Relation between Retention Rate and Graduation Rate among Online Universities

This research examines the relation between the retention rate (RR) and the graduation rate (GR) among online universities. Findings show a positive linear association between GR and RR. The study analyzes data from 29 online universities in the US and uses regression analysis to determine the significance of the relationship. The results provide insights for university management to improve retention and graduation rates.

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Purpose
This research purposes to examine the relation between the retention rate (RR) and the
graduation rate (GR) among online universities.
Background
Graduation rates and retention rates are significant indicators for determining whether an
academic institution is a good fit or not. The overall objective of students in enrolling in a
university is to stay in the institution and finally graduate with a degree (Talbert, 2012).
Whereas the admit rate shows the percentage of students that are enrolled into a college, the
retention rate shows the percentage of the students that stay in school and the graduation rate
informs us of the percentage that complete their undergraduate.
Statistics on graduation and retention rates have gained particular interest among potential
students, parents or guardians because of the employment industry that is becoming too
competitive and selective (Veenstra, 2009). The graduation rate for the sixth year
undergraduate programs was 150% in 2010 with that of the 4 year degree programs being at
60%. The National Student Clearinghouse (NSC) report, the GR in 2011 was 45% whereas
the retention rate was31% (National Student ClearingHouse, 2017). This has increased the
demand for employees with higher academic qualifications, thus making academic
institutions to experience an influx in student enrolment. This issue of particular interest to
the economist because one has to determine the number of students that successfully graduate
from an institution before committing time and money to it.
Method

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College RR(%) GR(%)
Western International University 7 25
South University 51 25
University of Phoenix 4 28
American InterContinental
University 29 32
Franklin University 33 33
Devry University 47 33
Tiffin University 63 34
Post University 45 36
Peirce College 60 36
Everest University 62 36
Upper Iowa University 67 36
Dickinson State University 65 37
Western Governors University 78 37
Kaplan University 75 38
Salem International University 54 39
Ashford University 45 41
ITT Technical Institute 38 44
Berkeley College 51 45
Grand Canyon University 69 46
Nova Southeastern University 60 47
Westwood College 37 48
Everglades University 63 50
Liberty University 73 51
LeTourneau University 78 52
Rasmussen College 48 53
Keiser University 95 55
Herzing College 68 56
National University 100 57
Florida National College 100 61
Data from the Online Education Database on the RR and GR of 29 online colleges in the US
was used to assess the association between the RR and GR was used to examine the
association between the study variables. A visual relation between the variables was
demonstrated using a scatter diagram. A regression equation was also developed to help
interpret the meaning of the slope coefficient and goodness of fit. All the analysis was done

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using Ms Excel Data Analysis Toolpak. A hypothesis for the analysis of variance was used to
find out the significance of the model as indicated below:
H0: Regression model is not significant
Ha: Regression model is significant
Results
Descriptive Analysis
Mean
57.4137
9
41.7586
2
SD
23.2402
3
9.86572
4
Max 100 61
Min 4 25
The mean GR for all the 29 online universities in the US is 41.76%, whereas the RR is
57.41%. Based on the SD of the two variables, there is a greater dispersion from the mean in
GR than RR. South University, the University of Phoenix and Western International
University had the least GR of 25% and 4% respectively. The National University and
Florida National College had the maximum RR of 100%, with the latter also having the
maximum RR of 61%.
Scatter Diagram

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0 20 40 60 80 100 120
0
10
20
30
40
50
60
70
f(x) = 0.284526002809143 x + 25.4229036318199
R² = 0.449228088348509
Scatter Diagram
Retention rate
Graduation rate
The scatter diagram shows a relatively strong, positive, linear association between GR and
RR. The Pearson correlation coefficient of 0.67 provides additional evidence which shows an
average positive linear association between GR and RR.
Regression Statistics
Multiple R
0.6702
45
R Square
0.4492
28
Adjusted R Square
0.4288
29
Standard Error
7.4561
05
Observations 29
ANOVA
df SS MS F
Significanc
e F
Regression 1
1224.28
6
1224.28595
6
22.0221
1 6.95E-05
Residual 27
1501.02
4
55.5934958
7
Total 28 2725.31
Coeffici Stand t Stat P- Lower Upper Lower Upper

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ents
ard
Error
valu
e 95% 95% 95.0% 95.0%
Intercept 25.4229
3.7462
84
6.786165
928
2.74
E-07
17.736
16
33.10964
31
17.736
16
33.109
64
X Variable
1
0.28452
6
0.0606
31
4.692771
862
6.95
E-05
0.1601
22
0.408929
906
0.1601
22
0.4089
3
Regression Equation
Y = 0.2845x + 25.423
The slope (retention) coefficient in the regression equation is 0.2845. This coefficient
represents the mean increase in graduation rate for every additional retention rate. In other
words, if the retention rate increased by one unit, the average graduation rate increased by
0.2845.
Statistical significance between GR and RR
There is a statistically significant relation between the study variables as shown by a p-value
of 0.000, which is thus less than 0.05, and thus we accept the alternative hypothesis.
Goodness of fit
R2 is an indicator of the goodness of fit. R squared = 0.45 (rounded to 2 digits), is moderate
goodness of fit. This also means that 45% of the variance in GR is accounted for by the RR.
In other words, about 55% is unexplained for by the model. Thus, the regression equation
provided a relatively good fit.
The Case of South University
The South University had the minimal GR of 25% among all other 28 online universities.
Assuming I was the president of the institution I will be much concerned about its
performance compared to other schools. This is because low GR is an indication of internal

