Tessema, Ready, Astani, 2014). My results seem to show
something slightly different. I took samples from full and part time students at LACC.
The working students were able to uphold high GPAs ranging from 3.5-4.0. The results
in GPA from the students who worked was not significantly different from the students
who didn’t work. I think this can be the result of multiple factors.

It’s important to take environment into account. Some students can have a more
supportive environment that leads to a better education even if they do work full-time. I
think it’s also important to take commute into consideration. I can personally say my
GPA suffered when I had to take a two hour bus ride to college. It’s important to factor in
every possibility that can lead to contributing to student’s GPA and I think work is just
one aspect.
The second study I looked at was from Cal State Marcos, “Factors Affecting GPA,” this
is the closest in line with my own findings. This study takes the time to look at multiple
factors leading to effects on GPA. As mentioned earlier, they concluded that it was
actually the time spent studying that had the biggest effect (Legpasi, Perez, Remigio,
Sengsourya, 2008) . I felt my own research could compliment this. My results indicate
that there was no difference in GPA between working and non working students at least
based on work alone.
I feel my research should lead to further research in this arena. There should be more
studies looking at factors that contribute to GPA in depth. Additionally, further research
to test to see which tools could be the most helpful for students who are working (such as
writing centers, tutoring, better access for students to have a place to study, and daycares
on campus). We can’t stop students from having a job. Jobs allow students to mature
mentally as adults and gain important work experience for their personal and professional
growth. I think it’s important to find out how to aid those students who are working to
stay motivated. I also think it’s important to do further research on students who don’t
hold jobs and their motivation in school, to better assist that group as well. GPA is an

important element to a college’s success and making sure students are performing well is
crucial.
I felt my research did have a few limitations. I didn’t look at the differences between
working part-time as opposed to full-time. I just grouped the two and had students fill out
either yes or no if they worked or not. This left a lot of room for error as I didn’t specify
any hours. Some students might work two hours a week on campus and yet be grouped
with students who are working forty hours a week. This might lead to differences in
GPA. I also grouped GPA in SPSS in a way that allowed room for error when leading to
my results. Under the value tab, I put the GPA into groups. 1 = 1.0 - 1.5, 2 = 1.5-2.0, and
so on. I used this code system to input GPA. I felt that perhaps I should have individually
entered the GPA separately for each student. Overall, I gained a lot of personal
knowledge on this topic and it helped to broaden my horizons.

References
Pickert, K (2014, November 19). The Tuition Fight in California is About the Future of
All Public Universities. Retrieved December 1, 2015 from http://time.com/3593732/uc-
tuition-hike-california-college-costs/
Tessema, M., Ready, K., & Astani, M. (2014). Does Part-Time Job Affect College
Students Satisfaction and Academic Performance (GPA)? The Case of a Mid-Sized
Public University. International Journal of Business Administration, Vol. 5(Issue 2),
Pages 50-59. Retrieved from
http://econpapers.repec.org/article/jfrijba11/v_3a5_3ay_3a2014_3ai_3a2_3ap_3a50-
59.htm
Legaspi, C., Perez, R., Remigio, A., & Sengsourya, J. (2008). Factors Affecting GPA.
Retrieved December 7, 2015, from
http://public.csusm.edu/fangfang/Teaching/BUS304/TeamPresentation-
Spr08/Report_Group3.pdf

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