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The Impact of Student Success Rates When Mandatory Tutoring is Applied
to a First-Semester Barrier Course in Writing at a Two-Year Community College.
A Doctoral Capstone Project
Submitted to the School of Graduate Studies and Research
Department of Education
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Education
Brian T. Schell
Pennsylvania Western University
August 2024
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@Copyright by
Brian T. Schell
All Rights Reserved
August 2024
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Pennsylvania Western University
School of Graduate Studies and Research
Department of Education
We hereby approve the capstone of
Brian T. Schell
Candidate for the Degree of Doctor of Education
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Dedication
I dedicate this work to my friend and mentor, Dr. Kenneth Klawitter. His
leadership style, ethics, values, and determination to best serve all stakeholders have
influenced me in more ways than I can express. He taught me the value of using the
concept of “goodness of fit” and the importance of being a leader who inspires the people
under them to grow to their fullest potential without seeking personal recognition. His
impact on countless others will transcend time and may never be fully realized. I am truly
a better person and a better educational leader because of Dr. Klawitter.
I also dedicate this to my mother for all the love and support she has provided me
throughout my life through the personal and professional pathways I have undertaken.
She was a Sunday school teacher for over forty years and taught me my first lessons in
religion and my first lessons on playing the piano. She was a natural teacher and
inspiration for the life I pursued.
Finally, I give all glory to God for His grace and for giving me the strength and
wisdom to follow my dreams and the plans He had for my life.
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Acknowledgments
I would like to thank Dr. John F. Ziegler, Doctoral Capstone Faculty Chair, and
Dr. Stacia Viscarda, Doctoral Capstone External Committee Member, for their help,
guidance, and constant encouragement and support while writing this work.
My thanks are also extended to the people at my research site who have supported
me throughout this process, including Cynthia Seaman, Provost; Kevin Coots, Associate
Provost; David Sweely, Dean of Assessment; Megan King, Director of Tutoring, and
Teresa Magdalia for her participation in the quasi-experimental project.
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Table of Contents
Dedication
iv
Acknowledgments
v
List of Tables
x
List of Figures
xii
Abstract
xiii
CHAPTER I. Introduction
1
Background
2
Capstone Focus
4
Research Questions
5
Expected Outcomes
6
Financial Implications
6
Summary
7
CHAPTER II. Literature Review
8
Community College Perspectives
10
Historical Development
10
Community College Data and Statistics
14
Unique Challenges Compared to Four-Year Institutions
15
Open Access/Enrollment
15
Housing Versus Commuting
16
Part-time versus Full-time Enrollment & Unique Demographics
17
Conceptual Frameworks
17
Predominate Themes Based on the Frameworks
20
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Retention/Persistence
20
At-risk Students
21
Self-Efficacy
23
Learning Transfer: Identical Elements
23
Gateway or Barrier Courses
25
Tutoring-Related Discourse
26
Definitions
Tutoring Models
26
28
Tutoring and Writing Centers
28
Embedded Tutoring
31
Mandatory Versus Voluntary Tutoring
32
Summary
35
CHAPTER III. Methodology
38
Purpose
40
Desired Outcomes
41
Research Questions
42
Setting and Participants
42
School Location
42
School Demographics
43
Participants
46
Research Plan
Plan/Intervention
Research Alignment to Intervention
47
47
50
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Fiscal Implications
52
Research Methods and Data Collection
52
Research Design
52
Data Collection Method and Timeline
53
IRB Approvals
55
Fiscal Implications to Research Method and Data Collection
55
Validity
56
Validity Types and Methods
56
Triangulation of Data
57
Summary
58
CHAPTER IV. Data Analysis and Results
60
Data Analysis
62
Results
63
Research Question One
63
Research Question Two
72
Research Question Three
78
Student Survey Data Results
83
Discussion
87
Summary
90
CHAPTER V. Conclusions and Recommendation
91
Conclusions
93
Research Question One
93
Research Question Two
95
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Research Question Three
97
Future Application and Financial Implications of Study Results
99
Limitations
100
Recommendations for Future Research
103
Summary
105
References
108
APPENDICES
117
APPENDIX A. Student Survey: Control Group
118
APPENDIX B. Student Survey: Experimental Group
119
APPENDIX C. IRB Approval Letter – Pennsylvania Western University
121
APPENDIX D. Confirmation Email for the Addition of Two Student Surveys
122
APPENDIX E. Permission Letter Reading Area Community College
123
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List of Tables
Table 1. Fall 2022 Student Body by Racial or Ethnic Group
Table 2. Fall 2022 Full-Time Student Body by Racial or Ethnic Group and Pell Recipient
Table 3. Comparison Between Mandatory and Voluntary Models as Measured by Final
Grades
Table 4. Frequency Comparison Between the Mandatory Model and Voluntary Model as
Measured by Final Grades
Table 5. Descriptive Statistics Comparison Between the Mandatory and Embedded
Model as Measured by Final Grades
Table 6. Frequency Comparison Between Mandatory Model and Embedded Model as
Measured by Final Grades
Table 7. ANOVA Between Mandatory and Voluntary Tutoring as Measured by Mid-term
Grades
Table 8. ANOVA Between Mandatory and Embedded Tutoring as Measured by Mid-term
Grades
Table 9. ANOVA Between Mandatory and Voluntary Tutoring as Measured by Final
Grades
Table 10. ANOVA Between Mandatory and Embedded Tutoring as Measured by Final
Grades
Table 11. Paired Sample T-test Between Mandatory and Voluntary Tutoring Models as
Measured by Mid-term Grades
Table 12. Paired Sample T-test Between Mandatory and Embedded Tutoring Model as
Measured by Mid-term Grades
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Table 13. Paired Sample T-test Between Mandatory and Voluntary Tutoring as Measured
by Final Grades
Table 14. Paired Sample T-test Between Mandatory and Embedded Tutoring as Measured
by Final Grades
Table 15. Chi-square Test Between First-generation Status and Mandatory Tutoring as
Measured by Success Rates
Table 16. Chi-square Test Between Pell-grant Status and Mandatory Tutoring as
Measured by Success Rate
Table 17. Chi-square Test Between Ethnicity/race and Mandatory Tutoring as Measured
by Success Rate
Table 18. Regression Between First-generation Status and Mandatory Tutoring as
Measured by Success Rate
Table 19. Regression Between Pell Status and Mandatory Tutoring as Measured by
Success Rate
Table 20. Success Rates Minus Withdraws
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List of Figures
Figure 1. Share of Enrollment by Pell Grants
Figure 2. Success Rates by Pell Status
Figure 3. Success Rates by Select Race/Ethnicity
Figure 4. Success Gaps Compared to White Students
Figure 5. Grading Policy for Mandatory Tutoring Sections
Figure 6. Alignment of Research Questions, Data Collection, Data Sources,
and Timelines.
Figure 7. Mid-term Grades: All Tutoring Models
Figure 8. Mid-term Grades: Mandatory Tutoring Model
Figure 9. Mid-term grades: Voluntary Tutoring Model
Figure 10. Mid-term grades: Embedded Tutoring Model
Figure 11. Final Grades: All Tutoring Models
Figure 12. Final Grades: Mandatory Tutoring Model
Figure 13. Final Grades: Voluntary Tutoring Model
Figure 14. Final Grades: Embedded Tutoring Model
Figure 15. Survey Results: Mandatory Tutoring Question One
Figure 16. Survey Results: Mandatory Tutoring Question Two
Figure 17. Survey Results: Mandatory Tutoring Question Three
Figure 18. Survey Results: Mandatory Tutoring Question Four
Figure 19. Survey Results: Voluntary Tutoring Sections Question One
Figure 20. Success Rates Including and Excluding Withdraws
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Abstract
Community colleges face unique challenges in educating students due to their openaccess policies and the need to retain students through successful completion of courses,
especially those identified as barrier courses. This study examined the impact of applying
a mandatory tutoring requirement in a first-year writing course to increase course success
rates and writing proficiencies. A Communications-121 writing course taught at a
community college in Southeastern Pennsylvania was identified as one of the top 10
barrier courses with a low course success rate of 62%. In order to address this issue, a
quasi-experimental study was designed to examine the impact of three different tutoring
models on course success rates: mandatory, embedded, and voluntary. The study also
explored the relationship between at-risk student populations (first-generation, ethnicity,
and Pell Grant recipients) and the various tutoring models. The mandatory tutoring
intervention used in this quantitative study was not shown to be the best model; however,
there was a positive relationship between at-risk students and the mandatory tutoring
model. Exit surveys also showed that a majority of students who used tutoring services
reported that they would use a tutor in future courses and would recommend tutoring to
their classmates.
Keywords: tutoring, mandatory tutoring, barrier courses, first-year writing
courses, retention, success rates
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CHAPTER I
Introduction
A persistent issue facing a two-year community college in Southeastern
Pennsylvania is that many first-year writing students are not utilizing the professional
tutoring services available to them in the Academic Learning Commons to improve their
writing proficiencies; in fact, the Director of Tutoring services for the college reported
that only 11% of the student population sought the assistance of a tutor in 2022-23.
Mattison (2012) suggested that educators needed to make instructional support programs
available through a wide range of offerings that could help to close achievement gaps.
This would include resources such as writing centers and professional tutors. There is a
need to increase the number of students who utilize the services of a professional writing
tutor, especially at-risk students such as first-generation students and economically
disadvantaged students. Writing centers and the use of tutoring to improve students’
literacy skills historically developed to accommodate low-skilled writers, especially
veterans, underprepared students, and minorities in need of improving the skill sets that
would allow them to successfully meet the challenges of higher education (Ball, 2014;
Missakian et al., 2016; Ugo, 2010).
Additionally, the college is a designated Hispanic Severing Institute (HSI) with a
population of over 40% Hispanic students. These students can also be first-generation
and economically disadvantaged students who would benefit from more individualized
tutoring support. In a study of academic supports within community colleges, Hendriksen
et al. (2005) found that tutored students had a 2.78 average grade point average (GPA)
compared with a 2.64 GPA for non-tutored students. Overall, tutored students had a 75%
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pass rate versus a 71% pass rate for non-tutored students. Any student at that college who
is unsuccessful in passing a reading and/or writing placement examination must enroll in
developmental courses until written communication skills are improved. The college’s
developmental courses receive college credit but do not count towards graduation
requirements and can often impact retention and on-time graduation rates. A study by
Rheinheimer et al. (2010) showed that tutoring was an overwhelmingly positive predictor
of persistence, retention, and degree completion for at-risk students and claimed that
tutoring was a valuable intervention for future academic success.
Background
The literature review for this capstone project formed the basis for the
development of this study and the connections to relevant frameworks that supported the
premise centered on the use of a mandatory tutoring model in a barrier/gateway course
for writing. This study considered the course success rates of students in first-year writing
courses when a mandatory, voluntary, or embedded tutoring model was applied. Several
key factors have been associated with analyzing the data in this study based on the
project topic and the unique environmental stressors and demographics associated with a
community college experience.
Communications-121 (COM-121) is a first-year writing course required of all
community college students and is considered one of the college’s top 10 barrier courses.
Student success rates below 70% in course completion constitute a barrier course. In
2022, the course success rates at the community college in Southeastern Pennsylvania
were 62% for all COM-121 courses. This meant that 38% of the students had to repeat
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and successfully complete the COM-121 course before moving on to other program
courses that often require COM-121 as a pre-requisite.
Many students fail in their first attempt at taking the COM-121 course and must
repeat the course two or three times before successful completion. Failure to pass a firstyear writing course may have detrimental impacts on retention and on-time graduation
rates, which are key performance indicators in the college’s five-year Strategic Goals.
Tinto (1999) argued that students need to be grounded in a learning environment that
promotes students as valued members of the institution. This is accomplished by having
supportive institutional mechanisms to encourage intentional contact with faculty, staff,
and other students to increase retention and student persistence.
One of the most prevalent challenges that community colleges face in increasing
student retention and persistence comes through their use of open-access enrollment.
Raby (2020) referred to open access as “A foundational philosophy of the community
college” (p. 41). This embedded philosophy is a cornerstone principle for all community
colleges charged to make education available to all students and to ensure no individual
will ever be denied access to education due to a selective admissions process.
Four-year college students can live on campus, which has clear advantages that
can help with retention and a sense of belonging that many community college students
cannot realize. Housing options can give students a sense of safety and support in a firstyear experience, the ability to bond with a potential roommate, and access to activities
and gatherings that encourage student connections with the campus (Chen, 2022).
Housing is not an option for most community colleges, so other types of campus
strategies must be developed to compensate for the deficit caused by a student's need to
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commute to the campus. One of these strategies is building relationships through
available student services; however, many first-year students at a community college do
not pursue them. Tutoring and writing center participation are two services available at
most higher education institutes that can help bridge the gap towards positive retention
and course completion, especially with barrier courses.
According to Phillippe (2023) from The American Association of Community
Colleges, part-time students outnumber full-time students by nearly 2 to 1. 66% of
students attended part-time while only 34% attended as full-time students. This also
included 30% of first-generation students, 16% of single parents, and a population of
35% of students between the ages of 22 and 39. These variables greatly impact
community colleges that are held to a high standard for reporting data to the Integrated
Postsecondary Education Data System (IPEDS). This system requires community
colleges to report graduation rates for first-time, full-time students who successfully
complete their degrees after three years. This is a very high bar to meet, given the unique
circumstances of community college students. Building relationships through campus
initiatives such as tutoring and writing centers can help close the retention and graduation
gaps and greatly impact first-year students' retention and persistence toward graduation.
Capstone Focus
The inherent problem for walk-in writing centers and tutoring labs is that they
assume struggling students will access the services that professional tutors can provide to
them; however, at-risk and struggling students often fail to consider this resource as a
means of improving the writing skills needed in all of their course work. Rheinheimer et
al. (2010) argued that at-risk students tend to avoid social resources like writing centers
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or professional tutors for help. These students may have educational backgrounds lacking
the skills needed to improve academic achievement and are reluctant to reach beyond
their comfort zones.
This research will focus on institutional ex-post facto (archival) data from past
semesters and data from a quasi-experimental project consisting of two sections of
Communications-121 (COM-121), a first-year writing course. Two sections of COM121 will function as the experimental group. They will be exposed to an independent
variable of a mandatory tutoring requirement, and two sections of COM-121 will
function as the control group without being exposed to the independent variable. This
experimental group will be analyzed and compared to the control group and ex-post
facto data, including past sections of COM-121 that utilized an embedded tutor.
Research Questions
This research study will be used to determine if significant differences in course
success rates can be realized when a mandatory tutoring requirement is included for firstyear students in a Communications-121 writing course at a two-year community college
in Southeastern Pennsylvania. Mid-term and final grades will be measured within a
quantitative study to determine course success rates with a sample group consisting of
students who participated in mandatory tutoring, students who participated in voluntary
or no tutoring, and students who had access to an embedded tutor as a viable but
voluntary resource. The study asks the following questions:
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term and
final grades?
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2. Is there a significant difference in writing proficiencies, as measured by course
grades, between students who participate in mandatory tutoring and those who
participate in voluntary tutoring, embedded tutoring, or those who never access
tutoring services?
3. What is the relationship between at-risk students (first-generation, economically
disadvantaged, or ethnicity/race) and mandatory tutoring as measured by success
rates when enrolled in a first-year (barrier) writing course?
Expected Outcomes
This action research study is intended to determine if mandatory tutoring can
increase course success rates of a first-year Communications-121 (COM-121) writing
course required of all degree-seeking students enrolled at a two-year community college.
Specific outcomes will include:
1. To determine if the collected data supports the implementation of mandatory
tutoring for all or some students of the COM-121 writing course
2. To analyze various tutoring practices and their impact on the successful
completion of a barrier course based on mid-term and final grades
3. To recommend the implementation of some variation of mandatory tutoring for
first-year writing students to increase student retention and on-time graduations
4. To determine if tutor relationships help students improve their self-efficacy as they
transfer acquired knowledge to future program courses
Financial Implications
The primary budget considerations for implementing a mandatory tutoring
requirement for all Communications-121 (COM-121) students would require hiring up to
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seven part-time tutors designated to service all COM-121 students in every section and
form of modality, including face-to-face, remote, and online offerings. The quasiexperimental model used in this study is based on each COM-121 student receiving a
minimum of five 30-minute tutoring sessions per semester. The fall and spring
semesters average about 600 enrolled students, and the summer term services
approximately 200 students for an estimated implementation cost of approximately
$50,000.00. This cost is based on a tutor's salary of $25.00 per hour, including 2.5
tutoring hours per student or a cost of $62.50 per student.
Summary
Many students fail the Communication-121 (COM-121) course on their first
attempt and must repeat it two or three times before successful completion. Passing
COM-121 is essential for enrollment in future courses requiring the course as a
prerequisite for completing a degree or certificate. COM-121 is a barrier course that can
impede a student’s ability to complete a degree and graduate within a three-year time
period.
The current three-year graduation rate for first-time/full-time (FTFT) students at
the community college is 25%. Finding positive interventions, such as mandatory
tutoring, may offer one way to get more students to complete their degrees on time. This
study will explore potential interventions and strategies to increase the number of
successful course completions for the COM-121 barrier course and to increase semesterto-semester retention and on-time graduation rates.
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CHAPTER II
Literature Review
Community colleges throughout the country share many common factors that
contribute to the successful completion rates of degree-seeking individuals. The unique
demographic composite of community college students, combined with an open-access
policy, presents numerous challenges in achieving successful on-time graduation rates
and overall student retention. According to Mullin (2017), an open-access policy allows
anyone in the community to enroll as opposed to a selective admission process used by
most 4-year institutes of higher education. Community colleges must embrace multiple
approaches to breaking down the barriers that can keep students from conferring a degree
that could potentially be a life-altering milestone for them.
One strategy to address student persistence and retention can be realized through
tutoring services available to students at a particular institution. Numerous models for
how and when to provide or require tutoring for students are addressed by student writing
and learning centers throughout the country. Finding the appropriate model to implement
at the community college level has multiple variables that must be considered. One of the
most prevalent variables contributing to student resistance to tutoring comes with the
additional out-of-class time that may be required. Students who have daily commutes to
the campus and are time-bound by family or job responsibilities may find the additional
time to be intrusive.
The approach to tutoring in higher education can vary greatly due to the
institution's specific requirements. Research and data related to tutoring models and their
use are not reporting categories within the Integrated Postsecondary Educational Data
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System (IPEDS) or the National Postsecondary Education Cooperative (NPEC);
however, extensive research and data are available relating to tutoring models and
structures for K -12 systems, especially in the post-covid era. This data provides an
essential context for this study because of the close relationship between high schoolaged students and freshman college students. The habits and mental models these high
school students bring with them to college concerning tutoring can dramatically impact
their willingness to embrace tutoring opportunities in a post-secondary environment.
Fong (2021) from the Institute of Educational Sciences reviewed important
information concerning the need for high-quality tutoring in a post-pandemic climate
within K-12 school systems. This model requires tutoring at school and during normal
school hours of three or more 30-minute sessions. These sessions should be staffed with
teachers of professional tutors who are well-trained beyond the scope of peer tutors,
volunteers, or parents (Fong, 2021; Sparks, 2023). Sparks (2023) further provided current
data that showed 40% of school leaders claimed that high-dosage or high-quality tutoring
had increased from 2021 to 2022, with an estimated 30% of students getting intensive
tutoring. 43% of high-poverty and high-minority schools provided this type of tutoring
versus only a 33% of more affluent schools or those serving fewer than 75% of minorities
or students of color.
Community Colleges are often a bridge for many students between high school
and their first higher education experience, but the environments are clearly different and
need to be given additional consideration due to the unique variables that influence all
aspects of the higher education experience. To better understand the relationship between
tutoring and the environments, it is important to have a context for understanding the role
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community colleges have played in the educational system from a historical and local
perspective.
Community Colleges Perspectives
Historical Development
National. The existence of the community college can be traced back to the
Morrill Act of 1862. Originally referenced as junior colleges or two-year colleges, the
Land Grant Act sought to expand access to public higher education by creating pathways
for individuals to attend college who had been formally denied access to higher education
for multiple reasons. A second Morrill Act of 1890 sought to withhold federal funding
from any land grant institution that restricted admission based on race unless a state
allowed minorities to attend a separate and established institute of higher learning. Under
the Morrill Act provisions, the first junior college in America was championed in 1901 by
William Raineu Harper, President of the University of Chicago (Drury, 2003; Goudas,
2020; Mello, 2000).
According to Jurgens (2010), a prevailing attitude in the mid-eighteen hundreds
was underway to create a junior college system that would relieve universities of the
responsibilities of providing general education to qualified high school graduates. Lowerdivision foundational education was considered to be a burden to the universities and
could impede the university’s true mission because they “believed that universities could
not successfully reach their true research maturity and remain exclusive developers of
higher education if they continued to be responsible for providing education to their
students” (p. 252). Teaching general education courses became a natural part of the
community college mission.
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Drury (2003) reported that by 1930, the American Association of Junior Colleges
was established to help navigate the changing landscape of the community college
movement. In 1930, the Junior College Journal was first published to discuss vocational
curricula and to supply training materials. A report by the Carnegie Foundation in 1932
found that state universities had a majority hold on research and training for higher
professions. The state colleges provided education for mid-professions such as teaching,
and the junior colleges provided general education for semi-professions and vocational
training (Drury, 2003). The delineation of the three academic paradigms was made clear
and encouraged a positive recognition of the role of community colleges.
Two major historical events served to be the impetus for the rise in community
college interest from the public. The first of these events would be the great depression
starting in 1929. Young people were out of work and needed training to find the few jobs
that were available. From 1929-1939, enrollment in community colleges grew from
56,000 to over 150,000 (Drury, 2003). College educations at this time were experiencing
a positive perception as they were seen as pathways to economic mobility and
opportunities for upward mobility from a social perspective. The second major event
came after W.W. II and the passing of the G.I. Bill of Rights of 1944, which provided
financial incentives for veterans to seek additional education or training for reintegration
into the American workforce (Drury, 2003; Goudas, 2020; Mello, 2000).
In 1947, the Truman Commission Report for the Higher Education for an
American Democracy was released to support the establishment of junior colleges as a
legitimate and viable academic entity. The report endorsed an objective of making
education available to everyone for little or no tuition (Drury, 2003; Jurgens, 2010;
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Mello, 2000). By 1957, a committee was established to recommend articulation
agreements and transfer credits from junior colleges to four-year institutions. In the
1960s, enrollments in community colleges were rapidly expanding, going from 1 million
in 1965 to 2.2 million by 1970. This same period of time saw the addition of Tribal
Colleges to serve the Native American populations. The 70’s and 80’s began movements
towards expansions in areas such as workforce development and joint ventures with
community colleges and business partners. This concept continued through the 1990s
when new relationships with high schools began forming as a pathway to higher
education (Drury, 2003).
The intentionality of a national movement towards supporting a community
college education has grown exponentially since the first college opened its doors in
1901; however, the mission and purpose of the community college experience remained
intact and strengthened through the partnerships within the communities they serve.
Ongoing communications with community members help establish clear directions for
program curriculums to serve the community's unique needs and ensure that students
receive the required skills to enter the workforce or transfer their general education
credits to a four-year program.
Pennsylvania. The state of Pennsylvania adopted the Community College Act of
1963 on August 24, 1963. This Act created the framework for establishing and operating
community college institutions throughout the Commonwealth. The 1963 Act authorized
school districts, county boards, and municipalities to sponsor community colleges
through specific taxes being levied by the districts and municipalities and by providing
reimbursements by the Commonwealth for certain costs and expenses (Community
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College Act, 1963). Part I, Chapter 35 of the Title 22 Pennsylvania Code further details
the required guidelines needed for the operation of a community college in the
Commonwealth.
According to Rink (2020), funding sources for community colleges in
Pennsylvania are to be shared in equal parts between the state, local sponsors, and tuition
and fees; however, that reality has never truly come to fruition; in fact, the state budgets
for community colleges remained flat for community colleges under Governor Wolfe.
Pennsylvania currently has 15 community colleges that operate on budgets from $13
million a year to more than $140 million for the largest systems. Local community
support also varies greatly from $1.2 million in Cambria County to over $30 million for
the city of Philadelphia and its community college.
Aiken (2023) reported that Governor Josh Shapiro had proposed a slight increase
for community colleges in the 2023-34 budget at a 2% funding bump. This would
represent an increase from $256 million to $261 million across the community college
system. Since the 2012-13 budget, state system funding for community colleges has
grown by 20.9%; however, there were many years when the budgets were flat during that
period. In 2023, a U.S. News and World Report ranking placed Pennsylvania 48th for low
debt and 47th for tuition and costs. The State Higher Education Executive Officers
Associations also reported that Pennsylvania ranked 48th for funding public college
students. Overall, Pennsylvania students received an average of $4100 less in funding
compared to national averages (Aiken, 2023).
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Community College Data and Statistics
The American Association of Community Colleges reported current data and
statistics pertaining to community colleges throughout the country, including the
following information: There are 932 public, 35 tribal, and 7 independent community
colleges that awarded 877,249 associate degrees and 592,863 certificates in 2020-2021.
In Fall 2021, headcount enrollments included 6.1 million college credits and 4.1 million
noncredit enrollments, down by .4% from Fall 2021 to Fall 2022 (Phillippe, 2023).
The average age of community college students is 27, and 30% of all students are
considered first-generation attendees. 66% of the student enrollments are part-time, while
34% are full-time students who pay an average annual tuition of $3,860, compared to the
average public 4-year college tuition of $10,940. Community College revenues included
21.8% in tuition, 18.5% in federal funding, 34.4% in state funding, 21.4% in local
funding, and 5.9% in other funding streams (Phillippe, 2023).
Shapiro (2020) from The National Student Clearinghouse Research Center
reported a positive movement in student enrollment in community colleges as the twoyear institutes continue to feel the impact of the COVID-19 pandemic. Community
colleges are starting to grow in spring 2023 (+2,1%) with a new infusion of dual
enrollments (age 17 and under) and incoming freshmen; in fact, dual enrollment went
from (+2.9% in 2022 to +12.8% in 2023). Certificate program enrollment was up
(+5.5%), while associate degrees saw a minimal (+0.3%) growth.
Overall graduation rates are based on a first-time full-time student’s ability to
graduate from a community college in three years; however, many students require more
time to fulfill the requirements of the degree they seek. Two-year retention rates overall
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THE IMPACT OF STUDENT SUCCESS RATES
were 46.9% for first-year students returning one year later. Full-time students were 59%,
and 2-year public part-time students were 39%, with a 2-year public graduation rate after
six years of 39.22% (Goudas, 2021).
Unique Challenges Compared to Four-Year Institutions
Open Access/Enrollment
One of the most prevalent challenges that community colleges face is the concept
of open-access enrollment. Raby (2020) referred to open access as “A foundational
philosophy of the community college” (p. 41). This embedded philosophy is a
cornerstone principle for all community colleges’ charge to make education available to
all students and to ensure no individual will ever be denied access through a selective
admissions process like is used by four-year institutes; therefore, community colleges
function with an unknown and fluctuating variable each semester. They cannot be as
intentional about expenditures and costs because they cannot rely on a level of funding
based on a stabilized student enrollment count attained through selective admissions
(Mullin, 2017).
Elfman (2023) reported on the challenges of an open-access policy in a postpandemic environment. Economic factors and funding support for community colleges
are being impacted by factors threatening open-access participation by the very
individuals who need it the most. These individuals cannot prioritize education for
various reasons, including “finances, family, illness, lack of internet or inability to adapt
to online learning” (p. 24). Social and economic barriers mean that community colleges
must continue finding new and innovative ways to offer students the required access and
flexibility. Community colleges must also be keenly aware of the workforce training
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THE IMPACT OF STUDENT SUCCESS RATES
needs in their community. They must respond quickly to changes in training and
curriculum to keep students marketable and competitive. The open access policy is a
noble practice for community colleges, but it can also create many unstable and unknown
factors in keeping the community college stable and viable.
Housing Versus Commuting
A significant consideration for the unique variables associated with community
colleges comes in understanding the impact that housing availability can have on student
retention and persistence. A study in 2022 revealed that 81% of public two-year colleges
provide students with housing options compared to only 29% of community colleges
(Phillippe, 2023). According to Abelson (2023), the National Center for Education
Statistics (NCES) recently reported on the struggles being felt by students in higher
education for basic needs. Nearly 23.4% of community college undergraduates are
experiencing low or inadequate food security, and 8% of all community college students
are experiencing some level of homelessness. These alarming statistics reveal the true
spirit of the community college ethos and the need to educate people from diverse
backgrounds and challenging circumstances to ensure a stronger future.
Students living on campus have clear advantages that can help with retention and
a sense of belonging not realized by students in a community college environment.
Housing options can give students a sense of safety and support in a first-year experience,
the ability to bond with a potential roommate, and access to activities and gatherings that
encourage student identity with the campus. Living on campus is not an option for most
community colleges, so other types of campus strategies must be developed to
compensate for the deficit caused by students' need to commute to the campus. One of
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THE IMPACT OF STUDENT SUCCESS RATES
these strategies is building relationships through available student services; however,
many first-year students at a community college do not pursue them. Tutoring and writing
center participation are two available services at most higher education institutes that can
help bridge the gap towards positive retention and course completion, especially with
barrier courses.
Part-time versus Full-time Enrollment & Unique Demographics
According to Phillippe (2023) from The American Association of Community
Colleges, part-time students outnumber full-time students by nearly 2 to 1. 66% of
students attended part-time, while only 34% attended as full-time students. This also
included 30% of first-generation students, 16% of single parents, and a population of
35% of students between the ages of 22 and 39. These variables greatly impact
community colleges, which are held to a high standard for reporting to the Integrated
Postsecondary Education Data System (IPEDS). This system requires community
colleges to declare graduation rates for first-time, full-time students who graduate after 3
years. This is a very high bar to meet, given the unique circumstances of students who
tend to attend a community college. A second measuring unit, the Voluntary Framework
of Accountability (VFA), measures all students and a six-year timeframe for completion.
In its recent report on community college data, the American Association of Community
Colleges (2023) reported the IPEDS rate at 25%, while the VFA reported success rates at
59%.
Conceptual Frameworks
The overarching framework used for consideration of this capstone is grounded in
the work of Tinto (1975) and his ongoing seminal work on the retention and persistence
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THE IMPACT OF STUDENT SUCCESS RATES
of first-year college students. Tinto’s initial framework considered the relationships
between the college environment of academic and social issues and the individuals who
experience the effects of these systems. The framework was presented as the Student
Integration Model. His initial premise and research have opened the door to expanded
consideration concerning retention and student success. Numerous researchers are
interested in finding ways to retain students once they enter higher education systems.
Tinto made a significant shift in thinking from previously held perspectives on student
persistence and retention. Before his study, mainstream thinking believed that certain
existing attributes, skills, and motivations impeded their performance in higher education
environments (Tinto, 2006).
Tinto (1999) continued with his seminal work in retention, acknowledging that
while new strategies were being implemented with some success, they were having a
limited impact and encouraged the notion that institutions needed to understand that the
core causes of retention are not simply about students. Still, it is also directly correlated
to the character of their settings. He presented four key components needed to help
improve retention: 1) provide clear, informational resources concerning the institute, 2)
the accessibility of academic, social, and personal supports, 3) create environments where
the students view themselves as a valued member, and 4) students must be learning.
By the early years of the 2000s, many theorists came to understand the
importance of the student in the equation and how a focus on student-related variables
needed to be considered on a deeper level. Tinto (2006) addressed this as a realization
that “It is one thing to understand why students leave; it is another to know what
institutions can do to help students stay and succeed” (p. 6). The focus on ways to
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THE IMPACT OF STUDENT SUCCESS RATES
increase student retention began to grow into many other areas, such as how the role of
families and their backgrounds influenced retention and persistence. Economic factors
began to be considered along with cultural and social differences and student engagement
variables in a particular institute (Tinto, 2006).
Tinto (2017) continued to be a strong voice in the area of persistence with his
assertion that “…student retention has been shaped by theories that view student retention
through the lens of institutional action and ask what institutions can do to retain their
students. Students, however, do not seek to be retained. They seek to persist” (p. 254).
Tinto also recognized early alert systems' role in identifying student needs, the
appropriate ways to respond to them, and being sensitive to social supports, especially for
first-generation and low-income students who need to foster self-efficacy to build
confidence and persistence. Viewed through the student’s eyes, persistence is only one
factor in their successful journey. A sense of belonging and the perceptions of how they
view the curriculum and its value to their studies are also contributing variables (p. 264).
A secondary framework will consider the use of Transfer Theory to ensure that
tutoring practices build foundational skills that can be applied beyond the writing course.
Various early theoretical models provide the basis for how this framework can be
considered a logical inclusion with the seminal work of Tinto. According to Hajian
(2019), transfer refers to the ability to apply prior learning and experience to a situation
that is different from the situation from which the original learning was presented.
Though many frameworks exist, this study will focus on the Theory of Identical
Elements.
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THE IMPACT OF STUDENT SUCCESS RATES
Thorndike and Woodworth (1901) advanced a theory that stated learning could be
transferred from one distinct activity to a similar activity and used the example of the
concept of training as related to the concept of performance. The researchers noticed that
some subject matters did not affect their abilities to become strong problem solvers. They
found that students were gaining general application of problem-solving; however, not to
the degree of transfer that would effectively translate to problem-solving in a real-life
scenario. This realization showed that an intentional relationship between curriculum and
real-life demands was imperative; their work became the early models of active learning
theories.
Predominate Themes Based on the Frameworks
Retention/Persistence
Burns (2010) addressed realities associated with student retention in community
colleges and open-access policy for enrollment. Community colleges appeal to students
with life circumstances that may limit their educational attainment. This can include child
or family member care, single parenting, negative financial situations, enrolling in
college later in life, being a first-generation student, needing to commute to college with
transportation restrictions, and working full or part-time jobs; in fact, 70% of community
college students can relate to at least one of these situations and 50% have reported
connecting with two or more of these variables (Barhoum, 2018; Burns, 2010; Fike,
2008; Martin et al., 2014).
Community college students often enroll in courses and are less prepared than
students attending four-year universities. Because those institutes have selective
admissions, many students fail to meet the criteria to enroll and turn to community
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THE IMPACT OF STUDENT SUCCESS RATES
college as an option. The impact of this resulted in a study by Fike (2008) that showed
Fall-to-Fall retention rates to range from a low of 45% to a high of 48.4% of first-time,
in-college (FTIC) students. One of the logistic regression models showed that enrollment
in student services, such as tutoring, positively impacted student retention and
persistence.