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problems. Low GR implies that either the students are not receiving adequate academic
support required to graduate, discouraged by the school staff, or the school life is not
affordable to the students (Webber and Ehrenberg, 2010). Therefore, I will work towards
solving the above internal issues or any other.
The case of University of Phoenix
The University of Phoenix has a minimal RR of 4% out of all other 28 online institutions. As
the institutions leader, I will be much worried about its productivity because the lowest RR is
an indication of problems at the institution and student level. Academic engagement
programs such as academic research for degree students affect retention, thus if students are
not contented with such services, they are likely to quit the school (Jensen, 2011). I will,
therefore, work towards providing strategies to solve such issues in order to improve RR and
consequently the performance of the school.
Discussion
The study found out that the average GR and RR among online universities in the US was
41.76% and 57.41% respectively. The deviation from the mean of the study variables was
higher in GR. The least GR was 25% and 4% and accounted for by Western International
University and South University and by the University of Phoenix respectively. The
maximum GR of 61% was accounted for by Florida National College, and 100% recorded by
National University and Florida National College. The scatter diagram showed a relatively
strong, positive, linear association between GR and RR. The slope coefficient from the
regression equation was 0.2845 which shows that if the RR increased by one unit, the average
graduation rate increased by 0.2845. Furthermore, the regression equation provided a
moderately good fit with a coefficient of 0.45. A p-value of 0.000 showed that there was a
statistically significant association between the rate of graduation and retention rate.

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These findings are relatively in agreement with those of Shapiro et al. (2012) who found out
that approximately 80% RR at four-year public and private institutions. At Penn State
University, the RR was at 93% and GR at 90% (Penn State University, 2018; DeAngelo et
al., 2011). The findings thus confirmed the existence of the relationship between GR and
RR, and school management can make use of the study to improve on their areas of
weakness.
The study also had two major limitations. First, the data provides a summary of the RR and
GR which can be caused by several factors at individual, institutional and social and external
level (Reason, 2009). Despite all these potential causes, the rates of the variables indicate the
performance of the school. This limits the practicality of the data in making informed
decisions about a given university. Secondly, the sample size for the data was too small to
warrant generalization in the entire US.
Owing to the significance of GR and RR on the economy and performance of universities
(Stillman, 2009), the findings of this research provide the policymakers with in-depth
information on the significance of the variables and thus assisting them to design policies that
focus on recruiting and retention of students.
Recommendations
Based on the findings, this study makes three recommendations:
1. The Future studies should include a relatively larger sample to allow generalization.
The present study only focused on 29 online universities.
2. Future studies can also focus on the specific factors that cause the difference in the
study variables so as to enable potential users to make informed decisions when
examining the GR and RR values.

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3. Additionally, the University of Phoenix with an RR of 4% and Western International
University and South University with RR of 25% should implement strategies for
improving the quality of their services and should be student-oriented. This can be
done by conducting a survey on the students about the possible causes for quitting the
school.

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References
DeAngelo, L., Franke, R., Hurtado, S., Pryor, J.H. and Tran, S. (2011) Completing college:
Assessing graduation rates at four-year institutions. Los Angeles: Higher Education Research
Institute, UCLA.
Jensen, U. (2011) Factors Influencing Student Retention in Higher Education. Summary of
Influential Factors in Degree Attainment and Persistence to Career or Further Education for
At-Risk/High Educational Need Students, by Pacific Policy Research Center. Honolulu, HI:
Kamehameha Schools–Research & Evaluation Division.
National Student Clearing House, (2017) Completing College – National – 2017. [online].
Available from: https://nscresearchcenter.org/signaturereport14/ [accessed 12 Feb. 19].
Penn State University, (2018) Penn State student-athletes deliver record-tying 90 percent
graduation rate. [online]. Available from:
https://news.psu.edu/story/547909/2018/11/14/athletics/penn-state-student-athletes-deliver-
record-tying-90-percent [accessed 12 Feb. 19].
Reason, R.D. (2009) Student variables that predict retention: Recent research and new
developments. NASPA journal, 46(3), pp.482-501.
Shapiro, D., Dundar, A., Chen, J., Ziskin, M., Park, E., Torres, V. and Chiang, Y.C. (2012)
Completing College: A National View of Student Attainment Rates. Signature [TM] Report
4. National Student Clearinghouse.
Stillman, M. (2009) Making the case for the importance of student retention. Enrollment
Management Journal, 3(2), pp.76-91.
Talbert, P.Y. (2012) Strategies to Increase Enrollment, Retention, and Graduation
Rates. Journal of Developmental Education, 36(1), p.22.

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Veenstra, C.P. (2009) A strategy for improving freshman college retention. Journal for
Quality and Participation, 31(4), pp.19-23.
Webber, D.A. and Ehrenberg, R.G. (2010) Do expenditures other than instructional
expenditures affect graduation and persistence rates in American higher
education?. Economics of Education Review, 29(6), pp.947-958.