Persistence and Retention of Adult Learners: Results of A Program Evaluation of Tuition

Funding Provided by Employers

_________________

A Dissertation in Practice

Presented to

the Faculty of the Morgridge College of Education

University of Denver

__________________

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Education

__________________

by

Andrea J. Gross

August 2023

Advisor: Dr. Cecilia M. Orphan

© Copyright by Andrea J. Gross 2023

All Rights Reserved.

Author: Andrea J. Gross
Title: Persistence and Retention of Adult Learners: Results of A Program Evaluation of
Tuition Funding Provided by Employers
Advisor: Dr. Cecilia M. Orphan
Degree Date: August 2023

ABSTRACT

As the looming enrollment cliff approaches and more adult learners return to

higher education, understanding the factors that affect their persistence and retention is

vital for higher education institutions. Previous studies have shown that external factors

influence post-traditional learners’ pursuit of higher education. This program evaluation

aimed to acquire knowledge of up-front employer tuition funding and its effects on adult

learners' persistence, retention, and time to degree completion. Through a quantitative

approach, this program evaluation examines the differences between students receiving

up-front employer tuition funding and those who do not. The results indicated that

students who received employer funding retained at higher rates than those who did not

across all programs except graduate certificates. The length of time and cost of the degree

affect how influential employer tuition funding is for the adult learner. The results also

indicated that employer tuition funding affects completion time while influencing a

student’s decision to return to higher education. Recommendations for consideration

include locking tuition rates for those who remain active with continuous enrollment,

reviewing transfer policies for undergraduate students to increase the courses allowed to

be used for transfer credits, awarding Prior Learning Assessment (PLA) credit for

college-level level knowledge and competencies at both the undergraduate and graduate-

levels, increasing scholarship opportunities for Master-level students, creating

articulation agreements with statewide community colleges, and reengage students who

ii
have stopped out by offering discounted or locked tuition to return. Understanding the

academic journey for adult learners and the influence employer tuition funding can help

institutions formulate practices and facilitate degree completion within the post-

traditional student population.

Keywords: post-traditional learner, adult learner, retention, persistence, stop-out, higher

education, employer tuition funding, cost

iii
 ACKNOWLEDGMENTS

Throughout this journey, I felt supported, encouraged, cheered on, and challenged

by many individuals. The list of those to thank is long, but I begin by thanking my wife,

Gini, who is my rock. She has supported me throughout my journey of completing my

EdD as I worked early morning and weekends, and she likely knows more about post-

traditional learners and retention than she has ever wanted to know. She provided

encouragement and a listening ear and was my biggest cheerleader throughout, even

when the alarm clock would go off at 3:00 a.m. Thank you to my committee: Dr. Cecilia

Orphan for being my advisor and champion, and for the endless edits and revisions

needed to get me to this place, Dr. Chris Nicholson for sparking my passion for serving

the adult learner, as well as your continued mentorship and support over the past nine

years, and for Dr. Laura Sponsler for supporting me during the final stretch of my

dissertation. Thank you to Dr. Bobbie Kite, my honorary committee member, for her

support, guidance, and mentorship throughout my dissertation's data collection and

analysis. A special thank you to my family and friends: to my parents, Art and Chris

Gross, who believed in me and have always challenged me to chase my dreams, to my

sister, Dr. Nicole Bartholomew, for sharing her expertise and lending a listening ear, and

to my friends who cheered me on along the way. Thank you to those colleagues who

completed their journey before me and alongside me for their critical thought partnership

and accountability. Thank you to my writing partners, Diana and Allyson; they provided

the accountability, friendship, and encouragement I needed to finish. Finally, thank you to

University College and my colleagues for their support over the past seven years.

iv
 TABLE OF CONTENTS

Chapter One: Introduction ...................................................................................................1

Preface......................................................................................................................1
Introduction ..............................................................................................................3
Problem Statement ...................................................................................................5
Purpose of Program Evaluation ...............................................................................8
Guild and University College Partnership ...............................................................9
Research Questions and Hypotheses .....................................................................10
Theoretical Framework .......................................................................................... 11
Methodology Summary .........................................................................................13
Results Summary ...................................................................................................13
Significance of Research........................................................................................14
Definition of Terms ................................................................................................16
Dissertation Overview ...........................................................................................18

Chapter Two: Literature Review ........................................................................................20

Historical Look at Retention ..................................................................................21
Retention Theory ...................................................................................................28
External Factors Impacting Retention ...................................................................40
Employer Funding Impact on Retention ................................................................43
Professional, Continuing, and Online Education Units .........................................47
Theoretical Framework ..........................................................................................49
Conclusion .............................................................................................................55

Chapter Three: Methodology .............................................................................................58

Evaluation Theory ..................................................................................................58
Problem Statement .................................................................................................62
Theoretical Framework ..........................................................................................63
Research Questions and Hypotheses .....................................................................64
Research Design.....................................................................................................66
Site Description......................................................................................................68
Selection of Participants ........................................................................................72
Instrumentation ......................................................................................................74
Assumptions...........................................................................................................75
Data Processing and Analysis ................................................................................77
Limitations and Delimitations................................................................................79
Positionality ...........................................................................................................82
Conclusion .............................................................................................................84

Chapter Four: Results ........................................................................................................85

Program Evaluation Purpose and Research Questions ..........................................85
Analyses of Guild and Organic Retention .............................................................86
Summary of Results .............................................................................................102

v
Chapter Five: Discussion, Implications, and Recommendations.....................................105
Introduction ..........................................................................................................105
Research Questions ..............................................................................................106
Summary of Results ............................................................................................108
Discussion of Results and Recommendations .....................................................109
Stakeholder Recommendations ............................................................................ 114
Suggestions for Further Research ........................................................................ 116
Evaluation Conclusion ......................................................................................... 118

Bibliography ....................................................................................................................121

Appendices .......................................................................................................................135
Appendix A. Visual Representation of Theoretical Framework ..........................135
Appendix B. Bean and Metzner (1985) Conceptual Model of Nontraditional
Undergraduate Student Attrition ..........................................................................136
Appendix C. Summary of Persistence/Retention Models, Frameworks, and
Key Ideas .............................................................................................................137
Appendix D. Historical Look at Retention ..........................................................139
Appendix E. Hallie Preskill (2012) Mutually Reinforcing Relationships
Between Strategy and Process .............................................................................140
Appendix F. Letter Requesting Use of Archived Data ........................................141

vi
 LIST OF TABLES

Chapter One: Introduction ...................................................................................................1

Table 1.1 Key Terms with Definitions ...................................................................16

Chapter Three: Methodology .............................................................................................58

Table 3.1 Guild Employer Partners and Launch of Partnership ............................71
Table 3.2 Guild Funding Levels.............................................................................78

Chapter Four: Results ........................................................................................................85

Table 4.1 Two-Sample T-Test with Unequal Variances–Guild/Organic
All levels Num Cred=1 ..........................................................................................87
Table 4.2 Two-Sample T-Test with Unequal Variances–Level=Grad
Num Cred=1 ..........................................................................................................88
Table 4.3 Two-Sample T-Test with Unequal Variances–Level=UG Num
Cred=1 ...................................................................................................................89
Table 4.4 Two-Sample T-Test with Unequal Variances–Degree=MS
Num Cred=1 ..........................................................................................................90
Table 4.5 Two-Sample T-Test with Unequal Variances–Degree=MA
Num Cred=1 ..........................................................................................................91
Table 4.6 Two-Sample T-Test with Unequal Variances–Degree=CRTG
Num Cred=1 ..........................................................................................................92
Table 4.7 Two-Sample T-Test with Unequal Variances–Degree=CRTM
Num Cred=1 ..........................................................................................................92
Table 4.8 Two-Sample T-Test with Unequal Variances–Level=GR
(MS and MA only) Num Cred=1 ...........................................................................94
Table 4.9 Regression Time to Completion Guild_Age_GPA_Race_
Gender if Degree=MS, MA, BA Num Cred=1 ......................................................97
Table 4.10 Regression Time to Completion Guild_Age_GPA_Race_
Gender if Degree=MS, MA Num Cred=1 .............................................................98
Table 4.11 Regression Time to Completion Guild_Age_GPA_Race_
Gender if Degree=BA Num Cred=1 ......................................................................99
Table 4.12 Regression Time to Completion Guild_Age_GPA_Race_
Gender if Degree=MS Num Cred=1 ....................................................................100
Table 4.13 Regression Time to Completion Guild_Age_GPA_Race_
Gender if Degree=MA Num Cred=1 ...................................................................101
Table 4.14 Descriptive Statistics for Independent Variable by Degree................104

vii
 LIST OF FIGURES

Chapter Two: Literature Review ........................................................................................20

Figure 2.1 The Undergraduate Dropout Process Model ........................................30
Figure 2.2 The Institutional Departure Model .......................................................32
Figure 2.3 The Student Attrition Model .................................................................34
Figure 2.4 The Student-Faculty Informal Contact Model......................................36
Figure 2.5 The Non-Traditional Undergraduate Student Attrition Model .............38
Figure 2.6 The Student Retention Integrated Model .............................................39
Figure 2.7 Theoretical Framework Used for Program Evaluation.........................50

viii
 CHAPTER ONE: INTRODUCTION

Preface

Susan finds herself at a crossroads yet again, the same one she has found herself

standing at in the past. Each time she has hit this crossroad, she has chosen to pivot

toward a different path and, yet again, finds herself at the very crossroad she stood at

years before. Susan continues to get stuck at the crossroads of education and career

advancement. She feels stuck on the corporate treadmill; her experience has helped her to

advance her career; however, she feels stagnant because others are passing her by, and

she has reached the ceiling for career advancement. She needs something more to

advance in her career, provide for her family, and attain her personal and professional

goals. Might furthering her education be the answer? Will an additional credential allow

her to break through the ceiling? She has what seems to be a hundred responsibilities on

her plate. Is it the right time to add another competing priority to her already hectic life?

She has been thinking of taking the leap, and her spouse is supportive but is the

investment of her time and money worth it for her and her family, and is additional

education the answer for her to advance her career?

After months of contemplation and her exhaustion from the corporate treadmill,

Susan was thrilled when her company announced that they had changed their educational

tuition benefits for their employees. This new policy will eliminate the requirement for

employees to pay tuition upfront and then be reimbursed by the company. Instead, the

1
company will cover tuition costs immediately. She needed this push to finally take the

leap and pursue additional education to advance her career. Her employer's change in

tuition funding policy significantly reduces her financial burden. She understands that

taking this leap means she will need to sacrifice her time and energy; however, the

reduction of financial costs makes this education endeavor possible, and she is excited

about this opportunity to reenter higher education. She plans to take advantage of the

opportunity to grow personally and professionally, and now that her dream is a reality,

her next step is to find the program that will help her take her career to the next level.

Susan is so grateful and excited for this opportunity for her and her family as they are all

in it together.

While this is a glimpse into Susan’s career and educational state, she is not much

different from Arthur, Angela, Michael, Louis, or the countless other post-traditional

learners who desire further education to advance their careers. This vignette tells the story

of a fictional character to demonstrate the millions of adult learners contemplating taking

the leap back into higher education and the challenges they face while pursuing higher

education (NCES, 2020). Some will return to complete the bachelor’s degree they started

years ago, others to upskill or reskill with certificates, and others to earn master’s degrees

(UPCEA, 2017). Millions of adult learners are and will continue to return to higher

education. Understanding how to support them in their academic journey is vital in

helping them persist and retain throughout their programs (Carnevale et al., 2015). The

persistence and retention of adult learners need to be at the forefront of postsecondary

administrators’ minds as this student population continues to grow.

2
Introduction

Across the United States, post-traditional learners–ages 25 and older, account for

56% of the students enrolled in postsecondary education (National Center for Educational

Statistics, 2022). These learners face obstacles different from those of students ages 18-

23. Finding the delicate balance required to excel academically while juggling the

competing demands of work, life, and family can be challenging for adult learners.

Thirty-eight percent of adult learners will drop out in their first year due to financial

pressure and family obligations (National Adult Learner Coalition, 2017). The impacts of

adult students stopping out extend beyond the higher education institutions they depart

from. Their departure impacts not only their lives but also the lives of their families and

communities. College graduates experience higher employment rates and personal

earnings compared to those who do not have a degree (Pew Research Center, 2014).

Individuals with four-year degrees have greater career mobility and are more likely to

vote and be engaged in their communities (UPCEA, 2017). Persistence and retention of

adult learners is an area that needs more research to fill the gaps of understanding on how

to best serve this growing student population.

While many institutional leaders across the country are thinking strategically

about how to provide access to the millions of adult learners through online education,

micro-credentialing, and technical degrees (Fong et al., 2017; Nichols, 2019), they must

also navigate the obstacles that impede their progress toward degree completion.

University College–University of Denver’s Professional and Continuing Education unit

has partnered with Guild to help attract, serve, and retain post-traditional learners. Guild

3
serves as the conduit between employers and higher education institutions to provide

educational opportunities for America’s workforce. Guild is a female-founded

organization whose mission is to unlock opportunities for America’s workforce through

education, upskilling, and opportunity (Guild website, n.d.). Guild’s focus is to transform

traditional tuition reimbursement, where an organization or company reimburses the

employee after the completion of a course, into a strategic investment that aligns

employees with company needs, therefore, increasing recruiting, retention, upskilling,

and brand equity in the process (Guild website, n.d.). Guild focuses on providing

opportunities to those who traditionally are not offered the opportunity to advance their

careers (Guild: You’re your talent rising, April 12, 2023). Guild’s approach is to reduce

the financial stress for the employee and not require the employee to pay the tuition up-

front, as few employees take advantage of the benefit when a company sets up the benefit

as a reimbursement versus up-front funding (EdAssist, 2012). Instead, Guild eliminates

the high out-of-pocket expenses and partners with companies and higher education

institutions to offer tuition funding up-front instead of as a reimbursement. This up-front

tuition funding is a win-win for employees, employers, university partners, communities,

and the economy (Gallup-Lumina Foundation, 2021).

University College began its partnership with Guild in 2017 and remains the only

Top-Ranked institution partnered with Guild. During the time frame of this program

evaluation, University College admitted, on average, 100-150 new students through the

Guild partnership across their academic programs each quarter (Guild Admissions

Report, 2023). University College has admitted approximately 2,600 students into a

University College program through the partnership with Guild, and this population

4
continues to grow as they admit between 50-70 new students each quarter (Guild

Admissions Report, 2023). Of these students, this program evaluation will focus on the

1,005 who have completed their degree(s) or credential(s) through one of University

College’s academic programs as of the fall 2022 quarter. These students have completed

the requirements for one or more of the following programs, Bachelor of Arts

Completion, Master’s, and Graduate Certificates. The Graduate Certificates consist of

four-course Specialized Graduate Certificates and six-course Graduate Certificates. With

the continued growth of the partnership and more than five years’ worth of data, this

program evaluation evaluated the effect of Guild employer tuition funding on the

persistence, retention, and time to degree completion of post-traditional learners as the

program evaluation compared students entering through the Guild partnership to those

who entered organically or not through the Guild partnership.

Problem Statement

Over the past 15 years, higher education institution leaders and policymakers have

increased their focus on retention, making retention a significant field of study across

different student classifications (Berger et al., 2005). Higher education institutions have

prioritized enhancing persistence and retention by examining various student populations

and their unique characteristics to determine the essential factors needed to support

students (Paulsen & St. John, 1997, 2002; Chen & Hossler, 2017; Tran & Smith, 2017).

Much of the research focuses on social integration, how connected a student is to the

institution, faculty, and other students (Tinto, 1993), self-efficacy, belief in their ability to

achieve or influence academic outcomes (Bandura, 1977), and belonging, student’s

perception of acceptance and affiliation with members of a group whom they share

5
similar attitudes, values, and goals (Braxton, 2014), and while each of these is important

factors, failing to understand the role funding plays leaves a significant gap in the

research. Continued research on post-traditional learners and the influence employer

funding may have on their ability to persist and retain toward degree completion is vital

to serving the growing adult student population. Bean and Metzner (1985) state, “The

chief difference between the attrition process of traditional and non-traditional students is

that non-traditional students are more affected by the external environment than by the

social integration variables affecting traditional student attrition” (p. 485). 1 Funding is a

crucial part of the external environment for adult learners as they often have more

financial obligations than traditional-aged students.

Many factors influence adult students' stop-out behaviors, including childcare,

family commitments, work demands, lack of flexibility from the institution, faculty-staff

connection, motivation, and cost (Bergman et al., 2014; Erisman & Steele, 2015; Merrill,

2015; Pearson, 2019; Renner & Shursha, 2022). These stop-out behaviors influence

retention and increase the time to degree completion. Even though these external

environmental factors affect persistence and retention, researchers often lump tuition

costs in with other factors, minimize external environmental factors, or even ignore them

when studying retention across all student populations. Research has demonstrated that

financial support positively affects college completion (Chen & Hossler, 2017; Pearson,

2019; Tran & Smith, 2017). According to labor statistics, adult degree programs are

crucial in meeting the growing demand for an educated workforce and are vital for the

1
Note that Bean and Metzner (1985) use the term non-traditional student when referring to the post-
traditional or adult learner. In this paper, this student population will be referred to as post-traditional or
adult learners to distinguish but not “other” this unique and growing population.
6
stability and growth of a nation's economy. There are more than 166 million people in the

U.S. workforce (Statista, 2023), and there are 20.3 million who are 25 and older with

some college but no degree (Causey et al., 2023). However, degree programs geared

toward the post-traditional learner often struggle with low student retention rates

(Bergman et al., 2014). As companies continue to partner with higher education

institutions and third-party organizations to help educate their workforce, research is

needed to understand how these tuition funding models affect the persistence and

retention of adult learners. Reducing the financial costs for the adult learner positively

influences a student’s persistence, retention, and time to degree completion (Chen &

Hossler, 2017; Tran & Smith, 2017). Reducing financial costs is critical to increasing the

retention rates of this unique student population. The benefit of tuition funding stretches

beyond the students themselves and affects the lives of their families, their communities,

and the overall economy (McKinsey Global Institute, 2021). Covid-19 has amplified the

employment gap for women, minorities, non-college-educated workers, and lower-wage

workers (McKinsey Global Institute, 2021). Economic recovery and employment levels

for women, those with lower income jobs, and lower educational attainment are expected

to lag behind and unlikely to recover by 2024 (McKinsey Global Institute, 2021). A

significant gap in the research on persistence and retention is the role of external factors,

specifically finances, in shaping a student’s commitment to retaining toward degree

completion.

Understanding the history of persistence and retention in the American higher

education system and building upon the already established retention theories will help

educators continue to best attract, serve, and retain the variety of student populations on

7
their campuses who attend in person and/or virtually. Efforts to find the solutions to the

retention problems we face across higher education need to be as unique as the student

populations served, and with the growing percentage of adult learners returning to high

education (National Center for Educational Statistics, 2022), researching the effects of

employer tuition funding on persistence and retention is critical to serving the adult

learner and the institutions enrolling these learners into their programs. The higher

education landscape is changing, and more post-traditional learners are entering higher

education across all types of institutions (Miller, 2014); thus, there is a need for research

to analyze how cost affects persistence, retention, and time to degree completion.

Purpose of Program Evaluation

Understanding the factors that affect their persistence and retention is vital for the

higher education institutions that admit these students. Previous studies have shown that

cost is a driving factor influencing post-traditional learners’ pursuit of education

(Bergman et al., 2014; Chen & Hossler, 2014; Tran & Smith, 2017). Evaluating the

University College and Guild partnership from both a use and methods perspective

provided an understanding of the influence of up-front employer tuition funding and

begins to fill the gap in research on how up-front employer tuition funding influences

persistence and retention for adult learners. It is common for companies to offer tuition

benefits as part of their benefits package to attract and retain employees. Research has

shown that tuition benefits are beneficial in increasing employee retention (Cappelli,

2004); however, the benefits for students and the influence these benefits have on

persistence and retention through to degree completion are less understood. This

quantitative program evaluation aimed to acquire knowledge of up-front employer tuition

8
funding and its effects on adult learners' persistence, retention, and time to degree

completion. Understanding how adult learners progress through degree completion and

the influence employer tuition funding has can help institutions formulate practices and

facility degree completion within the post-traditional student population. Providing

access and support to the millions of adult learners across all institution types helps lessen

the higher education equity gaps and meets workforce needs.

Guild and University College Partnership

Guild is an Ed Tech company that serves as the conduit between employers and

higher education institutions–often through Professional, Continuing, and Online

Education (PCO) units, by building strategic education and reskilling experiences. Guild

was founded in 2015 by Rachel Romer on a belief: “when opportunity is as evenly

distributed as talent, everyone benefits. Individuals rise, companies, grown and our

economy thrives” (Guild website, 2023, About Us section). Guild has expanded employer

tuition benefits beyond white-collar and salary employees into blue-collar occupations

and for hourly employees (Romer, 2023). Guild is a Denver-based company that serves

students and employers across the country and remains focused on equity and inclusion

within the educational benefits offered. Half of the students who completed a program

through one of Guild’s educational partners identify as a person of color, and 59%

identify as female (Guild website, 2023). Guild focuses on transforming traditional

tuition reimbursement into a strategic investment that aligns employees with company

needs, increasing recruiting, retention, upskilling, and brand equity (Guild Website,

2023). The partnership between University College and Guild began in 2017, and the

number of students in the program continues to grow as Guild adds new employers to

9
their employer portfolio. In 2019, Guild (formerly Guild Education) became a unicorn (a

startup company with a value of over one billion dollars) following a 157-million-dollar

fundraising round (Toussaint, 2020). In 2021, Guild offered more than 4.4 million

employees’ access to higher education through their partnerships with employers and

higher education institutions (Mann, 2023). During the 2021 calendar year, 310,000

employees took advantage of this benefit (Mann, 2023). As Guild continues to grow and

the Guild and University College partnership continues to mature gaining insight from

this partnership can lead to transformative change for University College and the students

they serve.