At-risk Students
First-generation students are susceptible to challenges that put them in an at-risk
status, especially in their first semester and year of college. These students are the first in
their families to go to college, with neither parent having attended college or been
awarded a college degree. According to Schelbe et al. (2019), first-generation students
begin their academic journey at a disadvantage over their peers. Family support is limited
because of the inability to fully appreciate the challenges and obstacles that impact the
social and emotional factors associated with the college experience. These students also
often fail to realize the new expectations and academic standards that will be imposed on
them through attendance at a higher education institution.
Markle and Stelzriede (2020) conducted research pertaining to first-generation
students who participated in a first-generation learning community. The study examined
variables related to the persistence and retention of first-generation students to
continuing-generation students. The results showed that first-generation students who
accessed the learning community saw gains in intellectual and interpersonal development
and engagement that emphasized diverse perspectives. Students in the study also had
lower household incomes, lower SAT scores, and lower levels of confidence. Students
also felt they were less academically prepared than other groups in the study (p. 294).
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THE IMPACT OF STUDENT SUCCESS RATES
Economically Disadvantaged populations are another variable within the at-risk
population. Clarence et al. (2013) stated that there is a strong link between low
socioeconomic status (SES) and students’ low level of literacy achievement. Everett
(2015) added an additional factor for first-generation students by asserting that they are
often included in another at-risk population of economically disadvantaged (ED).
Financial accessibility to funds for college can be a limiting factor for four-year colleges,
but funding at a community college may make the process easier. 58% of students
attending community colleges receive aid, with 38% receiving federal grants, 19%
receiving federal loans, 125 receiving state aid, and 13% receiving institutional aid (p.
53).
Demographics associated with ethnicity are often another key indicator of how
students may fare regarding persistence and retention. Hispanic Serving Institutions
(HSI) are designated when the population of Hispanics exceeds 25% of the overall
population. Karaman et al. (2021) identified the impact of two distinct constructs for
first-year Hispanic college students - academic self-concept and social support. Academic
self-confidence refers to a student’s self-reflective insights on how they perceive
individual academic abilities. This perception significantly correlates to academic
achievement and test anxieties, translating to a psychosocial factor that challenges student
retention among Hispanic students. Social support ranging from friends and family to
teachers and mentors was shown to have a significant impact based on the types of
support such as emotional, informational, feedback, or resources; however, students were
more successful in retention when they applied a strong level of resilience as a
characteristic (Karaman et al., 2021; Rahat & Ilhan, 2016).
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THE IMPACT OF STUDENT SUCCESS RATES
Self-Efficacy
Self-efficacy plays a significant role in a student's persistence and determination
to be successful in a higher education environment. Based on the work of Bandura
(1977), self-efficacy is grounded in an individual’s understanding that they have the skills
and knowledge needed to complete a task or to achieve a specific target or goal. Bandura
identified four areas of self-efficacy: mastery experiences, social modeling, social
persuasion, and psychological responses. The first three areas explain ways in which
individuals can learn and develop strategies to help with a positive image of themselves;
however, the fourth area, the psychological response, may be the best indicator of
struggling first-year college students. In this area, a person's emotional reactions to a
variety of situations create emotional and physical reactions that can cause a great deal of
anxiety and stress. When students lack self-confidence, they will likely not seek advice
and support mechanisms that can help them cope with feelings of inadequacy in tasks like
writing.
Learning Transfer: Identical Elements
Yang et al. (2013) and Rounsaville et al. (2022) referred to transfer as learning
that utilizes knowledge from past applications to make new learning more accessible.
Hajian (2019) isolated a specific form of transfer based on the theory of identical
elements where learning can be transferred from one activity to another (p. 95). This
theory includes low and high-road transfer concepts depending on the transfer level
applied. Low-road transfer exists when there are many similar concepts, ideas, or learned
tasks that can be easily transferred, while high-road transfer happens through the result of
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THE IMPACT OF STUDENT SUCCESS RATES
“mindful abstractions of general principles among different events on different contexts
and a deliberate search for connections among their structures” (p. 96).
Using tutoring models within a first-year writing course can help advance the
concept of low-road transfer by providing scaffolding of writing techniques and strategies
that can be applied to all writing situations within various programs and applications.
Rounsaville et al. (2022) addressed transfer theory within the context of writing by
raising the question of two distinct areas: 1) the role of conscious awareness in transfer
and 2) the role of habit or routine. The authors considered four themes of relational
character: Intentionality, Fidelity, directionality, and simultaneity (p. 140). While all areas
can impact learning transfer within a tutoring model, fidelity may be of the most value.
Fidelity represents the “likeness” associated with various context structures that
provide similarities or differences for the transfer process (Rounsaville et al., 2022). This
concept of fidelity is manifested through situatedness, simulation, and scaffolding. All of
these practices can help ensure that the learning applied within a tutoring mode can
provide the basis for allowing the learned concepts to transfer across the writing in a
specific course and into a generalized application within other courses that require
writing-intensive curriculums. Similar to high or low-road transfer, fidelity can also be
viewed as low-fidelity and high-fidelity constructs of learning transfer.
Hill (2016) and Devet (2015) argued that there is a need for writing centers and
tutoring models to be intentional about the process of transfer. Writing labs or tutoring
centers were discussed as places where transfer concepts must be fostered and guided so
students understand writing-related knowledge's transportability (Hill, 2016, p. 77). Hill
focused on the pedagogical techniques that were seen as the most salient practices to
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THE IMPACT OF STUDENT SUCCESS RATES
influence transfer from the writing centers to other applications. They included having a
high level of initial learning, seeing the similarities and differences between learning
situations, understanding key concepts about writing, using metacognitive reflections,
and promoting certain dispositions towards learning, such as active learning and
motivation (pp. 79-80).
Gateway or Barrier Courses
Koch and Pistilli (2015) defined gateway courses as being in one of two
categories. The first category includes any foundational course, such as developmental
courses, that may be credit-bearing or non-credit-bearing. The second category is highrisk courses where grades of D, F, W (withdraws), or I (incompletes) are awarded. It is
important to note that the W grade, which does not impact the GPA, is included in the
Satisfactory Academic Progress (SAP) formula, which has implications for eligibility for
financial aid. Once a student loses financial aid through excessive withdrawals, they often
drop out of school. This process often occurs because students are unable to successfully
complete identified barrier courses, such as first-year required writing courses.
Gateway courses present huge obstacles for certain groups of other identifiable atrisk students, including lower-income, first-generation, and underrepresented minority
groups. This population represents the same groups of students who are least likely to
attend college and may never finish a degree with a direct correlation to the inability to
complete barrier courses that keep them from advancing onto other courses that may have
the barrier course as a pre-requisite (Bloemer et al., 2017; Koch & Pistilli, 2015). Koch
and Pistilli (2015) also argued that gateway course failure is directly related to college
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THE IMPACT OF STUDENT SUCCESS RATES
retention rates. These students “leave with their dreams diverted if not extinguished and
frequently with debt that they might never be able to repay” (p. 15).
Bloemer et al. (2017) cautioned that the real challenge of gateway courses comes
from first identifying them and then being able to apply a fix that is appropriate and
effective in increasing the success rates of these courses. This may include curriculum
revisions or the complete redesign of a course that also considers staff changes or
providing additional support to students, such as an innovative tutoring model. Most
importantly, the authors suggested that gateway courses must be put into the context of
the students the course is meant to serve. “Simply put, it is not reasonable to expect all
courses to serve all students equally. Efforts to do so are doomed from the start and may
actually do harm” (p. 6).
Tutoring-Related Discourse
Definitions
At-Risk Students. At-risk students are not experiencing success in school and are
potential dropouts. They are usually low academic achievers who exhibit low self-esteem.
Disproportionate numbers of them are males and minorities. Generally, they are from
families with low socioeconomic status. “Students who are both low-income and of
minority status are at higher risk. Their parents may have low educational backgrounds
and may not have high educational expectations for their children” (Donnelly, 1987, p. 1)
Developmental Courses. These are courses assigned to students who failed to
meet qualifying scores on entrance exams in various subject areas. Students must
typically pass the developmental course before moving into college credit courses that
will apply to the degree being sought (Vick et al., 2015).
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THE IMPACT OF STUDENT SUCCESS RATES
Barrier/Gateway Courses. Barrier or gateway courses are basic and foundational
courses that are generally lower-division courses that receive credit and are needed to
satisfy pre-requisite requirements before taking other courses (Bloemer et al., 2017).
Drop-in Tutoring. A traditional model of one-to-one tutoring where two
individuals meet to increase the knowledge and learning of a student from a professional
tutor (Cooper, 2010, p. 21).
Mandatory Tutoring. The act of requiring students, especially first-year college
students, to participate in a mandatory tutoring process as a condition of their coursework
(Gordon, 2010).
Peer-Tutoring. Peer tutoring involves individuals from similar groups who are
not professional instructors. It is a system whereby learners help each other and learn by
teaching (Stewert et al., 2015).
Professional Tutors. These individuals possess a degree related to a particular
content and expertise. These are paid positions (often part-time) within a college’s writing
center and are sometimes supplemented with peer tutors in a specific subject, such as
math or English (Stewert et al., 2015).
Embedded Tutors. The embedded tutoring model and design can vary
considerably across different institutions; however, in this study, an embedded tutor is a
compensated individual assigned to specific course sections during the semester. The
tutor receives specialized training from the administrator responsible for tutoring
programming and works closely with the content teacher to establish the practices that
will be used in the course. Tutors support all students in a particular section and often
attend the course as an added support and opportunity to meet with students. The
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embedded tutor may have access to the grades and assignments as a means of monitoring
when a student is behind and may need encouragement or help in completing
assignments.
Tutoring Models
Tutoring and Writing Centers
Tutoring and/or writing centers are the single most popular and pervasive model
used by institutions within higher education. While no hard data exists to substantiate this
reality, a search of websites from 10 Pennsylvania State System of Higher Education
(PASSHE) schools, as well as all Pennsylvania Community Colleges, revealed that each
institute had some form or variation of a writing center, writing labs, or tutoring centers
where professional tutors and resources are available to service the students in face-toface or remote modalities.
Writing centers and the use of tutoring to improve students’ language skills
historically developed to accommodate low-skilled writers, especially veterans,
underprepared students, and minorities in need of improving the skills that would allow
them to successfully meet the challenges of higher education (Ball, 2014; Missakian et
al., 2016; Ugo, 2010). Missakian et al. (2016) also reported that academically proficient
students could also be susceptible to the same writing issues as at-risk students when
trying to meet qualifying placement exam scores. Failure to access the help of a tutor
leads to incomplete coursework and the inability to graduate on time.
Vick et al. (2015) reported that students who sought tutoring outscored others by a
55% to 45% margin and received final grade averages that were 10% better. Pfrenger et
al. (2017) also reported that tutored students successfully passed development courses at
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THE IMPACT OF STUDENT SUCCESS RATES
higher rates than non-tutored students. Using an English Lab or writing center can have
strong implications on how a student will succeed in their first year of college, so it is
important to pursue all options that will get students to access this resource. Gray and
Hoyt (2020) also found that people using writer centers saw average grades of 2.94
compared to 1.60 for those not using the center. The average grade in the specific courses
was 3.25 for students who used the center and 2.18 for other new freshmen who opted not
to use the center for support.
Despite the positive impact of the use of tutoring, Hedengren and Lockerd (2017)
reported on the negative perspectives that some students have concerning the use of a
writing center. The author’s study looked at students who reported non-directive, nonproductivity (NDNP) as the reason why they felt a writing consultation in the writing
center did not improve their writing product or their writing process; in fact, NDNP was
evident through student comments like, “This was a waste of time” (p. 133).
Dissatisfaction among the students reported that there was a lack of concrete objectives
during the sessions, which caused the students to be frustrated at the level of work that
was accomplished. “I left the writing center with no notes, thesis, or better understanding
of my argument” (p. 138). While this study involved a four-year institution, community
colleges experience similar findings among students.
Bright (2017) acknowledged that using tutors at two-year colleges has some
unique variables, such as needing to hire a wider variety of tutors, from English
instructors to peer tutors with diverse backgrounds and experience. English instructors
who enter the tutoring center environment may fail to make the switch from classroom
practices to the role of tutors in the more traditional sense. This may mean that
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THE IMPACT OF STUDENT SUCCESS RATES
consultations for students feel more like an office-hour visit with their instructor, and peer
tutors run the risk of high turnover and a lack of longevity that allows for more
sustainable and pervasive peer tutoring practices.
The inherent problem for walk-in writing centers and tutoring labs is that they
assume struggling students will access the services that professional tutors can provide to
them; however, at-risk and struggling students often fail to consider this resource as a
means of improving the writing skills needed in all of their course work. Rheinheimer et
al. (2010) argued that at-risk students tend to avoid social resources like writing centers
or professional tutors for help. These students often have educational backgrounds that
lack the skill sets needed to improve academic achievement, and they are reluctant to
reach out beyond their comfort zones; however, according to Bielinska-Kwapisz (2015),
students who accessed writing centers or labs have been shown to statistically outperform
those who do not utilize the tutoring services available to them. The use of tutoring to
improve academic writing skills increased student retention and student engagement.
Salem (2016) concluded that a parent’s educational background and exposure to
higher education can also play a factor in the desire of at-risk students to participate in
tutoring programs. Rheinheimer et al. (2010) discussed the need for at-risk students to
take advantage of programs in Pennsylvania that support economically disadvantaged
students as an academic assistance strategy through tutoring programs, and they
acknowledged that part of the problem is the failure of at-risk students to seek help when
they need it. They concluded that at-risk students who sought tutoring services
experienced higher student persistence, retention, and the likelihood of graduating.
Gordon (2010) reported on the positive impact of tutoring through comments made by
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THE IMPACT OF STUDENT SUCCESS RATES
two students in his study. One student commented, “The guy there helped me organize
my paper when I was stuck.” Another said, “It actually made me start thinking about my
paper” (p. 156). Hodges and White (2001) reported that students who access the services
of a writing center report positive experiences, but economically disadvantaged students
often have trouble seeking this type of intervention.
Embedded Tutoring
Embedded tutoring is an emerging practice that ultimately seeks to bring the tutor
to the student. Embedded models can vary greatly to meet specific and unique needs;
however, all models share the concept of tutors who are infused into a course in a regular
and visible manner. Webster and Hansen (2014) discussed one model that was used at the
University of Montana Writing Center, referred to as the Sidecar Project (SP). The
purpose of the tutor-embedded model is to provide real-time and accessible guidance for
both student and faculty growth. The model centers on four factors: “Management of
collaboration logistics, demonstrated faculty buy-in, faculty-tutor integration, and student
and faculty willingness to consider and respond to feedback” (p. 53).
The success of an embedded collaboration begins with faculty buy-in and the
need to proactively plan for collaboration time between the tutor and the faculty member
so that responsibilities and boundaries are clearly articulated in a formal or informal
agreement (Carpenter et al., 2014; Webster & Hansen, 2014). Carpenter et al. (2014)
reported that these types of embedded collaborations make a critical shift from the
traditional writing center philosophy by moving the tutors from the writing centers to the
classroom. Part of this philosophical shift requires faculty and students to realize that
classroom instruction and writing centers as outside resources can find common ground.
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This ability to develop synergy between the faculty and tutor inspires new and creative
practices that foster positive student learning and growth.
Chaves et al. (2023) reported that embedded tutoring is not a new concept;
however, it gained renewed interest during the COVID-19 pandemic as tutoring centers
across the county sought innovative ways to reimage methods to increase student tutoring
opportunities. This included finding ways to bring tutors to the students versus students
needing to come to writing centers through their own initiatives. Four models of
embedded tutoring were considered, including Harrisburg Area Community College
(HACC) in central Pennsylvania. HACC is Pennsylvania’s oldest and largest community
college, serving approximately 13,000 students in five physical locations (p. 157). The
college first piloted embedded tutoring in the late 2010s by accessing grant funding to
pursue the new endeavor that was also incorporated into the college’s Strategic Plan.
They began by infusing tutors into gateway/barrier courses and at-risk courses as a
vehicle to help increase student retention and success rates. All campuses now embrace
the embedded model in all learning modalities, with multiple tutors supporting a variety
of course sections with a focus on mathematics, biology, and English (Chaves et al.,
2023).
Mandatory Versus Voluntary Tutoring
Wells (2016) addressed the use of writing centers as a mandatory requirement,
especially for first-year students. This model requires students to participate as part of
their course structure and requirements. The author presented several viewpoints for and
against the practice of mandatory requirements, including the strain on institutional
resources and student frustrations with time-consuming requirements that often require
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long wait times in the writing centers. Students using writing centers achieved grades that
were found to be higher on average than non-center users (Bielinska-Kwapisz, 2015;
Hendriksen et al., 2005). Hendriksen et al. (2005) found that tutored students had a 2.78
average semester GPA compared with a 2.64 average semester GPA for non-tutored
students. Overall, tutored students had a 75% pass rate versus a 71% pass rate for nontutored students. Bielinska-Kwapisz (2015) found that a study of 315 first-year
undergraduates showed that a student’s intrinsic and extrinsic motivations determined if
they would utilize tutoring service; in fact, 40% of the students who sought help fell into
the top 40th percentile for grade distributions.
Edlin and Guy (2019) discussed using a mandatory supplemental instructor (SI)
model for an elementary Algebra course at a community college. All students took the
Systems-Wide Elementary Algebra Final Exam (SWEAFE) as a common assessment for
the study. The results showed that additional mandatory tutoring correlated with a 3.795point increase in the SWEAFE with a 95% confidence interval. The study also showed
that additional mandatory instruction created a 26.5% higher than without the additional
time. The study concluded that the additional mandatory requirement improved learning
overall.
Gray and Hoyt (2020) discussed the question of who should attend tutoring
despite their acknowledgment that tutoring “helps improve learning, retention of ideas,
and student grades” (p. 1). One inherent issue for tutoring comes in the perception it has
from students and faculty alike. Many students believe tutoring is reserved for struggling
students, and they may not see themselves that way. Faculty may perpetuate that reality
by having a similar perspective and by failing to understand that tutoring can benefit all
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students at their unique level of need. Fain (2012) noted that community colleges have
multiple supports (like tutoring or study prep) available to help students earn their
degrees; in fact, 48% of all colleges offer placement test study aids, but only 13% of
these colleges make that test prep mandatory (p. 1). Mandatory requirements in
community colleges may offer students a better chance for success in college-level
graduation requirements such as first-year writing courses.
Data on mandatory tutoring is limited, especially in the area of quantitative
studies; however, the recent study by Gray and Hoyt (2020) produced some encouraging
data for mandatory tutoring as a positive intervention for student success. The study also
used a mixed-method approach to allow qualitative data to be analyzed from the
participant's perspective. The study results showed that the average essay grade was 2.94
for mandatory participants versus 1.60 for students not using the writing center; in fact,
the average final grade was 3.25 for participants versus 2.18 for new freshmen not using
mandatory tutoring.
Pre- and post-student surveys supplied additional qualitative data on participants'
perceptions and attitudes. Three questions using a 5-point Likert scale revealed the
following outcomes.
Question 1: How likely are you to recommend writing centers to a friend
Pre-study: 2.90
Post-study 4.11
Question 2: How much do you think the writing center can help you on an essay?
Pre-study: 3.72
Post-study: 4.06
Question 3: How likely are you to visit the writing center for a future class?
Pre-study: 3.54
Pot-study: 4.13 (p. 3).
35
THE IMPACT OF STUDENT SUCCESS RATES
This recent study provided a solid context for continuing research on mandatory
tutoring as a positive intervention for helping students be more successful in writing
courses. More importantly, it shows that a mandatory requirement for tutoring changes
attitudes and negative perceptions of tutoring, creating positive habits of learning transfer
and the continued use of tutoring for future coursework.
Summary
Community colleges across the country face many challenges that are unique to
two-year institutes and the varied demographics of the students who attend them. The
common practice of open-access admissions for community college means that any
individual seeking to better themselves through higher education has that opportunity.
Community colleges that apply open access ensure attendance is guaranteed for
everyone, unlike four-year institutions, which may deny a student the ability to begin a
higher-education journey because they fail to meet the requirements for admission.
Selective enrollment institutions that use competitive enrollment quotas based on
academic excellence can discourage at-risk learners and keep them from starting their
post-secondary education. While noble in its intentions, the open-access policy does
come with a cost. Retention and course success rates for community college students are
often very low due to the many variables that impact these key performance indicators.
The literature reviewed showed that many factors contribute to the inability of
students to complete a degree at a community college. These include at-risk factors such
as being first-generation students, coming from low socioeconomic backgrounds, needing
to work full-time to support families, or being a part of a historically underperforming
ethnic group. These factors at a commuting college can add additional strains based on
36
THE IMPACT OF STUDENT SUCCESS RATES
childcare, transportation, shift working, and./or the need to financially support a family.
Overcoming some challenges requires determination and persistence; however, students
often don’t have the self-efficacy to get the help needed when obstacles arise, and they
lack a sense of belonging and community that may exist at an institute with dorms and
residency opportunities.
Addressing these student needs is a priority for community colleges that regularly
promote many student services to help them through these times. Unfortunately, the
literature shows that these students often fail to seek the support that is available, such as
tutoring and writing centers. Meeting face-to-face with tutors in writing centers helps
create a sense of belonging to the college by building positive relationships that include
faculty and staff members on the campus. The literature review shows that it takes a
multiple-focused approach to help students discover the best strategies to improve their
ability to be successful and continue their education through positive retention and
enrollment from semester to semester.
Applying a mandatory component to first-year writing students is one of the
strategies that can help the community college retention equation and increase course
success rates. The literature surrounding the positive effects of tutoring to increase
academic proficiencies is cogent and consistent in its outcomes; however, the use of a
mandatory approach to tutoring is not always a shared philosophy. The practice of a
mandatory tutoring component would require a shift in the ethos of the community
college that recognizes the constraints of their population but also accepts the realities of
how a strong foundational experience in a first-year writing course may provide the selfefficacy, confidence, and skills to transfer their knowledge to other courses that will be
37
THE IMPACT OF STUDENT SUCCESS RATES
required throughout their program pathway. The outcomes of this study can provide data
to be utilized for informed decisions about the potential of implementing a mandatory
requirement as a college policy. The research may also be used to develop a modified
mandatory program based on specific academic criteria, or it may be found to be an
ineffective practice that is not a good fit for the college.
Chapter III will examine the specific methodology applied to this action research
study and explain its purpose. It will also discuss the research plan, research design,
validity, and financial implications.
38
THE IMPACT OF STUDENT SUCCESS RATES
CHAPTER III
Methodology
A persistent issue faced by a two-year community college in Southeastern
Pennsylvania was that many first-year writing students were not utilizing the professional
tutoring services available in the Academic Learning Commons to improve their writing
proficiencies. Mattison (2012) suggested that educators needed to make instructional
support programs available through a wide range of offerings that could help to close
achievement gaps. This included resources such as writing centers and professional
tutors. There was a need to increase the number of students who sought the services of a
professional writing tutor, especially at-risk students such as first-generation students and
economically disadvantaged students.
The literature review for this study helped inform the researcher of the positive
impact tutoring had on first-year writing students in higher education. Vick et al. (2015)
reported that students who sought tutoring outscored others by a 55% to 45% margin and
received final grade averages that were 10% better. Pfrenger et al. (2017) also reported
that tutored students successfully passed development courses at higher rates than nontutored students. Using an English Lab or writing center had strong implications for how
a student would succeed in their first year of college, so it was important to pursue all
options that would get students to access this resource. Gray and Hoyt (2020) also found
that people using writing centers saw average grades of 2.94 compared to 1.60 for those
not using the center. The average grade in the specific courses was 3.25 for students who
used the center and 2.18 for other new freshmen who opted not to use the center for
support.
39
THE IMPACT OF STUDENT SUCCESS RATES
A second area of interest in the literature review came from looking at the unique
challenges faced by students in community colleges. Burns (2010) addressed realities
associated with student retention in community colleges due to open-access policies for
enrollment. Community colleges appealed to students with life circumstances that limited
their educational attainment. This included child or family member care, single parenting,
negative financial situations, enrolling in college later in life, being a first-generation
student, needing to commute to college with transportation restrictions, and working full
or part-time jobs; in fact, 70% of community college students related to at least one of
these situations and 50% reported connecting with two or more of these variables
(Barhoum, 2018; Burns, 2010; Fike, 2008).
These two areas of exploration within the literature review developed a sense of
synergy when applying a framework of persistence and retention of college students
through the seminal work of Tinto (1975). Tinto (1999) presented four key components
that are needed to help improve retention: 1) provide clear, informational resources
concerning the institute, 2) the accessibility of academic, social, and personal supports, 3)
create environments where the students view themselves as a valued member, and 4)
students must be learning. By the early years of the 2000s, many theorists understood the
importance of the student in the equation and how a focus on student-related variables
needed to be considered on a deeper level. Tinto (2006) addressed this as a realization
that “It is one thing to understand why students leave; it is another to know what
institutions can do to help students stay and succeed” (p.6).
This chapter considered how a quasi-experimental action research study was
developed to evaluate the impacts of mandatory tutoring for first-year writing students.
40
THE IMPACT OF STUDENT SUCCESS RATES
The study sought to determine if mandatory tutoring could improve course success rates
and writing proficiencies, contributing to stronger student retention and persistence
toward graduation. Applying a mandatory component to first-year writing students was
one of the strategies considered to help in community college retention and course
success rates. The literature surrounding the positive effects of tutoring to increase
academic proficiencies was cogent and consistent in its outcomes; however, the use of a
mandatory approach to tutoring was not always a shared philosophy. This study sought to
consider tutoring from a variety of perspectives and to weigh the value ascribed to a
mandatory tutoring requirement for all first-year students.
Purpose
This action research study was intended to determine if the use of mandatory
tutoring could increase course success rates of a first-year Communications-121 (COM121) writing course at a two-year community college in Southeastern Pennsylvania.
COM-121 was a first-year writing course required of all students at the community
college, and it was considered one of the top ten identified barrier or gateway courses. A
barrier/gateway course was identified as having course success rates of below 70%
completion. In 2022, the course success rates at a community college in Southeastern
Pennsylvania were 62% for all COM-121 courses. This meant that 38% of the students
were required to repeat and successfully complete the COM-121 course before they could
enroll in other courses that often require COM-121 as a pre-requisite. Failing COM-121
was a variable associated with a student’s ability to complete a degree on time.
The key performance indicator (KPI) for on-time graduation was a data point that
must be reported annually by all community colleges, and it was considered in choosing
41
THE IMPACT OF STUDENT SUCCESS RATES
the action research topic. Additional KPIs impacted by this action research study included
retention and course success rates. Selecting a KPI for action research that would most
significantly contribute to overall performance by measuring trends and comparison data
was crucial. Trends identified in research look at the data from year to year or at multiple
years across time, while comparisons look at similar data from an organizational process
perspective (Suryadi, 2007). This study focused on the organizational process of tutoring
practices within the broader KPIs of course success rates, retention, and on-time
graduation.
According to Stringer (2014), an isolated issue or organizational process
associated with KPI could be researched and implemented within a shorter and more
manageable time frame. It allows for practical and immediate improvements to be
realized by the research site. Hendricks (2017) added that action research is a systemic
process that requires the incorporation of specific and, therefore, measurable steps in a
repeating cycle of reflection, action, and evaluation. This process allowed for a problem
to be identified, a potential solution or action to be applied, and an evaluation of collected
data to be tested for the effectiveness of the action that was taken.
Desired Outcomes
Specific outcomes and research questions for the study:
1. To determine if the collected data supports the implementation of mandatory
tutoring for all or some students of the COM-121 writing course
2. To analyze various tutoring practices and their impact on the successful
completion of a barrier course based on mid-term and final grades
42
THE IMPACT OF STUDENT SUCCESS RATES
3. To recommend the implementation of some variation of mandatory tutoring for
first-year writing students to increase student retention and on-time graduations
4. To determine if tutor relationships help students improve their self-efficacy as
they transfer acquired knowledge to future program courses
Research Questions
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term and
final grades?
2. Is there a significant difference in writing proficiencies, as measured by course
grades, between students who participate in mandatory tutoring and those who
participate in voluntary tutoring, embedded tutoring, or those who never access
tutoring services?
3. What is the relationship between at-risk students (first-generation, economically
disadvantaged, or ethnicity/race) and mandatory tutoring as measured by success
rates when enrolled in a first-year (barrier) writing course?
Setting and Participants
School Location
A two-year community college in Southeastern Pennsylvania provided the setting
for a quasi-experimental study that considered the impact of mandatory tutoring in a firstyear writing course. Founded in 1971, the community college was one of fifteen
community colleges in Pennsylvania. The college was an accredited, comprehensive,
open-access institution of higher education. Accreditation was awarded through the
Middle States Commission of Higher Education (MSCHE). Educational opportunities
43
THE IMPACT OF STUDENT SUCCESS RATES
included associate degrees, certificate and diploma programs, career-focused training,
and skills training for business and industry. The college offered non-credit GED
preparation, English as a Second Language (ESL) instruction, and short-term workforce
training, primarily in healthcare and manufacturing technology.
School Demographics
The community college demographics for 2021-2022 included 6,457 students,
164 online courses, and 16 online programs. The average age of students was 26, with
68% female and 32% male students. 76% of students were part-time, and 24% were
enrolled as full-time students. The community college was a diverse campus and was one
of only two community colleges designated as a Hispanic Serving Institutes (HSI).
Hispanic populations (Table 1) and students from economically disadvantaged
backgrounds receiving Pell Grants (Table 2) represented two focus areas in this study.
The data described in the included tables from the Fall of 2022 reflect the college
composition.
Table 1
Fall 2022 Student body by Racial or Ethnic Group
44
THE IMPACT OF STUDENT SUCCESS RATES
Table 2
Fall 2022 Full-Time Student Body by Racial or Ethnic Group and Pell Recipient
The diversity of the students on the campus was a key consideration in any data to
be collected through this study. The number of students receiving Pell Grants at the
college was historically in the 60% range and suggested that 6 out of 10 students enrolled
at the college came from economically disadvantaged families (Figure 1). Despite this atrisk designation, success rates for these students across all classes averaged 70% (Figure
2). Data for ethnicity/race represented a larger divide among the population, especially
when African American and Hispanic students were compared to white students (Figure
3). This difference showed a significant achievement gap when comparing the white
population to the Hispanic population, where gaps increased from 12% in 2018 to 15% in
2020 (Figure 4).
45
THE IMPACT OF STUDENT SUCCESS RATES
Figure 1
Figure 2
Share of Enrollment by Pell Grants
Success Rates by Pell Status
SHARE OF ENROLLMENT
BY PELL GRANTS
37%
37%
63%
2017-18
43%
80%
40%
63%
2018-19
SUCCESS RATES BY PELL
STATUS
60%
57%
2019-20
2020-21
78%
70%
79%
72%
72%
70%
69%
2017-18
2018-19
2019-20
2020-21
Did Not Receive Pell Grant
Did Not Receive Pell Grant
Recieved Pell Grant
Recieved Pell Grant
Figure 3
Success Rates by Select Race/Ethnicity
SUCCESS RATES BY SELECT RACE/ETHNICITY
70%
70%
2018-19
81%
81%
66%
81%
68%
67%
2019-20
African American
Hispanic
66%
2020=21
White
46
THE IMPACT OF STUDENT SUCCESS RATES
Figure 4
Success Gaps Compared to White Students
SUCCESS GAPS COMPARED TO WHITE STUDENTS
12%
10%
2017-18
10%
11%
2018-19
African American
14%
13%
2019-20
14%
15%
2020=21
Hispanic
Participants
The research was focused on institutional ex-post facto (archival) data from the
fall 2023 semester and data from a quasi-experimental study conducted in the spring of
2024; therefore, the IRB approved the study as an exempt project that did not require
student consent. The study utilized 79 enrolled students in four sections of
Communications-121 (COM-121) being taught by the same instructor during the spring
2024 semester. Two sections included mandatory tutoring as a part of the curriculum, and
two sections operated with a voluntary approach to tutoring services. Sections were
limited to twenty-four seats. Initial enrollments for the two sections of mandatory
tutoring included 44 students and enrollments for the two sections without the mandatory
requirement included 35 students. Students learned of the mandatory tutoring
requirements for the course during the initial class meetings and had the option to enroll
in a different COM-121 section if desired.
The selection of participants was based strictly on student enrollment in each
unique section. A non-equivalent control group design allowed for two groups to be
established that were similar to each other; however, one group was subjected to the
independent variable of mandatory tutoring for the semester. Mertler (2022) stated that
47
THE IMPACT OF STUDENT SUCCESS RATES
this may be the best model in school settings since students are already assigned to
pre-existing variables such as classes, grade levels, or other fixed conditions. This
study utilized four of the thirty sections offered for the spring 2024 semester. Each
section contained pre-established enrollments and variables such as days and times of
the section offerings. Students registered through an advisor or a self-service
enrollment platform.
There was no indication during the registration process that identified sections as
having a mandatory tutoring requirement. Tutoring requirements vary across the
individual sections and are established by a unique instructor for each section. Students
registered through a self-service platform or through an advisor in the advising center. All
classes were face-to-face sections that were held between the hours of 9 am and 3 pm.
Demographic information for all students was collected after the semester to determine if
the various at-risk populations identified in the study were represented in the
experimental group.
The study included additional data from the fall semester of 2023, which
consisted of 65 students from three COM-121 sections that utilized an embedded tutor
model. The same instructor taught these three sections and the four sections of the spring
2024 quasi-experimental study.
Research Plan
Plan/Intervention
The development of this plan was driven by the need to increase the number of
students who could increase their course success rates in a first-year writing course
through the use of a tutor. Tutors at RACC were accessible to all students through face-
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THE IMPACT OF STUDENT SUCCESS RATES
to-face, remote, and online platforms; however, each modality required the student to
seek the intervention voluntarily. A recent study by the Director of Tutoring indicated that
only 11% of the student population had contacted a tutor during the 22-23 academic year.
A proposed intervention was considered to increase the number of students being exposed
to tutor services and to determine if the impact of mandatory tutoring could be a viable
solution for successfully completing a first-year writing course.
The quasi-experimental project included four sections of Communications-121
(COM-121), a first-year writing course. Two sections of COM-121 functioned as the
experimental group. They were exposed to an independent variable of a mandatory
tutoring requirement, and two sections of COM-121 functioned as the control group
without being exposed to the independent variable. The experimental group was
analyzed and compared to the control group and to ex-post facto data, including past
sections of COM-121 from the fall of 2023. The fall sections included three sections of
COM-121 that utilized an embedded tutor. All existing data from the fall of 2023 and
the quasi-experimental sections from the spring of 2024 were supplied in an
autonomous format by the Dean of Assessment, Research, and Planning.
Once the quasi-experimental study to collect quantitative data was created, a
volunteer instructor agreed to teach four select courses of COM-121. The instructor's
schedule included four sections of COM-121 that were held during the 15-week spring
semester of 2024. The classes were held at 9 am, 10:30 am, 12 pm, and 1:30 pm on
Tuesday and Thursday of each week. The spring 2024 experimental model was selected
based on student enrollments in these four specific COM-121 sections. Each course
had a cap of 24 students.
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THE IMPACT OF STUDENT SUCCESS RATES
Students within the mandatory tutoring sections were required to participate in at
least five thirty-minute sessions with a college-employed tutor. Students were also
required to attend three sessions before mid-semester grades, with two more sessions
expected by the end of the semester. The tutoring participation had a graded component
in the courses as outlined in the course syllabus (Figure 5). Points were awarded for each
completed tutoring session and calculated as part of the mid-term and final grades.
Tutoring sessions were one-on-one sessions in a face-to-face environment;
however, students were permitted to use two sessions that were online, remote, or in the
form of a drop-off service. This service allowed students to submit a paper to be
reviewed, annotated by a tutor, and returned to the student for review. Students had to
submit a summary of each session to the instructor, including a date and time stamp
document from the tutoring center.
Figure 5
Grading Policy for Mandatory Tutoring Section
50
THE IMPACT OF STUDENT SUCCESS RATES
A post-semester quantitative survey was distributed to all students enrolled in the
four spring 2024 sections of COM-121. One survey was distributed to the control group
(Appendix A), and one survey was distributed to the experimental group (Appendix B).
The survey for the experimental group asked Likert questions to determine if students
saw value in the tutoring experience to improve writing, whether they would seek the
help of a tutor in future courses, and how likely they were to recommend tutoring in the
future. Students in the control group (no mandatory tutoring required) were asked how
many times they had accessed the help of a tutor and whether they felt their writing had
improved through the use of a tutor if they had voluntarily accessed one while taking the
course.
Research Alignment to Intervention
The community college in Southeastern Pennsylvania was an open-access
institute for all individuals seeking credit and non-credit programs for college
advancement. All students enrolled in credit-bearing programs of study needed to achieve
minimum grade requirements in all courses, including general education requirements in
math and writing that are prerequisites for future coursework. Failure to complete these
courses with a passing grade greatly impacted a student’s persistence, especially if they
needed to repeat general education courses in math and reading with two or more
attempts.
While many variables contributed to a student’s ability to complete a program,
this study focused on a writing intervention of mandatory tutoring as one way to help
students pass a required first-year writing course. This researcher served as the Dean of
the Communications, Arts, and Humanities division of the community college, where a
51
THE IMPACT OF STUDENT SUCCESS RATES
first-year composition course was identified as a barrier course for students. An action
research model and a literature review on mandatory tutoring were utilized to inform the
plan for this study.
The literature review provided encouraging data on the positive impact of success
rates for students who accessed tutoring; however, the research was limited in
quantitative data for mandatory tutoring as a specific intervention. One recent study by
Gray and Hoyt (2020) found that students using writing centers saw average grades of
2.94 compared to 1.60 for those not using the center. The average grade in the specific
courses was 3.25 for students who used the center and 2.18 for students who opted not to
use the center for support. Though minimal, this difference could elevate marginal
students to a passing grade of a C or better in a barrier course. The research plan in this
study was designed to provide additional quantitative data for the use of a mandatory
tutoring requirement in barrier courses for writing.
The literature review also helped justify the consideration of a more invasive
intervention to tutoring, such as a mandatory requirement for all students. This study
addressed some of the stigmas and limitations of students, especially at-risk students,
who chose not to use the free tutoring services available. Burns (2010) suggested that atrisk populations, including first-generation students or economically disadvantaged
students, often lacked the self-efficacy to seek the help needed. Additional variables such
as single parenting, older learners, full and part-time workers, or being personal
caregivers for others contributed to students' availability and persistence in seeking the
help of a tutor; in fact, 70% of community college students related to at least one of these
52
THE IMPACT OF STUDENT SUCCESS RATES
situations and 50% reported connecting with two or more of the variables (Barhoum,
2018; Burns, 2010; Fike, 2008; Martin et al., 2014).
Fiscal Implications
The primary budget costs for implementing a mandatory tutoring requirement for
all Communications-121 (COM-121) students at the college would require hiring up to
seven part-time tutors designated to service all COM-121 students in every section and
form of modality, including face-to-face, remote, and online offerings. The quasiexperimental model used in this study was based on each COM-121 student in the
experimental group receiving at least five 30-minute tutoring sessions per semester. If
this model were fully implemented for future semesters, the fall and spring semesters
would average about 600 enrolled students, and the summer term would service
approximately 200 students for an estimated implementation cost of approximately
$50,000.00. This cost is based on a tutor's salary of $25.00 per hour, including 2.5
tutoring hours per student or a cost of $62.50 per student.
This study was conducted during the spring 2024 semester. There were 21
students enrolled in one section of mandatory tutoring and 23 students enrolled in the
second section. The intervention required five 30-minute tutoring sessions per student
throughout the semester, or 220 tutoring sessions in total. This required approximately
110 tutoring hours at $25.00 per hour or a total expense of $2,750.00; however, the
researcher was not charged for any additional hours of tutoring that the study
generated.
Research Methods and Data Collection
Research Design
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THE IMPACT OF STUDENT SUCCESS RATES
This study was conducted as a quantitative study with a quasi-experimental model
and the inclusion of ex-post facto (archival) data from past semesters designed to
analyze the cause and effect of a designated treatment to an experimental group and to
test for causal relationships. Gay et al. (2009) argued that quantitative data “relies on
the collection and analysis of numerical data to describe, explain, predict, or control
variables and phenomena of interest” (as cited in Mertler 2022, p.107). This study
examined mid-term and final grades, tutoring participation grades, ex-post facto data
from previous semesters, and end-of-semester quantitative data from student surveys
to determine the impact of a mandatory tutoring requirement for first-year writing
students.
Data Collection Method and Timeline
ANOVA, Chi-square, paired sample T-test, and regression analysis were
applied to SPSS statistic software with additional Google survey data using qualitative
questions and Likert scales. The action research paradigm utilized a quantitative
research method for data collection. The research model was considered a casualcomparative design using ex-post facto (archival) data from past semesters and data from
a quasi-experimental project with a control group, which used a mandatory intervention
for tutoring first-year composition students.
A post-semester quantitative survey was distributed to all students in the spring
2024 sections of Communications-121 used in the study. One survey was distributed to
the control group (Appendix A), and one survey was distributed to the experimental
group (Appendix B). Figure 6 represents a detailed alignment of information contained in
this section. All data was obtained through RACC’s Dean of Assessment, Research, and
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THE IMPACT OF STUDENT SUCCESS RATES
Planning, and all data mining was distributed to the researcher using autonomous
formats.
Figure 6
Alignment of Research Questions, Data Collection, Data Sources, and Timelines.
RESEARCH QUESTION(S)
TYPES OF DATA TO
COLLECT
DATA SOURCES
(detailed explanation of the types of data you will
collect)
TIMELINE
FOR
COLLECTING DATA
1. What is the impact of
mandatory tutoring
requirements for
increasing success rates
in a first-year (barrier)
writing course as
measured by mid-term
and final grades?
quantitative
Ex-Post Facto
Data will be
collected after
the Spring
semester on May
4, 2024.
2. Is there a significant
difference in writing
proficiencies, as
measured by course
grades, between
students who
participate in
mandatory tutoring and
those who participate in
voluntary tutoring,
embedded tutoring, or
those who never access
tutoring services?
quantitative
Mid-term and final grades will be collected
from 4 identified COM-121 Spring
semester sections taught by the same
instructor. Two sections are control groups,
and two are treatment groups with a
mandatory tutoring requirement.
Anonymized data will be collected from
the college's Dean of Assessment,
Research, and Planning and will serve as
Ex Post Facto data for the quasiexperimental study. Additional Ex Post
Facto will be acquired from the Dean of
Assessment, Research, and Planning to
look at historical data on mid-term and
final grades from additional COM-121
sections during the Fall 2023 semester.
Students write a total of three essays
throughout the course, including a personal
essay, a synthesis essay, and a research
essay. First essay grades and final essay
grades will also be considered as a subset
of the mid-term and final grades. Student
end-of-course surveys on tutoring use will
also be analyzed for comparisons.
Anonymized data will be collected from
the college's Dean of Assessment,
Research, and Planning for grades, and
anonymous student surveys regarding the
use of tutoring throughout the semester
will also be collected at the end of the
semester from the instructor of record for
the 4 sections.
Ex Post Facto Data will also be retrieved
from the Director of Tutoring and Dean of
Assessment about the use of embedded
tutoring that was recently added for barrier
courses (including COM-121) at the
college.
Historical data
from the Fall
2023 semester
will be collected
by mid-Spring
semester in
March.
Ex-Post Facto
Data will be
collected after
the Spring
semester on May
4, 2024.
Student surveys
will be collected
from the
instructor after
the semester ends
on May 4, 2024.
Historical data
from the Fall
2023 semester
will be collected
by mid-Spring
semester in
March
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THE IMPACT OF STUDENT SUCCESS RATES
3.What is the
relationship between atrisk students (firstgeneration,
economically
disadvantaged, or
ethnicity/race) and
mandatory tutoring as
measured by success
rates when enrolled in a
first-year (barrier)
writing course?
quantitative
Anonymized data will be collected from
the college's Dean of Assessment,
Research, and Planning and will serve as
Ex Post Facto data for the quasiexperimental study. The data will contain
grade distributions from the 4 identified
sections and additional demographic
information about the students that
includes at-risk identifiers, ethnicity, and/or
Pell Grant recipients as a measure of
economically disadvantaged students.
Ex-Post Facto
Data will be
collected after
the Spring
semester on May
4, 2024.
IRB Approvals
IRB approvals were requested on August 4, 2023, for the study titled: The Impact
of Success Rates When Mandatory Tutoring is Applied to a First-Semester Barrier
Courses in Writing at a Two-Year Community College. An exempt status for the
quantitative nature of the study was sought and approved by Pennsylvania Western
University (Appendix C). An additional request was made to add two student surveys to
the initial approval. This request was granted on February 3, 2024, and added to the
proposal through the IRB at Pennsylvania Western University (Appendix D). Permission
to study at the community college was also obtained from the Provost (Appendix E).
Based on the study parameters, the IRB approved the study as an exempt project that
did not require student consent.
Fiscal Implications to Research Method and Data Collection
The quasi-experimental model used in this study was based on each
Communication 121 (COM-121) student in the experimental group receiving at least
five 30-minute tutoring sessions per semester. The spring 2024 enrollment in the four
COM-121 sections associated with this study was 78 students, consisting of 42 in the
control group and 36 in the experimental group. The intervention required five 30-
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THE IMPACT OF STUDENT SUCCESS RATES
minute tutoring sessions per student throughout the semester, or 220 tutoring sessions
in total. This required approximately 110 tutoring hours at $25.00 per hour or a total
expense of $2,750.00; however, the researcher was not charged for any additional
hours of tutoring that the study generated.
Validity
Validity Types and Methods
Fraenkel et al. (2012) argued that “The critical point to remember is that validity
refers to the degree to which evidence supports the inferences a researcher makes…the
inferences are validated, not the instrument itself” (as cited in Mertler, 2022). Hendrick
(2017) suggested that researchers needed to be aware of two important distinctions within
the data produced in their action research. The action research needed to address both
credibility and validity in the study through the use of four trustworthiness criteria:
credibility, transferability, dependability, and conformability (p. 64). This action research
study established both criteria through the following methods.
Credibility was established by ensuring that data sets were approached through a
process of triangulation. It included using autonomous data collection provided by the
college’s Dean of Assessment, Research, and Planning. This included data sets from the
spring 2024 quasi-experimental study and all ex-post facto/archival data from the fall
2023 semester. Additionally, the same instructor was used for comparison data in all four
courses of the study and three additional ex-post facto sections of Communications-121
where the instructor previously used an embedded tutor. Using the same instructor
ensured that data sets were not influenced by different approaches to curriculum, tutoring,
or individual teaching styles.
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THE IMPACT OF STUDENT SUCCESS RATES
Transferability was achieved by providing detailed descriptions of the research
site and the unique environmental factors influencing student success through various atrisk factors and ethnicity/race. This information provided the means for duplication of the
study for future research or relative comparisons to similar demographics and
environmental conditions.
Finally, dependability was achieved through the use of the triangulation of data, as
well as by providing a format that would allow for the findings to be replicated with other
participants and settings of similar contexts for continued research of the capstone
project. Confirmability was also achieved through triangulation of data and the steps
taken to ensure that no bias existed on the researcher's part while analyzing data. Using
the same instructor within all tutoring models helped achieve a fair and balanced
perspective on the concepts explored throughout the study. Finally, student survey data
was collected through electronic Google Surveys with qualitative questions to ensure the
lack of researcher bias as vetted by the Pennsylvania Western University IRB (Appendix
D).
Triangulation of Data
James-Warren et al. (2013) spoke about the need for data-informed decisionmaking and the use of a step-by-step process to ensure the integrity of the process. They
promoted the use of a triangulation method to describe meaningful educational
interventions by using multiple data points surrounding the same issue, and they
encouraged looking for links between practice and the results of the data. Mertler (2020)
inferred that triangulation does not automatically imply that three data points are
required; in fact, the author suggested that a better identifier may be to call data collection
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THE IMPACT OF STUDENT SUCCESS RATES
polyangulation, a term that would imply “more than one or many” (as cited in Mertler,
2022, p. 14). Mertler (2022) also asserted that data should be able to show that
independent measures support the concept of agreement and do not contradict each other.
This study achieved the conditions of triangulation (polyangulation) through the
use of several data points that included qualitative data from a quasi-experimental model
involving four sections of Communications-121 (COM-121), quantitative survey data
collected at the end of the semester from the four sections of COM-121 in the study, and
the inclusion of ex-post facto (archival) data from past sections of COM-121. The data
from each of these areas were used to answer the research questions that framed the study
and to inform the recommendations and conclusions from the study.
Summary
The proposed intervention sought to develop a course tutoring model to increase
the number of students accessing professional tutors in the English Lab to improve
writing proficiencies and to improve course success rates. Many first-year writing
students who enrolled in college courses could not meet the expectations of college-level
writing, and they lacked the self-efficacy skills needed to seek additional help and
support. Bandura (1977) argued that students who lack self-confidence will likely not
seek advice and support mechanisms that can help them cope with feelings of inadequacy
in tasks like writing. Increasing writing proficiencies and course success rates through a
mandatory tutoring requirement was considered a consistent writing framework to be
applied to all first-year Communications-121 (COM-121) courses at the college.
The community college in Southeastern Pennsylvania operated a walk-in tutoring
model with no mandatory requirements to access professional tutors. Virtual tutoring and
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THE IMPACT OF STUDENT SUCCESS RATES
a drop-off tutoring system were also in place; however, mandatory tutoring requirements
were at the individual instructor's discretion for each course. The Director of Tutoring has
recently implemented the use of embedded tutors in selected barrier courses as part of a
Title V grant that included several sections of COM-121. This study focused on a
mandatory tutoring component for select first-year writing sections and compared course
success rates measured through mid-term and final grades between the various tutoring
models available to all college students.
Chapter III described how a research plan was designed to consider one possible
strategy to help increase course success rates, writing proficiencies, and retention in one
of the top 10 barrier courses for the college. The results of the spring 2024 quasiexperimental study and ex post facto data from the fall of 2023 will be examined in the
next chapter to determine if any significant results have been discovered that could help
to implement new or restructured ways to offer tutoring services at the college. Tinto
(1999) said, “Clearly, the most important condition that fosters student retention is
learning. Students who learn are students who stay” (p. 29). It is crucial for the college to
consider multiple variables associated with making a student’s college experience a
successful endeavor, and this study may provide a window of opportunity toward that
aspiration.
Chapter IV will examine various data statistic tools, including ANOVA, Chisquare, paired sample T-test, and regression models, to analyze and discuss the results
from the quantitative data collected from a quasi-experimental intervention, ex-post facto
data from past semesters, and student survey data.
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THE IMPACT OF STUDENT SUCCESS RATES
CHAPTER IV
Data Analysis and Results
Community colleges throughout Pennsylvania operated with an open-access
policy that guaranteed students access to the education they provide; however, they were
also challenged with how to engage students in ways that could ensure student success
and retention toward a goal of on-time graduation. Elfman (2023) reported on the
challenges of an open-access policy in a post-pandemic environment that threatens openaccess participation by the very individuals who need it the most, but who are unable to
make education a priority due to a variety of reasons, including “finances, family, illness,
lack of internet or inability to adapt to online learning” (p. 24). Elfman’ s observations
concerning the struggles in an open-access college environment helped shape this study's
focus and define its purpose.
This action research study aimed to examine a specific strategy within an openaccess environment that could help increase student retention through the successful
completion of a first-year barrier course in writing. The study sought to determine if
mandatory tutoring in a first-year writing course at a two-year community college in
Southeastern Pennsylvania could positively impact course success rates and the key
performance indicator (KPI) of student retention.
The study also sought to determine if there were significant differences in student
academic success and retention based on a variety of demographic considerations and atrisk factors that could also be impacting course success rates in a barrier course. Tinto
(2017) asserted that “…student retention has been shaped by theories that view student
retention through the lens of institutional action and ask what institutions can do to retain
their students” (p. 254). Tinto’s seminal work in retention became the framework for the
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THE IMPACT OF STUDENT SUCCESS RATES
study and the desire to explore potential strategies that could help all students find
success on their first attempt at a barrier course in writing.
Many students failed the Communications-121 (COM-121) course on their first
attempt and needed to repeat it two or three times before completing it. Passing COM121 was essential for enrolling in future courses that required this course as a
prerequisite. Failure to pass a first-year writing course had detrimental impacts on
retention and on-time graduation rates, which are data points of the college's five-year
Strategic Goals. This study considered how a mandatory tutoring requirement in an
identified barrier course for writing could impact course success rates and thereby help
with a student’s retention and ability to achieve on-time graduation within three years.
The following research questions were analyzed, and the results are discussed in this
chapter.
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term
and final grades?
2. Is there a significant difference in writing proficiencies, as measured by
course grades, between students who participate in mandatory tutoring and
those who participate in voluntary tutoring, embedded tutoring, or those who
never access tutoring services?
3. What is the relationship between at-risk students (first-generation,
economically disadvantaged, or ethnicity/race) and mandatory tutoring as
measured by success rates when enrolled in a first-year (barrier) writing
course?
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THE IMPACT OF STUDENT SUCCESS RATES
Data Analysis
A quantitative research model was conducted to consider student outcomes based
on mid-term and final grades within a Communication-121 (COM-121) course required
of all first-year students. COM-121 was a first-year writing course that needed to be
taken by all students in all programs offered at the college. It was also designated as one
of the top 10 barrier courses at the college due to its low course success rates for
completion. In 2022, the course success rates at the community college in Southeastern
Pennsylvania were 62% for all COM-121 courses.
Data was collected from a quasi-experimental study conducted during the spring
2024 semester and from archival data from the fall 2023 semester. The data set included
144 students in seven sections of COM-121. There were 44 students in two sections of
mandatory tutoring, 35 students in two sections of voluntary tutoring, and 65 students
in three sections with an embedded tutor.
The quasi-experimental project included four sections of Communications-121
(COM-121). Two sections of COM-121 functioned as the experimental group. They
were exposed to an independent variable of a mandatory tutoring requirement, and two
sections of COM-121 functioned as the control group without being exposed to the
independent variable. The experimental group was analyzed and compared to the
control group, and ex-post facto data from three previous sections of COM-121 from
the fall 2023 semester that included an embedded tutor. The Dean of Assessment,
Research, and Planning, who manages all institutional research data and state and
federal reporting, supplied all existing data in an autonomous format from the fall
2023 and spring 2024 semesters.
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THE IMPACT OF STUDENT SUCCESS RATES
The quantitative data from the quasi-experimental study were carefully
analyzed using various SPSS statistical models specifically chosen to accurately
interpret the research questions. The key tools used in this process were ANOVA, Chisquare, paired sample T-test, and regression analysis. The results were discussed and
were shared throughout the chapter. Additional quantitative data was collected through
a voluntary Google Survey where Likert questions were used to help triangulate the
data for the study. It's important to note that no survey results were available for the
ex-post facto data from the three embedded tutoring courses taught during the fall
2023 semester, which may have implications for the study's findings.
Results
To answer the three research questions, specific data was required to examine
participant demographics, including race/ethnicity, first-generation status, and Pell Grant
recipient status. These demographics were analyzed for their potential relationship to
learning outcomes based on mid-term and final grades within three different tutoring
models: mandatory, embedded, and voluntary tutoring. A student survey was also
analyzed to help triangulate the data and to determine student perceptions of tutoring and
if learning transfer of tutoring practices will be considered for future courses. The results
showed the following information:
Research Question One: What is the impact of mandatory tutoring requirements for
increasing course success rates in a first-year (barrier) writing course as measured by
mid-term and final grades?
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 7
Mid-term Grades: All Tutoring Models
Figure 7 shows mid-term grades from students in all three tutoring models in the
study. 28 students out of 144 scored an F in the mid-term test of the Communication-121
course. 21 students each scored grades A and B, 18 scored A-, 15 scored B+, 13 scored D,
eight scored B-, seven scored C, five scored C+, and three students scored D-.
Additionally, five students had null grades in the mid-term test. This distribution confirms
that the majority of the students scored grade F while the lowest number of students
scored D-. The overall success rate at the mid-term point, based on grades of an A, B, or
C was 66%. Mandatory models were at 57% (Figure 8), voluntary models were at 80%
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THE IMPACT OF STUDENT SUCCESS RATES
(Figure 9), and embedded models were at 65% (Figure 10). These results indicated that
the best-performing tutoring model for course success rates at the mid-term point was for
students who voluntarily accessed a tutor or did not utilize a tutor at all.
Figure 8
Mid-term Grades: Mandatory Tutoring Model
Figure 9
Mid-term Grades: Voluntary Tutoring Model
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 10
Mid-term Grades: Embedded Tutoring Model
Figure 11
Final Grades: All Tutoring Models
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 11 shows mid-term grades from students in all three tutoring models in the
study. 36 out of 144 students withdrew from the study. 19 students scored C as their Final
grade, 18 scored F and B, 13 scored A and A-, 10 scored B+, nine scored C+, four scored
D, three scored B-, and one scored D+. This implied that a higher number of students
withdrew from the study. Similarly, most students scored C as their final grade, while
only one scored D+. The overall course success rate for final grades, based on grades of
an A, B, or C was 59%. Mandatory models were at 50% (Figure 12), voluntary models
were at 74% (Figure 13), and embedded models were at 62% (Figure 14). These results
indicated that the best-performing tutoring model for course success rates at the final
grade point was for students who voluntarily accessed a tutor or did not utilize a tutor at
all.
Figure 12
Final Grades: Mandatory Tutoring Model
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 13
Final Grades: Voluntary Tutoring Model
Figure 14
Final grades: Embedded Tutoring Model
69
THE IMPACT OF STUDENT SUCCESS RATES
Table 3
Comparison Between Mandatory and Voluntary Models as Measured by Final Grades
Statistics
Final Grades Mandatory
Final Grades Voluntary
Model
Model
N
44
35
Mean
3.95
6.54
Median
3.5
8.00
Mode
0
10
Note. Descriptive statistics
According to Table 3, the number of students who participated in the mandatory
and voluntary model were 44 and 35, respectively. The mean final grade under the
voluntary model was slightly higher than that of the mandatory model, as the voluntary
model had a mean of 6.54, while the mandatory model had a mean of 3.95. The median
final grade of the mandatory model was 3.5, while the median of the voluntary model had
a median of 8.
Table 4
Frequency Comparison Between the Mandatory Model and Voluntary Model as
Measured by Final Grades
Grade
Mandatory
Model
Frequency
W
F
D
D+
17
4
1
0
Valid
Percent
38.6
9.1
2.3
0
Voluntary
Model
Frequency
Percent
7
1
1
0
20.0
2.9
2.9
0
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THE IMPACT OF STUDENT SUCCESS RATES
CC
C+
BB
B+
AA
Total
0
5
2
2
7
1
3
2
44
0
11.4
4.5
4.5
15.9
2.3
6.8
4.5
100
0
4
2
0
3
5
7
5
35
0
11.4
5.7
0
8.6
14.3
20.0
14.3
100
Note. Frequency comparison
According to Table 4, most of the students under the mandatory model withdrew
(n=17), while those under the voluntary model scored A- as the final grade with
withdraws at (n=7). Only one student scored an F under the voluntary model, while four
students student scored an F under the mandatory model. Moreover, more students scored
A and A- as final grades under the voluntary model (n=12) than in the mandatory model
(n=5). The observed impact was the high numbers of withdrawals in the mandatory and
voluntary models. Also, there was a higher performance in the voluntary model than in
the mandatory model as measured by the final grade. Additionally, few students scored an
F under the voluntary model as compared to the mandatory model.
Table 5
Descriptive Statistics Comparison Between the Mandatory and Embedded Model as
Measured by Final Grades
Statistics
Final Grades
Mandatory model
44
Final Grades
Embedded model
65
Mean
3.95
4.66
Median
3.5
5.00
0
1
N
Mode
Note. Descriptive statistics
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THE IMPACT OF STUDENT SUCCESS RATES
According to Table 5, the number of students who participated in the mandatory
and embedded model was 44 and 65, respectively. The mean final grade under the
embedded model was slightly higher than the mandatory model, as the embedded model
had a mean of 4.66, representing a C- final grade, while the mandatory model had a mean
of 3.95, representing a D+ final grade. The median final grade of the mandatory model
was 3.5, representing a grade of D+, while the median of the embedded model had a
median of 5, representing a final grade of C. Additionally, the mode final grade of the
mandatory model was zero, representing withdrawal, while in the embedded model, it
was 1, representing a grade F.
Table 6
Frequency Comparison Between Mandatory Model and Embedded Model as Measured
by Final Grades
Grade
W
F
D
D+
CC
C+
BB
B+
AA
Total
Mandatory
Model
Frequency
17
4
1
0
0
5
2
2
7
1
3
2
44
Valid Percent
38.6
9.1
2.3
0
0
11.4
4.5
4.5
15.9
2.3
6.8
4.5
100
Embedded
Model
Frequency
12
13
2
1
0
10
5
1
8
4
3
6
65
Percent
18.5
20.0
3.1
1.5
0
15.4
7.7
1.5
12.3
6.2
4.6
9.2
100
Note. Frequency comparison
According to Table 6, most of the students under the mandatory model withdrew
(n=17), while those under the embedded model scored an F as the final grade (n=13).
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THE IMPACT OF STUDENT SUCCESS RATES
Also, more students scored an F under the embedded model (n=13) than under the
mandatory model (n=4) as measured by final grade. Most of the students scored A and Aas final grades under the embedded model (n=9) compared to the mandatory model
(n=5). The impact was that there were more withdrawal cases in the mandatory model
than in the embedded model. Similarly, as shown by the final grade recordings, the
embedded model had a slightly higher performance than the mandatory model.
Additionally, few students scored an F grade under the mandatory model compared to the
embedded model, as specified in the final grades.
Research Question Two: Is there a significant difference in writing proficiencies, as
measured by course grades, between students who participate in mandatory tutoring
and those who participate in voluntary tutoring, embedded tutoring, or those who never
access tutoring services?
ANOVA and T-tests were applied to study data to establish whether there was a
significant difference in writing proficiencies, as measured by course grades between
students who participated in mandatory tutoring and those who participated in other
tutoring models.
Table 7
ANOVA Between Mandatory and Voluntary Tutoring as Measured by Mid-term Grades
ANOVA
Midterm Grades Voluntary
Sum of
Squares
Between
147.177
Groups
Within Groups 288.365
Total
Note. ANOVA
435.543
df
9
Mean
Square
16.353
25
11.535
34
F
Sig.
1.418
.233
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THE IMPACT OF STUDENT SUCCESS RATES
According to Table 7, a one-way ANOVA between the mandatory tutoring model
and voluntary tutoring model as measured by the mid-term grade was (F (9, 25) =1.418),
P=0.233). Since the P-value was more than an alpha value of 0.05 (P=0.233>0.05), it
implied that there was a statistically significant difference in writing proficiencies
between students who participated in the mandatory tutoring model and the voluntary
tutoring model.
Table 8
ANOVA Between Mandatory and Embedded Tutoring as Measured by Mid-term Grades
ANOVA
Mid-term Grades Embedded
Sum of
Squares
Between Groups
159.852
df
Mean Square
F
Sig.
9
17.761
1.245
.301
14.261
Within Groups
484.875
34
Total
644.727
43
Note. ANOVA
According to Table 8, a one-way ANOVA between the mandatory tutoring model
and embedded tutoring model as measured by the mid-term grade was (F (9, 34) =1.245),
P=0.301). Since the P-value was more than an alpha value of 0.05 (P=0.301>0.05), it
implied that there was a statistically significant difference in writing proficiencies
between students who participated in the mandatory tutoring model and the embedded
tutoring model.
Table 9
ANOVA Between Mandatory and Voluntary Tutoring as Measured by Final Grades
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THE IMPACT OF STUDENT SUCCESS RATES
ANOVA
Final Grade Voluntary
Sum of
Squares
Between Groups
326.519
df
Mean Square
F
Sig.
9
36.280
3.569
.006
10.167
Within Groups
254.167
25
Total
580.686
34
Note. ANOVA
According to Table 9, a one-way ANOVA between the mandatory tutoring model
and voluntary tutoring model as measured by the final grade was (F (9, 25) =3.569),
P=0.006). Since the P-value was less than an alpha value of 0.05 (P=0.006<0.05), it
implied that there was no statistically significant difference in writing proficiencies
between students who participated in the mandatory tutoring model and voluntary
tutoring model as measured by final grade.
Table 10
ANOVA Between Mandatory and Embedded Tutoring as Measured by Final Grades
ANOVA
Final Grade Embedded
Sum of
Squares
Between
204.608
Groups
Within Groups
460.120
Total
664.727
df
9
Mean
Square
22.734
34
13.533
F
Sig.
1.680
.132
43
Note. ANOVA
According to Table 10, a one-way ANOVA between the mandatory tutoring model
and embedded tutoring model as measured by the final grade was (F (9, 34) =1.680),
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THE IMPACT OF STUDENT SUCCESS RATES
P=0.132). Since the P-value was more than an alpha value of 0.05 (P=0.132>0.05), it
implied that there is a statistically significant difference in writing proficiencies between
students who participated in the mandatory tutoring model and the embedded tutoring
model as measured by final grade.
Overall, there was a statistically significant difference between mandatory,
embedded, and voluntary as measured by mid-term grades based on ANOVA. Similarly,
based on ANOVA, a statistically significant difference existed between the mandatory
model and embedded model as measured by final grades. However, there was no
statistically significant difference between the mandatory and voluntary models as
measured by the final grade.
Table 11
Paired Sample T-test Between Mandatory and Voluntary Tutoring Models as Measured by
Mid-term Grades
According to Table 11, the paired sample T-test between the mandatory tutoring
model and voluntary tutoring model as measured by the mid-term grade was (t (34) =2.171), P=0.037). Since the P-value was less than an alpha value of 0.05
(P=0.037<0.05), the results implied that the mean difference in writing proficiencies
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THE IMPACT OF STUDENT SUCCESS RATES
between students who participated in mandatory tutoring and voluntary tutoring model as
measured by mid-term grade was statistically significant. This meant a statistically
significant difference existed between students who participated in the mandatory and
voluntary tutoring models as measured by mid-term grades.
Table 12
Paired Sample T-test Between Mandatory and Embedded Tutoring Model as Measured by
Mid-term Grades
According to Table 12, the paired sample T-test between the mandatory tutoring
model and embedded tutoring model as measured by the mid-term grade was (t (43) =0.348), P=0.729). Since the P-value was more than an alpha value of 0.05
(P=0.729>0.05), it implied that the mean difference in writing proficiencies between
students who participated in the mandatory and embedded tutoring models as measured
by mid-term grades was not statistically significant. This meant that no statistically
significant difference existed between students who participated in the mandatory
tutoring and embedded tutoring model as measured by mid-term grades.
Table 13
Paired Sample T-test Between Mandatory and Voluntary Tutoring as Measured by Final
Grades
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THE IMPACT OF STUDENT SUCCESS RATES
According to Table 13, the paired sample T-test between the mandatory tutoring
model and voluntary tutoring model as measured by the final grade was (t (34) =-2.205),
P=0.034). Since the P-value was less than an alpha value of 0.05 (P=0.034<0.05), it
implied that the mean difference in writing proficiencies between students who
participated in the mandatory and voluntary tutoring models as measured by final grade
was statistically significant. The results showed that there was a statistically significant
difference between students who participated in the mandatory tutoring model and the
voluntary tutoring model as measured by final grades.
Table 14
Paired Sample T-test Between Mandatory and Embedded Tutoring as Measured by Final
Grades
According to Table 14, the paired sample T-test between the mandatory tutoring
model and embedded tutoring model as measured by the final grade was (t (43) =-0.409),
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THE IMPACT OF STUDENT SUCCESS RATES
P=0.684). Since the P-value was more than an alpha value of 0.05 (P=0.684>0.05), it
implied that the mean difference in writing proficiencies between students who
participated in the mandatory and embedded tutoring models as measured by final grade
was not statistically significant. This indicated that there was no statistically significant
difference between students who participated in the mandatory tutoring model and the
embedded tutoring model as measured by final grade.
Overall, the paired sample t-test showed a significant difference between the
mandatory and voluntary models, while there was no statistically significant difference
between the mandatory and embedded models as measured by mid-term and final grades.
Research Question Three: What is the relationship between at-risk students (firstgeneration, economically disadvantaged, or ethnicity/race) and mandatory tutoring as
measured by success rates when enrolled in a first-year (barrier) writing course?
The chi-square and regression tests were utilized to determine the relationship
between at-risk students (first-generation, economically disadvantaged, or ethnicity/race)
and mandatory tutoring as measured by success rates. The chi-square test showed
whether the variables were associated, while regression showed R, which measured the
degree of relationship between variables.
In total, 144 students from diverse backgrounds participated in this study. 49.31
percent of the students were Hispanic, 32.64 percent were white, 9.028 percent were
Black or African American, 8.333 percent were categorized as having two or more races,
and 0.694 percent were non-resident Aliens. This implied that the majority of the students
who participated in the study were Hispanic, while the least were non-resident Aliens.
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THE IMPACT OF STUDENT SUCCESS RATES
71.53 percent of the students who participated in the study were non-firstgeneration students, while 28.47 percent were first-generation students. This implied that
there were more students with non-first-generation status than first-generation status
students. 65.97 percent of the students involved in the study received Pell Grants,
whereas 34.03 percent did not. This inferred that more students received Pell Grants that
were awarded based on socioeconomic status
Table 15
Chi-square Test Between First-generation Status and Mandatory Tutoring as Measured
by Success Rate
Value
Chi-Square Tests
df
Asymp.