Research Questions and Hypotheses

In this program evaluation, I examine how up-front employer tuition funding

affects persistence, retention, and time to degree completion for post-traditional learners.

The following research questions guided the evaluation of the external partnership

between the University of Denver’s University College and Guild.

1) How does the retention of post-traditional students who receive funding

through the Guild partnership compare to students who do not receive this

funding?

2) How does time to time to degree completion for post-traditional students

compare across different funding levels?

3) How is the retention of post-traditional students affected by age, GPA, race,

gender, and employer tuition funding?

Little is known about post-traditional learners' enrollment and completion patterns, and

these research questions will provide insight into how employer tuition funding

10
influences persistence, retention, and time to degree completion for the post-traditional

student population. I hypothesize that there will be a positive relationship between up-

front employer tuition funding and persistence and retention and a negative relationship

between up-front employer funding and time to degree completion. In this evaluation, I

examined the effect of up-front employer tuition funding on various student populations,

including Bachelor of Arts Completion, Master of Science, Master of Arts, six-course

Graduate Certificates, and four-course Specialized Graduate Certificates. Finally, I

hypothesize that up-front employer tuition funding will influence retention most when

testing the independent variables of age, GPA, race, gender, and up-front employer tuition

funding for tuition and fees.

Theoretical Framework

The theoretical framework that supports this program evaluation comprises three

separate theories, each essential in understanding the persistence and retention of post-

traditional learners. Bean and Metzner’s (1985) Conceptual Model speaks of the

differences between traditional and post-traditional learners, pointing to the need for

further exploration of external environmental factors, including but not limited to cost,

when researching the effects of external environmental factors on persistence and

retention for post-traditional learners. Bean and Metzner built their model upon the

groundwork of organizational turnover, and one of the educational factors for degree

completion for the post-traditional student population is the perceived value of earning

the degree. Therefore, this is a fitting framework as it not only focuses on the post-

traditional learner, but I am using it to evaluate employer tuition funding. Employers

offer tuition benefits to help with employee retention and reduce organizational turnover.

11
The overall perceived value from Been and Metzner’s model can be explained further

with Human Capital Theory. I used Human Capital Theory to examine students as

product consumers and explain the cost-benefit analysis influencing post-traditional

learners (Long, 2007). Adult learners approach their return to higher education as a

business decision that affects not only the decision to begin a degree but also the decision

to continue toward degree completion (Bowers & Bergman, 2016). These theories serve

as the foundation of this program evaluation and strengthen the argument for up-front

employer tuition funding, increasing persistence and retention of post-traditional learners.

Employers who offer tuition benefits that pay for tuition up-front have a higher

percentage of employees engaging with the benefit than those who offer tuition benefits

as reimbursement (EdAssist, 2012). As the employer shares the funding costs, the

student’s return on investment increases considerably, reducing the financial burden for

the student. Understanding how the adult learner engages throughout their academic

journey through these two theories can help higher education leaders and policymakers

strategically approach persistence and retention for this population. The final theory used

is the Evaluative Inquiry for Learning in Organizations (EILO) (Preskill, 1999), which

allows for a reflective practice of strategic organizational practices and the application of

findings to improve persistence and retention for adult learners. I designed this program

evaluation to provide results that can guide how higher education leaders approach

strategic planning and organizational change when navigating the complex problem of

persistence and retention for adult learners. A visual representation of the theoretical

framework is available in Appendix A.

12
Methodology Summary

I used a quantitative approach to answer each research question in this program

evaluation. Through a statistical program, Stata, I analyzed archived data between 2017

and 2022 of University College students who completed their program(s) of study. I used

correlation and multiple regression to examine the relationship between the independent

variables (age, GPA, race, gender, and employer funding for tuition and fees) on the

dependent variable, retention, for different sample groups (Guild and Organic students). I

also utilized t-tests to compare the time to completion for those students funded by Guild

and those who are not. Aside from running statistical tests on just the overall Guild and

Organic populations, I also tested based on level of degree (graduate and undergraduate)

as well as by degree (Bachelor of Arts, Master of Science, Master of Arts, six-course

Graduate Certificate, and four-course Specialized graduate Certificate) of both Guild and

Organic students. Finally, I conducted a Kruskal Wallis Test to examine different levels of

employer tuition funding and the effects on time to degree completion. The three funding

levels included unlimited employer tuition funding, some employer tuition funding, and

no employer tuition funding.

Results Summary

The results suggest that employer funding significantly affects the time to degree

completion for each population tested except for six-course and four-course graduate

certificates. Employer tuition funding had the most significant influence on the students

who completed a Bachelor of Arts, followed by those in Master of Arts programs and

those in Master of Science programs. The length of a student’s program and the cost

associated with the program were likely contributing factors, as no significant effect was

13
found in either six-course or four-course Graduate Certificates. While the results suggest

employer tuition funding affects the time to completion and retention, employer tuition

funding was not the most influential factor. The independent variable GPA had the

greatest influence on time to completion across every population tested, followed by

employer tuition funding. The results align with Bean and Metzner’s (1985) model that

for the adult learning population, external environmental factors are important to

understanding the persistence and retention of post-traditional learners; however, the

factors that affect persistence, retention, and time to degree completion are as complex as

the learners themselves. The results also suggest that post-traditional learners with

unlimited employer tuition funding will complete their degrees the fastest, followed by

learners with no employer tuition funding and, finally, learners with some employer

tuition funding. These results align with Human Capital Theory, showing that post-

traditional learners decide to return to higher education and persist toward completion

based on a decision of return on investment (ROI) (Bowers & Bergman, 2016). Employer

funding plays a role in this ROI evaluation for the post-traditional learner, thus increasing

the likelihood that they will be retained and graduate.

Significance of Research

University College is the continuing and professional education unit of the

University of Denver. University College serves over 3,000 adult learners annually in

undergraduate and graduate academic programming and is the largest graduate school at

the University of Denver. University College facilitates postsecondary access to the most

diverse population of students on the University of Denver’s campus–90% have full-time

jobs while enrolled in classes, 65% reside outside the state of Colorado, 64% identify as

14
female, 25% identify as students of color, 10% are active duty or veteran students, and

the average age of students is 32 (University College Enrollment Report, 2022). To

effectively serve this unique population, educators and practitioners must understand the

academic journey of adult learners and how it differs from traditional-aged students.

Manchester (2008) states that the two primary reasons employers participate in

tuition funding programs are to promote employee retention and increase recruitment. As

employers continue to expand and rethink their tuition funding to attract and keep highly

skilled employees, research on the effects of tuition benefits should be a focus for

educational institutions. Tuition assistance programs create opportunities for companies

to develop their current employees and attract new employees. Much of the research and

studies on tuition benefits are from the vantage point of the employer assessing the

effectiveness of these benefits to the companies and their employees from a workplace

setting (Cappelli, 2004; Flaherty Manchester, 2012; Gallup-Lumina Foundation, 2016; St.

Amour, 2020). What is missing is an understanding of how these tuition benefits affect

the learner and the institutions admitting and supporting these students. Examining tuition

funding for these students is just as crucial for higher education institutions as it is for

their employers. Understanding the effect of cost on post-traditional learners can lead to

more strategic conversations within postsecondary institutions addressing tuition,

scholarships, and other financial benefits to attract and serve this unique student

population. Higher education professionals and leaders can use the results of this program

evaluation as a reference point when addressing the financial obstacles for adult learners.

While not every post-traditional or continuing education unit can or should partner with

Guild or another similar external partner to address persistence and retention problems

15
for post-traditional learners understanding how tuition costs affect adult learners is vital

to serving this growing population effectively. Adult students return to higher education

to upskill, reskill, or make career pivots, ultimately increasing their socioeconomic status.

However, the financial burden may be too significant of an obstacle to overcome, leading

to higher rates of stopping out and, thus, lower student retention rates for institutions.

Results of this program evaluation point to the significance of cost for the post-

traditional student population. The results of this program evaluation suggest that adult

learners are influenced by cost, which can be seen in decision patterns to return to higher

education and persist through to completion. Extrapolating research and studies centered

around traditional-aged students will not suffice when understanding the patterns of post-

traditional learners. This program evaluation is essential for leaders and administrators of

professional and continuing education units as they strategically plan for the future of

their departments or units and the student populations they serve.

Definition of Terms

Table 1.1

Key Terms with Definitions

Key Term Definition

Active Student Status Actively enrolling in at least one quarter per academic
year. (University College student policy)
Adult Learner Students aged 25 and older who pursue higher education
with the hopes of changing careers, expanding career
options, or staying competitive in their current careers
by earning new credentials. (Education Advisory Board,
EAB).
Guild Student A student who is admitted into a program (bachelor’s,
graduate certificate, or master’s) at the University of
Denver’s University College directly from the
partnership with Guild.

16
Organic Student A student admitted into a program (bachelor’s, graduate
certificate, or master’s) at the University of Denver’s
University College as a direct result of recruiting efforts
not tied to the partnership with Guild.
Persistence Continuous learning process from when a student enrolls
into a program until they reach their educational goal of
degree or graduate certificate completion (Tinto, 1975).
Post-Traditional Learner Students who frequently must balance life, work, and
their education concurrently. These students are
typically 25 and older, care for dependents, and work
full-time while enrolled (American Council on
Education).
Some studies instead refer to non-traditional learners, as
this term uses a deficit lens by categorizing adult
learners as not something, “othering” them, or giving the
perception that they are different from the norm; this
program evaluation will not use this term. Instead, it will
use the term post-traditional learner.
Retention Continuous enrollment quarter to quarter (or semester to
semester) from matriculation to graduation at the same
institution (Berger et al., 2005). It is common for adult
learners to stop-out for a quarter or two and then return
(UPCEA, 2017). Those who maintain active student
status based on University College policy will be
considered retained.
Stop-Out One who withdraws temporarily from a college or
university (Merriam-Webster).
Some studies instead refer to drop-out, as this term
places the responsibility solely on the students to retain
themselves rather than the institution to regain them; this
program evaluation will not use this term. Instead, it will
use the term stop-out
Time to Degree The attainment of a degree (bachelor’s, graduate
Completion certificate, or master’s).
This term is used in place of graduation as students
pursuing a graduate certificate do not graduate by
University College definitions they complete.
Tuition Reimbursement Tuition funding program where an organization or
company reimburses the employee for tuition and fees
after the completion of a course. This type of tuition
funding requires the employee/student to pay out-of-
pocket and receive reimbursement from the employer at
the end of the semester or quarter.
Up-Front Tuition Tuition funding program where an organization or
Funding company pays up-front for tuition and fees or before the
17
 course is completed. This type of tuition funding
eliminates the need for employees/students to have out-
of-pocket expenses up-front.

Dissertation Overview

This section outlines the organization of this program evaluation. Chapter One

began with a vignette to capture a typical adult learner and the obstacles they often face

in pursuing higher education, giving examples of the students behind the quantitative

approach to this program evaluation. Chapter One has also provided background

information on the Guild partnership; the students served, and a statement of the problem.

Chapter One also defined key terms used throughout the program evaluation and

provided the conceptual framework, summary of the methodology, and significance of

employer funding on the persistence and retention of adult learners.

Chapter Two outlines the literature review and conceptual framework used to

guide this program evaluation. The literature review is used to orient this program

evaluation within prior research. This chapter establishes a foundation for the program

evaluation by reviewing the history of retention and exploring the six most-cited

theoretical retention models. I review prior studies and existing literature on retention, the

effects of employer funding on retention, as well as professional and continuing

education units. I then establish the theoretical framework used for this program

evaluation using Bean and Metzner’s (1985) Conceptual Model, Human Capital Theory,

and Evaluative Inquiry for Learning in Organizations.

Chapter Three describes the methodology used in this program evaluation. I begin

by explaining the guiding framework of Evaluative Inquiry for Learning in Organizations

18
describing an outcomes approach to this program evaluation and tying it to strategic

planning. Next, I share my research design, including a detailed description of University

College, Guild, and the students served. I then provide details on my approach to

instrumentation and data collection procedures and the possible influence COVID-19

may have on the program evaluation. This chapter concludes with my positionality

statement, how it informs my research, and the decisions made throughout this program

evaluation.

Chapter Four presents the results of my program evaluation as they relate to each

research question. I present descriptive statistics and t-test results on the various student

populations. I then turn to an analysis of employer tuition funding levels using the

Kruskal Wallis Test. Finally, I present the results of the Guild and Organic student

populations established through correlation and multiple regression, where I break the

results down into subsets of populations including by level (graduate and undergraduate)

as well as by degree (Master of Science, Master of Arts, six-course Graduate Certificate,

four-course Specialized Graduate Certificates, and Bachelor of Arts).

In Chapter Five, I discuss the results of this program evaluation and how they

intersect with previous research conducted, and how this program evaluation begins to

fill the gap in research on the persistence and retention of post-traditional learners. I

conclude by discussing implications and recommendations for implementation into

practice, the need for partnerships and programs that support state workforce needs, and

the need for further research on the effects of external factors on the persistence and

retention of post-traditional learners.

19
 CHAPTER TWO: LITERATURE REVIEW

This literature review explores existing research on the effects of employer tuition

funding on post-traditional learners and is used to orient and place this program

evaluation within previous research. This literature review is organized into six sections.

In the first two sections, I explore retention within higher education, including a brief

history of the study of retention, the six major retention theories, and how the research

relates to the current issues of persistence and retention for adult learners. Examining the

literature on the study of retention shows not only the importance placed on retention

within higher education but also the need for more research on the persistence and

retention of serving adult learners. The third section examines the influence of external

environmental factors on adult learners, emphasizing the differences of these external

factors between traditional and post-traditional learners. In the fourth section, I delve into

the influence of the external factor of finances on post-traditional students and retention

rates. I explore the financial impact of employer tuition funding on students’ ability or

perceived ability to persist and complete their degrees. The fifth section examines

professional and continuing education units and the students they serve. A look at student

retention and completion and how this student population differs from a traditional-aged

student anchors the importance of this research on serving this unique student population.

The last section of the literature review incorporates the theoretical framework for this

program evaluation, drawing upon Hallie Preskill’s Evaluative Inquiry for Learning in

20
Organizations, Bean and Metzner’s Conceptual Model (see diagram in Appendix B), and

Human Capital Theory.

Historical Look at Retention

American colleges have existed for over 300 years, but it was in the early 1970s

that retention became a focus of institutions, educators, and researchers (Berger et al.,

2005). Berger and colleagues explain the development of retention by breaking it down

into nine eras:

• retention pre-history (the 1600s-mid 1800s)

• evolving toward retention (the mid-1800s-1900)
• early developments (1900-1950)
• dealing with expansion (the 1950s)
• preventing dropouts (the 1960s)
• building theory (the 1970s)
• managing enrollments (the 1980s)
• broadening horizons (the 1990s)
• current and future trends (early twenty-first century)

In the first era of student enrollment and retention, higher education institutions

were serving few students; therefore, retention was not a thought or consideration, as it

was likely not essential for the survival of a higher education institution (Berger et al.,

2005). Across higher education institutions, there was little to no concern with degree

attainment, as college was more of a luxury than a necessity (Berger et al., 2005). After

the American Revolution, new colleges were chartered; however, it would be years until

enrollments began to grow (Thelin, 2004). The early 1800s was a rapid expansion of

American colleges, private religious colleges emerged, and enrollments grew by over

80% (Berger et al., 2005). The expansion of college enrollment continued until the

economic crash of 1837.

21
 The second era of student enrollment and retention came about when institutions

began to see growth in degree attainment, quite the change from the first era of the

American Higher Education System. The birth of student life occurred during this era as

more students attended colleges, and the importance of co-curricular social activities

began; colleges created social curriculum, and extra curricular activities emerged (Berger

et al., 2005). While persistence was still not a concern during this time, the social

activities and connectedness that Spady (1971) and others will point to later began to

receive increased attention from higher education administrators.

The third era of student enrollment and retention brought about the birth of

selective admission practices as colleges grew and gained stability for the first time since

the inception of American colleges (Berger et al., 2005). While the thought of retention

may be in the minds of some, it was an afterthought for many as the focus during this era

was on attracting students–the right students–in this case, privileged students, generally

white and from higher socioeconomic backgrounds, not on keeping the students an

institution had already admitted and committed to serving (Berger et al., 2005). In 1938,

John McNeely published one of the first research studies on retention and the issues of

student departure (Berger et al., 2005). The title of McNeely’s study was “College

Student Mortality,” he completed his study on behalf of the United States Department of

Interior and the Office of Education. While the results of his research are important to the

study of retention, the idea of student mortality, or the death of a student associated with

the departure from a college, is problematic. The word mortality suggests that education

is a linear process, that all individuals must follow the same path to be successful, and

that leaving or stopping out is equivalent to a student’s figurative death. This insinuation

22
of death or suicide will continue throughout many theories of retention that I explore later

in this chapter. John McNeely (1938) pointed to academic dismissal, financial difficulty,

illness/death, lack of interest, and parents calling students home as the principal causes of

why students were departing from the higher education system. Twenty-five institutions

participated in McNeely’s study, and his research showed that of the 25 institutions, 10

showed that the largest percentage of students departed due to financial difficulties

(McNeely, 1938, p. 48). Tuition and funding are not new issues for retention; each has

existed since the first study of retention in higher education institutions across the United

States.

In the fourth era of student enrollment and retention, enrollments remained

constant and even grew in the late 1940s after the Second World War (Berger et al.,

2005). The GI Bill, which funded education for soldiers returning from war, was likely

the reason for the increase in enrollment growth across American higher education

institutions (Greenberg, 2004). This era saw higher education becoming increasingly tied

to economic and social development and was viewed as a way to improve oneself.

Retention remained an afterthought of higher education leaders during the 1950s while

enrollments continued a pattern of growth. With enrollment trends continuing upward,

higher education leaders did not feel the pressure to retain the students enrolled in their

programs.

In the 1960s, the fifth era of student enrollment and retention, the focus shifted to

preventing stop-outs. Universities–while still not racially or ethnically diverse, began

enrolling a more racially and ethnically diverse student body, and this change was met

with challenges (Stulberg & Chen, 2014). Higher education leaders’ concerns about the

23
lack of student completion led to studies that focused on individual student characteristics

and personality traits in attempts to predict student departure (Summerskill, 1962).

Student stop-out studies began in the late 1960s and became some of the foundations for

William Spady’s work. These early retention studies were conducted by Knoell (1960),

Marsh (1966), Panos and Astin (1968), Bayer (1968), and Trent and Medsker (1968).

These early retention theorists grounded their studies in psychology rather than sociology,

and thus they often explained retention in terms of student characteristics, personal

attributes, and shortcomings. These studies place the onus of retention solely on the

strengths and weaknesses of the students while ignoring the institutional and social

context. Psychological theories claim that higher education institutions can improve

retention through the selection process by admitting only those academically suited or by

improving students’ skills (Knoell, 1960; Marsh, 1966; Panos & Astin, 1968; Bayer,

1968, Trent & Medsker;1968; and Tinto, 1993). Restricting access or finding the right

students is problematic as it perpetuates an already flawed system built on privilege and

continues the oppression of minoritized students. Solving retention problems through the

admissions and selection process fails to address the structures, policies, procedures, and

supports an institution has or does not have and their influence on the student’s journey

toward completion (Swail, 2003). Addressing the issues of persistence and retention

through selective admission practices places the problem solely on the student while

ignoring the institution’s role and the bureaucratic system of higher education in

perpetuating the problem (Espenshade & Radford, 2009).

In the sixth era of student enrollment and retention, retention was a common

concern for higher education leaders. As enrollments were predicted to fall, the focus of

24
higher education leaders shifted to retaining students once they enrolled. Spady’s (1971)

article “Dropouts from Higher Education: An Interdisciplinary Review and Synthesis”

examined the interaction between the student and the college environment (Berger et al.,

2005). This study focused on traditional undergraduate students, and the findings

indicated that if there is alignment with the student and their environments, the student

will assimilate both socially and academically, leading to a higher likely hood of

persistence (Spady, 1971). Encouraging assimilation is problematic as students may feel

pressure to hide or ignore parts of their cultural identity to be more like the people around

them, which further oppresses minoritized students, especially considering that higher

education predominately serves white students (Rambaut, 2015). Vincent Tinto built upon

Spady’s Undergraduate Dropout Process Model (1971) to include psychological and

organizational theoretical models. Tinto’s model (1975, 1993) indicates that persistence is

tied to student characteristics and their initial commitment to the institution and

graduation. Tinto focuses on the assimilation of first-year undergraduate students into

their new environment. Tinto indicates that for students to persist, there must be academic

and social integration (Tinto, 1975, 1993). Other researchers who approached the study of

persistence from a sociological and psychological lens are Kamens (1971, 1974), Astin

(1977, 1985), and Pascarella and Terenzini (1979, 1980). Kamens (1971, 1974) argued

that student retention is linked to the status privilege their college can guarantee them in

the broader social order (p. 294). Astin (1977, 1985) indicated that the greater the

student’s involvement in their academic institution, the greater their persistence rate.

Pascarella and Terenzini (1979, 1980) tied student retention to student social and

academic life, including informal interactions between students and faculty. Retention

25
through the psychological lens places the onus of stopping out on the student instead of

shared ownership of student departure on both the student and institution. These theories

focus on the shortcomings or weaknesses of the student and exclude the influence social

or external factors may play in persistence and retention. The sociological perspective on

retention moves beyond student attributes and incorporates their social status within the

institution and society.