Sig. (2sided)
1
.870
1
1.000
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson Chi-Square .027a
Continuity
.000
b
Correction
Likelihood Ratio
.027
1
.870
Fisher's Exact Test
1.000
.576
Linear-by-Linear
.026
1
.871
Association
N of Valid Cases
44
a. 1 cells (25.0%) have an expected count of less than 5. The minimum expected
count is 4.77.
b. Computed only for a 2x2 table
Note. Chi-square test
Since the basis of undertaking a chi-square test was measuring the association
between variables, the only value the study reported was the Pearson Chi-Square.
Therefore, based on Table 15, the Pearson Chi-Square test between first-generation status
and mandatory tutoring as measured by success rate was 𝜒 (1) = 0.027, 𝑝 = 0.870.
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THE IMPACT OF STUDENT SUCCESS RATES
Since the P-value was more than the alpha value of 0.05 (p=0.870>0.05), there was no
statistically significant association between first-generation status and mandatory
tutoring, as depicted by the success rate.
Table 16
Chi-square Test Between Pell-grant Status and Mandatory Tutoring as Measured by
Success Rate
Chi-Square Tests
Value
df
Asymp.
Sig. (2sided)
a
.052
1
.820
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson ChiSquare
Continuity
.000
1
1.000
b
Correction
Likelihood Ratio
.052
1
.820
Fisher's Exact Test
1.000
.533
Linear-by-Linear
.051
1
.822
Association
N of Valid Cases
44
a. 0 cells (0.0%) have an expected count of less than 5. The minimum expected
count is 7.64.
b. Computed only for a 2x2 table
Note. Chi-square
According to Table 16, the Pearson Chi-Square test between Pell Grant status and
mandatory tutoring as measured by success rate was 𝜒 (1) = 0.052, 𝑝 = 0.820. Since the
P-value was more than the alpha value of 0.05 (p=0.820>0.05), there was no statistically
significant association between Pell status and mandatory tutoring as measured by
success rate.
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THE IMPACT OF STUDENT SUCCESS RATES
Table 17
Chi-square Test Between Ethnicity/race and Mandatory Tutoring as Measured by Success
Rate
Chi-Square Tests
Value
df
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear Association
3.650a
4.805
.890
3
3
1
Asymp. Sig. (2sided)
.302
.187
.345
N of Valid Cases
44
a. 5 cells (62.5%) have an expected count of less than 5. The minimum expected
count is 1.43.
Note. Chi-square test
According to Table 17, the Pearson Chi-Square test between ethnicity/race and
mandatory tutoring as measured by success rate was 𝜒 (3) = 3.650, 𝑝 = 0.302. Since the
P-value was more than the alpha value of 0.05 (p=0.302>0.05), there was no statistically
significant association between ethnicity/race and mandatory tutoring as measured by
success rate.
Table 18
Regression Between First-generation Status and Mandatory Tutoring as Measured by
Success Rate
Model
R
Model Summary
R Square
Adjusted R
Square
1
.025a
.001
-.023
a. Predictors: (Constant), First-generation status
Note. Regression model Summary
Std. Error of the
Estimate
4.600
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THE IMPACT OF STUDENT SUCCESS RATES
Since this regression analysis table showed the value of R, which is the
correlation that ascertains the relationship, other output tables were not utilized. Table 18
showed the correlation between first-generation status and mandatory tutoring as
measured by a success rate of 0.025 (R=0.025). This implied that, even though there was
a positive relationship between first-generation status and mandatory tutoring as
measured by success rate, the degree of relationship was very low.
Table 19
Regression Between Pell Status and Mandatory Tutoring as Measured by Success Rate
Model Summary
Model
R
R Square
Adjusted R
Square
Std. Error of the
Estimate
1
.034a
.001
-.023
4.598
a. Predictors: (Constant), Pell status
Note. Regression model summary
According to Table 19, the correlation between Pell Grant status and mandatory
tutoring as measured by a success rate of 0.034 (R=0.034). This implied that there was a
positive relationship between Pell Grant status and mandatory tutoring, as measured by
success rate. However, the degree of relationship was very low.
Overall, Chi-Square Tests showed no association between at-risk students (Firstgeneration status, Pell Grant status, and ethnicity) and mandatory tutoring as measured by
success rate. However, Regression analysis showed that there was a positive relationship
between at-risk students and mandatory tutoring as measured by success rate, although
the degree of relationship was very low.
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THE IMPACT OF STUDENT SUCCESS RATES
Student Survey Data Results
This quantitative study sought to achieve triangulation through various data
analyses, as presented in this chapter. One final data set came from a voluntary exit
survey of students who were part of the quasi-experimental study in the spring of 2024.
The brief survey sought to include a student voice perspective on tutoring through Likert
questions and responses. It should be noted that this survey was not available to students
in the embedded sections from the fall 2023 semester. The spring 2024 survey helped to
reflect on the framework of learning transfer theory and whether students would continue
to utilize tutoring beyond the barrier course of Communications-121. Student responses
for the mandatory tutoring sections represented 22 of 44 students or a 50% return.
Students from the voluntary tutoring sections represented 24 of 35 students or a 69%
return.
Figure 15
Survey Results: Mandatory Tutoring Question One
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 15 represents the number of mandatory tutoring sessions attended during
the spring 2024 semester. 18.2 percent of the students met or exceeded the five required
sessions, while 81.8 percent reported attending one to four sessions. This implied that 100
percent of the survey participants utilized tutoring services at some point over the course
of the semester, but the majority did not complete the mandatory five tutoring sessions.
Figure 16
Survey Results: Mandatory Tutoring Question Two
Figure 16 shows that 63.7 percent of students agree or strongly agree that tutoring
improved the quality of their writing during the semester. 31.8 percent neither agree nor
disagree that tutoring helps their writing, and 4.5 percent strongly disagree that tutoring
improves their writing. This implied that most students believe tutoring improved the
quality of their writing over the semester.
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 17
Survey Results: Mandatory Tutoring Question Three
Figure 17 shows that 54.6 percent of students are very likely to extremely likely
to use tutoring services for future courses, while 9.1 percent are not at all likely to use
tutoring for future courses. 36.4 percent of students are somewhat likely to use tutoring.
This implied that a majority of students will be inclined to access tutoring services for
future course
Figure 18
Survey Results: Mandatory Tutoring Sections Question Four
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 18 shows that 69.1 percent of students are very likely to extremely likely
to recommend tutoring to a classmate, while 4.5 percent are not at all likely to
recommend tutoring to a classmate. 36.4 percent of students are somewhat likely to
recommend tutoring to a classmate, which implied that most students would be inclined
to recommend tutoring to a classmate.
Figure 19
Survey Results: Voluntary Tutoring Sections Question One
Figure 19 represents the number of voluntary tutoring sessions attended during
the semester when no mandatory sessions were required. 50 percent of the students
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THE IMPACT OF STUDENT SUCCESS RATES
attended 1, 2-3, or 4-5 sessions in the semester; however, 25 percent attended only one
session. 50 percent of the students attended no tutoring session for the semester. This
implied that half of the students in a voluntary tutoring section of Communications-121
sought the help of a tutor on their own.
Figure 20
Survey Results: Voluntary Tutoring Sections Question Two
Figure 20 shows that 37.5 percent of the students who used a tutor during the
semester agree or strongly agree that the quality of their writing improved. 12.5 percent
neither agreed nor disagreed with whether their quality of writing had improved, and 50
percent of the students did not use a tutor during the semester. This implied that a
majority of students who used a tutor within a voluntary tutor model believed that their
writing improved over the semester.
Discussion
This action research study used a quantitative data collection process to determine
if a mandatory tutoring intervention in a first-year Communication-121 (COM-121)
barrier course could improve course success rates and ultimately help student retention
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THE IMPACT OF STUDENT SUCCESS RATES
rates. The study included data sets from a quasi-experimental study of two COM-121
sections with a mandatory tutoring requirement and two sections of COM-121 with a
voluntary approach to tutoring. Ex-post facto/archival data from three embedded tutoring
sections were also considered. The same instructor was used for comparison data in all
four courses of the spring 2024 study and the three additional ex-post facto sections of
COM-121 from fall 2023. Data were collected to answer the following three research
questions:
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term
and final grades?
2. Is there a significant difference in writing proficiencies, as measured by
course grades, between students who participate in mandatory tutoring and
those who participate in voluntary tutoring, embedded tutoring, or those who
never access tutoring services?
3. What is the relationship between at-risk students (first-generation,
economically disadvantaged, or ethnicity/race) and mandatory tutoring as
measured by success rates when enrolled in a first-year (barrier) writing
course?
Research question one sought to determine the impact of mandatory tutoring as a
potential intervention to increase course success rates. Mid-term and final grades were
the only factors considered as data points in this study. Based on descriptive and
comparison analytical models, the results showed that mandatory tutoring did not
positively impact final grades. Course success rates for mid-term grades (measured by
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THE IMPACT OF STUDENT SUCCESS RATES
mid-term grades of A, B, and C) included 57% for mandatory tutoring, 65% for
embedded tutoring, and 80% for voluntary tutoring. Course success rates for final grades
(measured by final grades of A, B, and C) included 50% for mandatory tutoring. 62% for
embedded tutoring and 74% for voluntary tutoring. In considering the three tutoring
models identified in this study, mandatory tutoring scored the lowest course success rates
in both mid-term and final grades.
Based on mid-term and final grades, research question two used paired T-tests and
ANOVA analytics to determine if a student’s writing proficiencies improved based on the
tutoring model used in a given course. Overall, there was a statistically significant
difference between mandatory, embedded, and voluntary as measured by mid-term grades
based on ANOVA. Similarly, based on ANOVA, a statistically significant difference
existed between the mandatory model and embedded as measured by final grades.
However, there was no statistically significant difference between the mandatory and
voluntary models as measured by the final grade.
Research question three applied Chi-Square tests and Regression analysis to
determine correlations between success rates, at-risk students (first-generation,
economically disadvantaged, or ethnicity/race), and mandatory tutoring. Chi-Square Tests
did not show any association between at-risk students (First-generation status, Pell Grant
status, and ethnicity) and mandatory tutoring as measured by course success rates.
However, Regression analysis showed a positive relationship between at-risk students
and mandatory tutoring as measured by success rate, although the degree of relationship
was very low.
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THE IMPACT OF STUDENT SUCCESS RATES
Summary
Chapter IV has taken an extensive look at the data collected in an action research
study that examined the intervention of various tutoring models in a Communications121 first-year writing course, an identified barrier course at the college where the study
was conducted. A mandatory tutoring approach was considered as an option to increase a
student’s writing proficiencies and their ability to complete the writing course
successfully on the first attempt. Data from a quasi-experimental study in the spring 2024
semester and ex-post facto data from the fall 2023 semester were analyzed, and the
results were presented in this chapter.
Chapter V will use the information from these results to draw conclusions and
suggest recommendations for how these results may be used to further the discussion on
student retention and student success rates in barrier courses at the college. Limitations to
the study and their impact on the validity of the data will also be shared in an effort to
refine, modify, and continue the cycle of action research required to best serve the
students at the college and the unique circumstances they face as students in a community
college environment
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CHAPTER V
Conclusions and Recommendations
One of the most prevalent challenges that community colleges faced in increasing
student retention and persistence came through their use of open-access enrollment. Raby
(2020) referred to open access as “A foundational philosophy of the community college”
(p. 41). This embedded philosophy is a cornerstone principle for all community colleges’
charge to make education available to all students and that no individual will ever be
denied access through a selective admissions process like is used by four-year institutes.
A study by Rheinheimer et al. (2010) showed that tutoring was an overwhelmingly
positive predictor of persistence, retention, and degree completion and claimed that
tutoring was a valuable intervention for future academic success. This type of initial
research became the impetus for considering a mandatory tutoring strategy to be applied
to a Communication-121 writing course at a Southeastern Community College in
Pennsylvania.
Communications-121 (COM-121) was a first-year writing course required of all
community college students and considered one of the top 10 barrier courses. A
barrier/gateway course was identified as a course with success rates of below 70%
completion. COM-121 at the college was required of all incoming students and had a low
success rate of 62% in 2022. This meant that 38% of the students were required to repeat
and successfully complete the COM-121 course before moving on to other program
courses that required COM-121 as a pre-requisite. Students who failed their first attempt
at taking the COM-121 course needed to repeat the course two or three times before
successful completion. Failure to pass a first-year writing course was considered a
potential factor for detrimental impacts on retention, on-time graduation, and course
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success rates. Measuring improvements in these key performance indicators was part of
the college's five-year strategic goals and the justification for the study's focus.
Once a focus for the study was established, the following research questions were
established within a quantitative study. The questions helped to determine if a mandatory
tutoring requirement for first-year writing courses could have a positive impact on
student success rates and retention:
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term and
final grades?
2. Is there a significant difference in writing proficiencies, as measured by course
grades, between students who participate in mandatory tutoring and those who
participate in voluntary tutoring, embedded tutoring, or those who never access
tutoring services?
3. What is the relationship between at-risk students (first-generation, economically
disadvantaged, or ethnicity/race) and mandatory tutoring as measured by success
rates when enrolled in a first-year (barrier) writing course?
Additional planning for the study included the identification of the following specific
outcomes to be considered while answering the research questions:
1. To determine if the collected data supports the implementation of mandatory
tutoring for all or some students of the COM-121 writing course
2. To analyze various tutoring practices and their impact on the successful
completion of a barrier course based on mid-term and final grades
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3. To recommend the implementation of some variation of mandatory tutoring for
first-year writing students to increase student retention and on-time graduations
4. To determine if tutor relationships help students improve their self-efficacy as
they transfer acquired knowledge to future program courses
This chapter will use the results from the research questions and outcomes to draw
conclusions and suggest recommendations for using these results to further the discussion
on student retention and success rates in barrier courses at the college. It will also share
limitations to the study and how they impact the validity of the results.
Conclusions
Data was collected from a quasi-experimental study that included four sections of
Communications-121 (COM-121) from the spring 2024 semester and ex-post facto data
from three previous sections of COM-121 from the fall 2023 semester, which included an
embedded tutor. The data set included 144 students in seven sections of COM-121. There
were 44 students in two sections of mandatory tutoring, 35 students in two sections of
voluntary tutoring, and 65 students in three sections with an embedded tutor.
Research Question One: What is the impact of mandatory tutoring requirements for
increasing course success rates in a first-year (barrier) writing course as measured by
mid-term and final grades?
To answer this question, mid-term and final grades were evaluated to determine
the level of successful course completion that occurred by the end of the semester in each
of the three tutoring models. Successful course completion was measured by students
who achieved a final grade of A, B, or C. Withdraws and course grades of D and F were
not considered successful completions. Using this metric, it was determined that a
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THE IMPACT OF STUDENT SUCCESS RATES
mandatory tutoring requirement did not outperform the embedded tutoring model or the
voluntary tutoring model; in fact, mandatory tutoring sections by the end of the semester
had the lowest success rates of 50% compared to 62% for the embedded model, and 74%
for the voluntary tutoring model. The mid-term grades showed similar results, with
mandatory tutoring success rates of 57% compared to 65% for the embedded model and
80% for the voluntary tutoring model.
Based on this study, mandatory tutoring as an intervention did not increase the
course success rates of students in a first-year writing course; however, it is interesting to
note that mandatory and embedded turning rates both increased from mid-term grades to
final grades, while the voluntary tutoring model decreased. Mandatory tutoring also had
the most withdrawals by the end of the semester, with a 39% withdrawal rate compared
to 18% for the embedded mode and 19% for the voluntary model.
The study also compared mandatory tutoring models in final grades between
embedded models and mandatory versus voluntary models. The embedded model was
slightly higher than the mandatory model, with a mean score of 4.66 compared to a mean
score of 3.95 for mandatory tutoring. Additionally, a frequency comparison of grades
showed that embedded tutoring models had more students receiving an A or A- grade;
however, more students in the embedded model received final grades of F than those
students in mandatory tutoring models. Frequencies for student withdrawals were 18.5 %
for the embedded model compared to 38.6% for mandatory modules.
The mean final grades in voluntary tutoring models were also slightly higher
than in the mandatory model, with a mean score of 6.54 compared to 3.95 for
mandatory tutoring. Frequency grade comparisons showed that more students in the
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THE IMPACT OF STUDENT SUCCESS RATES
voluntary model scored an A or A- for final grades. Additionally, fewer F grades were
given to students in the voluntary model than in the mandatory model. Frequencies for
student withdrawals were 20 % for the voluntary model compared to 38.6% for
mandatory modules.
The triangulation of data points to address this research question indicated that the
voluntary tutoring model in this study was shown to be the most successful model for
increasing course success rates by the end of the semester. Mandatory tutoring was the
least effective model for increasing success rates; however, it also had the highest number
of student withdrawals. This variable will be discussed in more detail under the
limitations section of this chapter.
Research Question Two: Is there a significant difference in writing proficiencies, as
measured by course grades, between students who participate in mandatory tutoring
and those who participate in voluntary tutoring, embedded tutoring, or those who never
access tutoring services?
To answer this question, final grades were evaluated to determine the writing
proficiencies achieved by the end of the semester. This did not include individual essay
grades throughout the course. The question looked at the end results based on the applied
tutoring model of mandatory tutoring, embedded tutoring, or voluntary tutoring.
It is important to note that 36 of the 144 students who initially began their writing
course withdrew before the end of the course. Of the remaining 108 students, 85 reached
a level of writing proficiency to pass the course successfully. This included 28 grades of
C, 31 of B, and 26 of A. These final grades indicated that 78% of the students who
completed the course achieved an acceptable level of writing proficiency. Students who
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completed the mandatory tutoring model had 81% writing proficiency, while the
embedded model was 70%, and the voluntary model was 93%.
This research question addressed the writing proficiencies of students who
remained in the course for the entire semester and received course grades of A, B, C, D,
or F. It does not address success rates that included students who withdrew from the
course and impacted the course completion statistics. Based on this metric, This research
question addressed the writing proficiencies of students who remained in the course for
the entire semester and received course grades of A, B, C, D, or F. This starkly contrasted
the success rates for mandatory tutoring at 50% versus the voluntary model at 74% when
withdrawals are included. Students who remained in the course had a 70-plus percent
chance of meeting a successful writing proficiency level, which will also ensure
successful completion of the Communication-121 barrier course for first-year writing.
ANOVA testing used to help answer this question included all final grades and
indicated that there is a statistically significant difference between the mandatory model
and embedded as measured by final grades. However, there was no statistically
significant difference between the mandatory and voluntary models as measured by the
final grade.
The paired T-test data showed the paired sample T-test between the mandatory
tutoring model and voluntary tutoring model as measured by the final grade was ((t (34)
=-2.205), P=0.034). Since the P-value was less than an alpha value of 0.05
(P=0.034<0.05), it implied that the mean difference in writing proficiencies between
students who participated in the mandatory tutoring model and voluntary tutoring model
as measured by final grade is statistically significant. The paired sample T-test between
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THE IMPACT OF STUDENT SUCCESS RATES
the mandatory tutoring model and embedded tutoring model as measured by the final
grade was (t (43) =-0.409), P=0.684). Since the P-value was more than an alpha value of
0.05 (P=0.684>0.05), it implied that the mean difference in writing proficiencies
between students who participated in the mandatory and embedded tutoring models as
measured by final grade was not statistically significant. Overall, the paired sample t-test
shows there was a significant difference between the mandatory and voluntary models,
while there was no statistically significant difference between the mandatory and
embedded models as measured by mid-term and final grades.
Similar to the course success rate data, the voluntary tutoring approach performed
the best, followed by mandatory tutoring and embedded tutoring. The one notable
difference was that the mandatory tutoring model was shown to be the second-best
indicator for writing proficiency for students who completed the course.
Research Question Three: What is the relationship between at-risk students (firstgeneration, economically disadvantaged, or ethnicity/race) and mandatory tutoring
as measured by success rates when enrolled in a first-year (barrier) writing course?
This research question concerned the correlations of demographic data and the
impact of a mandatory tutoring model for the Communication-121 barrier course for
writing. This was particularly interesting to the college due to its designation as a
Hispanic Serving Institute (HIS) and a community college with large populations of
first-generation and economically disadvantaged students who received Pell Grants.
Pearson Chi-square tests were used to show whether variables are associated, and
regressions measured the degree of relationship between variables.
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THE IMPACT OF STUDENT SUCCESS RATES
The Pearson Chi-Square test between first-generation status and mandatory
tutoring as measured by course success rate was 𝜒 (1) = 0.027, 𝑝 = 0.870. Since the Pvalue was more than the alpha value of 0.05 (p=0.870>0.05), there was no statistically
significant association between first-generation status and mandatory tutoring, as
depicted by the success rate. The correlation between first-generation status and
mandatory tutoring as measured by success rate was 0.025 (R=0.025). This implied a
positive relationship existed between first-generation status and mandatory tutoring as
measured by course success rates; however, the degree of relationship was very low.
The Pearson Chi-Square test between Pell Grant status and mandatory tutoring as
measured by success rate was 𝜒(1) = 0.052, 𝑝 = 0.820. Since the P-value was more
than the alpha value of 0.05 (p=0.820>0.05), there was no statistically significant
association between Pell status and mandatory tutoring as measured by success rate. The
correlation between Pell Grant status and mandatory tutoring, measured by course
success rate, was 0.034 (R=0.034). This implied that there is a positive relationship
between Pell Grant status and mandatory tutoring as measured by course success rates;
however, the degree of relationship was very low.
The Pearson Chi-Square test between ethnicity/race and mandatory tutoring as
measured by course success rate was 𝜒 (3) = 3.650, 𝑝 = 0.302. Since the P-value was
more than the alpha value of 0.05 (p=0.302>0.05), there was no statistically significant
association between ethnicity/race and mandatory tutoring as measured by success rate.
The correlation between ethnicity/race and mandatory tutoring as measured by success
rate was 0.144 (R=0.144). This implies that there was a positive relationship between
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THE IMPACT OF STUDENT SUCCESS RATES
ethnicity/race and mandatory tutoring as measured by success rate. However, the degree
of relationship was very low.
Overall, Chi-Square Tests have shown no association between at-risk students
(First-generation status, Pell Grant status, and ethnicity) and mandatory tutoring as
measured by success rate. However, Regression analysis has shown that there is a
positive relationship between at-risk students and mandatory tutoring as measured by
success rate. Although the degree of relationship was very low, a larger sample size could
address this at-risk factor as a future area of interest.
Future Application and Financial Implications of Study Results
This study considered implementing a mandatory tutoring requirement as an
intervention for the Communication-121 (COM-121) barrier courses for first-year writing
students. This strategy was designed to increase retention through course success rates
and to improve writing proficiencies. Data was collected from three types of tutoring
models: mandatory, embedded, and voluntary. Results showed that the mandatory
tutoring model was the least effective in this study; however, the results will be used to
continue discussions and intervention strategies that involve tutoring models and help
inform the Director of Tutoring Services at the college. The college used Title V grant
funding for many of the tutoring initiatives at the college, including the use of funds for
embedded tutoring in barrier courses across multiple disciplines.
The results will be used to recognize the impact of student withdrawals (W) on
their ability to complete a course successfully. This study focused on an intervention to
help students academically succeed by the end of the semester through tutoring options;
however, the study showed that tutoring in any form could not impact students who
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THE IMPACT OF STUDENT SUCCESS RATES
withdrew from the course before its completion. This suggested that more conversations
are needed to consider interventions that can prevent students from withdrawing from a
barrier course. Currently, the reasons for a student’s decision to withdraw from a course
are not tracked and shared with faculty members. Finding ways to mitigate the number of
withdrawals before the student self-initiates a course drop could significantly increase
success rates and retention factors. Preventing a withdrawal could give interventions like
tutoring a better chance of positively impacting course success rates, student retention,
and writing proficiencies.
The tutoring intervention that this study considered could have significant
financial implications if put into practice as a mandatory option. The primary budget
costs for implementing a mandatory tutoring requirement for all COM-121 students
would require hiring up to seven part-time tutors designated to service all COM-121
students in every section and form of modality, including face-to-face, remote, and online
offerings. The quasi-experimental model used in this study was based on each COM121 student receiving a minimum of five 30-minute tutoring sessions per semester. The
fall and spring semesters averaged about 600 enrolled students, and the summer term
serviced approximately 200 students for an estimated implementation cost of
approximately $50,000.00. This cost was based on a tutor's salary of $25.00 per hour,
including 2.5 tutoring hours per student or a student cost of $62.50 per semester.
Limitations
This action research project was limited by several factors that may have
impacted the overall results. The first limitation involved the study's sample size,
which was limited to seven sections across two semesters. 144 students registered for
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Communications-121 (COM-121) sections without any knowledge of the type of
tutoring used in the course. Sections were randomly selected based on one faculty
member’s course load from the spring semesters of 2024. Based on the random
enrollment of the courses, there was no guarantee that all of the at-risk and ethnic
groups to be included in the study would be represented.
The study was also limited by the data points analyzed to determine the results of
each research question. Only mid-term and final grades were collected; however, these
grades represent all assessments throughout the course, not just each of the three required
writing assignments in a COM-121 course. This worked well for the course success rate
data but was not as useful in determining if writing proficiencies increased throughout the
semester. Using grades from the three required writing assignments and their rough drafts
may have provided more valid data for the results in this area.
One final limitation that emerged when analyzing the data was the number of
student withdrawals from each section of the study. The college was required to report
students who withdrew from a course as having failed to complete it. This similarly
affects students who remain in the course and receive a grade less than C as a final grade.
Course success rates measure the number of students who finished the course with grades
of an A, B, or C. Students who withdrew from a course or had a final grade of D or F
counted against a faculty member’s course success rate data for each section taught.
Students may have withdrawn from courses for various reasons, but that data was not
collected in this study. Contributing factors may have been conflicts due to family
emergencies, financial issues, work conflicts, or other life-related issues. This unknown
variable may have helped to understand why there was such a large number of
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withdrawals from the mandatory sections and if the mandatory requirement played a role
in the student’s decision to withdraw.
Table 20 shows the significant difference in course success rates when the
withdraw (w) grades are removed from the results. The mandatory tutoring model, minus
withdraws, showed success rates of 81%, which outperformed the embedded model by
11%. The voluntary tutoring model was still the best tutoring model at 93%. The
implications of these results showed that more attention needs to be focused on
preventing student withdrawals from happening in the first place. The baseline for course
success rates in this study was 62% for all sections of COM-121 taught during the 202223 semesters. With withdrawals included in the success rate formula for this 2023-24
study, the mandatory and embedded models fell below 62%, and the voluntary model
exceeded the baseline by 12%. When withdrawals were not a determining factor for
course success rates, all three models showed scores above 62%. Once again, the
voluntary model was the best-performing model, with embedded tutoring being the
lowest-performing model.
Table 20
Success Rates Including and Excluding Withdraws
Model
N Count
Success
Rates
A, B, & C
Grades
Completed
D, F
Grades
Withdraws
Before
Completion
Success
Rates with
Withdraws
Success
Rates
Without
Withdraws
Mandatory
Voluntary
Embedded
44
35
65
50%
74%
57%
11%
7%
25%
39%
19%
18%
50%
74%
57%
81%
93%
70%
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THE IMPACT OF STUDENT SUCCESS RATES
Recommendations for Future Research
This study did not produce results that suggested implementing a mandatory
tutoring model for all students; however, this study, combined with information obtained
through the literature review, did support tutoring as an intervention to increase course
success rates, retention, and writing proficiencies. Future research may be needed to
expand upon the very low (but important) relationships that were found between at-risk
students and mandatory tutoring. The new research may need to move from a quantitative
study to a mixed-method design that could capture student and faculty data to better
understand why different tutoring models produce different student outcomes and why
students withdrew from the Communictions-121 (COM-121) barrier course. Other
considerations should be addressed, such as the COM-121 curriculum and the
consistency of course delivery based on individual teaching styles and levels of student
engagement.
Further consideration should also be centered on finding solutions to mitigate the
number of students withdrawing from a course before its completion. Tutoring was the
predominant form of academic support available to students on campus, but according to
the Director of Tutoring Services, the number of students who took advantage of this help
is limited. Only about 11% of the enrolled students took advantage of the free services
from the tutoring center. New or future interventions could include a tutoring variable to
be implemented for any student who shows early signs of struggles that could lead to a
student withdrawal if not addressed. This could include a tiered intervention system, such
as any student who falls below a C average must attend tutoring sessions until their grade
improves, or a student with a failing mid-term grade must attend tutoring sessions until
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THE IMPACT OF STUDENT SUCCESS RATES
their grade increases by a defined percent. This would allow a differentiated approach to
tutoring that would address the most vulnerable students in jeopardy of failing.
The embedded tutoring model, which was the second most effective tutoring
strategy, should also be evaluated to consider ways to make the embedded model have a
mandatory component based on the tiered intervention system. Embedded tutors at the
college were able to access student grades, monitor progress, and review late assignment
to reach out to students proactively. They were also present in the classroom as a student
resource during instruction and when students were given in-class time for writing. The
embedded tutors emailed students to encourage them to make appointments and were
available before and after class for questions; however, the current model did not require
students to use the embedded tutor as a resource. The embedded model could be modified
to force an intervention at designated time frames or specified grade ranges. Embedded
tutoring may be the best proactive model to help prevent a student from withdrawing,
especially if writing is not a strength for the student or if they have low self-confidence or
self-efficacy for seeking help. Embedded tutors were limited in the number of COM-121
sections assigned to them; however, using embedded tutors in all sections of COM-121
may need to be considered.
Finally, future studies on tutoring interventions should consider the quantitative
data collected from student surveys during the quasi-experimental component of this
study. That data showed that students who used tutoring as a resource overwhelmingly
believed that it helped their writing and that they would recommend tutoring to other
students. They also stated that they believed tutoring improved the quality of their
writing, and they would be inclined to use tutoring for future courses. This information
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THE IMPACT OF STUDENT SUCCESS RATES
showed that tutoring is making a difference for the students who accessed the free
services available to them at the college. This data suggested that ongoing reflection and
modifications to those services should remain a strong focus for the future.
Summary
This chapter has been a reflective process in determining the conclusions that can
be drawn from a qualitative action research study that focused on using a mandatory
tutoring requirement for first-year writing students. Communications-121 (COM-121)
was a required writing course for all students at a two-year community college in
Southeastern Pennsylvania, and passing with a C or better grade was necessary to
continue taking courses that required COM-121 as a pre-requisite. The journey in the
development of this study began with a basic needs assessment that isolated a problem
area at the college. The needs assessment determined that 38% of all students taking
COM-121, a top-ten barrier course for the college, failed to pass the course on their first
attempt. A tutoring intervention to help increase course success rates, retention, and
writing proficiencies for students was considered and implemented in a quasiexperimental study for the spring 2024 semester.
An initial review of existing research revealed several key factors that became the
focus of the action research and included 1) tutoring was shown to have positive impacts
on student success, 2) students often did not access tutoring due to fear of showing
weakness, 3) students lacked self-efficacy to help themselves, 4) students who failed
barrier courses lead to retention issues, and 5) community colleges had unique challenges
for educating students due to open-access practices.
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THE IMPACT OF STUDENT SUCCESS RATES
All of these key factors suggested a framework based on Tinto (1975) and his
seminal research in retention. Tinto (2017) was a strong voice in the area of persistence
with his assertion that “…student retention has been shaped by theories that view student
retention through the lens of institutional action and ask what institutions can do to retain
their students. Students, however, do not seek to be retained. They seek to persist” (p.
254). This action research study was built on Tinto’s belief that there needed to be strong
institutional support for students to improve their self-efficacy, to belong to a community,
and to have supportive resources for helping students. All of these conditions were met
within this study.
The conclusions of this particular study did not support the premise that a
mandatory tutoring component would be the best intervention to apply for increasing
course success rates, student retention, or writing proficiencies; however, limitations to
the study may have influenced the outcomes of the results, particularly because of the
impact from student withdraws. A student’s reason for a course withdrawal may range
from personal issues to a fear of writing or because the section has a mandatory tutoring
requirement. However, when withdrawals were removed from the data, the mandatory
turning model showed an 81% course success rate but was still second to the voluntary
tutoring model with a 93% course success rate. Embedded models were 70%.
The data obtained through the student exit surveys from the quasi-experimental
study were telling. Tutoring positively impacted students who chose to use the resources
provided by the college. They were building sustainable relationships with a professional
staff member that helped them to grow self-efficacy skills and to transfer the knowledge
they received to other courses throughout their college career. The students recognized
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THE IMPACT OF STUDENT SUCCESS RATES
the positive benefits of using the college’s tutoring services, and they overwhelmingly
said they would use tutoring again in other courses and would recommend tutoring to
their classmates. Whatever model is used, the tutoring process can change a student’s
academic trajectory, contribute strongly to a student’s academic proficiency, and
contribute to positive retention practices that will help ensure increased course success
rates, retention, writing proficiencies, and on-time graduation at the community college
level.
Finally, this action research study has helped this researcher, who is new to the
community college environment, gain tremendous respect for the role community
colleges play in the education and advancement of students in Pennsylvania. Community
colleges and their use of open access for all students have required them to be strong
community partners with the flexibility and autonomy to create programs and technical
training that meet the needs of all community members. The community college used in
this study embraced four hallmarks at the core of a comprehensive community college:
hope, access, opportunity, and excellence. Responding to the needs of students and the
community was at the cornerstone of this action research study, and the data collected
will help to ensure that the philosophy represented by the four hallmarks will continue
through the use of the systematic process of action research and the repeating cycles of
reflection, action, and evaluation.
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APPENDICES
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Appendix A
Student Survey: Control Group
119
THE IMPACT OF STUDENT SUCCESS RATES
Appendix B
Student Survey: Experimental Group
120
THE IMPACT OF STUDENT SUCCESS RATES
121
THE IMPACT OF STUDENT SUCCESS RATES
Appendix C
IRB Approval Letter – Pennsylvania Western University
122
THE IMPACT OF STUDENT SUCCESS RATES
Appendix D
Confirmation Email for the Addition of Two Student Surveys
123
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Appendix E
Permission Letter Reading Area Community College
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to a First-Semester Barrier Course in Writing at a Two-Year Community College.
A Doctoral Capstone Project
Submitted to the School of Graduate Studies and Research
Department of Education
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Education
Brian T. Schell
Pennsylvania Western University
August 2024
ii
THE IMPACT OF STUDENT SUCCESS RATES
@Copyright by
Brian T. Schell
All Rights Reserved
August 2024
iii
THE IMPACT OF STUDENT SUCCESS RATES
Pennsylvania Western University
School of Graduate Studies and Research
Department of Education
We hereby approve the capstone of
Brian T. Schell
Candidate for the Degree of Doctor of Education
iv
THE IMPACT OF STUDENT SUCCESS RATES
Dedication
I dedicate this work to my friend and mentor, Dr. Kenneth Klawitter. His
leadership style, ethics, values, and determination to best serve all stakeholders have
influenced me in more ways than I can express. He taught me the value of using the
concept of “goodness of fit” and the importance of being a leader who inspires the people
under them to grow to their fullest potential without seeking personal recognition. His
impact on countless others will transcend time and may never be fully realized. I am truly
a better person and a better educational leader because of Dr. Klawitter.
I also dedicate this to my mother for all the love and support she has provided me
throughout my life through the personal and professional pathways I have undertaken.
She was a Sunday school teacher for over forty years and taught me my first lessons in
religion and my first lessons on playing the piano. She was a natural teacher and
inspiration for the life I pursued.
Finally, I give all glory to God for His grace and for giving me the strength and
wisdom to follow my dreams and the plans He had for my life.
v
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Acknowledgments
I would like to thank Dr. John F. Ziegler, Doctoral Capstone Faculty Chair, and
Dr. Stacia Viscarda, Doctoral Capstone External Committee Member, for their help,
guidance, and constant encouragement and support while writing this work.
My thanks are also extended to the people at my research site who have supported
me throughout this process, including Cynthia Seaman, Provost; Kevin Coots, Associate
Provost; David Sweely, Dean of Assessment; Megan King, Director of Tutoring, and
Teresa Magdalia for her participation in the quasi-experimental project.
vi
THE IMPACT OF STUDENT SUCCESS RATES
Table of Contents
Dedication
iv
Acknowledgments
v
List of Tables
x
List of Figures
xii
Abstract
xiii
CHAPTER I. Introduction
1
Background
2
Capstone Focus
4
Research Questions
5
Expected Outcomes
6
Financial Implications
6
Summary
7
CHAPTER II. Literature Review
8
Community College Perspectives
10
Historical Development
10
Community College Data and Statistics
14
Unique Challenges Compared to Four-Year Institutions
15
Open Access/Enrollment
15
Housing Versus Commuting
16
Part-time versus Full-time Enrollment & Unique Demographics
17
Conceptual Frameworks
17
Predominate Themes Based on the Frameworks
20
vii
THE IMPACT OF STUDENT SUCCESS RATES
Retention/Persistence
20
At-risk Students
21
Self-Efficacy
23
Learning Transfer: Identical Elements
23
Gateway or Barrier Courses
25
Tutoring-Related Discourse
26
Definitions
Tutoring Models
26
28
Tutoring and Writing Centers
28
Embedded Tutoring
31
Mandatory Versus Voluntary Tutoring
32
Summary
35
CHAPTER III. Methodology
38
Purpose
40
Desired Outcomes
41
Research Questions
42
Setting and Participants
42
School Location
42
School Demographics
43
Participants
46
Research Plan
Plan/Intervention
Research Alignment to Intervention
47
47
50
viii
THE IMPACT OF STUDENT SUCCESS RATES
Fiscal Implications
52
Research Methods and Data Collection
52
Research Design
52
Data Collection Method and Timeline
53
IRB Approvals
55
Fiscal Implications to Research Method and Data Collection
55
Validity
56
Validity Types and Methods
56
Triangulation of Data
57
Summary
58
CHAPTER IV. Data Analysis and Results
60
Data Analysis
62
Results
63
Research Question One
63
Research Question Two
72
Research Question Three
78
Student Survey Data Results
83
Discussion
87
Summary
90
CHAPTER V. Conclusions and Recommendation
91
Conclusions
93
Research Question One
93
Research Question Two
95
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Research Question Three
97
Future Application and Financial Implications of Study Results
99
Limitations
100
Recommendations for Future Research
103
Summary
105
References
108
APPENDICES
117
APPENDIX A. Student Survey: Control Group
118
APPENDIX B. Student Survey: Experimental Group
119
APPENDIX C. IRB Approval Letter – Pennsylvania Western University
121
APPENDIX D. Confirmation Email for the Addition of Two Student Surveys
122
APPENDIX E. Permission Letter Reading Area Community College
123
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List of Tables
Table 1. Fall 2022 Student Body by Racial or Ethnic Group
Table 2. Fall 2022 Full-Time Student Body by Racial or Ethnic Group and Pell Recipient
Table 3. Comparison Between Mandatory and Voluntary Models as Measured by Final
Grades
Table 4. Frequency Comparison Between the Mandatory Model and Voluntary Model as
Measured by Final Grades
Table 5. Descriptive Statistics Comparison Between the Mandatory and Embedded
Model as Measured by Final Grades
Table 6. Frequency Comparison Between Mandatory Model and Embedded Model as
Measured by Final Grades
Table 7. ANOVA Between Mandatory and Voluntary Tutoring as Measured by Mid-term
Grades
Table 8. ANOVA Between Mandatory and Embedded Tutoring as Measured by Mid-term
Grades
Table 9. ANOVA Between Mandatory and Voluntary Tutoring as Measured by Final
Grades
Table 10. ANOVA Between Mandatory and Embedded Tutoring as Measured by Final
Grades
Table 11. Paired Sample T-test Between Mandatory and Voluntary Tutoring Models as
Measured by Mid-term Grades
Table 12. Paired Sample T-test Between Mandatory and Embedded Tutoring Model as
Measured by Mid-term Grades
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Table 13. Paired Sample T-test Between Mandatory and Voluntary Tutoring as Measured
by Final Grades
Table 14. Paired Sample T-test Between Mandatory and Embedded Tutoring as Measured
by Final Grades
Table 15. Chi-square Test Between First-generation Status and Mandatory Tutoring as
Measured by Success Rates
Table 16. Chi-square Test Between Pell-grant Status and Mandatory Tutoring as
Measured by Success Rate
Table 17. Chi-square Test Between Ethnicity/race and Mandatory Tutoring as Measured
by Success Rate
Table 18. Regression Between First-generation Status and Mandatory Tutoring as
Measured by Success Rate
Table 19. Regression Between Pell Status and Mandatory Tutoring as Measured by
Success Rate
Table 20. Success Rates Minus Withdraws
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THE IMPACT OF STUDENT SUCCESS RATES
List of Figures
Figure 1. Share of Enrollment by Pell Grants
Figure 2. Success Rates by Pell Status
Figure 3. Success Rates by Select Race/Ethnicity
Figure 4. Success Gaps Compared to White Students
Figure 5. Grading Policy for Mandatory Tutoring Sections
Figure 6. Alignment of Research Questions, Data Collection, Data Sources,
and Timelines.
Figure 7. Mid-term Grades: All Tutoring Models
Figure 8. Mid-term Grades: Mandatory Tutoring Model
Figure 9. Mid-term grades: Voluntary Tutoring Model
Figure 10. Mid-term grades: Embedded Tutoring Model
Figure 11. Final Grades: All Tutoring Models
Figure 12. Final Grades: Mandatory Tutoring Model
Figure 13. Final Grades: Voluntary Tutoring Model
Figure 14. Final Grades: Embedded Tutoring Model
Figure 15. Survey Results: Mandatory Tutoring Question One
Figure 16. Survey Results: Mandatory Tutoring Question Two
Figure 17. Survey Results: Mandatory Tutoring Question Three
Figure 18. Survey Results: Mandatory Tutoring Question Four
Figure 19. Survey Results: Voluntary Tutoring Sections Question One
Figure 20. Success Rates Including and Excluding Withdraws
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THE IMPACT OF STUDENT SUCCESS RATES
Abstract
Community colleges face unique challenges in educating students due to their openaccess policies and the need to retain students through successful completion of courses,
especially those identified as barrier courses. This study examined the impact of applying
a mandatory tutoring requirement in a first-year writing course to increase course success
rates and writing proficiencies. A Communications-121 writing course taught at a
community college in Southeastern Pennsylvania was identified as one of the top 10
barrier courses with a low course success rate of 62%. In order to address this issue, a
quasi-experimental study was designed to examine the impact of three different tutoring
models on course success rates: mandatory, embedded, and voluntary. The study also
explored the relationship between at-risk student populations (first-generation, ethnicity,
and Pell Grant recipients) and the various tutoring models. The mandatory tutoring
intervention used in this quantitative study was not shown to be the best model; however,
there was a positive relationship between at-risk students and the mandatory tutoring
model. Exit surveys also showed that a majority of students who used tutoring services
reported that they would use a tutor in future courses and would recommend tutoring to
their classmates.
Keywords: tutoring, mandatory tutoring, barrier courses, first-year writing
courses, retention, success rates
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THE IMPACT OF STUDENT SUCCESS RATES
CHAPTER I
Introduction
A persistent issue facing a two-year community college in Southeastern
Pennsylvania is that many first-year writing students are not utilizing the professional
tutoring services available to them in the Academic Learning Commons to improve their
writing proficiencies; in fact, the Director of Tutoring services for the college reported
that only 11% of the student population sought the assistance of a tutor in 2022-23.
Mattison (2012) suggested that educators needed to make instructional support programs
available through a wide range of offerings that could help to close achievement gaps.
This would include resources such as writing centers and professional tutors. There is a
need to increase the number of students who utilize the services of a professional writing
tutor, especially at-risk students such as first-generation students and economically
disadvantaged students. Writing centers and the use of tutoring to improve students’
literacy skills historically developed to accommodate low-skilled writers, especially
veterans, underprepared students, and minorities in need of improving the skill sets that
would allow them to successfully meet the challenges of higher education (Ball, 2014;
Missakian et al., 2016; Ugo, 2010).
Additionally, the college is a designated Hispanic Severing Institute (HSI) with a
population of over 40% Hispanic students. These students can also be first-generation
and economically disadvantaged students who would benefit from more individualized
tutoring support. In a study of academic supports within community colleges, Hendriksen
et al. (2005) found that tutored students had a 2.78 average grade point average (GPA)
compared with a 2.64 GPA for non-tutored students. Overall, tutored students had a 75%
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THE IMPACT OF STUDENT SUCCESS RATES
pass rate versus a 71% pass rate for non-tutored students. Any student at that college who
is unsuccessful in passing a reading and/or writing placement examination must enroll in
developmental courses until written communication skills are improved. The college’s
developmental courses receive college credit but do not count towards graduation
requirements and can often impact retention and on-time graduation rates. A study by
Rheinheimer et al. (2010) showed that tutoring was an overwhelmingly positive predictor
of persistence, retention, and degree completion for at-risk students and claimed that
tutoring was a valuable intervention for future academic success.
Background
The literature review for this capstone project formed the basis for the
development of this study and the connections to relevant frameworks that supported the
premise centered on the use of a mandatory tutoring model in a barrier/gateway course
for writing. This study considered the course success rates of students in first-year writing
courses when a mandatory, voluntary, or embedded tutoring model was applied. Several
key factors have been associated with analyzing the data in this study based on the
project topic and the unique environmental stressors and demographics associated with a
community college experience.
Communications-121 (COM-121) is a first-year writing course required of all
community college students and is considered one of the college’s top 10 barrier courses.
Student success rates below 70% in course completion constitute a barrier course. In
2022, the course success rates at the community college in Southeastern Pennsylvania
were 62% for all COM-121 courses. This meant that 38% of the students had to repeat
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THE IMPACT OF STUDENT SUCCESS RATES
and successfully complete the COM-121 course before moving on to other program
courses that often require COM-121 as a pre-requisite.
Many students fail in their first attempt at taking the COM-121 course and must
repeat the course two or three times before successful completion. Failure to pass a firstyear writing course may have detrimental impacts on retention and on-time graduation
rates, which are key performance indicators in the college’s five-year Strategic Goals.
Tinto (1999) argued that students need to be grounded in a learning environment that
promotes students as valued members of the institution. This is accomplished by having
supportive institutional mechanisms to encourage intentional contact with faculty, staff,
and other students to increase retention and student persistence.
One of the most prevalent challenges that community colleges face in increasing
student retention and persistence comes through their use of open-access enrollment.
Raby (2020) referred to open access as “A foundational philosophy of the community
college” (p. 41). This embedded philosophy is a cornerstone principle for all community
colleges charged to make education available to all students and to ensure no individual
will ever be denied access to education due to a selective admissions process.
Four-year college students can live on campus, which has clear advantages that
can help with retention and a sense of belonging that many community college students
cannot realize. Housing options can give students a sense of safety and support in a firstyear experience, the ability to bond with a potential roommate, and access to activities
and gatherings that encourage student connections with the campus (Chen, 2022).
Housing is not an option for most community colleges, so other types of campus
strategies must be developed to compensate for the deficit caused by a student's need to
4
THE IMPACT OF STUDENT SUCCESS RATES
commute to the campus. One of these strategies is building relationships through
available student services; however, many first-year students at a community college do
not pursue them. Tutoring and writing center participation are two services available at
most higher education institutes that can help bridge the gap towards positive retention
and course completion, especially with barrier courses.
According to Phillippe (2023) from The American Association of Community
Colleges, part-time students outnumber full-time students by nearly 2 to 1. 66% of
students attended part-time while only 34% attended as full-time students. This also
included 30% of first-generation students, 16% of single parents, and a population of
35% of students between the ages of 22 and 39. These variables greatly impact
community colleges that are held to a high standard for reporting data to the Integrated
Postsecondary Education Data System (IPEDS). This system requires community
colleges to report graduation rates for first-time, full-time students who successfully
complete their degrees after three years. This is a very high bar to meet, given the unique
circumstances of community college students. Building relationships through campus
initiatives such as tutoring and writing centers can help close the retention and graduation
gaps and greatly impact first-year students' retention and persistence toward graduation.
Capstone Focus
The inherent problem for walk-in writing centers and tutoring labs is that they
assume struggling students will access the services that professional tutors can provide to
them; however, at-risk and struggling students often fail to consider this resource as a
means of improving the writing skills needed in all of their course work. Rheinheimer et
al. (2010) argued that at-risk students tend to avoid social resources like writing centers
5
THE IMPACT OF STUDENT SUCCESS RATES
or professional tutors for help. These students may have educational backgrounds lacking
the skills needed to improve academic achievement and are reluctant to reach beyond
their comfort zones.
This research will focus on institutional ex-post facto (archival) data from past
semesters and data from a quasi-experimental project consisting of two sections of
Communications-121 (COM-121), a first-year writing course. Two sections of COM121 will function as the experimental group. They will be exposed to an independent
variable of a mandatory tutoring requirement, and two sections of COM-121 will
function as the control group without being exposed to the independent variable. This
experimental group will be analyzed and compared to the control group and ex-post
facto data, including past sections of COM-121 that utilized an embedded tutor.
Research Questions
This research study will be used to determine if significant differences in course
success rates can be realized when a mandatory tutoring requirement is included for firstyear students in a Communications-121 writing course at a two-year community college
in Southeastern Pennsylvania. Mid-term and final grades will be measured within a
quantitative study to determine course success rates with a sample group consisting of
students who participated in mandatory tutoring, students who participated in voluntary
or no tutoring, and students who had access to an embedded tutor as a viable but
voluntary resource. The study asks the following questions:
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term and
final grades?
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THE IMPACT OF STUDENT SUCCESS RATES
2. Is there a significant difference in writing proficiencies, as measured by course
grades, between students who participate in mandatory tutoring and those who
participate in voluntary tutoring, embedded tutoring, or those who never access
tutoring services?
3. What is the relationship between at-risk students (first-generation, economically
disadvantaged, or ethnicity/race) and mandatory tutoring as measured by success
rates when enrolled in a first-year (barrier) writing course?
Expected Outcomes
This action research study is intended to determine if mandatory tutoring can
increase course success rates of a first-year Communications-121 (COM-121) writing
course required of all degree-seeking students enrolled at a two-year community college.
Specific outcomes will include:
1. To determine if the collected data supports the implementation of mandatory
tutoring for all or some students of the COM-121 writing course
2. To analyze various tutoring practices and their impact on the successful
completion of a barrier course based on mid-term and final grades
3. To recommend the implementation of some variation of mandatory tutoring for
first-year writing students to increase student retention and on-time graduations
4. To determine if tutor relationships help students improve their self-efficacy as they
transfer acquired knowledge to future program courses
Financial Implications
The primary budget considerations for implementing a mandatory tutoring
requirement for all Communications-121 (COM-121) students would require hiring up to
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THE IMPACT OF STUDENT SUCCESS RATES
seven part-time tutors designated to service all COM-121 students in every section and
form of modality, including face-to-face, remote, and online offerings. The quasiexperimental model used in this study is based on each COM-121 student receiving a
minimum of five 30-minute tutoring sessions per semester. The fall and spring
semesters average about 600 enrolled students, and the summer term services
approximately 200 students for an estimated implementation cost of approximately
$50,000.00. This cost is based on a tutor's salary of $25.00 per hour, including 2.5
tutoring hours per student or a cost of $62.50 per student.
Summary
Many students fail the Communication-121 (COM-121) course on their first
attempt and must repeat it two or three times before successful completion. Passing
COM-121 is essential for enrollment in future courses requiring the course as a
prerequisite for completing a degree or certificate. COM-121 is a barrier course that can
impede a student’s ability to complete a degree and graduate within a three-year time
period.
The current three-year graduation rate for first-time/full-time (FTFT) students at
the community college is 25%. Finding positive interventions, such as mandatory
tutoring, may offer one way to get more students to complete their degrees on time. This
study will explore potential interventions and strategies to increase the number of
successful course completions for the COM-121 barrier course and to increase semesterto-semester retention and on-time graduation rates.
8
THE IMPACT OF STUDENT SUCCESS RATES
CHAPTER II
Literature Review
Community colleges throughout the country share many common factors that
contribute to the successful completion rates of degree-seeking individuals. The unique
demographic composite of community college students, combined with an open-access
policy, presents numerous challenges in achieving successful on-time graduation rates
and overall student retention. According to Mullin (2017), an open-access policy allows
anyone in the community to enroll as opposed to a selective admission process used by
most 4-year institutes of higher education. Community colleges must embrace multiple
approaches to breaking down the barriers that can keep students from conferring a degree
that could potentially be a life-altering milestone for them.
One strategy to address student persistence and retention can be realized through
tutoring services available to students at a particular institution. Numerous models for
how and when to provide or require tutoring for students are addressed by student writing
and learning centers throughout the country. Finding the appropriate model to implement
at the community college level has multiple variables that must be considered. One of the
most prevalent variables contributing to student resistance to tutoring comes with the
additional out-of-class time that may be required. Students who have daily commutes to
the campus and are time-bound by family or job responsibilities may find the additional
time to be intrusive.
The approach to tutoring in higher education can vary greatly due to the
institution's specific requirements. Research and data related to tutoring models and their
use are not reporting categories within the Integrated Postsecondary Educational Data
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THE IMPACT OF STUDENT SUCCESS RATES
System (IPEDS) or the National Postsecondary Education Cooperative (NPEC);
however, extensive research and data are available relating to tutoring models and
structures for K -12 systems, especially in the post-covid era. This data provides an
essential context for this study because of the close relationship between high schoolaged students and freshman college students. The habits and mental models these high
school students bring with them to college concerning tutoring can dramatically impact
their willingness to embrace tutoring opportunities in a post-secondary environment.
Fong (2021) from the Institute of Educational Sciences reviewed important
information concerning the need for high-quality tutoring in a post-pandemic climate
within K-12 school systems. This model requires tutoring at school and during normal
school hours of three or more 30-minute sessions. These sessions should be staffed with
teachers of professional tutors who are well-trained beyond the scope of peer tutors,
volunteers, or parents (Fong, 2021; Sparks, 2023). Sparks (2023) further provided current
data that showed 40% of school leaders claimed that high-dosage or high-quality tutoring
had increased from 2021 to 2022, with an estimated 30% of students getting intensive
tutoring. 43% of high-poverty and high-minority schools provided this type of tutoring
versus only a 33% of more affluent schools or those serving fewer than 75% of minorities
or students of color.
Community Colleges are often a bridge for many students between high school
and their first higher education experience, but the environments are clearly different and
need to be given additional consideration due to the unique variables that influence all
aspects of the higher education experience. To better understand the relationship between
tutoring and the environments, it is important to have a context for understanding the role
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THE IMPACT OF STUDENT SUCCESS RATES
community colleges have played in the educational system from a historical and local
perspective.
Community Colleges Perspectives
Historical Development
National. The existence of the community college can be traced back to the
Morrill Act of 1862. Originally referenced as junior colleges or two-year colleges, the
Land Grant Act sought to expand access to public higher education by creating pathways
for individuals to attend college who had been formally denied access to higher education
for multiple reasons. A second Morrill Act of 1890 sought to withhold federal funding
from any land grant institution that restricted admission based on race unless a state
allowed minorities to attend a separate and established institute of higher learning. Under
the Morrill Act provisions, the first junior college in America was championed in 1901 by
William Raineu Harper, President of the University of Chicago (Drury, 2003; Goudas,
2020; Mello, 2000).
According to Jurgens (2010), a prevailing attitude in the mid-eighteen hundreds
was underway to create a junior college system that would relieve universities of the
responsibilities of providing general education to qualified high school graduates. Lowerdivision foundational education was considered to be a burden to the universities and
could impede the university’s true mission because they “believed that universities could
not successfully reach their true research maturity and remain exclusive developers of
higher education if they continued to be responsible for providing education to their
students” (p. 252). Teaching general education courses became a natural part of the
community college mission.
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THE IMPACT OF STUDENT SUCCESS RATES
Drury (2003) reported that by 1930, the American Association of Junior Colleges
was established to help navigate the changing landscape of the community college
movement. In 1930, the Junior College Journal was first published to discuss vocational
curricula and to supply training materials. A report by the Carnegie Foundation in 1932
found that state universities had a majority hold on research and training for higher
professions. The state colleges provided education for mid-professions such as teaching,
and the junior colleges provided general education for semi-professions and vocational
training (Drury, 2003). The delineation of the three academic paradigms was made clear
and encouraged a positive recognition of the role of community colleges.
Two major historical events served to be the impetus for the rise in community
college interest from the public. The first of these events would be the great depression
starting in 1929. Young people were out of work and needed training to find the few jobs
that were available. From 1929-1939, enrollment in community colleges grew from
56,000 to over 150,000 (Drury, 2003). College educations at this time were experiencing
a positive perception as they were seen as pathways to economic mobility and
opportunities for upward mobility from a social perspective. The second major event
came after W.W. II and the passing of the G.I. Bill of Rights of 1944, which provided
financial incentives for veterans to seek additional education or training for reintegration
into the American workforce (Drury, 2003; Goudas, 2020; Mello, 2000).
In 1947, the Truman Commission Report for the Higher Education for an
American Democracy was released to support the establishment of junior colleges as a
legitimate and viable academic entity. The report endorsed an objective of making
education available to everyone for little or no tuition (Drury, 2003; Jurgens, 2010;
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THE IMPACT OF STUDENT SUCCESS RATES
Mello, 2000). By 1957, a committee was established to recommend articulation
agreements and transfer credits from junior colleges to four-year institutions. In the
1960s, enrollments in community colleges were rapidly expanding, going from 1 million
in 1965 to 2.2 million by 1970. This same period of time saw the addition of Tribal
Colleges to serve the Native American populations. The 70’s and 80’s began movements
towards expansions in areas such as workforce development and joint ventures with
community colleges and business partners. This concept continued through the 1990s
when new relationships with high schools began forming as a pathway to higher
education (Drury, 2003).
The intentionality of a national movement towards supporting a community
college education has grown exponentially since the first college opened its doors in
1901; however, the mission and purpose of the community college experience remained
intact and strengthened through the partnerships within the communities they serve.
Ongoing communications with community members help establish clear directions for
program curriculums to serve the community's unique needs and ensure that students
receive the required skills to enter the workforce or transfer their general education
credits to a four-year program.
Pennsylvania. The state of Pennsylvania adopted the Community College Act of
1963 on August 24, 1963. This Act created the framework for establishing and operating
community college institutions throughout the Commonwealth. The 1963 Act authorized
school districts, county boards, and municipalities to sponsor community colleges
through specific taxes being levied by the districts and municipalities and by providing
reimbursements by the Commonwealth for certain costs and expenses (Community
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THE IMPACT OF STUDENT SUCCESS RATES
College Act, 1963). Part I, Chapter 35 of the Title 22 Pennsylvania Code further details
the required guidelines needed for the operation of a community college in the
Commonwealth.
According to Rink (2020), funding sources for community colleges in
Pennsylvania are to be shared in equal parts between the state, local sponsors, and tuition
and fees; however, that reality has never truly come to fruition; in fact, the state budgets
for community colleges remained flat for community colleges under Governor Wolfe.
Pennsylvania currently has 15 community colleges that operate on budgets from $13
million a year to more than $140 million for the largest systems. Local community
support also varies greatly from $1.2 million in Cambria County to over $30 million for
the city of Philadelphia and its community college.
Aiken (2023) reported that Governor Josh Shapiro had proposed a slight increase
for community colleges in the 2023-34 budget at a 2% funding bump. This would
represent an increase from $256 million to $261 million across the community college
system. Since the 2012-13 budget, state system funding for community colleges has
grown by 20.9%; however, there were many years when the budgets were flat during that
period. In 2023, a U.S. News and World Report ranking placed Pennsylvania 48th for low
debt and 47th for tuition and costs. The State Higher Education Executive Officers
Associations also reported that Pennsylvania ranked 48th for funding public college
students. Overall, Pennsylvania students received an average of $4100 less in funding
compared to national averages (Aiken, 2023).
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THE IMPACT OF STUDENT SUCCESS RATES
Community College Data and Statistics
The American Association of Community Colleges reported current data and
statistics pertaining to community colleges throughout the country, including the
following information: There are 932 public, 35 tribal, and 7 independent community
colleges that awarded 877,249 associate degrees and 592,863 certificates in 2020-2021.
In Fall 2021, headcount enrollments included 6.1 million college credits and 4.1 million
noncredit enrollments, down by .4% from Fall 2021 to Fall 2022 (Phillippe, 2023).
The average age of community college students is 27, and 30% of all students are
considered first-generation attendees. 66% of the student enrollments are part-time, while
34% are full-time students who pay an average annual tuition of $3,860, compared to the
average public 4-year college tuition of $10,940. Community College revenues included
21.8% in tuition, 18.5% in federal funding, 34.4% in state funding, 21.4% in local
funding, and 5.9% in other funding streams (Phillippe, 2023).
Shapiro (2020) from The National Student Clearinghouse Research Center
reported a positive movement in student enrollment in community colleges as the twoyear institutes continue to feel the impact of the COVID-19 pandemic. Community
colleges are starting to grow in spring 2023 (+2,1%) with a new infusion of dual
enrollments (age 17 and under) and incoming freshmen; in fact, dual enrollment went
from (+2.9% in 2022 to +12.8% in 2023). Certificate program enrollment was up
(+5.5%), while associate degrees saw a minimal (+0.3%) growth.
Overall graduation rates are based on a first-time full-time student’s ability to
graduate from a community college in three years; however, many students require more
time to fulfill the requirements of the degree they seek. Two-year retention rates overall
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THE IMPACT OF STUDENT SUCCESS RATES
were 46.9% for first-year students returning one year later. Full-time students were 59%,
and 2-year public part-time students were 39%, with a 2-year public graduation rate after
six years of 39.22% (Goudas, 2021).
Unique Challenges Compared to Four-Year Institutions
Open Access/Enrollment
One of the most prevalent challenges that community colleges face is the concept
of open-access enrollment. Raby (2020) referred to open access as “A foundational
philosophy of the community college” (p. 41). This embedded philosophy is a
cornerstone principle for all community colleges’ charge to make education available to
all students and to ensure no individual will ever be denied access through a selective
admissions process like is used by four-year institutes; therefore, community colleges
function with an unknown and fluctuating variable each semester. They cannot be as
intentional about expenditures and costs because they cannot rely on a level of funding
based on a stabilized student enrollment count attained through selective admissions
(Mullin, 2017).
Elfman (2023) reported on the challenges of an open-access policy in a postpandemic environment. Economic factors and funding support for community colleges
are being impacted by factors threatening open-access participation by the very
individuals who need it the most. These individuals cannot prioritize education for
various reasons, including “finances, family, illness, lack of internet or inability to adapt
to online learning” (p. 24). Social and economic barriers mean that community colleges
must continue finding new and innovative ways to offer students the required access and
flexibility. Community colleges must also be keenly aware of the workforce training
16
THE IMPACT OF STUDENT SUCCESS RATES
needs in their community. They must respond quickly to changes in training and
curriculum to keep students marketable and competitive. The open access policy is a
noble practice for community colleges, but it can also create many unstable and unknown
factors in keeping the community college stable and viable.
Housing Versus Commuting
A significant consideration for the unique variables associated with community
colleges comes in understanding the impact that housing availability can have on student
retention and persistence. A study in 2022 revealed that 81% of public two-year colleges
provide students with housing options compared to only 29% of community colleges
(Phillippe, 2023). According to Abelson (2023), the National Center for Education
Statistics (NCES) recently reported on the struggles being felt by students in higher
education for basic needs. Nearly 23.4% of community college undergraduates are
experiencing low or inadequate food security, and 8% of all community college students
are experiencing some level of homelessness. These alarming statistics reveal the true
spirit of the community college ethos and the need to educate people from diverse
backgrounds and challenging circumstances to ensure a stronger future.
Students living on campus have clear advantages that can help with retention and
a sense of belonging not realized by students in a community college environment.
Housing options can give students a sense of safety and support in a first-year experience,
the ability to bond with a potential roommate, and access to activities and gatherings that
encourage student identity with the campus. Living on campus is not an option for most
community colleges, so other types of campus strategies must be developed to
compensate for the deficit caused by students' need to commute to the campus. One of
17
THE IMPACT OF STUDENT SUCCESS RATES
these strategies is building relationships through available student services; however,
many first-year students at a community college do not pursue them. Tutoring and writing
center participation are two available services at most higher education institutes that can
help bridge the gap towards positive retention and course completion, especially with
barrier courses.
Part-time versus Full-time Enrollment & Unique Demographics
According to Phillippe (2023) from The American Association of Community
Colleges, part-time students outnumber full-time students by nearly 2 to 1. 66% of
students attended part-time, while only 34% attended as full-time students. This also
included 30% of first-generation students, 16% of single parents, and a population of
35% of students between the ages of 22 and 39. These variables greatly impact
community colleges, which are held to a high standard for reporting to the Integrated
Postsecondary Education Data System (IPEDS). This system requires community
colleges to declare graduation rates for first-time, full-time students who graduate after 3
years. This is a very high bar to meet, given the unique circumstances of students who
tend to attend a community college. A second measuring unit, the Voluntary Framework
of Accountability (VFA), measures all students and a six-year timeframe for completion.
In its recent report on community college data, the American Association of Community
Colleges (2023) reported the IPEDS rate at 25%, while the VFA reported success rates at
59%.
Conceptual Frameworks
The overarching framework used for consideration of this capstone is grounded in
the work of Tinto (1975) and his ongoing seminal work on the retention and persistence
18
THE IMPACT OF STUDENT SUCCESS RATES
of first-year college students. Tinto’s initial framework considered the relationships
between the college environment of academic and social issues and the individuals who
experience the effects of these systems. The framework was presented as the Student
Integration Model. His initial premise and research have opened the door to expanded
consideration concerning retention and student success. Numerous researchers are
interested in finding ways to retain students once they enter higher education systems.
Tinto made a significant shift in thinking from previously held perspectives on student
persistence and retention. Before his study, mainstream thinking believed that certain
existing attributes, skills, and motivations impeded their performance in higher education
environments (Tinto, 2006).
Tinto (1999) continued with his seminal work in retention, acknowledging that
while new strategies were being implemented with some success, they were having a
limited impact and encouraged the notion that institutions needed to understand that the
core causes of retention are not simply about students. Still, it is also directly correlated
to the character of their settings. He presented four key components needed to help
improve retention: 1) provide clear, informational resources concerning the institute, 2)
the accessibility of academic, social, and personal supports, 3) create environments where
the students view themselves as a valued member, and 4) students must be learning.
By the early years of the 2000s, many theorists came to understand the
importance of the student in the equation and how a focus on student-related variables
needed to be considered on a deeper level. Tinto (2006) addressed this as a realization
that “It is one thing to understand why students leave; it is another to know what
institutions can do to help students stay and succeed” (p. 6). The focus on ways to
19
THE IMPACT OF STUDENT SUCCESS RATES
increase student retention began to grow into many other areas, such as how the role of
families and their backgrounds influenced retention and persistence. Economic factors
began to be considered along with cultural and social differences and student engagement
variables in a particular institute (Tinto, 2006).
Tinto (2017) continued to be a strong voice in the area of persistence with his
assertion that “…student retention has been shaped by theories that view student retention
through the lens of institutional action and ask what institutions can do to retain their
students. Students, however, do not seek to be retained. They seek to persist” (p. 254).
Tinto also recognized early alert systems' role in identifying student needs, the
appropriate ways to respond to them, and being sensitive to social supports, especially for
first-generation and low-income students who need to foster self-efficacy to build
confidence and persistence. Viewed through the student’s eyes, persistence is only one
factor in their successful journey. A sense of belonging and the perceptions of how they
view the curriculum and its value to their studies are also contributing variables (p. 264).
A secondary framework will consider the use of Transfer Theory to ensure that
tutoring practices build foundational skills that can be applied beyond the writing course.
Various early theoretical models provide the basis for how this framework can be
considered a logical inclusion with the seminal work of Tinto. According to Hajian
(2019), transfer refers to the ability to apply prior learning and experience to a situation
that is different from the situation from which the original learning was presented.
Though many frameworks exist, this study will focus on the Theory of Identical
Elements.
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THE IMPACT OF STUDENT SUCCESS RATES
Thorndike and Woodworth (1901) advanced a theory that stated learning could be
transferred from one distinct activity to a similar activity and used the example of the
concept of training as related to the concept of performance. The researchers noticed that
some subject matters did not affect their abilities to become strong problem solvers. They
found that students were gaining general application of problem-solving; however, not to
the degree of transfer that would effectively translate to problem-solving in a real-life
scenario. This realization showed that an intentional relationship between curriculum and
real-life demands was imperative; their work became the early models of active learning
theories.
Predominate Themes Based on the Frameworks
Retention/Persistence
Burns (2010) addressed realities associated with student retention in community
colleges and open-access policy for enrollment. Community colleges appeal to students
with life circumstances that may limit their educational attainment. This can include child
or family member care, single parenting, negative financial situations, enrolling in
college later in life, being a first-generation student, needing to commute to college with
transportation restrictions, and working full or part-time jobs; in fact, 70% of community
college students can relate to at least one of these situations and 50% have reported
connecting with two or more of these variables (Barhoum, 2018; Burns, 2010; Fike,
2008; Martin et al., 2014).