In the 1980s, as enrollments were expected to level off, the study of retention

increased. As the supply of students decreased, the demand for institutions to attract the

best and the brightest increased (Berger et al., 2005). While attracting and enrolling the

best and brightest students is subjective, the highly sought-after students were often from

privileged backgrounds, white, male, and those with higher socioeconomic status

(Carnevale & Rose, 2013). The need to attract this elite student population was a focus of

higher institutions, and thus the practice of Enrollment Management emerged (Hossler,

2002). Jack Maguire, the Dean of Enrollment for Boston College, coined the term

Enrollment Management in 1976 (Hossler, 2002). He and others knew that not only was

it becoming increasingly important to recruit new students, but it was now critical to

retain those students an institution had admitted (Berger et al., 2005). The practice of

enrollment management encompasses the vital role of an institution in admitting and

retaining its students. Bean (1980, 1983) offered a new theoretical retention model

adapted from organizational studies of worker turnover (Price & Mueller, 1981). By the

end of the 1980s, several models and theories were established across several institutional

types (Berger et al., 2005). I will cover the six most-cited retention models in depth later

26
in this chapter. Refer to Appendix C for a summary of many of the highly cited retention

models, frameworks, and key concepts.

In the 1990s, era eight of student enrollment and retention, retention was now

receiving substantial attention from academic institutions, policymakers, and researchers

alike (Berger et al., 2005). Much of the focus of retention was on students’ social and

academic integration; however, in the 1990s, researchers began to look at retention from

other lenses, including the impacts finances may have on retention (Berger et al., 2005).

Also, higher education institutions began to pay greater attention to the retention of

minority populations, especially predominantly white institutions (Berger et al., 2005).

In the ninth era of student enrollment and retention–the current era of retention;

the concept of retention is well established and is a noteworthy policy agenda within

higher education. College enrollment has increased from two million students to 20

million students in just over 60 years (Carnevale et al., 2015). There are widespread

efforts to serve and retain students, especially in highly competitive higher education

spaces, as retaining an institution’s students is cheaper than recruiting and finding new

students (Marsh, 2014). Refer to Appendix D for a historical look at the retention timeline

within the American Higher Education system.

More research is needed on the retention of unique student populations, including

the retention of underrepresented minority students, first-generation students, community

college students, students from lower socioeconomic backgrounds, adult students, and

online students (Berger et al., 2005). One size does not fit all when it comes to student

retention, and the efforts to serve and retain students should be as diverse as the students

who attend our higher education institutions (Cabrera et al., 1993). As student

27
populations diversify across college campuses, so do these institutions’ retention issues.

While much work and progress have been made on student retention research, more

research is needed to address retention in higher education institutions, especially

institutions serving adult learners.

Retention Theory

Having reviewed the history of retention as well as efforts to address retention

gaps and the foundation for this program evaluation, I will turn to the six most-cited

student retention theoretical models that serve as the framework for retention theory as

cited by available research. I determined the following retention theories as the most cited

by verifying citation counts in Google Scholar for each retention model listed in

Appendix C. These theoretical models are the Undergraduate Dropout Process Model

(Spady, 1970, 1971), the Institutional Departure Model (Tinto, 1975, 1993), the Student

Attrition Model (Bean, 1980, 1982), the Student-Faculty Informal Contact Model

(Pascarella, 1980), the Nontraditional Student Attrition Model (Bean & Metzner, 1985)

and the Student Retention Integrated Model (Cabrera & Castaneda, 1993). I present these

theories chronologically according to their publication dates. Refer to Appendix C for a

summary of these and other influential retention models, frameworks, and their key

concepts.

Undergraduate Dropout Process Model (Spady, 1970, 1971)

Many authors and researchers consider The Undergraduate Process Model (Spady,

1970, 1971) the first theoretical model and one of the main seminal articles on student

retention (Berger et al., 2012). William Spady’s work laid the foundation for student

retention theory, which considers the relationship between the student and institution and

28
the influence this relationship has on student retention and attrition. The Undergraduate

Process Model, coined by Spady (1970, 1971), linked the process of student attrition to

Durkheim’s Suicide Theory of social integration. Early retention models, including Spady

1970, 1971; Tinto, 1975, 1993, have linked the idea of student retention to Durkheim’s

theory (Aljohani, 2016). While the results of Spady’s and others’ research are important

to retention, the idea of suicide or the death of a student associated with the departure

from a college is problematic. The linkage suggests that a student who does not follow

the prescribed path for attaining education through the higher education system is

committing figurative suicide or death. This narrow understanding of educational success

does not account for the differences in student types, influences, obstacles they may face,

experiences, or paths of education and socioeconomic growth. In 1970, Spady claimed

that to explain the dropout process of undergraduate students; one must take an

interdisciplinary approach that examines the interaction between the student and the

college environment. Interactions that provide students with opportunities to assimilate

academically and socially are most beneficial for the student persisting (Spady, 1970, p.

77). The act of assimilation is problematic as students may feel pressure to hide or ignore

parts of their cultural identity to be more like the people around them, which in higher

education is a predominantly white population, further oppressing minoritized students

(Rambaut, 2015). Spady concluded that a student’s decision to continue or withdraw from

their current institution is influenced by two factors in each system, academic and social.

The two main factors within the academic system are grades and intellectual development

(Spady, 1970, p. 77-78). Within the social system, normative congruence (where

attitudes, interests, and personality dispositions are compatible with the attributes and

29
influences of the environment) and friendship support align with Durkheim’s (1951)

concept of social integration (Spady, 1970, pp. 77-78).

Spady (1971) tested his assumptions of the interactions between student

characteristics and the campus environment and adjusted his model after testing 653

traditional-aged undergraduate students who entered the University of Chicago in 1965.

Spady’s findings revealed that intrinsic rewarding academic activities and the

establishment of personal contact with faculty and peers are fundamental components of

integration, satisfaction, and commitment to the institution they are attending (Spady,

1971, p. 62). Many retention theorists cite Spady’s research, and while it is a seminal

study in retention theory, his work focused on traditional undergraduate students and

extrapolating results to the post-traditional learner does not address the differences in

student populations. See Figure 2.1 for the final version of Spady’s Undergraduate

Process Model.

Figure 2.1

The Undergraduate Dropout Process Model

30
Note. From “A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention
in Higher Education,” by O. Aljohani, 2016, Higher Education Studies, 6(2), p. 5.
(http://dx.doi.org/10.5539/hes.v6n2p1). Copyright 2016 by author.

Institutional Departure Model (Tinto, 1975, 1993)

Tinto (1975) explained the motivations of students to leave college prior to

completion by building upon Spady’s (1970, 1971) model and Durkheim’s (1951) Theory

of Suicide. Tinto (1993) also incorporated the rites of passage of tribal societies’ views of

social anthropologist Van Gennep (1960) into his work. Tinto links students’

incorporation into their academic institutions into three stages of passage: – separation,

transition, and integration. A gap in Tinto’s Institutional Departure Model (1975, 1993) is

the role of external factors such as finances, hours of employment, family responsibility,

outside encouragement, and outside commitments, and their influence on student

persistence. Later retention theories by Bean and Metzner (1985) and Cabrera and

colleagues (1993) incorporate more intentionally the external factors that influence

student retention; I cover these theories later in this section.

According to Tinto (1975, 1993), persistence is a function of the match between

the student’s motivation, academic ability, and the institution’s academic and social

characteristics. The match between the student’s and the institutions’ characteristics

shapes the student’s commitment to completing college–“goal commitment,” and

commitment to their institution–“institutional commitment.” Tinto’s model indicates that

the student’s goals and commitments are constantly changing based on their experience at

college. The stronger the student commitments, the higher the probability of that student

persisting and completing their degree.

31
 Tinto’s final model (1993) states that colleges consist of two systems – academic

and social, and students who persist integrate into both systems. In his model, Spady

measured academic integration by students’ grade performance and intellectual

development, while he measured social integration by students’ interactions with peers

and faculty. Tinto critiqued his own 1975 model, stating that “it does not adequately

distinguish between those behaviors that lead to institutional transfer and those that result

in permanent withdraw from higher education” (Tinto, 1982, p. 689). See Figure 2.2 for

Tinto’s Institutional Departure Model.

Figure 2.2

The Institutional Departure Model

Note. From “A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention
in Higher Education,” by O. Aljohani, 2016, Higher Education Studies, 6(2), p. 6
(http://dx.doi.org/10.5539/hes.v6n2p1). Copyright 2016 by author.

32
Student Attrition Model (Bean, 1980, 1982)

Bean’s Student Attrition Model (1980, 1982) builds upon James L. Price’s 1977

organizational turnover models of organizational turnover. Bean argues that a student’s

decision to stay at or leave the institution they are attending is like an employee’s

behavior and decisions within work organizations. Bean suggests that organizational

determinates influence student and employee satisfaction and their decision to persist or

stay. In Price’s research, he argued that employee satisfaction which leads to employee

turnover, misses the mark by itself, and both integration and salary or pay also influence

turnover. Instead of using the pay variable as Price (1977) did when thinking about the

influence of salary on employee retention, Bean (1980) used educational indicators,

including student GPA, student development, institutional quality, and overall value.

Bean (1982) built upon his own model, suggesting a linkage between student

attitudes and behavior, and used intentions and attitudes to predict the retention and

persistence of students. Bean’s model modifies Fishbein and Ajzen’s (1975) Social and

Personal Beliefs Model (SPBM). The key ideas of SPBM include the importance of

student intention, beliefs, and behavioral influences. Bean (1982) argues that when

developing a model of student attrition, four variables should always be present –

background, organizational outcomes and attitude, and environment. See Figure 2.3 for

Bean’s (1982) Student Attrition Model.

33
Figure 2.3

The Student Attrition Model

Note. From “A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention
in Higher Education,” by O. Aljohani, 2016, Higher Education Studies, 6(2), p. 8.
(http://dx.doi.org/10.5539/hes.v6n2p1). Copyright 2016 by author.

Student-Faculty Informal Contact Model (Pascarella, 1980)

Pascarella (1980) developed a conceptual model of students stopping out where

he emphasizes the importance of informal contact with faculty. Based on Spady’s (1970,

1971) and Tinto’s (1975) theoretical models, Pascarella argues that interactions between

students and faculty members influence student’s integration into both social and

academic systems. The model hypothesizes that students who have positive relationships

with their faculty outside the classroom, referred to as informal interactions, positively

impact student retention, especially in the first year. Pascarella (1980) argued that there

are different forms of student-faculty interactions, each with different levels of influence.

The most substantial influence on student retention comes from informal interactions that

extend beyond the knowledge shared in the classroom. Various factors influence this

34
interaction, including student background differences, faculty culture, classroom

experiences, peer involvement and culture, and the institution's size.

Pascarella’s work (1980) suggests significant associations between student-faculty

informal contact and education outcomes, and the quality of the informal contact leads to

better educational outcomes and, thus, continued persistence (p. 564-565). Not all

student-faculty informal contact is as influential as those focusing on intellectual/literary

or artistic interests, value issues, or future career concerns (Pascarella, 1980, p. 565).

According to Pascarella, factors such as initial student differences/background

characteristics, the faculty culture and classroom experiences, peer culture, and the

institution’s size influence the quality of informal student-faculty informal contact.

Pascarella’s model is centered around the traditional student and thus extending the

Student-Faculty Informal Contact Model to post-traditional learners without considering

other influencing factors is problematic. Most adult learners are not fully immersed in the

campus, and their faculty interactions differ significantly from traditional students. See

Figure 2.4 for Pascarella’s student-faculty informal contact model.

35
Figure 2.4

The Student-Faculty Informal Contact Model

Note. From “A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention
in Higher Education,” by O. Aljohani, 2016, Higher Education Studies, 6(2), p. 9
(http://dx.doi.org/10.5539/hes.v6n2p1). Copyright 2016 by author.

Nontraditional Student Attrition Model (Bean & Metzner, 1985)

Bean and Metzner (1985) argue that retention models neglect to examine the

experience of post-traditional undergraduate students. Early retention models established

by Spady (1970), Tinto (1975), Astin (1977), and Pascarella (1980) focus on socialization

and social integration which neglects the post-traditional learner as there is often a lack of

integration as students often commute to campus–and today are often online and

therefore are not fully immersed into the social activities and norms of the physical

campus environment. To fill this gap in the research, Bean and Metzner built the

Nontraditional Undergraduate Student Attrition Model. Bean and Metzner derived this

model from the Student Attrition Model of Bean (1982) and other theorists (Bentler &

Speckart, 1981; Fishbein & Ajen, 1975; Lewin, 1935; Locke, 1976). The Nontraditional

36
Student Attrition Model postulates that post-traditional students are different from

traditional-aged; therefore, external factors influence post-traditional learners more than

institutional socialization. Bean and Metzner’s conceptual framework is based on

academic performance, intent to leave, background and defining variables, and external

environmental variables.

According to Bean and Metzner (1985), external environmental factors the

institution has little to no control over including –finances, hours of employment, outside

encouragement, family responsibilities, and opportunity to transfer most directly affect

student retention and attrition for post-traditional students. Bean and Metzner claim these

external factors play a more significant role in retention for the post-traditional learner

than academic variables. While the Nontraditional Student Attrition Model focused on

post-traditional undergraduate students, the model can also be extended to examine post-

traditional learners at the graduate level. There are more similarities than differences

between post-traditional undergraduate and graduate learners; they face many of the same

obstacles of outside obligations of work and family; thus, this model could be extending

to test the retention of post-traditional graduate students. I will discuss this theory in

further detail as a part of the theoretical framework for this study. See Figure 2.5 for Bean

and Metzner’s Nontraditional Student Attrition Model.

37
Figure 2.5

The Non-Traditional Undergraduate Student Attrition Model

Note. From “A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention
in Higher Education,” by O. Aljohani, 2016, Higher Education Studies, 6(2), p. 10,
(http://dx.doi.org/10.5539/hes.v6n2p1). Copyright 2016 by author.

Student Retention Integrated Model (Cabrera et al., 1993)

Cabrera and colleagues (1993) suggested studying student retention through an

integrative framework by merging the variables of retention models from Tinto (1975)

and Bean (1982). Cabrera and colleagues conducted an empirical study to test the

convergence of these two theories in predicting student retention. The findings of Cabrera

and colleagues’ longitudinal study indicated the convergence of these two distinguished

retention models with a few amendments to provide a better understanding of the student

attrition process than either model on its own. The Student Retention Integrated Model

included all statistically significant variables from both theories; the model excluded

those variables that were insignificant (see Figure 2.6).

38
Figure 2.6

The Student Retention Integrated Model

Note. From “A Comprehensive Review of the Major Studies and Theoretical Models of Student Retention
in Higher Education,” by O. Aljohani, 2016, Higher Education Studies, 6(2), p. 11
(http://dx.doi.org/10.5539/hes.v6n2p1). Copyright 2016 by author.

Cabrera and colleagues (1993) study confirmed through a two-step structural

equation modeling strategy (a technique used to analyze structural relationships) the

assumptions from both theories to be valid. The Student Retention Integrated Model also

found that a more comprehensive understanding of student attrition results from complex

interactions, characteristics, and institutional fit. This study included the following

external variables: Encouragement from Friends and Family and Finance Attitudes and

the following internal variables: Academic Integration, Social Integration, and

Institutional Commitment. This study supports the claims made by Bean (1982) on the

importance of external environmental factors to student retention. Cabrera and colleagues

recommend that higher education professionals design student retention plans around the
39
variables most strongly influencing and encouraging student persistence. Cabrera and

colleagues recommend that academic institutions constantly revisit retention plans to

address student retention within their academic units, and these retention plans may need

to differ across units. This strategic approach to retention aligns with the decision to lean

into Hallie Preskill’s Evaluative Inquiry for Learning in Organizations as a strategic

evaluation approach for this program evaluation. I address Evaluative Inquiry for

Learning in Organizations in detail in Chapter Three.

Higher education administrators and policymakers focus on retention efforts

across campuses nationwide, as retention is a key indicator of institutional effectiveness.

There are many studies on persistence and retention, with a vast majority of the

theoretical student retention models focusing on traditional-aged students who are often

integrated into the campus community as a part of attending college and earning a degree;

however, these models do not explain the experience of adult learners who spend little if

any time on campus and have commitments outside of their academics to family and

often full-time employment (Graham et al., 2000). The differences between post-

traditional and traditional learners have been well established, and thus examining the

persistence and retention patterns of post-traditional learners in the same way traditional

students are examined is ineffective. To understand the patterns of persistence for the

adult learner, research must align with the characteristics and demographics of the

population.

External Factors Impacting Retention

The focus of many of the retention theories has been and continues to remain on

social and academic integration; however, for the adult student population, this focus

40
does not consider the environmental factors that Bean and Metzner (1985) focused their

research on. Bean and Metzner (1985) and Bergman and colleagues (2014) found that

more than student entry characteristics or social integration, external environment factors

played a vital role in the persistence of adult students. Bean and Metzner identify five

external environmental factors that directly affect post-traditional student retention. These

external factors are finances, hours of employment, outside encouragement, family

responsibility, and the opportunity to transfer. While no one factor is the sole contributor

to adult student retention and degree completion, examining financial factors is especially

important in this unique population (Bergman et al., 2014). The environmental factor of

finances is also the only one that the institution can have some influence on. Generally,

post-traditional learners are financially independent and carry the burden of financial

responsibility for themselves and others. A lack of financial support, including financial

aid, scholarships, or employer tuition funding, could deter an adult learner from starting

or completing their degree.

A significant gap in the research on persistence and retention is the role of

external factors–specifically finances, in shaping a student’s commitment to retaining

toward degree completion. Financial assistance for low-income community college

students who are often more affected by college pricing (McKinney & Burridge, 2015)

has been shown to strongly influence the retention of community college students

(Barrow et al., 2014). Castleman & Long (2016) studied the effects of need-based grant

eligibility on college completion. While Castleman & Long focused their research on

traditional undergraduate students, the results suggest that need-based aid has a positive

impact on persistence and degree attainment. Additional studies and research are needed

41
to explore the effects of finances on persistence for the adult student population. With

increases in employer tuition benefits offered from companies studying tuition support

through employer funding and its effects on the persistence of adult learners is an

important and relevant study across the higher education system.

Retention is a key indicator of institutional effectiveness, and the pandemic has

forced more institutions to intensify their retention efforts. The National Student

Clearinghouse Research Center (2022) shows a 7.4% drop in total enrollment across all

higher education institutions since 2020, partly attributed to Covid. Enrollment in adult

learners fell by 5.8%, with half of the decrease coming from the community college

system (National Student Clearinghouse Research Center, 2022). Higher education

reform has shifted from access to cost and completion as there is a higher scrutiny on the

cost of higher education and the retention rates of students, especially minoritized

populations (Carnevale et al., 2015). Colleges are suffering from historic enrollment

declines during the pandemic, suggesting the importance of retention and re-engaging

adult learners looking to complete degrees they began years ago and advance their

education through certificates and graduate degrees (Causey et al., 2023). Higher

education institutions are implementing retention efforts for post-traditional learners

through programs designed for the adult student population, online platforms, and the

implementation of systems to track student retention and success.

The Gallup and Lumina Foundation conducted a survey in 2021 to explore the

risks to the enrollment and retention of adult learners. They surveyed 5,215 adults

pursuing a bachelor’s or associate degree and 3,002 who had never enrolled in

postsecondary education. Over half of all unenrolled adults surveyed reported cost as a

42
fundamental reason for not continuing education (Gallup Lumina, 2021). Cost is the most

significant barrier to the never-enrolled student population and those who stopped out

after enrolling. The study also found that over half of currently enrolled students

continued in their educational pursuits because of the financial aid they received.

Examining the barriers finances place in the way of adult learners and the benefits of

more skilled and educated workers to employers and the economy can lead to a more

strategic approach to employer tuition assistance programs. These programs can benefit

more than just the students or employees who are taking advantage of them, but can also

benefit higher education institutions, companies, and the communities these students and

employees live in.

Employer Funding Impact on Retention

To help fill the skills gap, employers within the United States spend

approximately 17.7 million dollars on tuition assistance providing access to

postsecondary degrees and credentials (Gallup-Lumina Foundation, 2016). Employers of

all sizes offer these educational benefits; while the policies and caveats associated with

the educational benefits vary across employers, the benefits for the employees and

companies are apparent (Pelletier, 2019). The Lumina Foundation (2016) published a

report showing that investing in current employees can be one of the best returns on

investment and creates a competitive advantage. This report revealed that Cigna helped

control talent management costs through its educational assistance program; for every

dollar spent, Cigna saved $1.29. These tuition assistance programs led to a substantial

return on investment–129% for Cigna and 144% for Discover, in reducing hiring costs as

more employees were retained.

43
 In recent years organizations like Fed Ex Express, JP Morgan, Starbucks, Target,

Walmart, and The Walt Disney Company have received media attention for their

educational assistance programs offered to employees. Starbucks and FedEx Express

have direct partnerships with Arizona State University (Go to College, on us, 2022) and

the University of Memphis (LiFE: Learning inspired by FedEx, 2022), respectively,

where employees can earn online degrees tuition-free. In 2022 Waste Management

extended their employee tuition benefits to dependents and spouses (Waste Management,

2021). Waste Management is among the first employers to extend educational benefits

beyond their employees at this scale. Chipotle, Target, Walmart, The Walt Disney

Company, and many others are partnered with various higher education institutions

through their partnership with Guild (Guild Website, 2022).

When surveyed, employers report that upskilling offers the employee the

possibility to meet personal and often professional goals of earning a degree or credential

along with opportunities for career advancement, higher wages, and higher levels of job

satisfaction (Gallup-Lumina Foundation, 2021). The companies that offer tuition

assistance also benefit from having more skilled workers, advantages in a highly

competitive environment with a strong pool of candidates, and often higher employee

retention and job satisfaction (Gallup-Lumina Foundation, 2021).