Community college students often enroll in courses and are less prepared than
students attending four-year universities. Because those institutes have selective
admissions, many students fail to meet the criteria to enroll and turn to community
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THE IMPACT OF STUDENT SUCCESS RATES
college as an option. The impact of this resulted in a study by Fike (2008) that showed
Fall-to-Fall retention rates to range from a low of 45% to a high of 48.4% of first-time,
in-college (FTIC) students. One of the logistic regression models showed that enrollment
in student services, such as tutoring, positively impacted student retention and
persistence.
At-risk Students
First-generation students are susceptible to challenges that put them in an at-risk
status, especially in their first semester and year of college. These students are the first in
their families to go to college, with neither parent having attended college or been
awarded a college degree. According to Schelbe et al. (2019), first-generation students
begin their academic journey at a disadvantage over their peers. Family support is limited
because of the inability to fully appreciate the challenges and obstacles that impact the
social and emotional factors associated with the college experience. These students also
often fail to realize the new expectations and academic standards that will be imposed on
them through attendance at a higher education institution.
Markle and Stelzriede (2020) conducted research pertaining to first-generation
students who participated in a first-generation learning community. The study examined
variables related to the persistence and retention of first-generation students to
continuing-generation students. The results showed that first-generation students who
accessed the learning community saw gains in intellectual and interpersonal development
and engagement that emphasized diverse perspectives. Students in the study also had
lower household incomes, lower SAT scores, and lower levels of confidence. Students
also felt they were less academically prepared than other groups in the study (p. 294).
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THE IMPACT OF STUDENT SUCCESS RATES
Economically Disadvantaged populations are another variable within the at-risk
population. Clarence et al. (2013) stated that there is a strong link between low
socioeconomic status (SES) and students’ low level of literacy achievement. Everett
(2015) added an additional factor for first-generation students by asserting that they are
often included in another at-risk population of economically disadvantaged (ED).
Financial accessibility to funds for college can be a limiting factor for four-year colleges,
but funding at a community college may make the process easier. 58% of students
attending community colleges receive aid, with 38% receiving federal grants, 19%
receiving federal loans, 125 receiving state aid, and 13% receiving institutional aid (p.
53).
Demographics associated with ethnicity are often another key indicator of how
students may fare regarding persistence and retention. Hispanic Serving Institutions
(HSI) are designated when the population of Hispanics exceeds 25% of the overall
population. Karaman et al. (2021) identified the impact of two distinct constructs for
first-year Hispanic college students - academic self-concept and social support. Academic
self-confidence refers to a student’s self-reflective insights on how they perceive
individual academic abilities. This perception significantly correlates to academic
achievement and test anxieties, translating to a psychosocial factor that challenges student
retention among Hispanic students. Social support ranging from friends and family to
teachers and mentors was shown to have a significant impact based on the types of
support such as emotional, informational, feedback, or resources; however, students were
more successful in retention when they applied a strong level of resilience as a
characteristic (Karaman et al., 2021; Rahat & Ilhan, 2016).
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THE IMPACT OF STUDENT SUCCESS RATES
Self-Efficacy
Self-efficacy plays a significant role in a student's persistence and determination
to be successful in a higher education environment. Based on the work of Bandura
(1977), self-efficacy is grounded in an individual’s understanding that they have the skills
and knowledge needed to complete a task or to achieve a specific target or goal. Bandura
identified four areas of self-efficacy: mastery experiences, social modeling, social
persuasion, and psychological responses. The first three areas explain ways in which
individuals can learn and develop strategies to help with a positive image of themselves;
however, the fourth area, the psychological response, may be the best indicator of
struggling first-year college students. In this area, a person's emotional reactions to a
variety of situations create emotional and physical reactions that can cause a great deal of
anxiety and stress. When students lack self-confidence, they will likely not seek advice
and support mechanisms that can help them cope with feelings of inadequacy in tasks like
writing.
Learning Transfer: Identical Elements
Yang et al. (2013) and Rounsaville et al. (2022) referred to transfer as learning
that utilizes knowledge from past applications to make new learning more accessible.
Hajian (2019) isolated a specific form of transfer based on the theory of identical
elements where learning can be transferred from one activity to another (p. 95). This
theory includes low and high-road transfer concepts depending on the transfer level
applied. Low-road transfer exists when there are many similar concepts, ideas, or learned
tasks that can be easily transferred, while high-road transfer happens through the result of
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THE IMPACT OF STUDENT SUCCESS RATES
“mindful abstractions of general principles among different events on different contexts
and a deliberate search for connections among their structures” (p. 96).
Using tutoring models within a first-year writing course can help advance the
concept of low-road transfer by providing scaffolding of writing techniques and strategies
that can be applied to all writing situations within various programs and applications.
Rounsaville et al. (2022) addressed transfer theory within the context of writing by
raising the question of two distinct areas: 1) the role of conscious awareness in transfer
and 2) the role of habit or routine. The authors considered four themes of relational
character: Intentionality, Fidelity, directionality, and simultaneity (p. 140). While all areas
can impact learning transfer within a tutoring model, fidelity may be of the most value.
Fidelity represents the “likeness” associated with various context structures that
provide similarities or differences for the transfer process (Rounsaville et al., 2022). This
concept of fidelity is manifested through situatedness, simulation, and scaffolding. All of
these practices can help ensure that the learning applied within a tutoring mode can
provide the basis for allowing the learned concepts to transfer across the writing in a
specific course and into a generalized application within other courses that require
writing-intensive curriculums. Similar to high or low-road transfer, fidelity can also be
viewed as low-fidelity and high-fidelity constructs of learning transfer.
Hill (2016) and Devet (2015) argued that there is a need for writing centers and
tutoring models to be intentional about the process of transfer. Writing labs or tutoring
centers were discussed as places where transfer concepts must be fostered and guided so
students understand writing-related knowledge's transportability (Hill, 2016, p. 77). Hill
focused on the pedagogical techniques that were seen as the most salient practices to
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THE IMPACT OF STUDENT SUCCESS RATES
influence transfer from the writing centers to other applications. They included having a
high level of initial learning, seeing the similarities and differences between learning
situations, understanding key concepts about writing, using metacognitive reflections,
and promoting certain dispositions towards learning, such as active learning and
motivation (pp. 79-80).
Gateway or Barrier Courses
Koch and Pistilli (2015) defined gateway courses as being in one of two
categories. The first category includes any foundational course, such as developmental
courses, that may be credit-bearing or non-credit-bearing. The second category is highrisk courses where grades of D, F, W (withdraws), or I (incompletes) are awarded. It is
important to note that the W grade, which does not impact the GPA, is included in the
Satisfactory Academic Progress (SAP) formula, which has implications for eligibility for
financial aid. Once a student loses financial aid through excessive withdrawals, they often
drop out of school. This process often occurs because students are unable to successfully
complete identified barrier courses, such as first-year required writing courses.
Gateway courses present huge obstacles for certain groups of other identifiable atrisk students, including lower-income, first-generation, and underrepresented minority
groups. This population represents the same groups of students who are least likely to
attend college and may never finish a degree with a direct correlation to the inability to
complete barrier courses that keep them from advancing onto other courses that may have
the barrier course as a pre-requisite (Bloemer et al., 2017; Koch & Pistilli, 2015). Koch
and Pistilli (2015) also argued that gateway course failure is directly related to college
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THE IMPACT OF STUDENT SUCCESS RATES
retention rates. These students “leave with their dreams diverted if not extinguished and
frequently with debt that they might never be able to repay” (p. 15).
Bloemer et al. (2017) cautioned that the real challenge of gateway courses comes
from first identifying them and then being able to apply a fix that is appropriate and
effective in increasing the success rates of these courses. This may include curriculum
revisions or the complete redesign of a course that also considers staff changes or
providing additional support to students, such as an innovative tutoring model. Most
importantly, the authors suggested that gateway courses must be put into the context of
the students the course is meant to serve. “Simply put, it is not reasonable to expect all
courses to serve all students equally. Efforts to do so are doomed from the start and may
actually do harm” (p. 6).
Tutoring-Related Discourse
Definitions
At-Risk Students. At-risk students are not experiencing success in school and are
potential dropouts. They are usually low academic achievers who exhibit low self-esteem.
Disproportionate numbers of them are males and minorities. Generally, they are from
families with low socioeconomic status. “Students who are both low-income and of
minority status are at higher risk. Their parents may have low educational backgrounds
and may not have high educational expectations for their children” (Donnelly, 1987, p. 1)
Developmental Courses. These are courses assigned to students who failed to
meet qualifying scores on entrance exams in various subject areas. Students must
typically pass the developmental course before moving into college credit courses that
will apply to the degree being sought (Vick et al., 2015).
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THE IMPACT OF STUDENT SUCCESS RATES
Barrier/Gateway Courses. Barrier or gateway courses are basic and foundational
courses that are generally lower-division courses that receive credit and are needed to
satisfy pre-requisite requirements before taking other courses (Bloemer et al., 2017).
Drop-in Tutoring. A traditional model of one-to-one tutoring where two
individuals meet to increase the knowledge and learning of a student from a professional
tutor (Cooper, 2010, p. 21).
Mandatory Tutoring. The act of requiring students, especially first-year college
students, to participate in a mandatory tutoring process as a condition of their coursework
(Gordon, 2010).
Peer-Tutoring. Peer tutoring involves individuals from similar groups who are
not professional instructors. It is a system whereby learners help each other and learn by
teaching (Stewert et al., 2015).
Professional Tutors. These individuals possess a degree related to a particular
content and expertise. These are paid positions (often part-time) within a college’s writing
center and are sometimes supplemented with peer tutors in a specific subject, such as
math or English (Stewert et al., 2015).
Embedded Tutors. The embedded tutoring model and design can vary
considerably across different institutions; however, in this study, an embedded tutor is a
compensated individual assigned to specific course sections during the semester. The
tutor receives specialized training from the administrator responsible for tutoring
programming and works closely with the content teacher to establish the practices that
will be used in the course. Tutors support all students in a particular section and often
attend the course as an added support and opportunity to meet with students. The
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THE IMPACT OF STUDENT SUCCESS RATES
embedded tutor may have access to the grades and assignments as a means of monitoring
when a student is behind and may need encouragement or help in completing
assignments.
Tutoring Models
Tutoring and Writing Centers
Tutoring and/or writing centers are the single most popular and pervasive model
used by institutions within higher education. While no hard data exists to substantiate this
reality, a search of websites from 10 Pennsylvania State System of Higher Education
(PASSHE) schools, as well as all Pennsylvania Community Colleges, revealed that each
institute had some form or variation of a writing center, writing labs, or tutoring centers
where professional tutors and resources are available to service the students in face-toface or remote modalities.
Writing centers and the use of tutoring to improve students’ language skills
historically developed to accommodate low-skilled writers, especially veterans,
underprepared students, and minorities in need of improving the skills that would allow
them to successfully meet the challenges of higher education (Ball, 2014; Missakian et
al., 2016; Ugo, 2010). Missakian et al. (2016) also reported that academically proficient
students could also be susceptible to the same writing issues as at-risk students when
trying to meet qualifying placement exam scores. Failure to access the help of a tutor
leads to incomplete coursework and the inability to graduate on time.
Vick et al. (2015) reported that students who sought tutoring outscored others by a
55% to 45% margin and received final grade averages that were 10% better. Pfrenger et
al. (2017) also reported that tutored students successfully passed development courses at
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THE IMPACT OF STUDENT SUCCESS RATES
higher rates than non-tutored students. Using an English Lab or writing center can have
strong implications on how a student will succeed in their first year of college, so it is
important to pursue all options that will get students to access this resource. Gray and
Hoyt (2020) also found that people using writer centers saw average grades of 2.94
compared to 1.60 for those not using the center. The average grade in the specific courses
was 3.25 for students who used the center and 2.18 for other new freshmen who opted not
to use the center for support.
Despite the positive impact of the use of tutoring, Hedengren and Lockerd (2017)
reported on the negative perspectives that some students have concerning the use of a
writing center. The author’s study looked at students who reported non-directive, nonproductivity (NDNP) as the reason why they felt a writing consultation in the writing
center did not improve their writing product or their writing process; in fact, NDNP was
evident through student comments like, “This was a waste of time” (p. 133).
Dissatisfaction among the students reported that there was a lack of concrete objectives
during the sessions, which caused the students to be frustrated at the level of work that
was accomplished. “I left the writing center with no notes, thesis, or better understanding
of my argument” (p. 138). While this study involved a four-year institution, community
colleges experience similar findings among students.
Bright (2017) acknowledged that using tutors at two-year colleges has some
unique variables, such as needing to hire a wider variety of tutors, from English
instructors to peer tutors with diverse backgrounds and experience. English instructors
who enter the tutoring center environment may fail to make the switch from classroom
practices to the role of tutors in the more traditional sense. This may mean that
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THE IMPACT OF STUDENT SUCCESS RATES
consultations for students feel more like an office-hour visit with their instructor, and peer
tutors run the risk of high turnover and a lack of longevity that allows for more
sustainable and pervasive peer tutoring practices.
The inherent problem for walk-in writing centers and tutoring labs is that they
assume struggling students will access the services that professional tutors can provide to
them; however, at-risk and struggling students often fail to consider this resource as a
means of improving the writing skills needed in all of their course work. Rheinheimer et
al. (2010) argued that at-risk students tend to avoid social resources like writing centers
or professional tutors for help. These students often have educational backgrounds that
lack the skill sets needed to improve academic achievement, and they are reluctant to
reach out beyond their comfort zones; however, according to Bielinska-Kwapisz (2015),
students who accessed writing centers or labs have been shown to statistically outperform
those who do not utilize the tutoring services available to them. The use of tutoring to
improve academic writing skills increased student retention and student engagement.
Salem (2016) concluded that a parent’s educational background and exposure to
higher education can also play a factor in the desire of at-risk students to participate in
tutoring programs. Rheinheimer et al. (2010) discussed the need for at-risk students to
take advantage of programs in Pennsylvania that support economically disadvantaged
students as an academic assistance strategy through tutoring programs, and they
acknowledged that part of the problem is the failure of at-risk students to seek help when
they need it. They concluded that at-risk students who sought tutoring services
experienced higher student persistence, retention, and the likelihood of graduating.
Gordon (2010) reported on the positive impact of tutoring through comments made by
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THE IMPACT OF STUDENT SUCCESS RATES
two students in his study. One student commented, “The guy there helped me organize
my paper when I was stuck.” Another said, “It actually made me start thinking about my
paper” (p. 156). Hodges and White (2001) reported that students who access the services
of a writing center report positive experiences, but economically disadvantaged students
often have trouble seeking this type of intervention.
Embedded Tutoring
Embedded tutoring is an emerging practice that ultimately seeks to bring the tutor
to the student. Embedded models can vary greatly to meet specific and unique needs;
however, all models share the concept of tutors who are infused into a course in a regular
and visible manner. Webster and Hansen (2014) discussed one model that was used at the
University of Montana Writing Center, referred to as the Sidecar Project (SP). The
purpose of the tutor-embedded model is to provide real-time and accessible guidance for
both student and faculty growth. The model centers on four factors: “Management of
collaboration logistics, demonstrated faculty buy-in, faculty-tutor integration, and student
and faculty willingness to consider and respond to feedback” (p. 53).
The success of an embedded collaboration begins with faculty buy-in and the
need to proactively plan for collaboration time between the tutor and the faculty member
so that responsibilities and boundaries are clearly articulated in a formal or informal
agreement (Carpenter et al., 2014; Webster & Hansen, 2014). Carpenter et al. (2014)
reported that these types of embedded collaborations make a critical shift from the
traditional writing center philosophy by moving the tutors from the writing centers to the
classroom. Part of this philosophical shift requires faculty and students to realize that
classroom instruction and writing centers as outside resources can find common ground.
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THE IMPACT OF STUDENT SUCCESS RATES
This ability to develop synergy between the faculty and tutor inspires new and creative
practices that foster positive student learning and growth.
Chaves et al. (2023) reported that embedded tutoring is not a new concept;
however, it gained renewed interest during the COVID-19 pandemic as tutoring centers
across the county sought innovative ways to reimage methods to increase student tutoring
opportunities. This included finding ways to bring tutors to the students versus students
needing to come to writing centers through their own initiatives. Four models of
embedded tutoring were considered, including Harrisburg Area Community College
(HACC) in central Pennsylvania. HACC is Pennsylvania’s oldest and largest community
college, serving approximately 13,000 students in five physical locations (p. 157). The
college first piloted embedded tutoring in the late 2010s by accessing grant funding to
pursue the new endeavor that was also incorporated into the college’s Strategic Plan.
They began by infusing tutors into gateway/barrier courses and at-risk courses as a
vehicle to help increase student retention and success rates. All campuses now embrace
the embedded model in all learning modalities, with multiple tutors supporting a variety
of course sections with a focus on mathematics, biology, and English (Chaves et al.,
2023).
Mandatory Versus Voluntary Tutoring
Wells (2016) addressed the use of writing centers as a mandatory requirement,
especially for first-year students. This model requires students to participate as part of
their course structure and requirements. The author presented several viewpoints for and
against the practice of mandatory requirements, including the strain on institutional
resources and student frustrations with time-consuming requirements that often require
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THE IMPACT OF STUDENT SUCCESS RATES
long wait times in the writing centers. Students using writing centers achieved grades that
were found to be higher on average than non-center users (Bielinska-Kwapisz, 2015;
Hendriksen et al., 2005). Hendriksen et al. (2005) found that tutored students had a 2.78
average semester GPA compared with a 2.64 average semester GPA for non-tutored
students. Overall, tutored students had a 75% pass rate versus a 71% pass rate for nontutored students. Bielinska-Kwapisz (2015) found that a study of 315 first-year
undergraduates showed that a student’s intrinsic and extrinsic motivations determined if
they would utilize tutoring service; in fact, 40% of the students who sought help fell into
the top 40th percentile for grade distributions.
Edlin and Guy (2019) discussed using a mandatory supplemental instructor (SI)
model for an elementary Algebra course at a community college. All students took the
Systems-Wide Elementary Algebra Final Exam (SWEAFE) as a common assessment for
the study. The results showed that additional mandatory tutoring correlated with a 3.795point increase in the SWEAFE with a 95% confidence interval. The study also showed
that additional mandatory instruction created a 26.5% higher than without the additional
time. The study concluded that the additional mandatory requirement improved learning
overall.
Gray and Hoyt (2020) discussed the question of who should attend tutoring
despite their acknowledgment that tutoring “helps improve learning, retention of ideas,
and student grades” (p. 1). One inherent issue for tutoring comes in the perception it has
from students and faculty alike. Many students believe tutoring is reserved for struggling
students, and they may not see themselves that way. Faculty may perpetuate that reality
by having a similar perspective and by failing to understand that tutoring can benefit all
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THE IMPACT OF STUDENT SUCCESS RATES
students at their unique level of need. Fain (2012) noted that community colleges have
multiple supports (like tutoring or study prep) available to help students earn their
degrees; in fact, 48% of all colleges offer placement test study aids, but only 13% of
these colleges make that test prep mandatory (p. 1). Mandatory requirements in
community colleges may offer students a better chance for success in college-level
graduation requirements such as first-year writing courses.
Data on mandatory tutoring is limited, especially in the area of quantitative
studies; however, the recent study by Gray and Hoyt (2020) produced some encouraging
data for mandatory tutoring as a positive intervention for student success. The study also
used a mixed-method approach to allow qualitative data to be analyzed from the
participant's perspective. The study results showed that the average essay grade was 2.94
for mandatory participants versus 1.60 for students not using the writing center; in fact,
the average final grade was 3.25 for participants versus 2.18 for new freshmen not using
mandatory tutoring.
Pre- and post-student surveys supplied additional qualitative data on participants'
perceptions and attitudes. Three questions using a 5-point Likert scale revealed the
following outcomes.
Question 1: How likely are you to recommend writing centers to a friend
Pre-study: 2.90
Post-study 4.11
Question 2: How much do you think the writing center can help you on an essay?
Pre-study: 3.72
Post-study: 4.06
Question 3: How likely are you to visit the writing center for a future class?
Pre-study: 3.54
Pot-study: 4.13 (p. 3).
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THE IMPACT OF STUDENT SUCCESS RATES
This recent study provided a solid context for continuing research on mandatory
tutoring as a positive intervention for helping students be more successful in writing
courses. More importantly, it shows that a mandatory requirement for tutoring changes
attitudes and negative perceptions of tutoring, creating positive habits of learning transfer
and the continued use of tutoring for future coursework.
Summary
Community colleges across the country face many challenges that are unique to
two-year institutes and the varied demographics of the students who attend them. The
common practice of open-access admissions for community college means that any
individual seeking to better themselves through higher education has that opportunity.
Community colleges that apply open access ensure attendance is guaranteed for
everyone, unlike four-year institutions, which may deny a student the ability to begin a
higher-education journey because they fail to meet the requirements for admission.
Selective enrollment institutions that use competitive enrollment quotas based on
academic excellence can discourage at-risk learners and keep them from starting their
post-secondary education. While noble in its intentions, the open-access policy does
come with a cost. Retention and course success rates for community college students are
often very low due to the many variables that impact these key performance indicators.
The literature reviewed showed that many factors contribute to the inability of
students to complete a degree at a community college. These include at-risk factors such
as being first-generation students, coming from low socioeconomic backgrounds, needing
to work full-time to support families, or being a part of a historically underperforming
ethnic group. These factors at a commuting college can add additional strains based on
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THE IMPACT OF STUDENT SUCCESS RATES
childcare, transportation, shift working, and./or the need to financially support a family.
Overcoming some challenges requires determination and persistence; however, students
often don’t have the self-efficacy to get the help needed when obstacles arise, and they
lack a sense of belonging and community that may exist at an institute with dorms and
residency opportunities.
Addressing these student needs is a priority for community colleges that regularly
promote many student services to help them through these times. Unfortunately, the
literature shows that these students often fail to seek the support that is available, such as
tutoring and writing centers. Meeting face-to-face with tutors in writing centers helps
create a sense of belonging to the college by building positive relationships that include
faculty and staff members on the campus. The literature review shows that it takes a
multiple-focused approach to help students discover the best strategies to improve their
ability to be successful and continue their education through positive retention and
enrollment from semester to semester.
Applying a mandatory component to first-year writing students is one of the
strategies that can help the community college retention equation and increase course
success rates. The literature surrounding the positive effects of tutoring to increase
academic proficiencies is cogent and consistent in its outcomes; however, the use of a
mandatory approach to tutoring is not always a shared philosophy. The practice of a
mandatory tutoring component would require a shift in the ethos of the community
college that recognizes the constraints of their population but also accepts the realities of
how a strong foundational experience in a first-year writing course may provide the selfefficacy, confidence, and skills to transfer their knowledge to other courses that will be
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THE IMPACT OF STUDENT SUCCESS RATES
required throughout their program pathway. The outcomes of this study can provide data
to be utilized for informed decisions about the potential of implementing a mandatory
requirement as a college policy. The research may also be used to develop a modified
mandatory program based on specific academic criteria, or it may be found to be an
ineffective practice that is not a good fit for the college.
Chapter III will examine the specific methodology applied to this action research
study and explain its purpose. It will also discuss the research plan, research design,
validity, and financial implications.
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THE IMPACT OF STUDENT SUCCESS RATES
CHAPTER III
Methodology
A persistent issue faced by a two-year community college in Southeastern
Pennsylvania was that many first-year writing students were not utilizing the professional
tutoring services available in the Academic Learning Commons to improve their writing
proficiencies. Mattison (2012) suggested that educators needed to make instructional
support programs available through a wide range of offerings that could help to close
achievement gaps. This included resources such as writing centers and professional
tutors. There was a need to increase the number of students who sought the services of a
professional writing tutor, especially at-risk students such as first-generation students and
economically disadvantaged students.
The literature review for this study helped inform the researcher of the positive
impact tutoring had on first-year writing students in higher education. Vick et al. (2015)
reported that students who sought tutoring outscored others by a 55% to 45% margin and
received final grade averages that were 10% better. Pfrenger et al. (2017) also reported
that tutored students successfully passed development courses at higher rates than nontutored students. Using an English Lab or writing center had strong implications for how
a student would succeed in their first year of college, so it was important to pursue all
options that would get students to access this resource. Gray and Hoyt (2020) also found
that people using writing centers saw average grades of 2.94 compared to 1.60 for those
not using the center. The average grade in the specific courses was 3.25 for students who
used the center and 2.18 for other new freshmen who opted not to use the center for
support.
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THE IMPACT OF STUDENT SUCCESS RATES
A second area of interest in the literature review came from looking at the unique
challenges faced by students in community colleges. Burns (2010) addressed realities
associated with student retention in community colleges due to open-access policies for
enrollment. Community colleges appealed to students with life circumstances that limited
their educational attainment. This included child or family member care, single parenting,
negative financial situations, enrolling in college later in life, being a first-generation
student, needing to commute to college with transportation restrictions, and working full
or part-time jobs; in fact, 70% of community college students related to at least one of
these situations and 50% reported connecting with two or more of these variables
(Barhoum, 2018; Burns, 2010; Fike, 2008).
These two areas of exploration within the literature review developed a sense of
synergy when applying a framework of persistence and retention of college students
through the seminal work of Tinto (1975). Tinto (1999) presented four key components
that are needed to help improve retention: 1) provide clear, informational resources
concerning the institute, 2) the accessibility of academic, social, and personal supports, 3)
create environments where the students view themselves as a valued member, and 4)
students must be learning. By the early years of the 2000s, many theorists understood the
importance of the student in the equation and how a focus on student-related variables
needed to be considered on a deeper level. Tinto (2006) addressed this as a realization
that “It is one thing to understand why students leave; it is another to know what
institutions can do to help students stay and succeed” (p.6).
This chapter considered how a quasi-experimental action research study was
developed to evaluate the impacts of mandatory tutoring for first-year writing students.
40
THE IMPACT OF STUDENT SUCCESS RATES
The study sought to determine if mandatory tutoring could improve course success rates
and writing proficiencies, contributing to stronger student retention and persistence
toward graduation. Applying a mandatory component to first-year writing students was
one of the strategies considered to help in community college retention and course
success rates. The literature surrounding the positive effects of tutoring to increase
academic proficiencies was cogent and consistent in its outcomes; however, the use of a
mandatory approach to tutoring was not always a shared philosophy. This study sought to
consider tutoring from a variety of perspectives and to weigh the value ascribed to a
mandatory tutoring requirement for all first-year students.
Purpose
This action research study was intended to determine if the use of mandatory
tutoring could increase course success rates of a first-year Communications-121 (COM121) writing course at a two-year community college in Southeastern Pennsylvania.
COM-121 was a first-year writing course required of all students at the community
college, and it was considered one of the top ten identified barrier or gateway courses. A
barrier/gateway course was identified as having course success rates of below 70%
completion. In 2022, the course success rates at a community college in Southeastern
Pennsylvania were 62% for all COM-121 courses. This meant that 38% of the students
were required to repeat and successfully complete the COM-121 course before they could
enroll in other courses that often require COM-121 as a pre-requisite. Failing COM-121
was a variable associated with a student’s ability to complete a degree on time.
The key performance indicator (KPI) for on-time graduation was a data point that
must be reported annually by all community colleges, and it was considered in choosing
41
THE IMPACT OF STUDENT SUCCESS RATES
the action research topic. Additional KPIs impacted by this action research study included
retention and course success rates. Selecting a KPI for action research that would most
significantly contribute to overall performance by measuring trends and comparison data
was crucial. Trends identified in research look at the data from year to year or at multiple
years across time, while comparisons look at similar data from an organizational process
perspective (Suryadi, 2007). This study focused on the organizational process of tutoring
practices within the broader KPIs of course success rates, retention, and on-time
graduation.
According to Stringer (2014), an isolated issue or organizational process
associated with KPI could be researched and implemented within a shorter and more
manageable time frame. It allows for practical and immediate improvements to be
realized by the research site. Hendricks (2017) added that action research is a systemic
process that requires the incorporation of specific and, therefore, measurable steps in a
repeating cycle of reflection, action, and evaluation. This process allowed for a problem
to be identified, a potential solution or action to be applied, and an evaluation of collected
data to be tested for the effectiveness of the action that was taken.
Desired Outcomes
Specific outcomes and research questions for the study:
1. To determine if the collected data supports the implementation of mandatory
tutoring for all or some students of the COM-121 writing course
2. To analyze various tutoring practices and their impact on the successful
completion of a barrier course based on mid-term and final grades
42
THE IMPACT OF STUDENT SUCCESS RATES
3. To recommend the implementation of some variation of mandatory tutoring for
first-year writing students to increase student retention and on-time graduations
4. To determine if tutor relationships help students improve their self-efficacy as
they transfer acquired knowledge to future program courses
Research Questions
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term and
final grades?
2. Is there a significant difference in writing proficiencies, as measured by course
grades, between students who participate in mandatory tutoring and those who
participate in voluntary tutoring, embedded tutoring, or those who never access
tutoring services?
3. What is the relationship between at-risk students (first-generation, economically
disadvantaged, or ethnicity/race) and mandatory tutoring as measured by success
rates when enrolled in a first-year (barrier) writing course?
Setting and Participants
School Location
A two-year community college in Southeastern Pennsylvania provided the setting
for a quasi-experimental study that considered the impact of mandatory tutoring in a firstyear writing course. Founded in 1971, the community college was one of fifteen
community colleges in Pennsylvania. The college was an accredited, comprehensive,
open-access institution of higher education. Accreditation was awarded through the
Middle States Commission of Higher Education (MSCHE). Educational opportunities
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THE IMPACT OF STUDENT SUCCESS RATES
included associate degrees, certificate and diploma programs, career-focused training,
and skills training for business and industry. The college offered non-credit GED
preparation, English as a Second Language (ESL) instruction, and short-term workforce
training, primarily in healthcare and manufacturing technology.
School Demographics
The community college demographics for 2021-2022 included 6,457 students,
164 online courses, and 16 online programs. The average age of students was 26, with
68% female and 32% male students. 76% of students were part-time, and 24% were
enrolled as full-time students. The community college was a diverse campus and was one
of only two community colleges designated as a Hispanic Serving Institutes (HSI).
Hispanic populations (Table 1) and students from economically disadvantaged
backgrounds receiving Pell Grants (Table 2) represented two focus areas in this study.
The data described in the included tables from the Fall of 2022 reflect the college
composition.
Table 1
Fall 2022 Student body by Racial or Ethnic Group
44
THE IMPACT OF STUDENT SUCCESS RATES
Table 2
Fall 2022 Full-Time Student Body by Racial or Ethnic Group and Pell Recipient
The diversity of the students on the campus was a key consideration in any data to
be collected through this study. The number of students receiving Pell Grants at the
college was historically in the 60% range and suggested that 6 out of 10 students enrolled
at the college came from economically disadvantaged families (Figure 1). Despite this atrisk designation, success rates for these students across all classes averaged 70% (Figure
2). Data for ethnicity/race represented a larger divide among the population, especially
when African American and Hispanic students were compared to white students (Figure
3). This difference showed a significant achievement gap when comparing the white
population to the Hispanic population, where gaps increased from 12% in 2018 to 15% in
2020 (Figure 4).
45
THE IMPACT OF STUDENT SUCCESS RATES
Figure 1
Figure 2
Share of Enrollment by Pell Grants
Success Rates by Pell Status
SHARE OF ENROLLMENT
BY PELL GRANTS
37%
37%
63%
2017-18
43%
80%
40%
63%
2018-19
SUCCESS RATES BY PELL
STATUS
60%
57%
2019-20
2020-21
78%
70%
79%
72%
72%
70%
69%
2017-18
2018-19
2019-20
2020-21
Did Not Receive Pell Grant
Did Not Receive Pell Grant
Recieved Pell Grant
Recieved Pell Grant
Figure 3
Success Rates by Select Race/Ethnicity
SUCCESS RATES BY SELECT RACE/ETHNICITY
70%
70%
2018-19
81%
81%
66%
81%
68%
67%
2019-20
African American
Hispanic
66%
2020=21
White
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 4
Success Gaps Compared to White Students
SUCCESS GAPS COMPARED TO WHITE STUDENTS
12%
10%
2017-18
10%
11%
2018-19
African American
14%
13%
2019-20
14%
15%
2020=21
Hispanic
Participants
The research was focused on institutional ex-post facto (archival) data from the
fall 2023 semester and data from a quasi-experimental study conducted in the spring of
2024; therefore, the IRB approved the study as an exempt project that did not require
student consent. The study utilized 79 enrolled students in four sections of
Communications-121 (COM-121) being taught by the same instructor during the spring
2024 semester. Two sections included mandatory tutoring as a part of the curriculum, and
two sections operated with a voluntary approach to tutoring services. Sections were
limited to twenty-four seats. Initial enrollments for the two sections of mandatory
tutoring included 44 students and enrollments for the two sections without the mandatory
requirement included 35 students. Students learned of the mandatory tutoring
requirements for the course during the initial class meetings and had the option to enroll
in a different COM-121 section if desired.
The selection of participants was based strictly on student enrollment in each
unique section. A non-equivalent control group design allowed for two groups to be
established that were similar to each other; however, one group was subjected to the
independent variable of mandatory tutoring for the semester. Mertler (2022) stated that
47
THE IMPACT OF STUDENT SUCCESS RATES
this may be the best model in school settings since students are already assigned to
pre-existing variables such as classes, grade levels, or other fixed conditions. This
study utilized four of the thirty sections offered for the spring 2024 semester. Each
section contained pre-established enrollments and variables such as days and times of
the section offerings. Students registered through an advisor or a self-service
enrollment platform.
There was no indication during the registration process that identified sections as
having a mandatory tutoring requirement. Tutoring requirements vary across the
individual sections and are established by a unique instructor for each section. Students
registered through a self-service platform or through an advisor in the advising center. All
classes were face-to-face sections that were held between the hours of 9 am and 3 pm.
Demographic information for all students was collected after the semester to determine if
the various at-risk populations identified in the study were represented in the
experimental group.
The study included additional data from the fall semester of 2023, which
consisted of 65 students from three COM-121 sections that utilized an embedded tutor
model. The same instructor taught these three sections and the four sections of the spring
2024 quasi-experimental study.
Research Plan
Plan/Intervention
The development of this plan was driven by the need to increase the number of
students who could increase their course success rates in a first-year writing course
through the use of a tutor. Tutors at RACC were accessible to all students through face-
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THE IMPACT OF STUDENT SUCCESS RATES
to-face, remote, and online platforms; however, each modality required the student to
seek the intervention voluntarily. A recent study by the Director of Tutoring indicated that
only 11% of the student population had contacted a tutor during the 22-23 academic year.
A proposed intervention was considered to increase the number of students being exposed
to tutor services and to determine if the impact of mandatory tutoring could be a viable
solution for successfully completing a first-year writing course.
The quasi-experimental project included four sections of Communications-121
(COM-121), a first-year writing course. Two sections of COM-121 functioned as the
experimental group. They were exposed to an independent variable of a mandatory
tutoring requirement, and two sections of COM-121 functioned as the control group
without being exposed to the independent variable. The experimental group was
analyzed and compared to the control group and to ex-post facto data, including past
sections of COM-121 from the fall of 2023. The fall sections included three sections of
COM-121 that utilized an embedded tutor. All existing data from the fall of 2023 and
the quasi-experimental sections from the spring of 2024 were supplied in an
autonomous format by the Dean of Assessment, Research, and Planning.
Once the quasi-experimental study to collect quantitative data was created, a
volunteer instructor agreed to teach four select courses of COM-121. The instructor's
schedule included four sections of COM-121 that were held during the 15-week spring
semester of 2024. The classes were held at 9 am, 10:30 am, 12 pm, and 1:30 pm on
Tuesday and Thursday of each week. The spring 2024 experimental model was selected
based on student enrollments in these four specific COM-121 sections. Each course
had a cap of 24 students.
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THE IMPACT OF STUDENT SUCCESS RATES
Students within the mandatory tutoring sections were required to participate in at
least five thirty-minute sessions with a college-employed tutor. Students were also
required to attend three sessions before mid-semester grades, with two more sessions
expected by the end of the semester. The tutoring participation had a graded component
in the courses as outlined in the course syllabus (Figure 5). Points were awarded for each
completed tutoring session and calculated as part of the mid-term and final grades.
Tutoring sessions were one-on-one sessions in a face-to-face environment;
however, students were permitted to use two sessions that were online, remote, or in the
form of a drop-off service. This service allowed students to submit a paper to be
reviewed, annotated by a tutor, and returned to the student for review. Students had to
submit a summary of each session to the instructor, including a date and time stamp
document from the tutoring center.
Figure 5
Grading Policy for Mandatory Tutoring Section
50
THE IMPACT OF STUDENT SUCCESS RATES
A post-semester quantitative survey was distributed to all students enrolled in the
four spring 2024 sections of COM-121. One survey was distributed to the control group
(Appendix A), and one survey was distributed to the experimental group (Appendix B).
The survey for the experimental group asked Likert questions to determine if students
saw value in the tutoring experience to improve writing, whether they would seek the
help of a tutor in future courses, and how likely they were to recommend tutoring in the
future. Students in the control group (no mandatory tutoring required) were asked how
many times they had accessed the help of a tutor and whether they felt their writing had
improved through the use of a tutor if they had voluntarily accessed one while taking the
course.
Research Alignment to Intervention
The community college in Southeastern Pennsylvania was an open-access
institute for all individuals seeking credit and non-credit programs for college
advancement. All students enrolled in credit-bearing programs of study needed to achieve
minimum grade requirements in all courses, including general education requirements in
math and writing that are prerequisites for future coursework. Failure to complete these
courses with a passing grade greatly impacted a student’s persistence, especially if they
needed to repeat general education courses in math and reading with two or more
attempts.
While many variables contributed to a student’s ability to complete a program,
this study focused on a writing intervention of mandatory tutoring as one way to help
students pass a required first-year writing course. This researcher served as the Dean of
the Communications, Arts, and Humanities division of the community college, where a
51
THE IMPACT OF STUDENT SUCCESS RATES
first-year composition course was identified as a barrier course for students. An action
research model and a literature review on mandatory tutoring were utilized to inform the
plan for this study.
The literature review provided encouraging data on the positive impact of success
rates for students who accessed tutoring; however, the research was limited in
quantitative data for mandatory tutoring as a specific intervention. One recent study by
Gray and Hoyt (2020) found that students using writing centers saw average grades of
2.94 compared to 1.60 for those not using the center. The average grade in the specific
courses was 3.25 for students who used the center and 2.18 for students who opted not to
use the center for support. Though minimal, this difference could elevate marginal
students to a passing grade of a C or better in a barrier course. The research plan in this
study was designed to provide additional quantitative data for the use of a mandatory
tutoring requirement in barrier courses for writing.
The literature review also helped justify the consideration of a more invasive
intervention to tutoring, such as a mandatory requirement for all students. This study
addressed some of the stigmas and limitations of students, especially at-risk students,
who chose not to use the free tutoring services available. Burns (2010) suggested that atrisk populations, including first-generation students or economically disadvantaged
students, often lacked the self-efficacy to seek the help needed. Additional variables such
as single parenting, older learners, full and part-time workers, or being personal
caregivers for others contributed to students' availability and persistence in seeking the
help of a tutor; in fact, 70% of community college students related to at least one of these
52
THE IMPACT OF STUDENT SUCCESS RATES
situations and 50% reported connecting with two or more of the variables (Barhoum,
2018; Burns, 2010; Fike, 2008; Martin et al., 2014).
Fiscal Implications
The primary budget costs for implementing a mandatory tutoring requirement for
all Communications-121 (COM-121) students at the college would require hiring up to
seven part-time tutors designated to service all COM-121 students in every section and
form of modality, including face-to-face, remote, and online offerings. The quasiexperimental model used in this study was based on each COM-121 student in the
experimental group receiving at least five 30-minute tutoring sessions per semester. If
this model were fully implemented for future semesters, the fall and spring semesters
would average about 600 enrolled students, and the summer term would service
approximately 200 students for an estimated implementation cost of approximately
$50,000.00. This cost is based on a tutor's salary of $25.00 per hour, including 2.5
tutoring hours per student or a cost of $62.50 per student.
This study was conducted during the spring 2024 semester. There were 21
students enrolled in one section of mandatory tutoring and 23 students enrolled in the
second section. The intervention required five 30-minute tutoring sessions per student
throughout the semester, or 220 tutoring sessions in total. This required approximately
110 tutoring hours at $25.00 per hour or a total expense of $2,750.00; however, the
researcher was not charged for any additional hours of tutoring that the study
generated.
Research Methods and Data Collection
Research Design
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THE IMPACT OF STUDENT SUCCESS RATES
This study was conducted as a quantitative study with a quasi-experimental model
and the inclusion of ex-post facto (archival) data from past semesters designed to
analyze the cause and effect of a designated treatment to an experimental group and to
test for causal relationships. Gay et al. (2009) argued that quantitative data “relies on
the collection and analysis of numerical data to describe, explain, predict, or control
variables and phenomena of interest” (as cited in Mertler 2022, p.107). This study
examined mid-term and final grades, tutoring participation grades, ex-post facto data
from previous semesters, and end-of-semester quantitative data from student surveys
to determine the impact of a mandatory tutoring requirement for first-year writing
students.
Data Collection Method and Timeline
ANOVA, Chi-square, paired sample T-test, and regression analysis were
applied to SPSS statistic software with additional Google survey data using qualitative
questions and Likert scales. The action research paradigm utilized a quantitative
research method for data collection. The research model was considered a casualcomparative design using ex-post facto (archival) data from past semesters and data from
a quasi-experimental project with a control group, which used a mandatory intervention
for tutoring first-year composition students.
A post-semester quantitative survey was distributed to all students in the spring
2024 sections of Communications-121 used in the study. One survey was distributed to
the control group (Appendix A), and one survey was distributed to the experimental
group (Appendix B). Figure 6 represents a detailed alignment of information contained in
this section. All data was obtained through RACC’s Dean of Assessment, Research, and
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THE IMPACT OF STUDENT SUCCESS RATES
Planning, and all data mining was distributed to the researcher using autonomous
formats.
Figure 6
Alignment of Research Questions, Data Collection, Data Sources, and Timelines.
RESEARCH QUESTION(S)
TYPES OF DATA TO
COLLECT
DATA SOURCES
(detailed explanation of the types of data you will
collect)
TIMELINE
FOR
COLLECTING DATA
1. What is the impact of
mandatory tutoring
requirements for
increasing success rates
in a first-year (barrier)
writing course as
measured by mid-term
and final grades?
quantitative
Ex-Post Facto
Data will be
collected after
the Spring
semester on May
4, 2024.
2. Is there a significant
difference in writing
proficiencies, as
measured by course
grades, between
students who
participate in
mandatory tutoring and
those who participate in
voluntary tutoring,
embedded tutoring, or
those who never access
tutoring services?
quantitative
Mid-term and final grades will be collected
from 4 identified COM-121 Spring
semester sections taught by the same
instructor. Two sections are control groups,
and two are treatment groups with a
mandatory tutoring requirement.
Anonymized data will be collected from
the college's Dean of Assessment,
Research, and Planning and will serve as
Ex Post Facto data for the quasiexperimental study. Additional Ex Post
Facto will be acquired from the Dean of
Assessment, Research, and Planning to
look at historical data on mid-term and
final grades from additional COM-121
sections during the Fall 2023 semester.
Students write a total of three essays
throughout the course, including a personal
essay, a synthesis essay, and a research
essay. First essay grades and final essay
grades will also be considered as a subset
of the mid-term and final grades. Student
end-of-course surveys on tutoring use will
also be analyzed for comparisons.
Anonymized data will be collected from
the college's Dean of Assessment,
Research, and Planning for grades, and
anonymous student surveys regarding the
use of tutoring throughout the semester
will also be collected at the end of the
semester from the instructor of record for
the 4 sections.
Ex Post Facto Data will also be retrieved
from the Director of Tutoring and Dean of
Assessment about the use of embedded
tutoring that was recently added for barrier
courses (including COM-121) at the
college.
Historical data
from the Fall
2023 semester
will be collected
by mid-Spring
semester in
March.
Ex-Post Facto
Data will be
collected after
the Spring
semester on May
4, 2024.
Student surveys
will be collected
from the
instructor after
the semester ends
on May 4, 2024.
Historical data
from the Fall
2023 semester
will be collected
by mid-Spring
semester in
March
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THE IMPACT OF STUDENT SUCCESS RATES
3.What is the
relationship between atrisk students (firstgeneration,
economically
disadvantaged, or
ethnicity/race) and
mandatory tutoring as
measured by success
rates when enrolled in a
first-year (barrier)
writing course?
quantitative
Anonymized data will be collected from
the college's Dean of Assessment,
Research, and Planning and will serve as
Ex Post Facto data for the quasiexperimental study. The data will contain
grade distributions from the 4 identified
sections and additional demographic
information about the students that
includes at-risk identifiers, ethnicity, and/or
Pell Grant recipients as a measure of
economically disadvantaged students.
Ex-Post Facto
Data will be
collected after
the Spring
semester on May
4, 2024.
IRB Approvals
IRB approvals were requested on August 4, 2023, for the study titled: The Impact
of Success Rates When Mandatory Tutoring is Applied to a First-Semester Barrier
Courses in Writing at a Two-Year Community College. An exempt status for the
quantitative nature of the study was sought and approved by Pennsylvania Western
University (Appendix C). An additional request was made to add two student surveys to
the initial approval. This request was granted on February 3, 2024, and added to the
proposal through the IRB at Pennsylvania Western University (Appendix D). Permission
to study at the community college was also obtained from the Provost (Appendix E).
Based on the study parameters, the IRB approved the study as an exempt project that
did not require student consent.
Fiscal Implications to Research Method and Data Collection
The quasi-experimental model used in this study was based on each
Communication 121 (COM-121) student in the experimental group receiving at least
five 30-minute tutoring sessions per semester. The spring 2024 enrollment in the four
COM-121 sections associated with this study was 78 students, consisting of 42 in the
control group and 36 in the experimental group. The intervention required five 30-
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THE IMPACT OF STUDENT SUCCESS RATES
minute tutoring sessions per student throughout the semester, or 220 tutoring sessions
in total. This required approximately 110 tutoring hours at $25.00 per hour or a total
expense of $2,750.00; however, the researcher was not charged for any additional
hours of tutoring that the study generated.
Validity
Validity Types and Methods
Fraenkel et al. (2012) argued that “The critical point to remember is that validity
refers to the degree to which evidence supports the inferences a researcher makes…the
inferences are validated, not the instrument itself” (as cited in Mertler, 2022). Hendrick
(2017) suggested that researchers needed to be aware of two important distinctions within
the data produced in their action research. The action research needed to address both
credibility and validity in the study through the use of four trustworthiness criteria:
credibility, transferability, dependability, and conformability (p. 64). This action research
study established both criteria through the following methods.
Credibility was established by ensuring that data sets were approached through a
process of triangulation. It included using autonomous data collection provided by the
college’s Dean of Assessment, Research, and Planning. This included data sets from the
spring 2024 quasi-experimental study and all ex-post facto/archival data from the fall
2023 semester. Additionally, the same instructor was used for comparison data in all four
courses of the study and three additional ex-post facto sections of Communications-121
where the instructor previously used an embedded tutor. Using the same instructor
ensured that data sets were not influenced by different approaches to curriculum, tutoring,
or individual teaching styles.
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THE IMPACT OF STUDENT SUCCESS RATES
Transferability was achieved by providing detailed descriptions of the research
site and the unique environmental factors influencing student success through various atrisk factors and ethnicity/race. This information provided the means for duplication of the
study for future research or relative comparisons to similar demographics and
environmental conditions.
Finally, dependability was achieved through the use of the triangulation of data, as
well as by providing a format that would allow for the findings to be replicated with other
participants and settings of similar contexts for continued research of the capstone
project. Confirmability was also achieved through triangulation of data and the steps
taken to ensure that no bias existed on the researcher's part while analyzing data. Using
the same instructor within all tutoring models helped achieve a fair and balanced
perspective on the concepts explored throughout the study. Finally, student survey data
was collected through electronic Google Surveys with qualitative questions to ensure the
lack of researcher bias as vetted by the Pennsylvania Western University IRB (Appendix
D).
Triangulation of Data
James-Warren et al. (2013) spoke about the need for data-informed decisionmaking and the use of a step-by-step process to ensure the integrity of the process. They
promoted the use of a triangulation method to describe meaningful educational
interventions by using multiple data points surrounding the same issue, and they
encouraged looking for links between practice and the results of the data. Mertler (2020)
inferred that triangulation does not automatically imply that three data points are
required; in fact, the author suggested that a better identifier may be to call data collection
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THE IMPACT OF STUDENT SUCCESS RATES
polyangulation, a term that would imply “more than one or many” (as cited in Mertler,
2022, p. 14). Mertler (2022) also asserted that data should be able to show that
independent measures support the concept of agreement and do not contradict each other.
This study achieved the conditions of triangulation (polyangulation) through the
use of several data points that included qualitative data from a quasi-experimental model
involving four sections of Communications-121 (COM-121), quantitative survey data
collected at the end of the semester from the four sections of COM-121 in the study, and
the inclusion of ex-post facto (archival) data from past sections of COM-121. The data
from each of these areas were used to answer the research questions that framed the study
and to inform the recommendations and conclusions from the study.
Summary
The proposed intervention sought to develop a course tutoring model to increase
the number of students accessing professional tutors in the English Lab to improve
writing proficiencies and to improve course success rates. Many first-year writing
students who enrolled in college courses could not meet the expectations of college-level
writing, and they lacked the self-efficacy skills needed to seek additional help and
support. Bandura (1977) argued that students who lack self-confidence will likely not
seek advice and support mechanisms that can help them cope with feelings of inadequacy
in tasks like writing. Increasing writing proficiencies and course success rates through a
mandatory tutoring requirement was considered a consistent writing framework to be
applied to all first-year Communications-121 (COM-121) courses at the college.
The community college in Southeastern Pennsylvania operated a walk-in tutoring
model with no mandatory requirements to access professional tutors. Virtual tutoring and
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THE IMPACT OF STUDENT SUCCESS RATES
a drop-off tutoring system were also in place; however, mandatory tutoring requirements
were at the individual instructor's discretion for each course. The Director of Tutoring has
recently implemented the use of embedded tutors in selected barrier courses as part of a
Title V grant that included several sections of COM-121. This study focused on a
mandatory tutoring component for select first-year writing sections and compared course
success rates measured through mid-term and final grades between the various tutoring
models available to all college students.
Chapter III described how a research plan was designed to consider one possible
strategy to help increase course success rates, writing proficiencies, and retention in one
of the top 10 barrier courses for the college. The results of the spring 2024 quasiexperimental study and ex post facto data from the fall of 2023 will be examined in the
next chapter to determine if any significant results have been discovered that could help
to implement new or restructured ways to offer tutoring services at the college. Tinto
(1999) said, “Clearly, the most important condition that fosters student retention is
learning. Students who learn are students who stay” (p. 29). It is crucial for the college to
consider multiple variables associated with making a student’s college experience a
successful endeavor, and this study may provide a window of opportunity toward that
aspiration.
Chapter IV will examine various data statistic tools, including ANOVA, Chisquare, paired sample T-test, and regression models, to analyze and discuss the results
from the quantitative data collected from a quasi-experimental intervention, ex-post facto
data from past semesters, and student survey data.
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THE IMPACT OF STUDENT SUCCESS RATES
CHAPTER IV
Data Analysis and Results
Community colleges throughout Pennsylvania operated with an open-access
policy that guaranteed students access to the education they provide; however, they were
also challenged with how to engage students in ways that could ensure student success
and retention toward a goal of on-time graduation. Elfman (2023) reported on the
challenges of an open-access policy in a post-pandemic environment that threatens openaccess participation by the very individuals who need it the most, but who are unable to
make education a priority due to a variety of reasons, including “finances, family, illness,
lack of internet or inability to adapt to online learning” (p. 24). Elfman’ s observations
concerning the struggles in an open-access college environment helped shape this study's
focus and define its purpose.
This action research study aimed to examine a specific strategy within an openaccess environment that could help increase student retention through the successful
completion of a first-year barrier course in writing. The study sought to determine if
mandatory tutoring in a first-year writing course at a two-year community college in
Southeastern Pennsylvania could positively impact course success rates and the key
performance indicator (KPI) of student retention.
The study also sought to determine if there were significant differences in student
academic success and retention based on a variety of demographic considerations and atrisk factors that could also be impacting course success rates in a barrier course. Tinto
(2017) asserted that “…student retention has been shaped by theories that view student
retention through the lens of institutional action and ask what institutions can do to retain
their students” (p. 254). Tinto’s seminal work in retention became the framework for the
61
THE IMPACT OF STUDENT SUCCESS RATES
study and the desire to explore potential strategies that could help all students find
success on their first attempt at a barrier course in writing.
Many students failed the Communications-121 (COM-121) course on their first
attempt and needed to repeat it two or three times before completing it. Passing COM121 was essential for enrolling in future courses that required this course as a
prerequisite. Failure to pass a first-year writing course had detrimental impacts on
retention and on-time graduation rates, which are data points of the college's five-year
Strategic Goals. This study considered how a mandatory tutoring requirement in an
identified barrier course for writing could impact course success rates and thereby help
with a student’s retention and ability to achieve on-time graduation within three years.
The following research questions were analyzed, and the results are discussed in this
chapter.
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term
and final grades?
2. Is there a significant difference in writing proficiencies, as measured by
course grades, between students who participate in mandatory tutoring and
those who participate in voluntary tutoring, embedded tutoring, or those who
never access tutoring services?
3. What is the relationship between at-risk students (first-generation,
economically disadvantaged, or ethnicity/race) and mandatory tutoring as
measured by success rates when enrolled in a first-year (barrier) writing
course?
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THE IMPACT OF STUDENT SUCCESS RATES
Data Analysis
A quantitative research model was conducted to consider student outcomes based
on mid-term and final grades within a Communication-121 (COM-121) course required
of all first-year students. COM-121 was a first-year writing course that needed to be
taken by all students in all programs offered at the college. It was also designated as one
of the top 10 barrier courses at the college due to its low course success rates for
completion. In 2022, the course success rates at the community college in Southeastern
Pennsylvania were 62% for all COM-121 courses.
Data was collected from a quasi-experimental study conducted during the spring
2024 semester and from archival data from the fall 2023 semester. The data set included
144 students in seven sections of COM-121. There were 44 students in two sections of
mandatory tutoring, 35 students in two sections of voluntary tutoring, and 65 students
in three sections with an embedded tutor.
The quasi-experimental project included four sections of Communications-121
(COM-121). Two sections of COM-121 functioned as the experimental group. They
were exposed to an independent variable of a mandatory tutoring requirement, and two
sections of COM-121 functioned as the control group without being exposed to the
independent variable. The experimental group was analyzed and compared to the
control group, and ex-post facto data from three previous sections of COM-121 from
the fall 2023 semester that included an embedded tutor. The Dean of Assessment,
Research, and Planning, who manages all institutional research data and state and
federal reporting, supplied all existing data in an autonomous format from the fall
2023 and spring 2024 semesters.
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THE IMPACT OF STUDENT SUCCESS RATES
The quantitative data from the quasi-experimental study were carefully
analyzed using various SPSS statistical models specifically chosen to accurately
interpret the research questions. The key tools used in this process were ANOVA, Chisquare, paired sample T-test, and regression analysis. The results were discussed and
were shared throughout the chapter. Additional quantitative data was collected through
a voluntary Google Survey where Likert questions were used to help triangulate the
data for the study. It's important to note that no survey results were available for the
ex-post facto data from the three embedded tutoring courses taught during the fall
2023 semester, which may have implications for the study's findings.
Results
To answer the three research questions, specific data was required to examine
participant demographics, including race/ethnicity, first-generation status, and Pell Grant
recipient status. These demographics were analyzed for their potential relationship to
learning outcomes based on mid-term and final grades within three different tutoring
models: mandatory, embedded, and voluntary tutoring. A student survey was also
analyzed to help triangulate the data and to determine student perceptions of tutoring and
if learning transfer of tutoring practices will be considered for future courses. The results
showed the following information:
Research Question One: What is the impact of mandatory tutoring requirements for
increasing course success rates in a first-year (barrier) writing course as measured by
mid-term and final grades?
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 7
Mid-term Grades: All Tutoring Models
Figure 7 shows mid-term grades from students in all three tutoring models in the
study. 28 students out of 144 scored an F in the mid-term test of the Communication-121
course. 21 students each scored grades A and B, 18 scored A-, 15 scored B+, 13 scored D,
eight scored B-, seven scored C, five scored C+, and three students scored D-.
Additionally, five students had null grades in the mid-term test. This distribution confirms
that the majority of the students scored grade F while the lowest number of students
scored D-. The overall success rate at the mid-term point, based on grades of an A, B, or
C was 66%. Mandatory models were at 57% (Figure 8), voluntary models were at 80%
65
THE IMPACT OF STUDENT SUCCESS RATES
(Figure 9), and embedded models were at 65% (Figure 10). These results indicated that
the best-performing tutoring model for course success rates at the mid-term point was for
students who voluntarily accessed a tutor or did not utilize a tutor at all.
Figure 8
Mid-term Grades: Mandatory Tutoring Model
Figure 9
Mid-term Grades: Voluntary Tutoring Model
66
THE IMPACT OF STUDENT SUCCESS RATES
Figure 10
Mid-term Grades: Embedded Tutoring Model
Figure 11
Final Grades: All Tutoring Models
67
THE IMPACT OF STUDENT SUCCESS RATES
Figure 11 shows mid-term grades from students in all three tutoring models in the
study. 36 out of 144 students withdrew from the study. 19 students scored C as their Final
grade, 18 scored F and B, 13 scored A and A-, 10 scored B+, nine scored C+, four scored
D, three scored B-, and one scored D+. This implied that a higher number of students
withdrew from the study. Similarly, most students scored C as their final grade, while
only one scored D+. The overall course success rate for final grades, based on grades of
an A, B, or C was 59%. Mandatory models were at 50% (Figure 12), voluntary models
were at 74% (Figure 13), and embedded models were at 62% (Figure 14). These results
indicated that the best-performing tutoring model for course success rates at the final
grade point was for students who voluntarily accessed a tutor or did not utilize a tutor at
all.
Figure 12
Final Grades: Mandatory Tutoring Model
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 13
Final Grades: Voluntary Tutoring Model
Figure 14
Final grades: Embedded Tutoring Model
69
THE IMPACT OF STUDENT SUCCESS RATES
Table 3
Comparison Between Mandatory and Voluntary Models as Measured by Final Grades
Statistics
Final Grades Mandatory
Final Grades Voluntary
Model
Model
N
44
35
Mean
3.95
6.54
Median
3.5
8.00
Mode
0
10
Note. Descriptive statistics
According to Table 3, the number of students who participated in the mandatory
and voluntary model were 44 and 35, respectively. The mean final grade under the
voluntary model was slightly higher than that of the mandatory model, as the voluntary
model had a mean of 6.54, while the mandatory model had a mean of 3.95. The median
final grade of the mandatory model was 3.5, while the median of the voluntary model had
a median of 8.
Table 4
Frequency Comparison Between the Mandatory Model and Voluntary Model as
Measured by Final Grades
Grade
Mandatory
Model
Frequency
W
F
D
D+
17
4
1
0
Valid
Percent
38.6
9.1
2.3
0
Voluntary
Model
Frequency
Percent
7
1
1
0
20.0
2.9
2.9
0
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THE IMPACT OF STUDENT SUCCESS RATES
CC
C+
BB
B+
AA
Total
0
5
2
2
7
1
3
2
44
0
11.4
4.5
4.5
15.9
2.3
6.8
4.5
100
0
4
2
0
3
5
7
5
35
0
11.4
5.7
0
8.6
14.3
20.0
14.3
100
Note. Frequency comparison
According to Table 4, most of the students under the mandatory model withdrew
(n=17), while those under the voluntary model scored A- as the final grade with
withdraws at (n=7). Only one student scored an F under the voluntary model, while four
students student scored an F under the mandatory model. Moreover, more students scored
A and A- as final grades under the voluntary model (n=12) than in the mandatory model
(n=5). The observed impact was the high numbers of withdrawals in the mandatory and
voluntary models. Also, there was a higher performance in the voluntary model than in
the mandatory model as measured by the final grade. Additionally, few students scored an
F under the voluntary model as compared to the mandatory model.
Table 5
Descriptive Statistics Comparison Between the Mandatory and Embedded Model as
Measured by Final Grades
Statistics
Final Grades
Mandatory model
44
Final Grades
Embedded model
65
Mean
3.95
4.66
Median
3.5
5.00
0
1
N
Mode
Note. Descriptive statistics
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THE IMPACT OF STUDENT SUCCESS RATES
According to Table 5, the number of students who participated in the mandatory
and embedded model was 44 and 65, respectively. The mean final grade under the
embedded model was slightly higher than the mandatory model, as the embedded model
had a mean of 4.66, representing a C- final grade, while the mandatory model had a mean
of 3.95, representing a D+ final grade. The median final grade of the mandatory model
was 3.5, representing a grade of D+, while the median of the embedded model had a
median of 5, representing a final grade of C. Additionally, the mode final grade of the
mandatory model was zero, representing withdrawal, while in the embedded model, it
was 1, representing a grade F.
Table 6
Frequency Comparison Between Mandatory Model and Embedded Model as Measured
by Final Grades
Grade
W
F
D
D+
CC
C+
BB
B+
AA
Total
Mandatory
Model
Frequency
17
4
1
0
0
5
2
2
7
1
3
2
44
Valid Percent
38.6
9.1
2.3
0
0
11.4
4.5
4.5
15.9
2.3
6.8
4.5
100
Embedded
Model
Frequency
12
13
2
1
0
10
5
1
8
4
3
6
65
Percent
18.5
20.0
3.1
1.5
0
15.4
7.7
1.5
12.3
6.2
4.6
9.2
100
Note. Frequency comparison
According to Table 6, most of the students under the mandatory model withdrew
(n=17), while those under the embedded model scored an F as the final grade (n=13).
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THE IMPACT OF STUDENT SUCCESS RATES
Also, more students scored an F under the embedded model (n=13) than under the
mandatory model (n=4) as measured by final grade. Most of the students scored A and Aas final grades under the embedded model (n=9) compared to the mandatory model
(n=5). The impact was that there were more withdrawal cases in the mandatory model
than in the embedded model. Similarly, as shown by the final grade recordings, the
embedded model had a slightly higher performance than the mandatory model.
Additionally, few students scored an F grade under the mandatory model compared to the
embedded model, as specified in the final grades.
Research Question Two: Is there a significant difference in writing proficiencies, as
measured by course grades, between students who participate in mandatory tutoring
and those who participate in voluntary tutoring, embedded tutoring, or those who never
access tutoring services?
ANOVA and T-tests were applied to study data to establish whether there was a
significant difference in writing proficiencies, as measured by course grades between
students who participated in mandatory tutoring and those who participated in other
tutoring models.
Table 7
ANOVA Between Mandatory and Voluntary Tutoring as Measured by Mid-term Grades
ANOVA
Midterm Grades Voluntary
Sum of
Squares
Between
147.177
Groups
Within Groups 288.365
Total
Note. ANOVA
435.543
df
9
Mean
Square
16.353
25
11.535
34
F
Sig.
1.418
.233
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THE IMPACT OF STUDENT SUCCESS RATES
According to Table 7, a one-way ANOVA between the mandatory tutoring model
and voluntary tutoring model as measured by the mid-term grade was (F (9, 25) =1.418),
P=0.233). Since the P-value was more than an alpha value of 0.05 (P=0.233>0.05), it
implied that there was a statistically significant difference in writing proficiencies
between students who participated in the mandatory tutoring model and the voluntary
tutoring model.
Table 8
ANOVA Between Mandatory and Embedded Tutoring as Measured by Mid-term Grades
ANOVA
Mid-term Grades Embedded
Sum of
Squares
Between Groups
159.852
df
Mean Square
F
Sig.
9
17.761
1.245
.301
14.261
Within Groups
484.875
34
Total
644.727
43
Note. ANOVA
According to Table 8, a one-way ANOVA between the mandatory tutoring model
and embedded tutoring model as measured by the mid-term grade was (F (9, 34) =1.245),
P=0.301). Since the P-value was more than an alpha value of 0.05 (P=0.301>0.05), it
implied that there was a statistically significant difference in writing proficiencies
between students who participated in the mandatory tutoring model and the embedded
tutoring model.
Table 9
ANOVA Between Mandatory and Voluntary Tutoring as Measured by Final Grades
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THE IMPACT OF STUDENT SUCCESS RATES
ANOVA
Final Grade Voluntary
Sum of
Squares
Between Groups
326.519
df
Mean Square
F
Sig.
9
36.280
3.569
.006
10.167
Within Groups
254.167
25
Total
580.686
34
Note. ANOVA
According to Table 9, a one-way ANOVA between the mandatory tutoring model
and voluntary tutoring model as measured by the final grade was (F (9, 25) =3.569),
P=0.006). Since the P-value was less than an alpha value of 0.05 (P=0.006<0.05), it
implied that there was no statistically significant difference in writing proficiencies
between students who participated in the mandatory tutoring model and voluntary
tutoring model as measured by final grade.
Table 10
ANOVA Between Mandatory and Embedded Tutoring as Measured by Final Grades
ANOVA
Final Grade Embedded
Sum of
Squares
Between
204.608
Groups
Within Groups
460.120
Total
664.727
df
9
Mean
Square
22.734
34
13.533
F
Sig.
1.680
.132
43
Note. ANOVA
According to Table 10, a one-way ANOVA between the mandatory tutoring model
and embedded tutoring model as measured by the final grade was (F (9, 34) =1.680),
75
THE IMPACT OF STUDENT SUCCESS RATES
P=0.132). Since the P-value was more than an alpha value of 0.05 (P=0.132>0.05), it
implied that there is a statistically significant difference in writing proficiencies between
students who participated in the mandatory tutoring model and the embedded tutoring
model as measured by final grade.
Overall, there was a statistically significant difference between mandatory,
embedded, and voluntary as measured by mid-term grades based on ANOVA. Similarly,
based on ANOVA, a statistically significant difference existed between the mandatory
model and embedded model as measured by final grades. However, there was no
statistically significant difference between the mandatory and voluntary models as
measured by the final grade.
Table 11
Paired Sample T-test Between Mandatory and Voluntary Tutoring Models as Measured by
Mid-term Grades
According to Table 11, the paired sample T-test between the mandatory tutoring
model and voluntary tutoring model as measured by the mid-term grade was (t (34) =2.171), P=0.037). Since the P-value was less than an alpha value of 0.05
(P=0.037<0.05), the results implied that the mean difference in writing proficiencies
76
THE IMPACT OF STUDENT SUCCESS RATES
between students who participated in mandatory tutoring and voluntary tutoring model as
measured by mid-term grade was statistically significant. This meant a statistically
significant difference existed between students who participated in the mandatory and
voluntary tutoring models as measured by mid-term grades.
Table 12
Paired Sample T-test Between Mandatory and Embedded Tutoring Model as Measured by
Mid-term Grades
According to Table 12, the paired sample T-test between the mandatory tutoring
model and embedded tutoring model as measured by the mid-term grade was (t (43) =0.348), P=0.729). Since the P-value was more than an alpha value of 0.05
(P=0.729>0.05), it implied that the mean difference in writing proficiencies between
students who participated in the mandatory and embedded tutoring models as measured
by mid-term grades was not statistically significant. This meant that no statistically
significant difference existed between students who participated in the mandatory
tutoring and embedded tutoring model as measured by mid-term grades.
Table 13
Paired Sample T-test Between Mandatory and Voluntary Tutoring as Measured by Final
Grades
77
THE IMPACT OF STUDENT SUCCESS RATES
According to Table 13, the paired sample T-test between the mandatory tutoring
model and voluntary tutoring model as measured by the final grade was (t (34) =-2.205),
P=0.034). Since the P-value was less than an alpha value of 0.05 (P=0.034<0.05), it
implied that the mean difference in writing proficiencies between students who
participated in the mandatory and voluntary tutoring models as measured by final grade
was statistically significant. The results showed that there was a statistically significant
difference between students who participated in the mandatory tutoring model and the
voluntary tutoring model as measured by final grades.
Table 14
Paired Sample T-test Between Mandatory and Embedded Tutoring as Measured by Final
Grades
According to Table 14, the paired sample T-test between the mandatory tutoring
model and embedded tutoring model as measured by the final grade was (t (43) =-0.409),
78
THE IMPACT OF STUDENT SUCCESS RATES
P=0.684). Since the P-value was more than an alpha value of 0.05 (P=0.684>0.05), it
implied that the mean difference in writing proficiencies between students who
participated in the mandatory and embedded tutoring models as measured by final grade
was not statistically significant. This indicated that there was no statistically significant
difference between students who participated in the mandatory tutoring model and the
embedded tutoring model as measured by final grade.
Overall, the paired sample t-test showed a significant difference between the
mandatory and voluntary models, while there was no statistically significant difference
between the mandatory and embedded models as measured by mid-term and final grades.