Carnevale and colleagues (2015) identified tuition assistance as the most

important factor for working students because

in the absence of financial support from an external source, such as need-based

grants, parental support, or student loans, the majority of workers simply could
not afford the cost of tuition and fees for postsecondary enrollment each semester.
(p. 20)

44
The economy is pushing for a more educated workforce, as are companies; however,

without funding to assist with tuition, specifically for working adults, it is unlikely they

will start, let alone complete their degrees, based on the financial pressures this student

population faces. Some financial pressures these students face is housing, childcare, bills,

incurring additional debt, caring for aging parents, and other financial needs, each

impacting adult learners’ pursuit of education (Deutsch & Schmertz, 2011). Carnevale

and colleagues (2015) identified tuition assistance as the most crucial component in

removing barriers for working learners, as most workers could not afford the cost of

tuition without financial support. Financial constraints of the adult learner are a

significant concern and often play a more prominent role in the pursuit of higher

education than traditional-aged students.

Tran and Smith (2017) researched the impacts of employer-sponsored educational

assistance benefits on community college students. Tran and Smith took a quantitative

approach to determine the impact of funding for 5,201 community college students who

began at a public community college from 2003-04. This national study found that 90%

of community college students did not receive educational benefits from employers;

however, those who did have better retention and attainment outcomes (Tran & Smith,

2017). Trans and Smith found that those who received employer funding were 2.7% less

likely to stop-out and 2.6% more likely to continue onto a four-year degree after

completing their associate degree (p. 88). Tran and Smith also found evidence that

employer-sponsored education assistance positively impacts on longer-term student

outcomes, such as completion of their program over more immediate ones, such as GPA

and completed credit hours at the end of their first year (p. 93). Across the United States,

45
post-traditional learners–ages 25 and up comprise 56% of the students enrolled in

postsecondary education (National Center for Educational Statistics, 2022). Continued

research on employer funding models, student retention, and degree completion for post-

traditional learners is vital to serving this growing student population.

Employer tuition programs are often as different as the employers themselves;

however, recently, there has been a push for employers to provide programs that offer up-

front tuition funding rather than reimbursing employees afterward (Guild website, n.d.).

A two-year study conducted by the Lumina Foundation (2023), found that tuition

reimbursement programs have a return on investment (ROI) of 1.29 dollars for every

dollar spent. While the average ROI for Guild partners, each offering up-front tuition

funding, is 3 dollars for every dollar spent (Guild, 2023). The high up-front out-of-pocket

costs of the tuition reimbursement model may prevent some from utilizing the benefits if

their employer refunds the employee versus paying the tuition up-front (St. Amour,

2020). The policy of requiring employer reimbursement versus the employer paying up

front disproportionally impacts those employees of lower socioeconomic status. A 2012

review of tuition assistance programs found that only 40% of programs offered up-front

funding instead of tuition reimbursement, and notably, the companies that offered up-

front funding had 3% more employees taking advantage of the benefit (EdAssist, 2012).

Recently, employers have been making changes to modernize their tuition assistance

programs, offering tuition funding up-front instead of as a reimbursement. Employers are

also increasing tuition funding levels and the pool of eligible employees, where

employees are eligible for education benefits 60-90 days after employment (versus nine

months) – Tyson Foods recently announced that employees are eligible for tuition

46
funding benefits on day one of employment. Many employers, including but not limited

to Amazon, Bank of America, Home Depot, McDonalds, Target, and UPS even extend

tuition benefits to part-time employees (Higher Ed Insight, 2021). New and emerging

partnerships between employers and postsecondary institutions also lead to more

innovative programs. Some employers are developing these tuition benefit programs

through a direct relationship with higher education institutions, and others are creating

partnerships through third-party companies such as Guild, Education at Work, Ed Assist,

and others. As companies refine their education benefit packages finding the right fit for

these adult learners is key, and many are turning to institutions or colleges that specialize

in serving adult learners.

Professional, Continuing, and Online Education Units

Higher education institutions no longer serve just those who live in or near the

communities in which their campus is located, and the ages of the student population

extend beyond the 18-23-year-old traditional student. According to the National Center

for Education Statistics (NCES, 2020), the adult student population in the United States

grew from 5.1 million in 2000 to 6.2 million in 2017. Post-traditional enrollment numbers

are expected to continue in their upward trajectory. Predictions expect this student

population to increase by 11% from fall 2017 to fall 2028 (NCES, 2020). The

composition of higher education institutions has shifted to a population that is more

diverse, is typically working part or full-time, has greater financial and family

commitments which create competing priorities for students (Osam et al., 2017). These

student predictions and the changing landscape of higher education emphasize the need

47
for studying adult students instead of clumping them in with the traditional student

population or overlooking them completely.

Many private and public institutions have divisions or departments where lifelong

learning is at their core, focusing their work on adult learners often hidden in plain sight

across many campuses. Many names are used to refer to these units; however, in this

program evaluation, I will categorize all these units as Professional, Continuing, and

Online Education (PCO) units. These PCO units are geared toward serving post-

traditional learners through alternative educational pathways and advocating for those

who often do not have a voice on campus and are distinctly different from traditional full-

time students (UPCEA, 2017). PCO units often function quite differently from the

traditional units on campus, with extended operational hours, different or varied policies,

and various course modality offerings to provide the flexibility a post-traditional student

needs to balance work, family, and academics. The faculty and staff in these units serve

as the champions for this growing population of adult learners' unique needs in all aspects

of their educational journey (UPCEA, 2017). PCO units offer a variety of professional

programs characterized by the rapid invention of new jobs and categories of work;

careers that span 60 years and involve numerous job changes across many distinct areas;

the knowledge that provides immediate value in jobs; and regionalized and localized

occupational needs (UPCEA, 2017, p. 8). With the connection of each of these

characteristics to the jobs and careers of the students who attend these units, researching

the connection of employer funding to the success and completion of these students is not

only essential but necessary.

48
Theoretical Framework

The theoretical framework for this program evaluation is comprised of Bean and

Metzner’s Conceptual Model, Human Capital Theory, and Evaluative Inquiry for

Learning in Organizations. Each of these models and theories are essential in providing

structure to the program evaluation as they each serve as a cog in the wheel of

understanding persistence and retention for post-traditional learners. Utilizing Bean and

Metzner’s Conceptual Model shows the differences between traditional and post-

traditional learners, pointing to the need to explore external environmental factors further

when researching persistence and retention for post-traditional learners. Bean and

Metzner’s Model was built upon organizational turnover and speaks to overall perceived

value of a student earning their degree. I used Human Capital Theory to address a

student’s perceived value in education. Human Capital Theory allows the program

evaluation to examine students as product consumers and explain the cost-benefit

analysis of post-traditional learners, which impacts the decision to start a degree, continue

toward completion of a degree, or stop-out. Finally, Hallie Preskill’s Evaluative Inquiry

for Learning in Organizations (EILO) allowed for a reflective practice of strategic

organizational practices and applying results to improve persistence for adult learners.

Utilizing EILO allows the results of this program evaluation to become a catalyst for

growth for each of the stakeholders as the program evaluation was designed to create

transformative learning. Figure 2.7 highlights the major points for each model or theory

as a foundation for this program evaluation. Each model and theory will be discussed in

turn.

49
Figure 2.7

Theoretical Framework Used for Program Evaluation

A full visual representation of the theoretical framework is available in the Appendix,

listed as Appendix A.

Bean and Metzner’s Conceptual Model

Retention efforts are a significant focus of nearly every college campus

nationwide, as retention is often considered an indicator of institutional effectiveness

(Berger et al., 2005). Many unresolved problems in student retention highlight the need to

build upon the contributions of the early retention theorist Spady (1970), Tinto (1975),

Astin (1977), and Pascarella (1980), who have led the way in developing theories and

models around the persistence and retention of students, specifically traditional-aged

students. Early retention theorists focus on how social belonging, connectedness, and the

internal college environment impact students’–typically traditional-aged, persistence and

retention. Social interaction and connectedness to campus are key elements for traditional

learners but are often not as relevant for adult learners. In contrast to the importance of
50
the social integration factors for traditional students Bean and Metzner (1985) argue that

these social integration factors are far less important than external environmental factors

for post-traditional learners. While institutions have little control over these external

factors, understanding each and their influence on the persistence of adult learners is key

to closing the gap in retention and persistence for adult learners.

To address the differences between traditional and post-traditional students, Bean

(1980, 1983) offered a new theoretical retention model adapted from organizational

studies of worker turnover (Price & Mueller, 1981), which Bean and Metzner expanded

on in 1985. Bean and Metzner’s research focused on the non-traditional (termed post-

traditional or adult learner in this paper) undergraduate students, concluding that the

external environment affects this student population more than social integration

variables (p. 530). Bean and Metzner define the environmental variables as finances,

hours of employment, outside encouragement, family responsibilities, and opportunity to

transfer. Bean and Metzner demonstrate that each factor influences the persistence of

adult learners and that further research on adult learners is needed to continue to

understand the persistence of this student population.

While Bean and Metzner’s (1985) work focused on post-traditional aged

undergraduate students extending this model to post-traditional graduate students makes

sense as the external factors remain relevant. Understanding the role finances plays for

adult learners is critical to increasing the persistence and retention of post-traditional

learners within higher education institutions. Many variables can be used to measure the

ability to finance education, often related to the socioeconomic status of the student’s

parents, income (student or parent), perception or uncertainty around finances, and access

51
to financial aid. Many studies have concluded that financial stress positively relates to

students’ decision to stop-out (Lenning et al., 1980; Marsh, 1966; Pantages & Credon,

1978; Summerskill, 1962). While many adult learners also work full-time, and employers

shift toward a more progressive tuition benefits model, examining the effects of employer

tuition funding will provide a better understanding of the influence of finances as an

external environmental factor on persistence and retention. Cabrera and colleagues

(1990), Ability to Pay model indicates that students with a greater ability to pay for

college integrate themselves into college life and are more likely to succeed. By applying

Bean and Metzner’s (1985) model with the understanding of how the increased financial

ability to pay positively influences students’ persistence, this program evaluation will

take a closer look at the environmental factor of finances and specifically employer

tuition funding as a source of funding and the influence it has on adult learners’

persistence, retention, and time to degree completion.

Human Capital Theory

Human capital theory suggests that a student’s decision-making process is

grounded in establishing a return on investment associated with the decision to begin and

continue the pursuit of a higher education degree or stop-out (Long, 2007; Becker, 1975).

If or when the cost-time and money outweigh the reward–economic gain, the student is

likely to stop-out instead of persisting through to completion. Opinion polling data shows

that 74% of adults agree two-and four-year degrees are now equally or more important in

securing a successful career than 20 years ago (Gallup Lumina, 2023). The same research

also shows that many Americans have doubts about the cost and quality of a college

education leading to the return on investment of a student’s time and money. While there

52
are many benefits–increased social and economic mobility, increased access to job

opportunities, and marketability to those who earn a college degree, if those benefits are

not evident or are not perceived by students to outweigh the growing costs of higher

education, students are unlikely to begin or stop-out instead of persisting through to

completion of their program.

Consumers consider both the cost of a purchase as well as the perceived value of

that purchase. Perceived values are “what consumers get for what they give” or a cost-

benefit evaluation that includes prices and the time and effort invested (Hoyt & Howell,

2011, p. 23). Students are consumers, and their decision to pursue a college degree

follows the pattern of other large purchases, often associated with a cost-benefit

evaluation. Their decision-making process continues each quarter as they assess their

perceived value when deciding to re-enroll in the next quarter. This is a decision they

continue to revisit as they pay with their time and money each time registration rolls

around. Students are not obligated to continue based on their decision to begin a program

and therefore assess the value of their education before registering for each quarter,

similar to a repeat buyer of any other product. The groundwork for the impacts of

removing financial barriers to improve retention through studies by Alberto Cabrera

1990, 1992, 1993; Amaury Nora 1992, 1993; Edward St. John 1997, 2002; and Michael

Paulsen 1997, 2002. Through the examination of the Financial Nexus Model, Paulsen and

St. John (2002) support the view that students engage in a series of choices regarding

college choice and re-enrollment, and each state of their decision is affected by financial

factors. According to their model, the ability of financial aid to affect decisions depends

upon both the availability of student aid and the student’s perception of the overall cost

53
(Paulsen & St. John, 1997, 2002). Students are more likely to complete their degrees

when the value of the benefits exceed the cost of attending.

Chen and Hossler (2017) suggest that non-traditional students of two-year

institutions are more likely to drop out in the third year of college and that each type of

financial aid studied–Pell Grants, subsidized student loans, and unsubsidized student

loans–appeared effective for reducing stop-out risk. Reducing the monetary cost of

tuition can be the tipping point in one’s perception of their return on investment.

Employer funding provides an immediate financial benefit to balance the out-of-pocket

costs associated with higher education. In addition, the immediate reduction in financial

costs allows for the vision of long-term benefits associated with earning a degree–

whether undergraduate or graduate- including advancement or promotion in their current

position or increased opportunities with new employers. One way the cost of education

can be reduced for post-traditional students is with employer tuition funding. Reducing

the cost of education increases the return on investment for adult learners deciding to

return to higher education or persist through to completion.

Other businesses evaluate consumer satisfaction by examining repeat purchases

and willingness to recommend a product or service to others to measure customer loyalty.

In higher education, customer loyalty is often measured through persistence, retention,

and referrals. For students to persist, retain, or provide referrals to others, they need to

perceive value in their purchase and see a positive evaluation of the cost-benefit analysis

they complete–literally or figuratively each quarter they decide to re-enroll or stop-out.

54
Bringing the Theories Together

The theoretical framework composed of Bean and Metzner’s Conceptual Model,

Human Capital Theory, and Evaluative Inquiry for Learning in Organizations is essential

to this program evaluation. Thinking of each model or theory as a gear that interlocks

with the others gives the analogy that explains the importance of each theory as they are

interdependent. When studying the retention and persistence of adult learners, the

absence of any of these theories leaves a gap in understanding of this unique student

population. Bean and Metzner’s (1985) conceptual model emphasizes the impacts of

external environmental factors on the post-traditional population and speaks to the

financial impacts felt by adult learners. Their study is built upon the underpinnings of

organizational turnover, and one of the educational factors is the overall value perceived

by the student for earning or completing their education. This overall perceived value can

be explained through Human Capital theory. Human Capital theory shows how adult

learners–based on the definition, approach returning to higher education as a business

decision. Returning to college, whether for the bachelor’s degree they never completed or

earning a master’s degree or graduate certificate, is a business decision based on

evaluating the return on investment on themselves. These theories serve as the foundation

for this program evaluation as they strengthen the argument for the need for employer

tuition funding for adult learners and the ultimate impacts on increasing the persistence

and retention of adult learners.

Conclusion

There are widespread efforts to serve and retain students, especially in highly

competitive higher education spaces, as retaining an institution's students is relatively

55
cheaper than recruiting and finding new students. Many unresolved issues around

retention include retention of underrepresented minority students, first-generation

students, community college students, students from lower socioeconomic backgrounds,

adult students, and online students (Berger et al., 2005). Through the exploration of the

history of retention and retention theories, research specific to adult learners is necessary

as the post-traditional student population continues to grow and the enrollment cliff for

traditional-aged undergraduate students is quickly approaching. One-size-fits-all models

will not work for student retention, and efforts to serve and retain students should reflect

the diverse student populations our higher education systems serve. While much work

and progress has been made, there is more to addressing retention in our higher education

institutions, especially regarding the adult learner population.

To navigate and understand student retention and persistence of adult learners,

one must consider the many complex variables that contribute to the academic journey of

adult learners. A plethora of research is conducted on persistence and retention; however,

much of the research focuses on traditional undergraduate students, often leaving out the

surging population of adult learners (Spady, 1970, 1971; Kamens, 1971, 1974; Tinto,

1975, 1993; Astin, 1977, 1985; Pascarella & Terenzini, 1979, 1980). With the shift in the

higher education landscape toward a more diverse and older student population, there has

been an increase in post-traditional students returning to higher education, and these

learners are flocking to our institutions as career-focused professionals. As funding is an

obstacle that impacts adult learners’ ability to begin, persist, retain, and complete their

degrees, we must explore ways to reduce these financial pressures and increase the return

on investment allowing adult learners to return to higher education and complete the

56
degrees they start. This evaluation fills a gap in the research by researching the effects of

up-front employer tuition funding on persistence, retention, and time to degree

completion for adult learners.

The Human Capital Theory examines the return on investment, asking does the

cost–both time and money–outweigh the benefits of perceived career advancement?

While the answer to this question is individual for each student, it is a part of the

decision-making process when a student decides to return, continue, or stop pursuing

their degree. Finally, as the partnership between University College and Guild is current

and ongoing, understanding the outcomes of funding on adult learners can be used for

transformative learning and can impact strategic planning and organizational change

moving forward, thus impacting not only the adult learners who are entering University

College through this partnership but those who have not yet committed to investing in

themselves both through the Guild partnership or through organic channels. A visual

representation of the theoretical framework is available in Appendix A. Chapter Three

will discuss the methodology used to test each research question and the hypothesis based

on previous research.

57
 CHAPTER THREE: METHODOLOGY

This chapter describes the data and methodology of the program evaluation. First,

I discuss the guiding framework used to guide the research questions and analysis of this

program evaluation and the importance of this framework for transformative change.

Second, I revisit the problem statement, research questions, and hypotheses of this

program evaluation. Third, I discuss the research design, including the site description,

and participant selection. I then move on to discuss my methodological approaches,

which include the use of descriptive statistics, t-tests, the Kruskal Wallis Test, and

multiple regression. Next, I describe my approach to the cleaning of the data as well as

the analysis I then state the limitations of the program evaluation. Finally, I share my

positionally as a researcher and how it informed my approach to this program evaluation

and the methodological decisions throughout.

Evaluation Theory

The guiding framework for this evaluation was Evaluative Inquiry for Learning in

Organizations (EILO). Hallie Preskill (1999) derived this theory which focuses on

organizational learning and development. Preskill spent over 20 years in academia

teaching graduate-level courses in program evaluation, training design and development,

and organizational learning. Her research has focused on evaluation capacity building,

transfer of learning and training, evaluation use, and evaluation as a catalyst for growth

for individuals, teams, and organizations. Several elements of EILO align with other

58
stakeholder and collaborative evaluation modes; however, Preskill stresses that

evaluation should be ongoing and reflexive, and the research should also embed

evaluation in organizational practice (Preskill & Torres, 1999). Learning from the

evaluation process is an important goal, and the evaluator should work with all

stakeholders to apply the learning from the techniques and findings. Preskill envisions

EILO as an ongoing process for analyzing and understanding critical issues; this process

becomes a catalyst for continued growth and improvement for the organization and the

individual employees (Preskill & Torres, 1999). She acknowledges that evaluation occurs

within a complex system and is influenced by the organization’s infrastructure.

Conducting this significant program evaluation on the effects of employer tuition funding

on the persistence, retention, and time to degree completion for adult learners loses

meaning if the outcomes are not relevant, practical, and used to further organizational

learning and development. Evaluation should be a mechanism for gaining knowledge,

and there is much yet to be learned about the persistence and retention of adult learners

across all higher education institutions. Program stakeholders should use the outcomes of

this evaluation to strategically plan how the organization–in this case, University College

continues to approach the problem of persistence and retention for post-traditional

learners with a solutions-oriented approach.

The evaluation emphasized using this data for both University College moving

forward and other higher education institutions that serve post-traditional learners. I

designed this program evaluation with EILO specifically to provide results that can guide

strategic planning and organizational change when navigating the complex problem of

persistence, retention, and time to completion for adult learners within a complex

59
organizational system. This evaluation aimed to create transformative learning, defined

by Preskill and Torres (2000), as a process where individuals, teams, and organizations

identify, examine, and understand the information or process needed to meet specific

goals. I intend to align strategy and evaluation to create learning opportunities for higher

education leadership and administration serving the post-traditional student population

beyond the University of Denver’s campus. Shulha and Wilson (2003) explain:

When adults are immersed in challenging contexts where learning is supported by

a social structure such as a collaborative partnership, the conditions are ripe for
the development of knowledge structures that transcend that task. In the context
of social program evaluation, collaborative inquiry has demonstrated the ability to
inspire participants to think and act in new and productive ways. (p. 653)

The partnership between University College and Guild is ongoing; thus, conducting the

evaluation based on a theory of use was appropriate for internal growth and learning

opportunities. It is plausible that sharing the knowledge learned from this program

evaluation beyond University College with other stakeholders, including Guild or other

higher education institutions, will allow for more learning and understanding of the

influence employer tuition funding and cost has on adult learners’ persistence, retention,

and time to completion. An outcome of designing this evaluation with an emphasis on use

was that doing so would “result in more useful recommendations and enhance the use of

evaluation findings” (Preskill et al., 2003, p. 424).

One of the goals of this evaluation was to influence learning and strategy and

move from simply having outputs to establishing meaningful outcomes. Evaluating from

the use perspective allows stakeholders to implement the evaluation's results or outputs to

influence change and strategy, as referred to by Preskill. Every program evaluation or

study has results or outputs, but when stakeholders act upon those outputs, they become

60
outcomes. Implementing these outcomes allows an organization to progress and improve

strategic decisions. The outputs or results of this program evaluation can provide a

framework for University College’s next strategic planning cycle. From course planning

and predictions to possible policy changes, understanding how cost influences the adult

learners can facilitate change that positively impacts the students, University College, and

the University of Denver. Preskill explains that the potential for positive change and

impact increases when strategy and evaluation are interwoven. She explains that

evaluation and strategy should not be mutually exclusive, and instead they should be fluid

and reinforce each other (Alkin, 2012) (see Appendix E). Taking a use approach allows

for the program evaluation to serve as a model for change and addressing obstacles

surrounding persistence, retention, and time to degree completion for adult learners.

Preskill explains that strategic evaluation often focuses on different questions than

program-level evaluations (Alkin, 2012, p. 331). Some of the questions she focuses on

are: to what extent are we making the right strategic choices; what are we learning about

how well our programs are progressing in implementing our strategy; what else should

we be doing; how should we refine our strategy in the future? I have shaped my research

questions with these focuses in mind as they have served as a framework for examining

data and delivering results and implications.

The partnership between Guild and University College was a strategic approach

to propel University College forward to serve the growing number of adult learners who

may not have previously had access to higher education. Using Preskill’s evaluation

model allows a reflexive look at the strategic decision to partner with Guild, what

University College has learned from the implementation of the partnership, and what

61
changes need to occur to meet the goals of this partnership. A strategic approach needs to

be continually tested and refined and conducting this essential program evaluation allows

for a data-informed approach toward improving persistence, retention, and degree

completion for both Guild and Organic adult learners.

Problem Statement

Understanding student persistence and retention, particularly focusing on post-

traditional learners, is critical to implementing changes and strategies to serve this unique

population. Much of the research and retention theories focus on traditional learners,

pointing to social connection, self-efficacy, and belonging as essential factors in the study

of retention (Spady, 1970, 1971; Tinto, 1975, 1993; Pascarella, 1980; Cabrera et al.,

1993). While these are important factors for traditional students, they miss the mark when

examining persistence and retention for the post-traditional student population. Finding

the solutions to the retention problems faced across higher education needs to be as

unique as the student populations served. With the growing percentage of adult learners

returning to higher education, we must look at how this population is influenced by

external environmental factors which are different from traditional learners. Bean and

Metzner (1985) define environmental variables such as finances, hours of employment,

outside encouragement, family obligations, and the opportunity to transfer as having the

most significant impact on adult learners, and Bound et al. (2010) demonstrated that

financial support has a positive effect on college completion. Based on previous

persistence and retention research, continued research on the effects of employer tuition

funding on persistence and retention is critical to serving the adult learner and the

institutions enrolling these learners into their programs.

62
Theoretical Framework

This program evaluation was supported by a theoretical framework composed of

three different theories, which are all essential in exploring and solving the problem of

persistence and retention of post-traditional learners. I expanded upon EILO earlier in

this chapter and used EILO and Bean and Metzner’s (1985) Conceptual Model and

Human Capital Theory to ground my research. Bean and Metzner’s Conceptual Model

establishes the differences between traditional and post-traditional learners and the need

for further research to understand the effects of external environmental factors when

researching the impacts of persistence and retention for post-traditional learners.

Organizational turnover is the groundwork for their study, and one of the educational

factors for completing one’s degree is the perceived value of earning the degree. I explain

the perceived value of earning one’s degree with the use of Human Capital Theory.

Human Capital Theory establishes the cost-benefit analysis or business decision adult

learners make each quarter as they move toward or away from degree completion. The

combination of these theories strengthens the argument that employer tuition funding

positively affects post-traditional learners' persistence and retention.

The theoretical framework of Bean and Metzner’s (1985) Conceptual Model,

Human Capital Theory, and Evaluative Inquiry for Learning in Organizations are

essential to this program evaluation. Each theory or model is interdependent like

interlocked gears. When one gear moves, each of the others moves along as if none

functions independently. Bean and Metzner’s model and Human Capital Theory

illuminate the influence cost and funding have on adult learners, and EILO provides the

63
approach to strategically think about how higher education leaders approach the retention

and persistent problems of adult learners. This program evaluation's design and

methodological approach were intended to provide results that can impact strategic

planning and organizational change to address the persistence and retention problem for

post-traditional learners.

Research Questions and Hypotheses

This program evaluation explored how employer tuition funding increases

persistence and retention and decreases time to degree completion for post-traditional

learners. The following research questions align with the established theoretical

framework, which guides the evaluation of the external partnership between the

University of Denver’s University College and Guild.

1) How does the retention of post-traditional students who receive funding

through the Guild partnership compare to students who do not receive this

funding?

2) How does time to time to degree completion for post-traditional students

compare across different funding levels?

3) How is the retention of post-traditional students affected by age, GPA, race,

gender, and employer tuition funding?

While many independent variables can influence persistence, retention, and

degree completion for post-traditional learners, I hypothesize that the most significant

influence on persistence, retention, and degree completion can be attributed to tuition

funding from one’s employer (Long, 2007; Becker, 1975). According to Bean and

Metzner (1985), adult learners are most directly affected by external environmental

64
factors, one of which is finances. These research questions focus on the importance and

influence of the external factor of finances for adult learners. I expect the relationship

between up-front employer tuition funding (independent variable) and the dependent

variable of persistence/retention to be positive. Therefore, I expect to see Guild students

retain and persist at higher rates as they have up-front employer tuition funding where

Organic students do not (Frankfort-Nachmias & Leon-Guerrero, 2011). I also expect the

relationship between employer tuition funding (independent variable) and time to

completion (dependent variable) to be negative, such that as tuition funding from

employers increases the time to completion of the student’s program decreases

(Frankfort-Nachmias & Leon-Guerrero, 2011). Finally, I hypothesize that up-front

employer funding will have the greatest influence on retention (dependent variable) when

examining the independent variables of age, GPA, race, gender, and up-front employer

funding for tuition and fees.

The theoretical framework discussed in Chapter Two established the differences

between post-traditional learners from traditional learners and a need for more research

on this unique population. Understanding the differences between post-traditional and

traditional-aged learners shows that extrapolating from retention theories that focus on

traditional students (Spady, 1970, 1971; Tinto, 1975, 1993; Pascarella, 1980, Cabrera et

al., 1993) may not be helpful when examining the post-traditional student population.

Instead, the differences in these student populations illuminate the need for further

research on external environmental factors to describe and understand the persistence and

retention of adult learners. Each research question in this program evaluation focuses on

the external environmental factor of finances and, more specifically, on the impact of up-

65
front employer tuition funding. Understanding how employer funding influences adult

learners’ decision–a cost-benefit analysis, to pursue education and continue toward

completion is essential if higher education leaders want to address the persistence and

retention of post-traditional students. If students find value in their degree and do not

carry the financial burden, they are more likely to begin a degree, persist through it, and

finally complete it.

Research Design

I used a quantitative approach, specifically descriptive statistics, t-tests, Kruskal

Wallis Test, and multiple regression, to study the relationship age, GPA, race, gender, and

employer tuition funding (independent variables) have on persistence/retention and time

to degree completion (dependent variables). I examined the relationship between the

dependent variables and the five independent variables using a multiple regression model,

which provided the ability to estimate and predict future outcomes (Mendenhall &

Sincich, 2012). The program evaluation used archival data from 2017-2022 to compare

two separate groups of adult learners: those students who entered a University College

academic program through the partnership with Guild–referred to as Guild students, and

those students who are not a part of the partnership–referred to as Organic students. I

examined Guild and Organic students across University College’s academic programs to

understand and gain further insights on the importance of employer tuition funding. I was

interested in the linear relationship between these variables, so I analyzed the data using

t-tests, correlation, and multiple regression models (Mendenhall & Sincich, 2012).

To examine how employer tuition funding levels affect post-traditional learner

time to degree completion, I conducted Kruskal Wallis Test. In this test, I tested three

66
different levels of employer tuition funding: unlimited employer tuition funding, some

employer tuition funding, and no employer tuition funding. Those students who receive

employer tuition receive between 10,000 and 3,000 dollars per calendar year for tuition,

and fees were all grouped into the employer tuition funding group labeled as some

employer tuition funding. While the funding range is relatively large, this grouping was

necessary for testing purposes due to the lower population numbers of students with some

employer tuition funding compared to unlimited employer tuition funding and no

employer tuition funding.

Using multiple regression models, I tested each of the five independent variables–

age, GPA, race, gender, and employer tuition funding for tuition and fees, against the

dependent variables–persistence/retention and time to degree completion. I tested various

subsets of the archived dataset. The subsets included testing the data by level (graduate

(Master of Science and Master of Arts only) and undergraduate) and degree (Master of

Science, Master of Arts, and Bachelor of Arts). This program evaluation does not

examine the independent variables separately, as they are all expected to have varying

levels of influence on each dependent variable. This allowed for the ability to control the

effects of each variable independently of each other (Frankfort-Nachmias & Leon-

Guerrero, 2011).

The dependent variable of time to degree completion represents a generic unit of

time to provide comparison across all groups. I created a unit of time by taking the

completion quarter minus the beginning quarter for every student across the dataset.

Throughout this program evaluation, I will refer to “unit of time” when describing the

results on tuition retention and time to degree completion, as time is not equivalent to

67
months or quarters and instead to an arbitrary unit of time that is consistent across all

students regardless of program or level. An example of this conversion is a student who

began their program in winter 2019 (201910) and completed it in spring 2021 (202130)

quarter would have their unit of time represented as 220 or 10 quarters.

Site Description

University College is the College of Continuing and Professional Studies at the

University of Denver (DU). Its mission is to deliver enduring professional growth and

personal development by providing adult learners access to DU through alternative

educational pathways (University College Website, 2022). In the mission statement, the

word “access” is used, but what is not mentioned but is found in University College

policies and business rules is the word support. University College has built support

systems and procedures that differ from the rest of the DU campus. These systems and

procedures are designed for post-traditional learners to transition back into higher

education and persist toward their personal, professional, and academic goals. University

College offers career-focused content through both credit and non-credit academic

pathways. This program evaluation focuses on the credit-bearing academic programs

offered through University College, which are a part of the Guild partnership. University

College provides a variety of degree paths for adult learners; I chose to focus on adult

students pursuing master’s degrees, graduate certificates (both six-course and four-

course), and bachelor’s degrees through a Bachelor of Arts Completion program. The

similarities across these programs allowed for more reliability in the overall program

evaluation and results. Although University College students are DU students, they do not

fit the traditional mold of other DU students. University College students are often

68
balancing work and family obligations while attending school, and many are completing

their coursework fully or mostly online. To cater to the adult learner University College

has adjusted policies, procedures, and best practices to account for the differences of this

unique student population.

Each quarter, 80% of University College enrollments are online in synchronous

and asynchronous modalities. Most University College students complete over 70% of

their program requirements online, and many complete their entire program online

without stepping foot on campus until graduation day. These students are more than

numbers and segmented categories; however, it is helpful to understand the post-

traditional learners in this program evaluation and the diversity they bring to the DU

campus by a variety of classifications. The students in this program evaluation represent

diversity in a variety of ways and are representative of other Professional, Continuing,

and Online Education (PCO) units–90% have full-time jobs while enrolled in classes,

65% reside outside the state of Colorado, 64% identify as female, 25% identify as

students of color, 10% are active duty or veteran students, and the average age is 32

(University College Enrollment Report, 2022).

Guild serves as the conduit between employers and higher education institutions–

often through Professional, Continuing, and Online Education (PCO) units, by building

strategic education and reskilling experiences. Guild’s mission is to unlock opportunities

for America’s workforce through education and reskilling by working to bridge the gap

between education and employment for working adults in the United States to help them

succeed in the future of work (Guild Website, 2022). Guild focuses on transforming

traditional tuition reimbursement into a strategic investment that aligns employees with

69
company needs, increasing recruiting, retention, upskilling, and brand equity (Guild

Website, 2022). The partnership between University College and Guild began in 2017,

and the number of students in the program continues to grow as Guild adds new

employers to their portfolio. During the timeframe of this program evaluation, University

College admitted 100-150 new students each quarter through the Guild partnership across

all their academic programs–master’s, graduate certificates, and the Bachelor of Arts

Completion Program (Guild Admissions Report, 2022). University College continues to

admit 50-70 new Guild students each quarter; the numbers of new students fluctuate with

the changes in employers and funded programs. Once a Guild student is approved, by

Guild and their company, for employer tuition funding and admitted into an academic

program, they are grandfathered into this funding if they remain with the employer. These

students are more than the companies they are associated with; however, it will be helpful

to understand the employer population associated with the Guild student population and

when each employer began their partnership with Guild. Table 3.1 provides a complete

list of all Guild employer partners associated with University College, listed

alphabetically. The table demonstrates many industries Guild has partnered with,

including but not limited to healthcare, financial, hospitality, fast casual, and supply chain

and transportation. The diversity of companies Guild partners with shows the company’s

commitment to upskilling America’s workforce across various industries. Each employer

works with Guild to set funding levels and approved portfolios of academic programs and

educational partners based on the company’s available budget, goals, and best practices.

70
Table 3.1

71
Selection of Participants

University College has approximately 3,200 active credit-bearing students during

any given year (not including students in the Frontline Manager Leadership Program,

(FMLP)). Thirty to 35% of new credit-bearing students each quarter enter University

College through the Guild partnership. In this evaluation, I tested different samples as

subsets of the entire archived dataset to generalize observations back to the overall

University College student population (Frankfort-Nachmias & Leon-Guerrero, 2011). To

ensure the reliability of the program evaluation, I used representative samples for various

subsets across the population. These subsets included students who have completed

master’s, graduate certificates, and bachelor’s degrees, thus allowing for generalization

back to the greater population for these program samples. Ensuring that each sample was

representative of the larger population allowed for generalizations of the relationships of

the variables back to the larger population (Mendenhall & Sincich, 2012). This program

evaluation does not include any students admitted to the FMLP program as the program

is a bespoke corporate program and, therefore, not available to Organic students. This

program evaluation did not use randomized sampling as the dataset only included

students who meet the program evaluation criteria, meaning they completed their degrees

between fall 2017 and fall 2022. I examined the results by level (graduate and

undergraduate) as well as degree (Master of Science, Master of Arts, six-course Graduate

Certificates, four-course Specialized Graduate Certificates, and Bachelor of Arts) to

account for possible differences that may occur in different subsets of the overall

population.

72
 The program evaluation did not limit or categorize data based on the

demographics of students. While demographic data was available and included in the

reporting of individuals in each sample, decisions on whom to include or exclude were

not determined based on these demographics. Rather, the ability to speak to the

relationship of employer tuition funding on persistence, retention, and time to degree

completion for adult learners was not limited by age, race, ethnicity, gender, or the

program the student completed. The program evaluation included only those students

who completed one credential between fall 2017 and fall 2022. It is common for students

to stack degrees at University College or complete multiple degrees simultaneously. The

stackable credentials at University College allow students to begin with a smaller

credential and then use those credits earned toward a master’s degree or to add a graduate

certificate onto their master’s degree without taking six additional courses. Accounting

for the overlap in courses will reduce the reliability of the results; thus, students who

completed multiple degrees during the timeframe of the program evaluation were not

used in the data.

I thoroughly cleaned the data to ensure the reliability and validity of the results.

Participant inclusion criteria included having available data for all variables–dependent

and independent. There were no inclusion or exclusion data required for the following

variables: Student ID, Student Name, Level, Ethnicity, Race, Completion Quarter, Guild,

Award Category Description, Degree, Gender, GPA Level, Credits Earned, Credits

Passed, and Credits Attempted. I excluded any student with the program variable of

‘TRMG’ as this program does not align with the program evaluation. ‘TRMG’ is a cohort

program, and this program is not a part of the Guild portfolio of programs, meaning

73
Guild students may not choose this program of study. I excluded any student with a

concentration variable of ‘LBA’ as this concentration is associated with a specific

partnership through Centura. The ‘LBA’ concentration is not a part of the Guild portfolio

of programs, meaning Guild students may not choose this concentration of study. I

excluded six students from the GPA variable who did not graduate and therefore did not

meet the criteria of the dataset. I excluded two students from the Transfer Hours variable

who did not graduate and therefore did not meet the criteria of the dataset. I excluded two

students from the Credits Attempted variable who did not graduate and therefore did not

meet the criteria of the dataset. I excluded 17 students from the GradStatusDesc variable

who did not graduate and therefore did not meet the criteria of the dataset. I kept a log

reporting all demographic and variable data for those individuals removed from the

student population. The dataset only includes students who have completed programs, as

predicting graduation dates for the post-traditional learner population who are in progress

toward their degree would produce less reliable data and impact the program evaluation

results.

Instrumentation

This program evaluation examines the relationship of different sample groups

(Guild students and Organic students) using archival data and a statistical program–Stata.

First, I ran t-tests to compare the mean of Organic and Guild students to determine if

there was a significant difference between the two groups. Once I determined that there

was a significant difference between the two groups, I ran multiple regressions using

Stata to examine the relationship between the independent variables (age, GPA, race,

gender, and employer tuition funding for tuition and fees) on each of the dependent

74
variables (persistence/retention and time to degree completion). Finally, I used the

Kruskal Wallis Test to test the effects of different funding levels on time to degree

completion.

The alpha–the level of probability for this program evaluation was set at .05. It is

customary to set the alpha for a quantitative study at .05, .01, or .001 (Frankfort-

Nachmias & Leon-Gerrero, 2011). As .01 and .001 are more cautionary levels of risk

often used within clinical assessments, a probability of .05, allowing for a five percent

error in sampling, is appropriate for this evaluation (Frankfort-Nachmias & Leon-

Gerrero, 2011). I also used Cronbach’s alpha of .80 to show the measure of reliability

across the program evaluation (Mendenhall & Sincich, 2012). I also tested the effect size

of each sample using Stata. I ensured the validity of the results by testing multiple runs of

the data to compare results for consistency. I tested the data as a large sample and smaller

subsample sets across different levels and degrees to ensure that the independent

variable–employer funding for tuition and fees- was the primary influence on each

dependent variable (persistence/ retention and time to degree completion). The

subsamples of levels and degree remained consistent throughout all testing to assure that

there were not differences across different student or degree types. Similar results across

different subsets demonstrated both reliability and validity.

Assumptions

I verified the following assumptions independence, normality, and equal variance,

which are all needed to produce effective results. Independence indicates there is no

relationship between observations in each group, normality indicates the distribution of

scores is normally distributed along a bell curve, and equal variance is when the

75
variances are approximately the same across the samples (Mendenhall & Sincich, 2012).

The variances of the two populations (Guild and Organic) were unequal, and therefore I

used Welch’s formula for unequal variances when running t-tests on each of these

populations. I had planned to examine the relationship of employer funding levels on

time to degree completion, using analysis of variance (ANOVA) to test the various levels

of Guild employer funding. The data did not allow for ANOVA testing as the distribution

across the three employer funding levels was not evenly distributed. This violates the

assumptions that must be met to conduct an ANOVA, as the n is not high enough across

the three levels. There were still violations at three funding levels (zero employer tuition

funding, some employer tuition funding, and unlimited employer tuition funding).

Therefore, I used the non-parametric Kruskal Wallis Test to test the influence of funding

levels on time to degree completion.

I ensured the following six assumptions before running regression model tests to

produce effective and reliable results (Mendenhall & Sincich, 2012, pp. 110-111):

1. The relationship between the dependent variable and independent variables is

linear.

2. The error term has a mean of zero.

3. The error term has a constant variance.

4. The errors are uncorrelated.

5. The errors are normally distributed.

6. The independent variables are fixed; therefore, the least-squares method is the

best linear unbiased estimator.

76
Data Processing and Analysis

The data for all University College students–Guild and Organic, is available and

stored as archival data in several university systems. I requested permission to use this

data and pulled reports based on the data via a formal letter addressed to the then

Assistant Dean of Enrollment, Marketing, and Partnerships of University College (see

letter in Appendix F). Dr. Chris Nicholson is now the Associate Dean of Enrollment,

Marketing, and Partnerships.

In the first research question of the evaluation, I examined the relationship

between persistence and retention of post-traditional learners who receive employer

tuition funding through the Guild partnership compared to those students not in the Guild

partnership. I ran t-test analyses to determine if there was a significant difference between

the retention of Guild and Organic students. Once I determined there was a significant

difference in the retention of Guild and Organic students, I used different sample sets to

examine students across levels (graduate and undergraduate) and degrees (master’s,

graduate certificates, and bachelor’s degrees) to ensure accurate comparisons. I expected

that there would be a positive relationship between employer funding and persistence for

adult learners. The null hypothesis states the difference in group means is zero and the

alternate hypothesis that the different in the group means is different from zero.

H0: µGuild -µOrganic = 0

Ha: µGuild -µOrganic > 0

In the second research question of the evaluation, I examined how different

funding levels affect the time to degree completion for post-traditional learners. To

account for the violations in assumptions, I ran a Kruskal Wallis Test, a non-parametric

77
test, to compare funding at three different levels. I grouped the funding levels into three

categories: unlimited up-front employer tuition funding, some up-front employer tuition

funding, and zero up-front employer tuition funding. I grouped those students who

receive employer tuition funding between 10,000 and 3,000 dollars per calendar year into

the employer tuition funding group labeled as some employer tuition funding. Table 3.2

shows employer tuition funding levels distribution across each funding level from this

program evaluation. I hypothesized that the time to completion would decrease as up-

front employer tuition funding increased.

H0: Time to degree completion is equal across all funding levels.

H1: There is a significant difference in time to degree completion across different

funding levels.

Table 3.2

In the third research question, I ran multiple regression analyses to determine the

relationship using each independent variable (age, GPA, race, gender, and employer

funding for tuition and fees) on the dependent variable of time to degree completion.

Once the relationship for each independent variable was determined, I examined and

78
compared across the same sample sets used in the previous research questions. I

hypothesized that age, GPA, race, gender, and employer funding for tuition and fees

would all affect persistence; however, employer tuition funding would have the greatest

effect on persistence/retention for post-traditional students. I expected that there would be

a negative relationship between employer funding and time to degree completion.

H0: 𝛽𝛽 employer funding = β age = β GPA = β race = β gender = 0

H1: At least one of the coefficients ≠ 0

I examined research questions one and three across all levels and degrees using

archival data, thus allowing for comparison across program levels and degree types. I

hypothesized that the greatest determinant of improved persistence rates for post-

traditional students would be employer tuition funding aligning with Bean and Metzner’s

(1985) Conceptual model of Non-traditional Undergraduate Student Attrition. Therefore,

I expected to see post-traditional students who receive employer funding through the

Guild partnership persist and retain at higher rates than the Organic post-traditional

learners who do not receive tuition funding through the Guild partnership. I also expected

the results to indicate that post-traditional students receiving employer tuition funding

(Guild students) have quicker completion times than those not receiving tuition funding

through their employer (Organic students).