Research Question Three: What is the relationship between at-risk students (firstgeneration, economically disadvantaged, or ethnicity/race) and mandatory tutoring as
measured by success rates when enrolled in a first-year (barrier) writing course?
The chi-square and regression tests were utilized to determine the relationship
between at-risk students (first-generation, economically disadvantaged, or ethnicity/race)
and mandatory tutoring as measured by success rates. The chi-square test showed
whether the variables were associated, while regression showed R, which measured the
degree of relationship between variables.
In total, 144 students from diverse backgrounds participated in this study. 49.31
percent of the students were Hispanic, 32.64 percent were white, 9.028 percent were
Black or African American, 8.333 percent were categorized as having two or more races,
and 0.694 percent were non-resident Aliens. This implied that the majority of the students
who participated in the study were Hispanic, while the least were non-resident Aliens.
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THE IMPACT OF STUDENT SUCCESS RATES
71.53 percent of the students who participated in the study were non-firstgeneration students, while 28.47 percent were first-generation students. This implied that
there were more students with non-first-generation status than first-generation status
students. 65.97 percent of the students involved in the study received Pell Grants,
whereas 34.03 percent did not. This inferred that more students received Pell Grants that
were awarded based on socioeconomic status
Table 15
Chi-square Test Between First-generation Status and Mandatory Tutoring as Measured
by Success Rate
Value
Chi-Square Tests
df
Asymp.
Sig. (2sided)
1
.870
1
1.000
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson Chi-Square .027a
Continuity
.000
b
Correction
Likelihood Ratio
.027
1
.870
Fisher's Exact Test
1.000
.576
Linear-by-Linear
.026
1
.871
Association
N of Valid Cases
44
a. 1 cells (25.0%) have an expected count of less than 5. The minimum expected
count is 4.77.
b. Computed only for a 2x2 table
Note. Chi-square test
Since the basis of undertaking a chi-square test was measuring the association
between variables, the only value the study reported was the Pearson Chi-Square.
Therefore, based on Table 15, the Pearson Chi-Square test between first-generation status
and mandatory tutoring as measured by success rate was 𝜒 (1) = 0.027, 𝑝 = 0.870.
80
THE IMPACT OF STUDENT SUCCESS RATES
Since the P-value was more than the alpha value of 0.05 (p=0.870>0.05), there was no
statistically significant association between first-generation status and mandatory
tutoring, as depicted by the success rate.
Table 16
Chi-square Test Between Pell-grant Status and Mandatory Tutoring as Measured by
Success Rate
Chi-Square Tests
Value
df
Asymp.
Sig. (2sided)
a
.052
1
.820
Exact Sig.
(2-sided)
Exact Sig.
(1-sided)
Pearson ChiSquare
Continuity
.000
1
1.000
b
Correction
Likelihood Ratio
.052
1
.820
Fisher's Exact Test
1.000
.533
Linear-by-Linear
.051
1
.822
Association
N of Valid Cases
44
a. 0 cells (0.0%) have an expected count of less than 5. The minimum expected
count is 7.64.
b. Computed only for a 2x2 table
Note. Chi-square
According to Table 16, the Pearson Chi-Square test between Pell Grant status and
mandatory tutoring as measured by success rate was 𝜒 (1) = 0.052, 𝑝 = 0.820. Since the
P-value was more than the alpha value of 0.05 (p=0.820>0.05), there was no statistically
significant association between Pell status and mandatory tutoring as measured by
success rate.
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THE IMPACT OF STUDENT SUCCESS RATES
Table 17
Chi-square Test Between Ethnicity/race and Mandatory Tutoring as Measured by Success
Rate
Chi-Square Tests
Value
df
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear Association
3.650a
4.805
.890
3
3
1
Asymp. Sig. (2sided)
.302
.187
.345
N of Valid Cases
44
a. 5 cells (62.5%) have an expected count of less than 5. The minimum expected
count is 1.43.
Note. Chi-square test
According to Table 17, the Pearson Chi-Square test between ethnicity/race and
mandatory tutoring as measured by success rate was 𝜒 (3) = 3.650, 𝑝 = 0.302. Since the
P-value was more than the alpha value of 0.05 (p=0.302>0.05), there was no statistically
significant association between ethnicity/race and mandatory tutoring as measured by
success rate.
Table 18
Regression Between First-generation Status and Mandatory Tutoring as Measured by
Success Rate
Model
R
Model Summary
R Square
Adjusted R
Square
1
.025a
.001
-.023
a. Predictors: (Constant), First-generation status
Note. Regression model Summary
Std. Error of the
Estimate
4.600
82
THE IMPACT OF STUDENT SUCCESS RATES
Since this regression analysis table showed the value of R, which is the
correlation that ascertains the relationship, other output tables were not utilized. Table 18
showed the correlation between first-generation status and mandatory tutoring as
measured by a success rate of 0.025 (R=0.025). This implied that, even though there was
a positive relationship between first-generation status and mandatory tutoring as
measured by success rate, the degree of relationship was very low.
Table 19
Regression Between Pell Status and Mandatory Tutoring as Measured by Success Rate
Model Summary
Model
R
R Square
Adjusted R
Square
Std. Error of the
Estimate
1
.034a
.001
-.023
4.598
a. Predictors: (Constant), Pell status
Note. Regression model summary
According to Table 19, the correlation between Pell Grant status and mandatory
tutoring as measured by a success rate of 0.034 (R=0.034). This implied that there was a
positive relationship between Pell Grant status and mandatory tutoring, as measured by
success rate. However, the degree of relationship was very low.
Overall, Chi-Square Tests showed no association between at-risk students (Firstgeneration status, Pell Grant status, and ethnicity) and mandatory tutoring as measured by
success rate. However, Regression analysis showed that there was a positive relationship
between at-risk students and mandatory tutoring as measured by success rate, although
the degree of relationship was very low.
83
THE IMPACT OF STUDENT SUCCESS RATES
Student Survey Data Results
This quantitative study sought to achieve triangulation through various data
analyses, as presented in this chapter. One final data set came from a voluntary exit
survey of students who were part of the quasi-experimental study in the spring of 2024.
The brief survey sought to include a student voice perspective on tutoring through Likert
questions and responses. It should be noted that this survey was not available to students
in the embedded sections from the fall 2023 semester. The spring 2024 survey helped to
reflect on the framework of learning transfer theory and whether students would continue
to utilize tutoring beyond the barrier course of Communications-121. Student responses
for the mandatory tutoring sections represented 22 of 44 students or a 50% return.
Students from the voluntary tutoring sections represented 24 of 35 students or a 69%
return.
Figure 15
Survey Results: Mandatory Tutoring Question One
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 15 represents the number of mandatory tutoring sessions attended during
the spring 2024 semester. 18.2 percent of the students met or exceeded the five required
sessions, while 81.8 percent reported attending one to four sessions. This implied that 100
percent of the survey participants utilized tutoring services at some point over the course
of the semester, but the majority did not complete the mandatory five tutoring sessions.
Figure 16
Survey Results: Mandatory Tutoring Question Two
Figure 16 shows that 63.7 percent of students agree or strongly agree that tutoring
improved the quality of their writing during the semester. 31.8 percent neither agree nor
disagree that tutoring helps their writing, and 4.5 percent strongly disagree that tutoring
improves their writing. This implied that most students believe tutoring improved the
quality of their writing over the semester.
85
THE IMPACT OF STUDENT SUCCESS RATES
Figure 17
Survey Results: Mandatory Tutoring Question Three
Figure 17 shows that 54.6 percent of students are very likely to extremely likely
to use tutoring services for future courses, while 9.1 percent are not at all likely to use
tutoring for future courses. 36.4 percent of students are somewhat likely to use tutoring.
This implied that a majority of students will be inclined to access tutoring services for
future course
Figure 18
Survey Results: Mandatory Tutoring Sections Question Four
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THE IMPACT OF STUDENT SUCCESS RATES
Figure 18 shows that 69.1 percent of students are very likely to extremely likely
to recommend tutoring to a classmate, while 4.5 percent are not at all likely to
recommend tutoring to a classmate. 36.4 percent of students are somewhat likely to
recommend tutoring to a classmate, which implied that most students would be inclined
to recommend tutoring to a classmate.
Figure 19
Survey Results: Voluntary Tutoring Sections Question One
Figure 19 represents the number of voluntary tutoring sessions attended during
the semester when no mandatory sessions were required. 50 percent of the students
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THE IMPACT OF STUDENT SUCCESS RATES
attended 1, 2-3, or 4-5 sessions in the semester; however, 25 percent attended only one
session. 50 percent of the students attended no tutoring session for the semester. This
implied that half of the students in a voluntary tutoring section of Communications-121
sought the help of a tutor on their own.
Figure 20
Survey Results: Voluntary Tutoring Sections Question Two
Figure 20 shows that 37.5 percent of the students who used a tutor during the
semester agree or strongly agree that the quality of their writing improved. 12.5 percent
neither agreed nor disagreed with whether their quality of writing had improved, and 50
percent of the students did not use a tutor during the semester. This implied that a
majority of students who used a tutor within a voluntary tutor model believed that their
writing improved over the semester.
Discussion
This action research study used a quantitative data collection process to determine
if a mandatory tutoring intervention in a first-year Communication-121 (COM-121)
barrier course could improve course success rates and ultimately help student retention
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rates. The study included data sets from a quasi-experimental study of two COM-121
sections with a mandatory tutoring requirement and two sections of COM-121 with a
voluntary approach to tutoring. Ex-post facto/archival data from three embedded tutoring
sections were also considered. The same instructor was used for comparison data in all
four courses of the spring 2024 study and the three additional ex-post facto sections of
COM-121 from fall 2023. Data were collected to answer the following three research
questions:
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term
and final grades?
2. Is there a significant difference in writing proficiencies, as measured by
course grades, between students who participate in mandatory tutoring and
those who participate in voluntary tutoring, embedded tutoring, or those who
never access tutoring services?
3. What is the relationship between at-risk students (first-generation,
economically disadvantaged, or ethnicity/race) and mandatory tutoring as
measured by success rates when enrolled in a first-year (barrier) writing
course?
Research question one sought to determine the impact of mandatory tutoring as a
potential intervention to increase course success rates. Mid-term and final grades were
the only factors considered as data points in this study. Based on descriptive and
comparison analytical models, the results showed that mandatory tutoring did not
positively impact final grades. Course success rates for mid-term grades (measured by
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mid-term grades of A, B, and C) included 57% for mandatory tutoring, 65% for
embedded tutoring, and 80% for voluntary tutoring. Course success rates for final grades
(measured by final grades of A, B, and C) included 50% for mandatory tutoring. 62% for
embedded tutoring and 74% for voluntary tutoring. In considering the three tutoring
models identified in this study, mandatory tutoring scored the lowest course success rates
in both mid-term and final grades.
Based on mid-term and final grades, research question two used paired T-tests and
ANOVA analytics to determine if a student’s writing proficiencies improved based on the
tutoring model used in a given course. Overall, there was a statistically significant
difference between mandatory, embedded, and voluntary as measured by mid-term grades
based on ANOVA. Similarly, based on ANOVA, a statistically significant difference
existed between the mandatory model and embedded as measured by final grades.
However, there was no statistically significant difference between the mandatory and
voluntary models as measured by the final grade.
Research question three applied Chi-Square tests and Regression analysis to
determine correlations between success rates, at-risk students (first-generation,
economically disadvantaged, or ethnicity/race), and mandatory tutoring. Chi-Square Tests
did not show any association between at-risk students (First-generation status, Pell Grant
status, and ethnicity) and mandatory tutoring as measured by course success rates.
However, Regression analysis showed a positive relationship between at-risk students
and mandatory tutoring as measured by success rate, although the degree of relationship
was very low.
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Summary
Chapter IV has taken an extensive look at the data collected in an action research
study that examined the intervention of various tutoring models in a Communications121 first-year writing course, an identified barrier course at the college where the study
was conducted. A mandatory tutoring approach was considered as an option to increase a
student’s writing proficiencies and their ability to complete the writing course
successfully on the first attempt. Data from a quasi-experimental study in the spring 2024
semester and ex-post facto data from the fall 2023 semester were analyzed, and the
results were presented in this chapter.
Chapter V will use the information from these results to draw conclusions and
suggest recommendations for how these results may be used to further the discussion on
student retention and student success rates in barrier courses at the college. Limitations to
the study and their impact on the validity of the data will also be shared in an effort to
refine, modify, and continue the cycle of action research required to best serve the
students at the college and the unique circumstances they face as students in a community
college environment
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CHAPTER V
Conclusions and Recommendations
One of the most prevalent challenges that community colleges faced in increasing
student retention and persistence came through their use of open-access enrollment. Raby
(2020) referred to open access as “A foundational philosophy of the community college”
(p. 41). This embedded philosophy is a cornerstone principle for all community colleges’
charge to make education available to all students and that no individual will ever be
denied access through a selective admissions process like is used by four-year institutes.
A study by Rheinheimer et al. (2010) showed that tutoring was an overwhelmingly
positive predictor of persistence, retention, and degree completion and claimed that
tutoring was a valuable intervention for future academic success. This type of initial
research became the impetus for considering a mandatory tutoring strategy to be applied
to a Communication-121 writing course at a Southeastern Community College in
Pennsylvania.
Communications-121 (COM-121) was a first-year writing course required of all
community college students and considered one of the top 10 barrier courses. A
barrier/gateway course was identified as a course with success rates of below 70%
completion. COM-121 at the college was required of all incoming students and had a low
success rate of 62% in 2022. This meant that 38% of the students were required to repeat
and successfully complete the COM-121 course before moving on to other program
courses that required COM-121 as a pre-requisite. Students who failed their first attempt
at taking the COM-121 course needed to repeat the course two or three times before
successful completion. Failure to pass a first-year writing course was considered a
potential factor for detrimental impacts on retention, on-time graduation, and course
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success rates. Measuring improvements in these key performance indicators was part of
the college's five-year strategic goals and the justification for the study's focus.
Once a focus for the study was established, the following research questions were
established within a quantitative study. The questions helped to determine if a mandatory
tutoring requirement for first-year writing courses could have a positive impact on
student success rates and retention:
1. What is the impact of mandatory tutoring requirements for increasing course
success rates in a first-year (barrier) writing course as measured by mid-term and
final grades?
2. Is there a significant difference in writing proficiencies, as measured by course
grades, between students who participate in mandatory tutoring and those who
participate in voluntary tutoring, embedded tutoring, or those who never access
tutoring services?
3. What is the relationship between at-risk students (first-generation, economically
disadvantaged, or ethnicity/race) and mandatory tutoring as measured by success
rates when enrolled in a first-year (barrier) writing course?
Additional planning for the study included the identification of the following specific
outcomes to be considered while answering the research questions:
1. To determine if the collected data supports the implementation of mandatory
tutoring for all or some students of the COM-121 writing course
2. To analyze various tutoring practices and their impact on the successful
completion of a barrier course based on mid-term and final grades
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3. To recommend the implementation of some variation of mandatory tutoring for
first-year writing students to increase student retention and on-time graduations
4. To determine if tutor relationships help students improve their self-efficacy as
they transfer acquired knowledge to future program courses
This chapter will use the results from the research questions and outcomes to draw
conclusions and suggest recommendations for using these results to further the discussion
on student retention and success rates in barrier courses at the college. It will also share
limitations to the study and how they impact the validity of the results.
Conclusions
Data was collected from a quasi-experimental study that included four sections of
Communications-121 (COM-121) from the spring 2024 semester and ex-post facto data
from three previous sections of COM-121 from the fall 2023 semester, which included an
embedded tutor. The data set included 144 students in seven sections of COM-121. There
were 44 students in two sections of mandatory tutoring, 35 students in two sections of
voluntary tutoring, and 65 students in three sections with an embedded tutor.
Research Question One: What is the impact of mandatory tutoring requirements for
increasing course success rates in a first-year (barrier) writing course as measured by
mid-term and final grades?
To answer this question, mid-term and final grades were evaluated to determine
the level of successful course completion that occurred by the end of the semester in each
of the three tutoring models. Successful course completion was measured by students
who achieved a final grade of A, B, or C. Withdraws and course grades of D and F were
not considered successful completions. Using this metric, it was determined that a
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mandatory tutoring requirement did not outperform the embedded tutoring model or the
voluntary tutoring model; in fact, mandatory tutoring sections by the end of the semester
had the lowest success rates of 50% compared to 62% for the embedded model, and 74%
for the voluntary tutoring model. The mid-term grades showed similar results, with
mandatory tutoring success rates of 57% compared to 65% for the embedded model and
80% for the voluntary tutoring model.
Based on this study, mandatory tutoring as an intervention did not increase the
course success rates of students in a first-year writing course; however, it is interesting to
note that mandatory and embedded turning rates both increased from mid-term grades to
final grades, while the voluntary tutoring model decreased. Mandatory tutoring also had
the most withdrawals by the end of the semester, with a 39% withdrawal rate compared
to 18% for the embedded mode and 19% for the voluntary model.
The study also compared mandatory tutoring models in final grades between
embedded models and mandatory versus voluntary models. The embedded model was
slightly higher than the mandatory model, with a mean score of 4.66 compared to a mean
score of 3.95 for mandatory tutoring. Additionally, a frequency comparison of grades
showed that embedded tutoring models had more students receiving an A or A- grade;
however, more students in the embedded model received final grades of F than those
students in mandatory tutoring models. Frequencies for student withdrawals were 18.5 %
for the embedded model compared to 38.6% for mandatory modules.
The mean final grades in voluntary tutoring models were also slightly higher
than in the mandatory model, with a mean score of 6.54 compared to 3.95 for
mandatory tutoring. Frequency grade comparisons showed that more students in the
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voluntary model scored an A or A- for final grades. Additionally, fewer F grades were
given to students in the voluntary model than in the mandatory model. Frequencies for
student withdrawals were 20 % for the voluntary model compared to 38.6% for
mandatory modules.
The triangulation of data points to address this research question indicated that the
voluntary tutoring model in this study was shown to be the most successful model for
increasing course success rates by the end of the semester. Mandatory tutoring was the
least effective model for increasing success rates; however, it also had the highest number
of student withdrawals. This variable will be discussed in more detail under the
limitations section of this chapter.
Research Question Two: Is there a significant difference in writing proficiencies, as
measured by course grades, between students who participate in mandatory tutoring
and those who participate in voluntary tutoring, embedded tutoring, or those who never
access tutoring services?
To answer this question, final grades were evaluated to determine the writing
proficiencies achieved by the end of the semester. This did not include individual essay
grades throughout the course. The question looked at the end results based on the applied
tutoring model of mandatory tutoring, embedded tutoring, or voluntary tutoring.
It is important to note that 36 of the 144 students who initially began their writing
course withdrew before the end of the course. Of the remaining 108 students, 85 reached
a level of writing proficiency to pass the course successfully. This included 28 grades of
C, 31 of B, and 26 of A. These final grades indicated that 78% of the students who
completed the course achieved an acceptable level of writing proficiency. Students who
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completed the mandatory tutoring model had 81% writing proficiency, while the
embedded model was 70%, and the voluntary model was 93%.
This research question addressed the writing proficiencies of students who
remained in the course for the entire semester and received course grades of A, B, C, D,
or F. It does not address success rates that included students who withdrew from the
course and impacted the course completion statistics. Based on this metric, This research
question addressed the writing proficiencies of students who remained in the course for
the entire semester and received course grades of A, B, C, D, or F. This starkly contrasted
the success rates for mandatory tutoring at 50% versus the voluntary model at 74% when
withdrawals are included. Students who remained in the course had a 70-plus percent
chance of meeting a successful writing proficiency level, which will also ensure
successful completion of the Communication-121 barrier course for first-year writing.
ANOVA testing used to help answer this question included all final grades and
indicated that there is a statistically significant difference between the mandatory model
and embedded as measured by final grades. However, there was no statistically
significant difference between the mandatory and voluntary models as measured by the
final grade.
The paired T-test data showed the paired sample T-test between the mandatory
tutoring model and voluntary tutoring model as measured by the final grade was ((t (34)
=-2.205), P=0.034). Since the P-value was less than an alpha value of 0.05
(P=0.034<0.05), it implied that the mean difference in writing proficiencies between
students who participated in the mandatory tutoring model and voluntary tutoring model
as measured by final grade is statistically significant. The paired sample T-test between
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the mandatory tutoring model and embedded tutoring model as measured by the final
grade was (t (43) =-0.409), P=0.684). Since the P-value was more than an alpha value of
0.05 (P=0.684>0.05), it implied that the mean difference in writing proficiencies
between students who participated in the mandatory and embedded tutoring models as
measured by final grade was not statistically significant. Overall, the paired sample t-test
shows there was a significant difference between the mandatory and voluntary models,
while there was no statistically significant difference between the mandatory and
embedded models as measured by mid-term and final grades.
Similar to the course success rate data, the voluntary tutoring approach performed
the best, followed by mandatory tutoring and embedded tutoring. The one notable
difference was that the mandatory tutoring model was shown to be the second-best
indicator for writing proficiency for students who completed the course.
Research Question Three: What is the relationship between at-risk students (firstgeneration, economically disadvantaged, or ethnicity/race) and mandatory tutoring
as measured by success rates when enrolled in a first-year (barrier) writing course?
This research question concerned the correlations of demographic data and the
impact of a mandatory tutoring model for the Communication-121 barrier course for
writing. This was particularly interesting to the college due to its designation as a
Hispanic Serving Institute (HIS) and a community college with large populations of
first-generation and economically disadvantaged students who received Pell Grants.
Pearson Chi-square tests were used to show whether variables are associated, and
regressions measured the degree of relationship between variables.
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The Pearson Chi-Square test between first-generation status and mandatory
tutoring as measured by course success rate was 𝜒 (1) = 0.027, 𝑝 = 0.870. Since the Pvalue was more than the alpha value of 0.05 (p=0.870>0.05), there was no statistically
significant association between first-generation status and mandatory tutoring, as
depicted by the success rate. The correlation between first-generation status and
mandatory tutoring as measured by success rate was 0.025 (R=0.025). This implied a
positive relationship existed between first-generation status and mandatory tutoring as
measured by course success rates; however, the degree of relationship was very low.
The Pearson Chi-Square test between Pell Grant status and mandatory tutoring as
measured by success rate was 𝜒(1) = 0.052, 𝑝 = 0.820. Since the P-value was more
than the alpha value of 0.05 (p=0.820>0.05), there was no statistically significant
association between Pell status and mandatory tutoring as measured by success rate. The
correlation between Pell Grant status and mandatory tutoring, measured by course
success rate, was 0.034 (R=0.034). This implied that there is a positive relationship
between Pell Grant status and mandatory tutoring as measured by course success rates;
however, the degree of relationship was very low.
The Pearson Chi-Square test between ethnicity/race and mandatory tutoring as
measured by course success rate was 𝜒 (3) = 3.650, 𝑝 = 0.302. Since the P-value was
more than the alpha value of 0.05 (p=0.302>0.05), there was no statistically significant
association between ethnicity/race and mandatory tutoring as measured by success rate.
The correlation between ethnicity/race and mandatory tutoring as measured by success
rate was 0.144 (R=0.144). This implies that there was a positive relationship between
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ethnicity/race and mandatory tutoring as measured by success rate. However, the degree
of relationship was very low.
Overall, Chi-Square Tests have shown no association between at-risk students
(First-generation status, Pell Grant status, and ethnicity) and mandatory tutoring as
measured by success rate. However, Regression analysis has shown that there is a
positive relationship between at-risk students and mandatory tutoring as measured by
success rate. Although the degree of relationship was very low, a larger sample size could
address this at-risk factor as a future area of interest.
Future Application and Financial Implications of Study Results
This study considered implementing a mandatory tutoring requirement as an
intervention for the Communication-121 (COM-121) barrier courses for first-year writing
students. This strategy was designed to increase retention through course success rates
and to improve writing proficiencies. Data was collected from three types of tutoring
models: mandatory, embedded, and voluntary. Results showed that the mandatory
tutoring model was the least effective in this study; however, the results will be used to
continue discussions and intervention strategies that involve tutoring models and help
inform the Director of Tutoring Services at the college. The college used Title V grant
funding for many of the tutoring initiatives at the college, including the use of funds for
embedded tutoring in barrier courses across multiple disciplines.
The results will be used to recognize the impact of student withdrawals (W) on
their ability to complete a course successfully. This study focused on an intervention to
help students academically succeed by the end of the semester through tutoring options;
however, the study showed that tutoring in any form could not impact students who
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withdrew from the course before its completion. This suggested that more conversations
are needed to consider interventions that can prevent students from withdrawing from a
barrier course. Currently, the reasons for a student’s decision to withdraw from a course
are not tracked and shared with faculty members. Finding ways to mitigate the number of
withdrawals before the student self-initiates a course drop could significantly increase
success rates and retention factors. Preventing a withdrawal could give interventions like
tutoring a better chance of positively impacting course success rates, student retention,
and writing proficiencies.
The tutoring intervention that this study considered could have significant
financial implications if put into practice as a mandatory option. The primary budget
costs for implementing a mandatory tutoring requirement for all COM-121 students
would require hiring up to seven part-time tutors designated to service all COM-121
students in every section and form of modality, including face-to-face, remote, and online
offerings. The quasi-experimental model used in this study was based on each COM121 student receiving a minimum of five 30-minute tutoring sessions per semester. The
fall and spring semesters averaged about 600 enrolled students, and the summer term
serviced approximately 200 students for an estimated implementation cost of
approximately $50,000.00. This cost was based on a tutor's salary of $25.00 per hour,
including 2.5 tutoring hours per student or a student cost of $62.50 per semester.
Limitations
This action research project was limited by several factors that may have
impacted the overall results. The first limitation involved the study's sample size,
which was limited to seven sections across two semesters. 144 students registered for
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Communications-121 (COM-121) sections without any knowledge of the type of
tutoring used in the course. Sections were randomly selected based on one faculty
member’s course load from the spring semesters of 2024. Based on the random
enrollment of the courses, there was no guarantee that all of the at-risk and ethnic
groups to be included in the study would be represented.
The study was also limited by the data points analyzed to determine the results of
each research question. Only mid-term and final grades were collected; however, these
grades represent all assessments throughout the course, not just each of the three required
writing assignments in a COM-121 course. This worked well for the course success rate
data but was not as useful in determining if writing proficiencies increased throughout the
semester. Using grades from the three required writing assignments and their rough drafts
may have provided more valid data for the results in this area.
One final limitation that emerged when analyzing the data was the number of
student withdrawals from each section of the study. The college was required to report
students who withdrew from a course as having failed to complete it. This similarly
affects students who remain in the course and receive a grade less than C as a final grade.
Course success rates measure the number of students who finished the course with grades
of an A, B, or C. Students who withdrew from a course or had a final grade of D or F
counted against a faculty member’s course success rate data for each section taught.
Students may have withdrawn from courses for various reasons, but that data was not
collected in this study. Contributing factors may have been conflicts due to family
emergencies, financial issues, work conflicts, or other life-related issues. This unknown
variable may have helped to understand why there was such a large number of
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withdrawals from the mandatory sections and if the mandatory requirement played a role
in the student’s decision to withdraw.
Table 20 shows the significant difference in course success rates when the
withdraw (w) grades are removed from the results. The mandatory tutoring model, minus
withdraws, showed success rates of 81%, which outperformed the embedded model by
11%. The voluntary tutoring model was still the best tutoring model at 93%. The
implications of these results showed that more attention needs to be focused on
preventing student withdrawals from happening in the first place. The baseline for course
success rates in this study was 62% for all sections of COM-121 taught during the 202223 semesters. With withdrawals included in the success rate formula for this 2023-24
study, the mandatory and embedded models fell below 62%, and the voluntary model
exceeded the baseline by 12%. When withdrawals were not a determining factor for
course success rates, all three models showed scores above 62%. Once again, the
voluntary model was the best-performing model, with embedded tutoring being the
lowest-performing model.
Table 20
Success Rates Including and Excluding Withdraws
Model
N Count
Success
Rates
A, B, & C
Grades
Completed
D, F
Grades
Withdraws
Before
Completion
Success
Rates with
Withdraws
Success
Rates
Without
Withdraws
Mandatory
Voluntary
Embedded
44
35
65
50%
74%
57%
11%
7%
25%
39%
19%
18%
50%
74%
57%
81%
93%
70%
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Recommendations for Future Research
This study did not produce results that suggested implementing a mandatory
tutoring model for all students; however, this study, combined with information obtained
through the literature review, did support tutoring as an intervention to increase course
success rates, retention, and writing proficiencies. Future research may be needed to
expand upon the very low (but important) relationships that were found between at-risk
students and mandatory tutoring. The new research may need to move from a quantitative
study to a mixed-method design that could capture student and faculty data to better
understand why different tutoring models produce different student outcomes and why
students withdrew from the Communictions-121 (COM-121) barrier course. Other
considerations should be addressed, such as the COM-121 curriculum and the
consistency of course delivery based on individual teaching styles and levels of student
engagement.
Further consideration should also be centered on finding solutions to mitigate the
number of students withdrawing from a course before its completion. Tutoring was the
predominant form of academic support available to students on campus, but according to
the Director of Tutoring Services, the number of students who took advantage of this help
is limited. Only about 11% of the enrolled students took advantage of the free services
from the tutoring center. New or future interventions could include a tutoring variable to
be implemented for any student who shows early signs of struggles that could lead to a
student withdrawal if not addressed. This could include a tiered intervention system, such
as any student who falls below a C average must attend tutoring sessions until their grade
improves, or a student with a failing mid-term grade must attend tutoring sessions until
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their grade increases by a defined percent. This would allow a differentiated approach to
tutoring that would address the most vulnerable students in jeopardy of failing.
The embedded tutoring model, which was the second most effective tutoring
strategy, should also be evaluated to consider ways to make the embedded model have a
mandatory component based on the tiered intervention system. Embedded tutors at the
college were able to access student grades, monitor progress, and review late assignment
to reach out to students proactively. They were also present in the classroom as a student
resource during instruction and when students were given in-class time for writing. The
embedded tutors emailed students to encourage them to make appointments and were
available before and after class for questions; however, the current model did not require
students to use the embedded tutor as a resource. The embedded model could be modified
to force an intervention at designated time frames or specified grade ranges. Embedded
tutoring may be the best proactive model to help prevent a student from withdrawing,
especially if writing is not a strength for the student or if they have low self-confidence or
self-efficacy for seeking help. Embedded tutors were limited in the number of COM-121
sections assigned to them; however, using embedded tutors in all sections of COM-121
may need to be considered.
Finally, future studies on tutoring interventions should consider the quantitative
data collected from student surveys during the quasi-experimental component of this
study. That data showed that students who used tutoring as a resource overwhelmingly
believed that it helped their writing and that they would recommend tutoring to other
students. They also stated that they believed tutoring improved the quality of their
writing, and they would be inclined to use tutoring for future courses. This information
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showed that tutoring is making a difference for the students who accessed the free
services available to them at the college. This data suggested that ongoing reflection and
modifications to those services should remain a strong focus for the future.
Summary
This chapter has been a reflective process in determining the conclusions that can
be drawn from a qualitative action research study that focused on using a mandatory
tutoring requirement for first-year writing students. Communications-121 (COM-121)
was a required writing course for all students at a two-year community college in
Southeastern Pennsylvania, and passing with a C or better grade was necessary to
continue taking courses that required COM-121 as a pre-requisite. The journey in the
development of this study began with a basic needs assessment that isolated a problem
area at the college. The needs assessment determined that 38% of all students taking
COM-121, a top-ten barrier course for the college, failed to pass the course on their first
attempt. A tutoring intervention to help increase course success rates, retention, and
writing proficiencies for students was considered and implemented in a quasiexperimental study for the spring 2024 semester.
An initial review of existing research revealed several key factors that became the
focus of the action research and included 1) tutoring was shown to have positive impacts
on student success, 2) students often did not access tutoring due to fear of showing
weakness, 3) students lacked self-efficacy to help themselves, 4) students who failed
barrier courses lead to retention issues, and 5) community colleges had unique challenges
for educating students due to open-access practices.
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All of these key factors suggested a framework based on Tinto (1975) and his
seminal research in retention. Tinto (2017) was a strong voice in the area of persistence
with his assertion that “…student retention has been shaped by theories that view student
retention through the lens of institutional action and ask what institutions can do to retain
their students. Students, however, do not seek to be retained. They seek to persist” (p.
254). This action research study was built on Tinto’s belief that there needed to be strong
institutional support for students to improve their self-efficacy, to belong to a community,
and to have supportive resources for helping students. All of these conditions were met
within this study.
The conclusions of this particular study did not support the premise that a
mandatory tutoring component would be the best intervention to apply for increasing
course success rates, student retention, or writing proficiencies; however, limitations to
the study may have influenced the outcomes of the results, particularly because of the
impact from student withdraws. A student’s reason for a course withdrawal may range
from personal issues to a fear of writing or because the section has a mandatory tutoring
requirement. However, when withdrawals were removed from the data, the mandatory
turning model showed an 81% course success rate but was still second to the voluntary
tutoring model with a 93% course success rate. Embedded models were 70%.
The data obtained through the student exit surveys from the quasi-experimental
study were telling. Tutoring positively impacted students who chose to use the resources
provided by the college. They were building sustainable relationships with a professional
staff member that helped them to grow self-efficacy skills and to transfer the knowledge
they received to other courses throughout their college career. The students recognized
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the positive benefits of using the college’s tutoring services, and they overwhelmingly
said they would use tutoring again in other courses and would recommend tutoring to
their classmates. Whatever model is used, the tutoring process can change a student’s
academic trajectory, contribute strongly to a student’s academic proficiency, and
contribute to positive retention practices that will help ensure increased course success
rates, retention, writing proficiencies, and on-time graduation at the community college
level.
Finally, this action research study has helped this researcher, who is new to the
community college environment, gain tremendous respect for the role community
colleges play in the education and advancement of students in Pennsylvania. Community
colleges and their use of open access for all students have required them to be strong
community partners with the flexibility and autonomy to create programs and technical
training that meet the needs of all community members. The community college used in
this study embraced four hallmarks at the core of a comprehensive community college:
hope, access, opportunity, and excellence. Responding to the needs of students and the
community was at the cornerstone of this action research study, and the data collected
will help to ensure that the philosophy represented by the four hallmarks will continue
through the use of the systematic process of action research and the repeating cycles of
reflection, action, and evaluation.
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APPENDICES
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Appendix A
Student Survey: Control Group
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Appendix B
Student Survey: Experimental Group
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Appendix C
IRB Approval Letter – Pennsylvania Western University
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Appendix D
Confirmation Email for the Addition of Two Student Surveys
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Appendix E
Permission Letter Reading Area Community College
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