Limitations and Delimitations

As with all research, limitations exist, and I address the limitations of this

program evaluation in this section. Within the dataset, some Organic students had tuition

funding from the U.S. Department of Veteran Affairs (VA), outside scholarships, or their

employers as tuition reimbursement. Although these students had some funding, they

79
were not admitted to University College through the Guild partnership and therefore were

classified as Organic in this program evaluation. While some organic students may

receive funding from outside funding sources, including their employer, the vast majority

who receive employer tuition funding receive that funding as a reimbursement versus

receiving up-front tuition funding like Guild students. I chose not to remove these

Organic students from the program evaluation, as I did not expect the small number of

Organic students who received outside funding to influence or compromise the program

evaluation results. The inclusion of these Organic students who may have outside funding

means that the results of this program evaluation may be understated as the tuition cost to

these Organic students would be lower as they may not be funding their education

entirely on their own or through the use of financial aid.

It is also important to recognize that this program evaluation spans a time in

which Coronavirus Disease 2019 (COVID-19) impacted the globe. While there are many

global impacts of COVID-19, including but not limited to economic and social, it is not

yet determined to what extent COVID-19 has impacted higher education as a whole and

this program evaluation particularly. Everything during the pandemic shifted, including

how students engaged with higher education. PCO units, including University College,

saw a greater demand for education during the peak of COVID-19 (National Center for

Educational Statistics, 2021). As the world moved from a pandemic to an endemic, the

demand for higher education decreased, and the competition for attracting students across

higher education institutions increased, with more programs now offering online

programming. While there are a variety of impacts of COVID-19 to consider, it is

80
important to recognize that we still do not fully understand the extent of the economic,

social, and higher education repercussions.

The United States faced historic unemployment rates during these times, 26.4

million Americans filed for unemployment between March, 2020 and April, 2020

(Soergel, 2020). Researchers projected that 54 million jobs were vulnerable to reductions

in hours or pay temporary furloughs, or permanent layoffs (McKinsey & Company, 2021;

Strada Education, 2020). This economic shift because of COVID-19 impacted higher

education as higher education enrollment tends to follow a countercyclical trend to the

U.S. economy (Barr & Turner, 2013; Kantrowitz, 2010). As individuals faced uncertainty

in employment, many adult learners sought higher education to help them reskill, upskill,

and retool (National Center for Educational Statistics, 2021). With the massive layoffs

across the United States, many used the opportunity to make a career shift or pivot. This

influx in the post-traditional student population and the changes Guild employer partners

made to their tuition funding may have influenced the results of this program evaluation.

Many of the Guild students who pursue their education through University

College as a part of the Guild partnership are or were employed by The Walt Disney

Company (Disney) and used Disney Aspire funding to fund their education., Disney laid

off many employees during the COVID-19 pandemic and reduced tuition funding for

those who remained employed to counter the financial impacts from many months of

park closures. Furloughed employees, who had already been admitted to programs, still

received benefits through Disney, including their educational benefits through the Disney

Aspire program; however, thousands of employees were laid off and no longer eligible

for benefits. University College provided a $500 per course tuition relief grant to provide

81
financial and academic support for those University College students who lost their jobs

because of the pandemic. University College offered this tuition relief grant to Guild

students who lost funding and Organic students alike. As these changes occurred in the

middle of the program evaluation and COVID-19 was still impacting our world, it is

unclear if and how COVID-19 influenced this program evaluation. Before COVID-19,

Disney funded all employees who wished to pursue higher education with unlimited

tuition funding. Disney implemented a course cap to their funding model for all Disney

employees including those furloughed as a result of the pandemic. This course cap

reduced the employer tuition funding for Disney students from unlimited funding, prior

to covid. The reduced employer funding afforded graduate-level students tuition funding

for one course per quarter, and undergraduate students funding for two courses per

quarter. Disney implemented the funding course cap from the winter 2021 quarter

through the fall 2021 quarter, which could have influenced the results of each research

question in this program evaluation.

Finally, University College experienced an influx of organic students during the

fall 2020 quarter who returned to education to upskill due to layoffs and economic

uncertainty. It is unclear how the influx of fall 2020 organic students may have affected

the study as this is an anomaly in the data and deviates heavily from the number of new

Organic students in any other quarter prior to or since fall 2022.

Positionality

Over the past nine years, I have dedicated my professional efforts to serving adult

learners in their academic journey. Whether they are returning to education to complete a

degree, they began years ago, upskilling to advance their career, or retooling for a career

82
pivot, serving this growing population is my passion. I stumbled into a job as an

academic advisor in May of 2014 at University College and have now made a career of

serving adult students. I advise students in our Bachelor of Arts Completion Program

(BACP), many of whom have entered through the partnership with Guild. I also oversee

the Enrollment Management team and co-lead University College’s Guild partnership

alongside our Associate Dean of Enrollment, Marketing, and Partnerships. I have been

heavily involved with the Guild partnership since its inception in 2017 and have

experienced the growing pains of establishing a large (both monetarily and student

headcount) partnership and the benefits for University College, the University of Denver,

and the students who entered our programs through the Guild partnership. My deep

knowledge and understanding of the Guild partnership and the Guild and Organic student

populations give me the insider’s perspective needed to analyze the data. I can bring the

statistical analysis to life through my understanding of the intricacies of both the Guild

and Organic student populations. This knowledge and understanding allowed me to

approach the dataset from a point of view others do not have as they do not have the

intimate knowledge of the partnership or the student populations, I have gained over my

time with University College and specifically my in-depth work with the Guild

partnership.

I currently hold the Director of Enrollment Management position at University

College and have served in this position since August 2020. My roles and responsibilities

as the Director of Enrollment are as complex as the adult students we enroll and serve.

Having a complete understanding of enrollment best practices, including providing

access and implementing strategies, policies, and systems to retain students once they

83
begin their program is vital to my position within University College. I collaborate with

University College leadership to predict enrollment numbers and ensure we meet

enrollment and new student goals. While I often report on numeric goals, I approach my

position and responsibility from a mindset of creating an exceptional and inclusive

student experience for each learner, whether admitted organically or through the Guild

partnership. Increasing persistence and retention not only benefits the University of

Denver and University College's bottom line but also benefits the learner, their families,

their communities, and our overall economy.

Conclusion

This program evaluation analyzes the effects employer tuition funding has on

post-traditional learners and their persistence, retention, and time to degree completion. I

used t-tests and multiple regression models to test the relationship between employer

tuition funding and persistence/retention and the time to degree completion for students

entering the program through the Guild partnership and students who entered the program

outside of the partnership. This evaluation demonstrates how influential employer tuition

funding can be for post-traditional learners. I will share the results of this program

evaluation with stakeholders for organizational learning and strategic planning. In

Chapter Four, I provide an in-depth explanation and breakdown of the results of this

program evaluation.

84
 CHAPTER FOUR: RESULTS

In this chapter, I present the results from my program evaluation of the University

College and Guild partnership. I took a quantitative approach to examine the partnership

and the potential effects of employer tuition funding on adult learners' persistence and

retention. My results are based on descriptive analysis, t-tests, Kruskal Wallis Test, and

multiple regression models. Throughout this chapter, I frame the results using each of my

research questions.

Program Evaluation Purpose and Research Questions

The purpose of this program evaluation was to acquire knowledge of employer

tuition funding and its effects on the persistence and retention of adult learners. Bean and

Metzner’s (1985) Nontraditional Student Attrition Model supports the need for further

research and this program evaluation. Understanding the effects of employer funding is

vital to serving the growing adult learner population. By examining the University

College and Guild partnership, I was able to compare different subsets of post-traditional

student populations and how employer funding affected time to completion and retention

compared to students who do not have similar funding. The following research questions

guided my evaluation of the University College and Guild partnership.

1) How does the retention of post-traditional students who receive funding

through the Guild partnership compare to students who do not receive this

funding?

85
 2) How does time to time to degree completion for post-traditional students

compare across different funding levels?

3) How is the retention of post-traditional students affected by age, GPA, race,

gender, and employer tuition funding?

Analyses of Guild and Organic Retention

Research Question One: How does the retention of post-traditional students who

receive funding through the Guild partnership compared to students who do not receive

this funding?

H0: µGuild -µOrganica = 0

Ha: µGuild -µOrganic > 0

To examine this hypothesis, I conducted an independent-sample t-test with

unequal variances for the overall population and sub-sets of the population. The variances

of the two populations (Guild and Organic) were unequal, and therefore I used Welch’s

formula for unequal variances when running t-tests on each of these populations. I used

the t-test command in Stata 17 (StataCorp., 2023) to calculate t-tests comparing time to

completion for Guild and Organic students. Table 4.1 reveals the average time to

completion among Guild students (𝑀𝑀 = 181.0204, 𝑆𝑆𝑆𝑆 = 66.05064) is significantly

lower than that of Organic students (𝑀𝑀 = 204.4223, 𝑆𝑆𝑆𝑆 = 121.0128), 𝑡𝑡(2394) =

7.0655, 𝑝𝑝 < .001. I used the esize command in Stata 17 (StataCorp., 2023) to calculate

the effect size. Cohen describes the measures of magnitude in effect size and breaks them

down effect into three categories small (𝑑𝑑 = 0.2); medium (𝑑𝑑 = 0.5); and large (𝑑𝑑 ≥

0.8) (Cohen, 1977). The effect size result for this first t-test was small (𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 =

.211). According to Cohen (1977), a small effect of .2, while noticeably smaller than a
86
medium effect size, does not make the result trivial. Even with a small effect size, the

results suggest that Guild students are more likely to be retained at higher rates than

Organic students when examining the entire population.

Table 4.1

I continued testing retention for Guild and Organic students by level (graduate

and undergraduate) as well as by degree [Master of Science (MS), Master of Arts (MA),

six-course graduate certificate (CRTG), four-course graduate certificate (CRTM), and

Bachelor of Arts (BA)] to examine the effects of employer funding on these different

subsets of the overall population.

Table 4.2 reveals that the average time to completion among Guild graduate

students (which includes MS, MA, CRTG, and CRTM) (𝑀𝑀 = 178.6301, 𝑆𝑆𝐷𝐷 =

63.94689) is significantly lower than that of Organic graduate students (𝑀𝑀 = 198.8868,

𝑆𝑆𝑆𝑆 = 105.359), 𝑡𝑡(1941.7) = 6.4597, 𝑝𝑝 < .001. The effect size was small

(𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 = .207). While the effect size of these results was small, they do suggest that

Guild graduate students are retained at higher rates than Organic graduate students. When

comparing the results from this sub population to the overall population, the mean
87
difference of time to complete decreased by 3.145 units of time, and the effect size

decreased slightly by .004 compared to the overall population. The removal of the

undergraduate students decreased the overall mean difference in time to complete

between the Guild and Organic students, suggesting undergraduate students were

influenced more by employer tuition funding than graduate students.

Table 4.2

Table 4.3 reveals that the average time to completion among undergraduate Guild

students (𝑀𝑀 = 213.333, 𝑆𝑆𝑆𝑆 = 84.0485) is significantly lower than that of Organic

undergraduate students (𝑀𝑀 = 373.2558, 𝑆𝑆𝑆𝑆 = 307.148), 𝑡𝑡(104.589) = 4.5640, 𝑝𝑝 <

.001. The effect size was medium (𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 = .648). These results suggest that

undergraduate Guild students are more likely to be retained than Organic undergraduate

students. When comparing the results from this sub population to the overall population,

the mean and effect size increased drastically. The mean increased by 136.521 units of

time, and the effect size increased by .437 compared to the overall population. These

results suggest differences in the effects of employer funding in the graduate-level and

undergraduate-level student populations. As such, the results suggest that undergraduate

88
students are more significantly influenced by employer tuition funding benefits than

graduate students.

Table 4.3

Table 4.4 reveals that the average time to completion among Master of Science

(MS) Guild students (𝑀𝑀 = 184.8872, 𝑆𝑆𝑆𝑆 = 58.05809) is significantly lower than that of

MS Organic students (𝑀𝑀 = 218.4265, 𝑆𝑆𝑆𝑆 = 97.72358), 𝑡𝑡(567.064) = 7.7186, 𝑝𝑝 <

.001. The effect size was small (𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 = .361). These results suggest that MS Guild

students are retained at higher rates than MS Organic students. When comparing the

results from this subpopulation to the overall population, the mean and effect size

increased. The mean increased by 10.137 units of time, and the effect size increased by

.15 compared to the overall population. These results suggest that the retention of

students pursuing MS degrees is influenced by employer funding but not by the same

magnitude as undergraduate students were retained. The mean and effect size also

increased when comparing MS students to the overall graduate-level (MS, MA, CRTG,

CRTM) results. The mean increased by 13.283 units of time, and the effect size increased

89
by .154. These results suggest differences in the effects of employer funding among

different types of graduate-level student populations based on degree type.

Table 4.4

Table 4.5 reveals that the average time to completion among Master of Arts (MA)

Guild students (𝑀𝑀 = 190.8635, 𝑆𝑆𝑆𝑆 = 60.8054) is significantly lower than that of MA

Organic students (𝑀𝑀 = 235.4545, 𝑆𝑆𝐷𝐷 = 111.5526), 𝑡𝑡(703.98) = 7.1790, 𝑝𝑝 < .001.

The effect size was much closer to medium yet is still considered small (𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 =

.483). These results suggest that MA Guild students are more likely to be retained at

higher rates than MA Organic students. When comparing the results from this sub

population to the overall population, the mean difference in time to complete increased

by 21.189, and the effect size increased by .272 in this group compared to the overall

population. The mean and effect size also increased when comparing MA students to the

overall graduate-level (MS, MA, CRTG, CRTM) results. The mean difference in time to

complete increased by 24.334, and the effect size increased by .276. The results indicate

that employer funding has a greater influence on students in a MA program than an MS

90
program. While the results for both the MS and MA student populations are significant,

indicating Guild students are more likely to be retained, the mean difference in time to

complete and the effect size were larger for MA students than MS students. While MA

students are more greatly influenced by employer tuition funding than MS students,

employer tuition funding has the greatest influence on persistence at the undergraduate

level.

Table 4.5

Table 4.6 reveals that the average time to completion among six-course graduate

certificate (CRTG) Guild students (𝑀𝑀 = 142.9032, 𝑆𝑆𝑆𝑆 = 53.20505) is higher than that

of CRTG Organic students (𝑀𝑀 = 136.4618, 𝑆𝑆𝑆𝑆 = 85.29227), 𝑡𝑡(102.851) = −0.8371,

𝑝𝑝 = .040; however, the results are not significant. The effect size was insignificant

(𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 = −0.078). These results suggest no significant difference in the retention of

CRTG Guild and Organic students.

91
Table 4.6

Table 4.7 reveals that the average time to completion among four-course graduate

certificate (CRTM) Guild students (𝑀𝑀 = 89.30233, 𝑆𝑆𝑆𝑆 = 50.01882) is higher than that

of CRTM Organic students (𝑀𝑀 = 82.03704, 𝑆𝑆𝑆𝑆 = 54.88747), 𝑡𝑡(86.1265) = −0.7831,

𝑝𝑝 = .436; however, the results are not significant. The effect size was insignificant

(𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 = −.136). These results suggest no significant difference in the retention of

CRTM Guild and Organic students.

Table 4.7

92
 As the previous results showed no significant difference in retention for CRTG

and CRTM students, I decided to examine the difference between graduate-level degree-

seeking students, excluding those in CRTG and CRTM programs. Table 4.8 reveals that

the average time to completion among graduate Guild students (MS and MA only) (𝑀𝑀 =

188.32, 𝑆𝑆𝑆𝑆 = 59.67777) is significantly lower than that of Organic graduate students

(MS and MA only) (𝑀𝑀 = 222.2144, 𝑆𝑆𝑆𝑆 = 101.1824), 𝑡𝑡(1805.88) = 10.2785, 𝑝𝑝 <

.001. The effect size was small (𝐶𝐶𝐶𝐶ℎ𝑒𝑒𝑒𝑒’𝑠𝑠 𝑑𝑑 = .365). These results suggest that Guild

students pursuing MS or MA programs are more likely to be retained at higher rates than

Organic students in the same programs. When comparing the results from this sub

population to the overall population, the mean difference in time to complete increased

by 10.492 units of time, and the effect size increased by .154 in this group compared to

the overall population. By removing the CRTG and CRTM students from the overall

graduate calculations that included both CRTG and CRTM, the mean difference in time

to complete increased by 13.638 units of time, and the effect size increased by .158. This

suggests that the overall time to completion of a degree may influence the effects of

employer tuition funding on retention for post-traditional learners. CRTG students only

have six courses to complete their program, CRTM students only have four courses to

complete their program, while MS and MA students need 12 courses to complete their

program. This aligns with the premise that students make educational decisions based on

return on investment used from the Human Capital Theory. The investment of time and

money for CRTG and CRTM students is less than that for MS and MA students.

93
Table 4.8

Student Retention. Given these results, the hypothesis that Guild students would

retain at a higher rate than Organic students was supported for all student populations

except those in graduate certificates (CRTG and CRTM). Based on the results of the

previous tests, I determined that examining the relationship between the number of

courses needed to complete the degree and employer tuition funding would be relevant.

The results support the idea that the more courses a student needs to complete their

degree, the more employer tuition funding affects retention. CRTG and CRTM Guild

students were not found to be retained at higher rates than Organic students. These results

may be partly due to the shorter time and smaller financial commitments for CRTM and

CRTG students, as the cost associated with these programs is far less than that incurred

by students completing a master’s or bachelor’s degree. The analysis indicates that

employer tuition funding has the greatest influence on retention for undergraduate

students, followed by students in MA programs, and finally by students in MS programs.

Research Question Two: How does time to time to degree completion for post-

traditional students compare across different funding levels?

94
 H0: Time to degree completion is equal across all funding levels.

H1: There is a significant difference in time to degree completion across different

funding levels.

I used the Kruskal Wallis Test to evaluate the differences across the three funding

levels (unlimited up-front employer tuition funding, some up-front employer tuition

funding, and no up-front employer tuition funding) on time to degree completion for

post-traditional learners. The test results revealed a statistically significant difference in

time to completion across the three funding levels, 𝜒𝜒2 (2, 𝑁𝑁 = 3,493) = 12.35, 𝑝𝑝 <

.002. Time to degree completion was fastest in the unlimited up-front employer tuition

funding (𝑀𝑀𝑀𝑀 = 160) followed by those who had no up-front employer tuition funding

(𝑀𝑀𝑀𝑀 = 180), and finally those who had some up-front employer tuition funding (𝑀𝑀𝑀𝑀 =

210). These results align with my theoretical framework used to support this program

evaluation. Those students who receive unlimited funding complete their degrees quicker

than the other two groups of students suggesting that employer tuition funding does affect

retention and time to degree completion and is consistent with the results from research

question one. Initially, I had expected those students who receive some tuition funding to

finish quicker than those with no tuition funding; however, these results may suggest that

the decision to return to higher education is strongly influenced by the tuition funding

benefit offered by their employers. Based on the results of this research question, students

with some funding are taking a slower approach to completing their degree to maximize

their funding from their employer. As students with some funding have a capped tuition

model from their employer they are choosing to go at a slower pace even taking quarters

off waiting for their funding to return at the beginning of the calendar year. This aligns

95
with the Human Capital theory, where the students weigh higher education and the return

on investment (ROI) partially on funding and proceed through the program at a slower

rate to maximize employer tuition funding benefits.

Research Question Three: How is the retention of post-traditional students

affected by age, GPA, race, gender, and employer tuition funding?

H0: 𝛽𝛽 employer funding = β age = β GPA = β race = β gender = 0

H1: At least one of the coefficients ≠ 0

To examine this hypothesis, I conducted a multiple linear regression analysis to

evaluate the relationship between the independent variables (age, GPA, race, gender, and

employer tuition funding) on the dependent variable of time to completion for the overall

population as well as sub-sets of the overall population. I used the regress and beta

commands in Stata 17 (StataCorp., 2023) to calculate all regression models. As the t-test

results suggested, there was no significant difference in the retention of Guild and

Organic students completing either of the graduate-level certificates (CRTG and CRTM);

I excluded these students from all regression models.

I followed the same sequence of testing throughout the entire program evaluation,

examining the overall population (MS, MA, and BA students), followed by graduate-

level only (MS and MA), followed by undergraduate only (BA). As the t-test results

indicated, tuition funding had a greater influence on MA students’ completion time than

on MS students; I also tested each of these populations separately. The first regression

examines the independent variables tuition funding (Guild), age, GPA, race, and gender

on the dependent variable time to completion for the entire population (MS, MA, and

BA), 𝑛𝑛 = 2,743. The proportion of variation accounted for by the independent variables

96
in this model was 20% (𝑅𝑅𝑅𝑅𝑅𝑅 = .201). The results showed a significant influence for

each independent variable on time to completion (dependent variable) except for gender,

which was not significant. The independent variables of Guild and GPA had a negative

relationship with time to completion, whereas tuition funding and GPA increase, the time

to completion decreases. The Beta coefficients show each independent variable's relative

rank order of contribution to the model. While tuition funding significantly decreases

time to completion, a student’s overall GPA has a greater influence on the dependent

variable of time to completion. The results suggest that both GPA and employer tuition

funding affect the time to degree completion for post-traditional learners. Students with

higher GPAs may be able to register for more courses at a time leading to quicker

completion times than those with lower GPAs. Table 4.9 provides all results for the entire

population of MS, MA, and BA students.

Table 4.9

The second regression model examines the same independent and dependent

variables for the graduate student population (MS and MA), 𝑛𝑛 = 2,603. The proportion

of variation accounted for by the independent variables in this model was 18% (𝑅𝑅𝑅𝑅𝑅𝑅 =
97
.181). The results mirror those of the entire population in that each independent variable

significantly influences time to completion (dependent variable). The independent

variables of Guild and GPA again had a negative relationship with time to completion;

therefore, as tuition funding and GPA increase, the time to completion decreases. The

Beta coefficients show each independent variable's relative rank order of contribution to

the model. While tuition funding significantly influences decreasing time to completion,

a student’s overall GPA has a greater influence on the dependent variable of time to

completion. The results suggest that GPA contributes to time to degree completion for

graduate-level students; however, it was not as significant as for undergraduate-level

students. Table 4.10 provides all results for the graduate population of MS and MA

students.

Table 4.10

The third regression model examines the same independent and dependent

variables as the previous two models for the undergraduate student population (BA), 𝑛𝑛 =

140. The proportion of variation accounted for by the independent variables in this model

was 29% (𝑅𝑅𝑅𝑅𝑅𝑅 = .293). The results of this regression model differ from the previous
98
two models. The results showed a significant influence of age and GPA on the dependent

variable of time to completion. The independent variables of Guild (𝑝𝑝 = .06), race (𝑝𝑝 =

.54), and gender (𝑝𝑝 = .81) were shown not to be significant. The results of employer

tuition funding influencing retention fall slightly outside the 𝑝𝑝 < .05 baseline. This may

be partly due to one of the limitations of this program evaluation and the change enforced

by Disney on employer tuition funding mid-evaluation, limiting undergraduate students

to taking two courses per quarter instead of the unlimited funding they received prior to

winter 2021 due to COVID. The limitation of taking two courses aligns with the two-

course requirement for any undergraduate student utilizing financial aid, creating some

similarity in the number of courses registered for across Guild and Organic students. If

Disney employees wished to go beyond the course cap, they would have to pay for the

additional courses. The Beta coefficients again show the relative rank order of

contribution of each independent variable to the model, with overall GPA indicating the

greatest influence on the dependent variable of time to completion. Table 4.11 provides

all results for the undergraduate population of students.

Table 4.11

99
 The fourth regression model examines the same independent and dependent

variables as the previous models for the graduate-level MS student population, 𝑛𝑛 =

1,804. The proportion of variation accounted for by the independent variables in this

model was 17% (𝑅𝑅𝑅𝑅𝑅𝑅 = .170). The results of this regression model differ from the

overall population and the graduate-only (MS and MA) population. The results showed a

significant influence of Guild, age, and GPA on the dependent variable of time to

completion. The independent variables of race (𝑝𝑝 = .07), and gender (𝑝𝑝 = .64) are not

significant. The Beta coefficients again show the relative rank order of contribution of

each independent variable to the model, with overall GPA indicating the greatest

influence on the dependent variable of time to completion for graduate students pursuing

an MS degree. Table 4.12 provides all results for the graduate MS population of students.

Table 4.12

The final regression model examines the same independent and dependent

variables as the previous models for the graduate-level MA student population, 𝑛𝑛 = 799.

The proportion of variation accounted for by the independent variables in this model was

100
22% (𝑅𝑅𝑅𝑅𝑅𝑅 = .222). The results of this regression model mirror the results from the

overall population (MS, MA, and BA) and the graduate-only (MS and MA) population.

The results showed a significant influence of all independent variables, Guild, age, GPA,

and race, on the dependent variable of time to completion. The independent variable of

gender (𝑝𝑝 = .30) was not significant. The Beta coefficients show the relative rank order

of contribution of each independent variable to the model, with overall GPA indicating

the greatest influence on the dependent variable of time to completion for graduate

students pursuing a MA degree. Table 4.13 provides all results for the graduate MA

population of students. The proportion of variance R-squared ranged from 18%-29%

across the populations tested. This is a relatively low R-squared indicating there are other

independent variables affecting time to completion and retention. Post-traditional learners

are juggling many responsibilities, including family and work obligations, and these

regression models only consider one environmental factor, funding. Adding additional

environmental factors such as hours worked, marital status, children, and others would

likely increase the proportion of variance for adult learners.

Table 4.13

101
 Student Retention. Given these results, the hypothesis that Guild students would

show higher retention than Organic students and that the independent variable of

employer tuition funding would have the greatest influence was not supported in any of

the populations tested. The results support that employer tuition funding does influence

retention in the overall population (MS, MA, and BA) and the graduate-level population

(MS and MA); however, tuition funding was not significant across the undergraduate

population. GPA was the greatest indicator of retention across each of the populations

tested. Therefore, one would expect that graduate students who have higher GPAs, as

well as employer tuition funding, would retain at higher rates than those students who

have employer tuition funding and lower GPAs or higher GPAs and no employer funding

(Cabrera et al., 1990; Pearson, 2019). Other environmental factors that may influence

time to degree completion and retention that were not considered in this program

evaluation are hours of employment, outside encouragement, family obligations, and the

opportunity to transfer (Bean & Metzner, 1985).

Summary of Results

The results of this program evaluation indicate that the independent variable of

employer tuition funding significantly influences time to degree completion for all

populations tested except for six-course and four-course graduate certificate students.

Guild students in MS, MA, or BA programs retained at higher rates, and thus, their time

to degree completion was shorter than Organic students in similar programs. While

employer tuition funding was shown to affect time to completion and retention, it was not

shown to be the highest contributing factor. In each population, GPA was shown to have

the most significant influence on time to completion.

102
 Employer tuition funding was not found to influence the time to degree

completion for those graduate students pursuing only graduate certificates (CRTG and

CRTM). This may be partly due to the length and cost of these programs compared to

master’s or bachelor’s degree programs. Each MS and MA program requires 12 total

courses, double that of a CRTG degree and triple that of a CRTM degree. The BA

program is a completion program where students must have transferable credit hours to

be admitted into the Bachelor of Arts Completion Program; depending on the number of

transferable credit hours, students would have somewhere between 12-39 courses to

complete their BA degree. In this program evaluation, I accounted for transfer credits for

those students who transferred credits into their degree. Aside from the length and cost of

these programs, it is important to note that four-course graduate certificates (CRTM) do

not qualify for Title IV funding, meaning that students who pursue these degrees will

need to pay without the assistance of financial aid and therefore are likely from high

socioeconomic backgrounds. While the demographics of CRTM students resemble the

demographics of the overall and sub-populations, this program evaluation did not

consider socioeconomic status as that variable was not available in the dataset. Table 4.14

displays all descriptive data for each independent variable used throughout this program

evaluation.

While the results show the significance of employer tuition funding, they do not

show that it has the greatest influence on retention and time to degree completion. This

result does show the importance of external environmental factors on the persistence and

retention of post-traditional learners. Continuing to understand the complex adult learner

and that their persistence and retention to degree completion is influenced by more than

103
academic and social factors is essential to addressing the retention needs of this unique

population. In the next chapter, I will elaborate on my conclusions and interpretations and

provide suggestions for further research.

Table 4.14

104
 CHAPTER FIVE: DISCUSSION, IMPLICATIONS, AND RECOMMENDATIONS

In this chapter, I discuss the results from the program evaluation of the University

College and Guild partnership. I compare the retention between Guild and Organic

students, dive into the different levels of employer tuition funding, and discuss how the

independent variables of age, GPA, gender, and employer tuition funding influence

retention. I tie the results back to the theoretical framework used to guide the evaluation.

Then I move on to stakeholder recommendations and conclude with suggestions for

further research.

Introduction

Across the United States, post-traditional learners account for 56% of the students

enrolled in postsecondary education (National Center for Educational Statistics, 2022).

The percentage of adult learners continues to grow as higher education enrollments of

traditional students is approaching higher education enrollment cliff (Nathan Grawe,

2018). The enrollment cliff is predicted to begin in 2025 as there is a dramatic drop in

traditional-aged students due to the low birthrates. The need for higher educational

institutions to begin adjusting to the adult learner is past due. The need for updated

policies, procedures, and student supports that align more appropriately with the adult

learner is essential for higher education institutions. This is not to say that higher

education leaders and administrators should ignore traditional-aged students but to

understand that serving the adult learner is quite different from serving the traditional-

105
aged learner as the needs of this population do not align with the needs of traditional-

aged students. Many colleges and institutions will face declining and stagnant student

enrollment numbers. Taking a strategic approach to the shift in student demographics will

be necessary for the vitality of higher education institutions (Campion, 2022).

Much of the research on persistence and retention has focused on traditional-aged

students pointing to social connection, self-efficacy, and belonging as essential factors

(Spady, 1970, 1971; Tinto, 1975, 1993; Pascarella, 1980; Cabrera et al., 1993). These

theories fail to include environmental factors that influence post-traditional learners. The

groundwork for the removal of financial aid and tuition cost barriers that affect retention

has been laid by many theorists (Cabrera et al., 1990, 1992, 1993; Lenning et al., 1980;

Marsh, 1966; Nora, 1992, 1993; Pantages & Credon, 1978; Paulsen, 1997, 2002; St.

John, 1997, 2002; Summerskill, 1962). This program evaluation builds upon these

theories by examining the influence up-front employer tuition funding has on persistence,

retention, and time to degree completion for post-traditional learners. The results of this

program evaluation begin to fill the gap in the research on how employer funding affects

post-traditional learners’ persistence through to completion.

Research Questions

This program evaluation explored how employer tuition funding increases

persistence and retention and decreases time to degree completion for post-traditional

learners using an Evaluative Inquiry for Learning in Organizations (EILO) approach

(Preskill, 1999). The following research questions align with the established theoretical

framework, which guides the evaluation of the external partnership between the

University of Denver’s University College and Guild.

106
 1) How does the retention of post-traditional students who receive funding

through the Guild partnership compare to students who do not receive this

funding?

2) How does time to time to degree completion for post-traditional students

compare across different funding levels?

3) How is the retention of post-traditional students affected by age, GPA, race,

gender, and employer tuition funding?

As students who enter an academic program through the Guild partnership use up-

front education funding, provided by their employer, comparing these students to Organic

students who do not have this type of funding provides valuable insight into the effect

funding and cost have on persistence and retention for the post-traditional population.

Reducing the financial costs for the adult learner and the relationship it has to their

persistence and retention and time to degree completion is critical to recruiting more

adult learners back to higher education and increasing the retention rates of this unique

student population (Chen & Hossler, 2017; Tran & Smith, 2017). Understanding the

effects of employer funding is vital to serving the growing adult learner population.

Conducting this program evaluation in a way that allowed for comparison across different

subsets of the post-traditional student allows University College to evaluate the different

types of adult learners they serve strategically.

In this chapter, I provide a high-level summary and interpretation of the results of

this program evaluation. I tie the results to existing literature and the theoretical model I

used to frame this program evaluation. Finally, I provide implications, recommendations

for the program evaluation stakeholders, and suggestions for future research.

107
Summary of Results

Research Question One: How does the retention of post-traditional students who

receive funding through the Guild partnership compare to students who do not receive

this funding?

H0: µGuild -µOrganica = 0

Ha: µGuild -µOrganic > 0

The results supported the hypothesis that Guild students would retain at higher

rates than Organic students. When comparing across programs, the results supported the

hypothesis that Guild students retain at higher rates than Organic students in MS, MA,

and BA programs. The results did not support the hypothesis that Guild students retain at

higher rates than Organic students for those who completed graduate certificate programs

(CRTG or CRTM). When ranking levels of influence employer tuition funding had on

retention, the greatest influence was found for BA students, followed by MA students,

and finally, MS students.,

Research Question Two: How does time to time to degree completion for post-

traditional students compare across different funding levels?

H0: Time to degree completion is equal across all funding levels.

H1: There is a significant difference in time to degree completion across different

funding levels.

In the second research question, the results supported the hypothesis that there is a

significant difference in time to completion across different employer funding levels. The

results of this testing indicated that students with unlimited tuition funding had the

shortest time to degree completion; each student in this category of the program

108
evaluation was a Guild student. Those students with no employer tuition funding had the

second shortest time to degree completion; each student in this category was an Organic

student. Finally, the students who had some tuition funding had the longest time to degree

completion; each student in his category was a Guild student.

Research Question Three: How is the retention of post-traditional students

affected by age, GPA, race, gender, and employer tuition funding?

H0: 𝛽𝛽 employer funding = β age = β GPA = β race = β gender = 0

H1: at least one of the coefficients ≠ 0

The third research question indicated that employer tuition funding significantly

influences retention; however, GPA had the greatest influence across all levels of students

tested (MS, MA, and BA). Although the results were significant, the hypothesis that

employer tuition funding would have the greatest influence on retention was not

supported. In the next section, I will discuss the results, implications, and

recommendations for each research question in depth.

Discussion of Results and Recommendations

In this section, I discuss all results of the program evaluation and ground them

within previous research and the theoretical framework I used. As the guiding framework

for this evaluation was Evaluative Inquiry for Learning in Organizations (EILO), I also

present recommendations to the program stakeholders as a catalyst for growth and

improvement.

Comparison of retention between Guild and Organic students. The results

supported the hypothesis that Guild students would retain at higher rates than Organic

students. While the results of the overall population were still significant when including

109
all degree levels, removing the CRTG and CRTM students from the overall graduate

calculations increased the mean difference of time to complete by 13.638 units of time,

and the effect size increased by .158. The lack of significant retention differences in the

CRTG and CRTM students may be due in part to the length and cost of the programs.

CRTG students are committing to half of a master’s degree, and CRTM students are

committing to a third of the time and money of a master’s degree. Human Capital Theory

can be used to explain the difference between CRTG and CRTM students. The cost-

benefit analysis students make when applying for one of these shorter programs differs

from those contemplating a 12-course master’s degree. While cost plays into a student’s

decision, students pursuing a six-course or four-course graduate certificate have half or a

third, respectively, of cost considerations of time and money. It is also important to note

that four-course graduate certificates do not qualify for federal financial aid. Therefore, it

would be fair to say that the Organic students choosing to enter one of these certificates

have the financial means to support out-of-pocket costs of four graduate courses of

approximately 11,500 dollars. As CRTG students have no option for financial assistance,

the cost is likely not a determining factor in returning to higher education.

Employer tuition funding greatly influenced students within the Bachelor of Arts

Completion Program. When comparing the results from the students pursuing a BA to the

overall population (which includes CRTG and CRTM), both the mean and effect size

increased drastically. The mean increased by 136.521 units of time, and the effect size

increased by .437 compared to the overall population. Accounting for the insignificant

results for CRTG and CRTM students, I also compared the results of the BA population

to the MS and MA students only, and the mean still increased drastically, by 126.028

110
units of time; however, the effect size only increased slightly by .072. These results

suggest differences in the effects of employer tuition funding in the graduate-level and

undergraduate-level student populations. These results support Bean and Metzner’s

(1985) model that external environmental factors, including finances, influence the

retention of post-traditional undergraduate students. While Bean and Metzner’s study did

not include graduate students based on the results of this program evaluation, the Non-

traditional Student Attrition Model aligns with students in master’s degree programs.

Thinking about the results through the lens of Human Capital Theory, it also makes sense

that employer tuition funding would have a greater influence on retention for BA students

as their path toward completion is longer than that of graduate-level students. While the

per-course cost is less for an undergraduate student, the number of courses needed to

complete could be double or triple that of a graduate-level student. Bean and Metzner’s

Non-traditional Student Attrition Model and Human Capital Theory can be used to

explain these results. Human Capital Theory suggests students consider ROI in decisions

of enrollment and Bean and Metzner’s model suggests that post-traditional learners are

heavily influenced by external environmental factors.

Employer tuition funding levels. I would have liked to evaluate each employer

tuition funding level separately; however, due to the low numbers of students within

certain funding levels, I needed to assess tuition funding levels at three different levels,

unlimited employer tuition funding, some employer tuition funding (between 10,000 and

3,000 dollars), and no employer tuition funding. Initially, I was shocked by the results

because those students who had some employer tuition funding completed their degrees

slower than those students who had no employer tuition funding. While the result was

111
surprising, it indicates that cost is a significant determining factor for post-traditional

students. As the students with some employer tuition funding completed the slowest, they

were likely making registration decisions based on the amount of tuition funding

available to them through their employers. As these students had capped employer tuition

funding that refreshes on January 1 of every year, they were likely taking a slower

approach and even taking quarters off to maximize the amount of tuition funding received

by their employer (Bowers & Bergman, 2016). This premise aligns with my theoretical

framework that environmental factors influence post-traditional learners (Bean &

Metzner, 1985), and post-traditional learners make higher education decisions based on a

cost-benefit analysis (Becker, 1975; Long, 2007). This leads me to wonder how many of

these students chose to return to higher education regardless of degree program due to the

funding available from their employer. This raises the question of whether the social and

economic mobility of earning a credential was now more attractive and attainable for the

student due in part to the financial support of their employer? The results of testing the

employer tuition funding levels mimics the vignette at the start of this paper; maybe the

tuition funding from their employer, even though it was capped, was the push they

needed to jump back into higher education.

Independent variables, Age, GPA, race, gender, and employer tuition funding

influence on retention. The results showed that employer tuition funding does influence

retention for adult learners except for BA students. While it was surprising that employer

tuition funding was insignificant (𝑝𝑝 = .06) for undergraduate students, this result could

be related to the COVID-19 limitations of this program evaluation which were discussed

at length in chapter three. Based on employer tuition funding levels results, it is plausible

112
that if a course cap did not limit Disney students, they would have completed their degree

even quicker, resulting in a higher difference between the Guild and Organic student

groups. The course cap for undergraduate students also likely influenced the effect size

and mean difference in time to completion results of research question one. The

limitation of taking two courses for Disney undergraduate students aligns with the two-

course requirements for any undergraduate student utilizing financial aid, creating some

similarity in the number of courses registered for across Guild and Organic students.

Further studies are needed to understand if and how COVID-19 impacted this program

evaluation of post-traditional students’ time to degree completion and the effects of

employer tuition funding.

The hypothesis was not supported that employer tuition funding would have the

greatest influence on retention; instead, GPA was shown to have the greatest influence on

retention for undergraduate and graduate-level post-traditional learners of this program

evaluation. The influence of GPA on retention was unsurprising as it aligns with previous

research indicating the correlation between GPA and retention (Bean, 1980, 1983;

Cabrera et al., 1993; Pascarella & Terenzini, 1979; Pearson, 2019; Tinto 1975, 1982). The

results demonstrated a positive relationship between the independent variables employer

tuition funding and GPA and retention for graduate-level students. Therefore, one would

expect that graduate students who have higher GPAs, as well as employer tuition funding,

would retain at higher rates than graduate students who have employer tuition funding

and lower GPAs or higher GPAs and no employer funding (Cabrera et al., 1990; Pearson,

2019).

113
Stakeholder Recommendations

The stakeholder recommendations are grounded in the evaluation theory used to

frame this program evaluation, Evaluative Inquiry for Learning in Organizations (ELIO).

The goal of this program evaluation was to provide results that could be implemented and

used as a catalyst for growth. As University College enters into a new strategic planning

cyle the hope is that the results of this study are imbedded into future decision making.

This program evaluation should be seen as a living document as the Guild and University

College Partnership is ongoing and the results can be imbedded into strategic planning

and can inform practice moving forward.

Based on the program evaluation results, I recommend that University College

leadership evaluate how they can reduce costs for all students, particularly organic

students, to increase the marketability of academic programs and the retention of

students. A few considerations on how University College could increase the ROI for

adult learners and increase persistence and retention include locking tuition rates for

those who remain active with continuous enrollment and increasing scholarship

opportunities for MS and MA students (National Adult Learner Coalition, 2017).

Reviewing transfer policies for undergraduate students to increase the courses allowed as

transfer credits, creating articulation agreements with statewide community colleges, and

awarding Prior Learning Assessment (PLA) credit for college-level level knowledge and

competencies at both the undergraduate and graduate-levels (Pearson, 2019; Bergman et

al., 2014; Gast, 2013; National Adult Learner Coalition, 2017). Providing discount tuition

for the University of Denver undergraduates to return to and complete graduate-level

degrees within three years of completing their undergraduate degree, and reengaging

114
students who have stopped out by offering discounted or locked tuition to return

(Erisman & Steele, 2015).

Based on the program evaluation results, I also recommend considering tuition

price-point as part of the strategy for attracting and recruiting post-traditional learners

through the Guild channel. As the competition to attract adult learners continues to rise,

University College could increase the number of Guild students by reducing the financial

costs for Guild students and their employers. Reducing the price point for Guild students

further would provide value to all stakeholders including the University of Denver,

University College, the employer partner, and the students. Reducing the per-credit-hour

cost even further will likely increase the number of employer partners who include

University College in their portfolio of academic partners and may influence the number

of academic programs covered along with funding level. While the price point for Guild

students would be lower University College would make up the tuition dollars with

increased volumes of students.

Employer tuition funding for Guild students has been shown to significantly

influence retention rates, considering other partnerships could prove fruitful. Cultivating

the relationship with local or state employers outside of the Guild partnership may

provide a pipeline of students with employer tuition. The results of this study can be used

with other outside partnerships to show the benefits of employer tuition funding to the

employers as well as the students.

The Guild partnership should continue to be evaluated to assess if and how the

partnership influences student access to DU and retention of these students. I would also

encourage a full assessment of University College scholarships and grants to determine

115
how influential those dollars have been for Organic students and what changes could be

made to create a greater impact across the Organic student population. Understanding the

enrollment and retention patterns of adult learners at University College allows

institutional leaders to strategically implement department changes that increase access

and support for this growing population.

Suggestions for Further Research

As this program evaluation utilized data from fall 2017 through fall 2020, the data

does not allow for high degrees of testing on the various funding levels. Since fall 2020,

Guild has continued adding new employer partners at various funding levels. I

recommend that further research be conducted on Guild employer tuition funding levels

and the effects it has on time to degree completion and retention for post-traditional adult

learners. Based on the results of my first and third research questions, it would also be

essential to test each tuition funding level instead of grouping them into three level. This

could provide further insight into the funding amount needed to influence students in

different programs. As more students enter University College through the Guild

partnership and complete their degrees, research should be conducted on each employer

funding level instead of the three this program evaluation used. As the average time to

complete a master’s degree at University College is three years, I recommend revisiting

my second research question or some variation of the question utilizing archived data,

once available, from fall 2017 through fall 2024. Further research with a larger dataset

would also allow for testing the populations pre-COVID-19, during COVID-19, and post-

COVID-19. The outcomes of these findings could help all stakeholders understand how

employer funding levels influence post-traditional learners’ ROI on deciding to return to

116
higher education and then retain toward completion and the implications and effects of

COVID-19.

Another potential research area would explore just the graduate-level post-

traditional student. While the demographics of the post-traditional learners in this

program evaluation where similar, there are likely differences in socioeconomic status

between those who do not already have an undergraduate degree and those who do. The

time to degree completion for a master’s degree is much shorter than for bachelor’s

students, and therefore, the cost-benefit analysis would likely be different across these

different populations. Considering a mix-methods approach could provide insights on

student’s decision to return to higher education and the extent to which employer tuition

funding influenced their decision.

Another potential research area would be to explore motivation and how

motivation influences post-traditional learners’ decision to return to higher education or

complete their degree (Gardner et al., 2022; Sogunro, 2014; Yoo & Huang, 2013).

Understanding how motivation could be influenced by employer funding, socioeconomic

status (SES), as well as how career or salary outcomes after earning one’s degree.

Studying motivation, SES, and employer tuition funding and the possible

interdependence of these three independent variables and the influence on persistence and

retention of adult learns may provide some insightful results in how to best attract and

serve this population.

This program evaluation focused on up-front employer tuition funding and the

influence on post-traditional learners’ persistence, retention, and time to degree

completion. There are many outside factors that have been shown to affect post-

117
traditional learners’ persistence and retention including but not limited to hours of

employment, outside encouragement, family responsibilities, opportunity to transfer

(Bean and Metzner, 1985), childcare, and policies and guidelines of corporate tuition

funding. Understanding the influence of each of these variables independently as well as

holistically will continue to add to the understanding of post-traditional learners’

persistence, retention, and time to degree completion. I hope the results of this study

ignite further research to more fully understand this growing population. Having greater

information on the differences in traditional and post-traditional learners will help leaders

within higher education as well as companies derive strategic approaches to help this

unique population instead of hindering their academic, personal, and professional growth.

Further research is necessary to determine if employer tuition funding during and

outside COVID reveals similar effects on persistence, retention, and time to degree

completion for post-traditional learners. Further research can explore the University

College Guild partnership, other institutions that partner with Guild, or other similar

third-party partnerships to understand more fully if and how the pandemic influenced or

potentially influenced the results of this program evaluation. As higher education leaders

are thinking strategically about providing access to the millions of adult learners through

different paths, including micro-credentials and other short-form courses and certificates,

studying the factors influencing graduate-level learners could be valuable in launching

these program options.

Evaluation Conclusion

Evaluative Inquiry for Learning in Organizations (EILO) is an ongoing process

for analyzing and understanding critical issues; this process then becomes a catalyst for

118
continued growth and improvement for the organization and the individual employees

(Preskill & Torres, 1999). This study's results fill the research gap focusing on the

growing student population of adult learners while highlighting the important work of

PCO units. Connecting the job and career-focused educational approach of PCO units to

employer tuition funding is not only important research but necessary. The knowledge

gained will help institutions strategically approach admitting, serving these students, and

increasing retention rates.

In 2017, Guild and University College began their partnership. This partnership

was intended to propel University College forward in serving the growing adult learners

and provide access to many post-traditional learners who have previously not had access

to higher education. I intend to align strategy and evaluation to create learning

opportunities for higher education leadership and administration serving the post-

traditional student population beyond the University of Denver’s walls.

As financial aid shrinks and the cost of higher education increases, leveraging

employer funding can help offset the financial strain for adult learners. Employer funding

is not a one-size-fits-all answer to solving the persistence and retention problems across

the higher education system for adult learners; however, it does play a role in the

decision-making process for this unique student population. To effectively serve this

unique population we as educators and practitioners must understand the academic

journey of adult learners and how it differs from traditional-aged students.

Adult students are returning to higher education to upskill, reskill, or make career

pivots and ultimately increase their socioeconomic status, yet the financial burden may be

too large of an obstacle to overcome leading to higher rates of stopping out and thus

119
lower rates of retention for institutions. While not every post-traditional or continuing

education unit can or should partner with Guild or another similar external partner to

address persistence and retention problems for post-traditional learners, understanding

how cost affects adult learners is important to serve this growing population effectively.

These program evaluation results align with Bean and Metzner’s Non-Traditional

Attrition Model (1985) and Human Capital Theory and advance the understanding of cost

on post-traditional learners. Understanding the effect of cost on post-traditional learners

can lead to more strategic conversations addressing tuition, scholarships, and other

financial benefits to attract and serve this unique student population.

120
 BIBLIOGRAPHY

Aljohani, O. (2016). A comprehensive review of the major studies and theoretical models

of student retention in higher education. Higher Education Studies, 6(2), 1-18.

https://du.idm.oclc.org/login?url=https://search-proquest-com.du.idm.oclc.org/

docview/1826527184?accountid=14608

Alkin, M. C. (Ed.). (2012). Evaluation roots: A wider perspective of theorists’ views and

influences. https://ebookcentral.proquest.com

Astin, A. W. (1975). Preventing students from dropping out. Jossey-Bass.

Astin, A.W. (1977). Four critical years. Josey-Bass.

Astin, A. W. (1984). Student involvement: A developmental theory for higher education.

Journal of College Student Personnel, 25(4), 297-308.

Bandura, A. (1977). Self-Efficacy: Toward a unifying theory of behavioral

change. Psychological Review, 84(2), 191-215.

Barr, & Turner, S.E. (2013). Expanding enrollments and contracting state budgets: The

effect of the Great Recession on higher education. The annuals of the American

Academy of Political and Social Science, 650(1), 168-193.

https://doi.org/10.1177/0002716213500035

Barrow, L., Richburg-Hayes, L., Rouse, C.E., & Brock, T. (2014). Paying for

performance: The education impacts of a community college scholarship program

for low-income adults. Journal of Labor Economics, 32(3), 563-599.

121
Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of

student attrition. Research in Higher Education, 12(2), 155-187.

Bean, J. (1981). The synthesis of a theoretical model of student attrition / John P. Bean.

Bean, J., & Metzner, B. (1985). A conceptual model of nontraditional undergraduate

student attrition. Review of Educational Research, 55(4), 485-540.

www.jstor.org/stable/1170245

Becker, G. S. (1975). Human Capital: A theoretical and empirical analysis, with special

reference to education / by Gary S. Becker (2nd ed.). National Bureau of Economic

Research: Distributed by Columbia UP, Print. Human Behavior and Social

Institutions; 5.

Berger, J. B., Ramírez, G. B., & Lyons, S. (2005). Past to present. College Student

Retention: Formula for Student Success, 1.

Bergman, M., Gross, J. P. K., Berry, M., & Shuck, B. (2014). If life happened but a

degree didn’t: Examining factors that impact adult student persistence. The

Journal of Continuing Higher Education, 62(2), 90-101.

Bonsick. (2016). An examination of employer-sponsored college tuition reimbursement

programs: Employee participation and implications for career success. ProQuest

Dissertations Publishing.

Bound, J., Lovenheim, M.F., & Turner, S. (2010). Why have college completion rates

declined? An analysis of changing student preparation and collegiate resources.

American Economic Journal: Applied Economics, 2(3), 129-157.

122
Bowers, A., & Bergman, M. (2016). Affordability and the return on investment of college

completion: Unique challenges and opportunities for adult learners. The Journal

of Continuing Higher Education, 64(3), 144-151.

Braxton. (2014). Rethinking college student retention (1st ed.). Jossey Bass.

Cabrera, A. F., Stampen, J. O., & Hansen, W. L. (1990). Exploring the effects of ability to

pay on persistence in college. Review of Higher Education, 13(3), 303-336.

Cabrera, N. A., & Castañeda, M. B. (1992). The role of finances in the persistence

process: A structural model. Research in Higher Education, 33(5), 571-593.

https://doi.org/10.1007/BF00973759

Cabrera, N. A., & Castañeda, M. (1993). College persistence - Structural equations

modeling test of an integrated model of student retention. The Journal of Higher

Education (Columbus), 64(2), 123-139. https://doi.org/10.2307/2960026

Campion. (2022). Leading through the enrollment cliff of 2026 (Part II). TechTrends,

66(1), 112-113. https://doi.org/10.1007/s11528-021-00688-4

Cappelli. (2004). Why do employers pay for college? Journal of Econometrics, 121(1),

213-241. https://doi.org/10.1016/j.jeconom.2003.10.014

Carnevale, A. P., & Rose, S. (2013). Socioeconomic status, race/ethnicity, and selective

college admissions.

Carnevale, A., Smith, N., Melton, M., Price, E., & Georgetown University, Center on

Education the Workforce. (2015). Learning while earning: The new normal /

Anthony P. Carnevale, Nicole Smith, and Michelle Melton.

123
Castleman, B. L., & Long, B. T. (2013). Looking beyond enrollment: The causal effect of

need-based grants on college access, persistence, and graduation. NBER

Working Paper Series (19306). National Bureau of Economic Research.

Causey, J., Kim, H., Ryu, M., Scheetz, A., & Shapario, D. (2023, April). Some College,

No Credential, Student, Annual Progress Report – Academic Year 2020/21.

National Student Clearinghouse Research Center.

Chen, J., & Hossler, D. (2017). The effects of financial aid on college success of two-year

beginning nontraditional students. Research in Higher Education, 58(1), 40-76.

Cohen. (1977). Statistical power analysis for the behavioral sciences (Rev. ed.).

Academic Press.

Deutsch, & Schmertz, B. (2011). “Starting from Ground Zero”: Constraints and

experiences of adult women returning to college. Review of Higher Education,

34(3), 477-504. https://doi.org/10.1353/rhe.2011.0002

EdAssist. (2012) Annual review of employer tuition assistance programs. Bright

Horizons Family Solutions.

Erisman, W., & Steele, P. (2015). Adult college completion in the 21st century: What we

know and what we don’t. HigherEd Insight.

https://higheredinsight.files.wordpress.com/2015/06/adult_college_completion_2

0151.pdf

Espenshade, T. J. & Radford, A. W. (2009). No longer separate, not yet equal: Race and

class in elite college admission and campus life. Princeton University Press.

https://doi.org/10.1515/9781400831531

124
Flaherty Manchester, C.N. (2012). General human capital and employee mobility: How

tuition reimbursement increases retention through sorting and participation.

Industrial and Labor Relations Review, 65(4), 951-974.

https://doi.org/10.1177/001979391206500408

Fong, J., Halfond, J., & Schroeder, R. (2017) The changing landscape for professional

and continuing education in the U.S.

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2011). Social statistics for a diverse

society (6th ed.). Pine Forge Press Ser. in Research Methods and Statistics.

Gallup-Lumina Foundation. (2021). The American Upskilling Study: Empowering

workers for the jobs of tomorrow. https://www.gallup.com/analytics/354374/the-

american-upskilling-study.aspx

Gallup-Lumina Foundation. (2016). Talent investments: Cigna realizes return on

investment from tuition benefits.

https://www.luminafoundation.org/files/resources/talent-investments-pay-off-

cigna-full.pdf

Gallup-Lumina Foundation. (2023). The State of Higher Education 2023: Breaking down

the barriers to student enrollment and retention.

https://www.luminafoundation.org/wp-content/uploads/2023/05/state-of-higher-

education-2023.pdf

Gardner, A. C., Maietta, H. N., Gardner, P. D., & Perkins, N. (2022). Postsecondary adult

learner motivation: An analysis of credentialing patterns and decision making

within higher education programs. Adult Learning, 33(1), 15-31.

125
Gast, A. (2013). Current trends in adult degree programs: how public universities respond

to the needs of adult learners. New Directions for Adult and Continuing

Education, 2013(140), 17-25. https://doi.org/10.1002/ace.20070

Go to College, On Us. (2022, February 27). https://starbucks.asu.edu/

Graham, S. W., Donaldson, J. F., Kasworm, C., & Dirkx, J. (2000). The experiences of

adult undergraduate students: What shapes their learning? Distributed by ERIC

Clearinghouse. ED440275.

Grawe, N. (2018). Demographics and the Demand for Higher Education. John Hopkins

University Press.

Greenberg, M. (2004). How the GI Bill changed higher education. The Chronicle of

Higher Education, 50(41), B.9-.

Guild Admissions Report. (2022, June 30).

Guild (2023, January, 1) Average of all ROI analyses for employer partners

Guild Website. (n.d.). Guild. https://www.guild.com

Guild: Keep your talent rising. (2023, April 12).

https://www.youtube.com/watch?v=uPcxKDfv5l4

Higher Ed Insight. (2021, August 12). Two ways employers can help increase adult

postsecondary attainment. https://higheredinsight.com/portfolio/two-ways-

employers-can-help-increase-adult-postsecondary-attainment/

Hossler, D. (2002). Enrollment management. In J. J. F. Forest, & K. Kinser (Eds.),

Higher education in the United States: An encyclopedia, Volume 1. ABC-CLIO.

126
Hoyt, & Howell, S. L. (2011). Beyond customer satisfaction: Reexamining customer

loyalty to evaluate continuing education programs. The Journal of Continuing

Higher Education, 59(1), 21-33. https://doi.org/10.1080/07377363.2011.544979

Kamens. (1971). The college “Charter” and college size: Effects on occupational choice

and college attrition. Sociology of Education, 44(3), 270-296.

https://doi.org/10.2307/2111994

Kamens. (1974). Colleges and elite formation: The case of prestigious American

colleges. Sociology of Education, 47(3), 354–378.

https://doi.org/10.2307/2111910

Kantrowitz, M. (2010). Countercyclicality of college enrollment trends. Student Aid

Policy Analysis

LiFE: Learning inspired by FedEx. (2022, February 27).

https://www.memphis.edu/uofmglobal/life/

Long, B. T. (2007). The contributions of economics to the study of college access and

success. Teachers College Record, 109(10), 2367-2443.

https://du.idm.oclc.org/login?url=https://search-proquest-

com.du.idm.oclc.org/docview/61934646?accountid=14608

Manchester, C. F. (2008). The effect of tuition reimbursement on turnover: A case study

analysis. In The analysis of firms and employees: Quantitative and qualitative

approaches (pp. 197-228). University of Chicago Press.

Mann, J. (2022, March 31). Guild Education named one of 2022’s most influential

companies. https://www.bizjournals.com/denver/news/2022/03/30/guild-

education-named-time100-influential.html

127
Manyanga, F., Sithole, A., & Hanson, S. M. (2017). Comparison of student retention

models in undergraduate education from the past eight decades. Journal of

Applied Learning in Higher Education, 7, 30-42.

https://du.idm.oclc.org/login?url=https://search-proquest-

com.du.idm.oclc.org/docview/2101886285?accountid=14608

Marsh, G. (2014). Institutional characteristics and student retention in public 4-year

colleges and universities. Journal of College Student Retention: Research, Theory

and Practice, 16(1), 127-151. https://doi.org/10.2190/CS.16.1.g

McKinsey & Company. (2021, February). Achieving an inclusive US economic recovery.

https://www.mckinsey.com/industries/public-and-social-sector/our-

insights/achieving-an-inclusive-us-economic-recovery

McKinsey Global Institute. (2021) The post pandemic economy: The future of work after

COVID-19. https://www.mckinsey.com/~/media/mckinsey/featured%

20insights/future%20of%20organizations/the%20future%20of%20work%20after

%20covid%2019/the-future-of-work-after-covid-19-report-vf.pdf

McKinney, L., & Burridge, A.B. (2015). Helping or hindering? The effects of loans on

community college student persistence. Research in Higher Education, 56(4),

299-324.

McNeely, J., & United States Department of the Interior, Office of Education. (1938).

Project in research in universities: College student mortality. Bulletin, 1937, No.

11 / John H. McNeely.

Mendenhall, W., & Sincich, T. (2012). A second course in statistics: Regression analysis

(7th ed.). Prentice Hall.

128
Merriam-Webster.com. (n.d.). https://www.merriam-webster.com/dictionary/stop%20out

Merrill, B. (2015). Determined to stay or determined to leave? A tale of learner identities,

biographies and adult students in higher education. Studies in Higher Education

(Dorchester-on-Thames), 40(10), 1859-1871.

https://doi.org/10.1080/03075079.2014.914918

Miller, N. (2014). Nontraditional student graduation rate benchmarks. The Journal of

Continuing Higher Education, 62(3), 114-151.

https://doi.org/10.1080/07377363.2014.953437

National Adult Learner Coalition. (2017). Strengthening America's economy by

expanding educational opportunities for working adults: Policy opportunities to

connect the working adult to today's economy through education and credentials.

National Center for Education Statistics. (2021). Percent of students enrolled in distance

education courses. https://nces.ed.gov/ipeds/TrendGenerator/app/answer/2/42

National Center for Education Statistics. (2022, May). Characteristics of postsecondary

students. https://nces.ed.gov/programs/coe/indicator/csb/postsecondary-students

National Center for Education Statistics. (2020). Projections of education statistics to

2028. https://nces.ed.gov/programs/PES/section-5.asp

National Student Clearinghouse Research Center. (2022, April 28). Spring 2022

enrollment estimates report. https://nscresearchcenter.org/wp-

content/uploads/CTEE_Report_Spring_2022.pdf

Nichols, L. (2019) Recognize, revise and reimagine: how continuing education drives

higher education’s evolution. The EvoLLLution: A Destiny Solutions Illumination.

(56-57).

129
Osam, E.K., Bergman, M., & Cumberland, D. M. (2017). An integrative literature review

on the barriers impacting adult learners’ return to college. Adult Learning

(Washington, D.C.), 28(2), 54-60. https://doi.org/10.1177/1045159516658013

Pascarella, E., & Terenzini, P. (1980). Predicting freshman persistence and voluntary

dropout decisions from a theoretical model. The Journal of Higher Education,

51(1), 60-75.

Paulsen, & St. John, E. P. (1997). The financial nexus between college choice and

persistence. New Directions for Institutional Research, 1997(95), 65-82.

https://doi.org/10.1002/ir.9504

Paulsen, & St. John, E. P. (2002). Social class and college costs: Examining the financial

nexus between college choice and persistence. The Journal of Higher Education

(Columbus), 73(2), 189-236. https://doi.org/10.1353/jhe.2002.0023

Pearson. (2019). Persistence of adult students. The Journal of Continuing Higher

Education, 67(1), 13-23. https://doi.org/10.1080/07377363.2019.1627166

Pelletier, S. (2019, Spring). Navigating successful corporate partnerships. Unbound:

Reinventing Higher Education. https://unbound.upcea.edu/leadership-

strategy/continuing-education/professional-education/navigating-successful-

corporate-partnerships/

Pew Research Center (2014, December). Wealth inequality has widened along racial,

ethnic lines since end of great recessions. https://www.pewresearch.org/short-

reads/2014/12/12/racial-wealth-gaps-great-recession/

Preskill, & Torres, R. T. (1999). Evaluative inquiry for learning in organizations. Sage

Publications.

130
Preskill, H., & Torres, R. T. (2000). The learning dimension of evaluation use. New

Directions for Evaluation, 88, 25-37.

https://du.idm.oclc.org/login?url=https://search-proquest-

com.du.idm.oclc.org/docview/62338569?accountid=14608

Preskill, H., Zuckerman, B., & Matthews, B. (2003). An exploratory study of process use:

Findings and implications for future research. American Journal of Evaluation,

24(4), 423-442.

Price J. L., & Mueller, C. W. (1981). A causal model of turnover for nurses. Academy of

Management Journal, 24, 543-565.

Renner, B., & Shursha, E. (2022). Support for adult students to overcome barriers and

improve persistence. The Journal of Continuing Higher Education, 1-10.

https://doi.org/10.1080/07377363.2022.2065435

Romer, R. (Host). (2023, June 6). Opportunity Divide with Special Guest Adam Grant

[Audio podcast]. Apple Podcasts.

Rumbaut, R. G., (2015). Assimilation of immigrants. International Encyclopedia of the

Social & Behavioral Sciences, 2nd edition, 2, 81-87.

Sandier. (2000). Career decision-making self-efficacy, perceived stress, and an integrated

model of student persistence: A structural model of finances, attitudes, behavior,

and career development. Research in Higher Education, 41(5), 537-580.

https://doi.org/10.1023/A:1007032525530

Shulha, L., & Wilson, R.J. (2003). Collaborative mixed methods research. In A.

Tashakkori, & C. Teddlie (Eds.), Handbook of mixed methods in social and

behavioral research. Sage.

131
Soergel, A. (2020, April 23). More than 26 million Americans file for unemployment

amid coronavirus outbreak. U.S. News & World Report News

https://www.usnews.com/news/economy/articles/2020-04-23/more-than-26-

million-americans-file-for-unemployment-amid-coronavirus-outbreak

Sogunro. (2014). Motivating Factors for Adult Learners in Higher

Education. International Journal of Higher Education, 4(1).

https://doi.org/10.5430/ijhe.v4n1p22

Spady, W. (1971). Dropouts from higher education: An interdisciplinary review and

synthesis. Interchange, 1(1), 64-85.

St. Amour, M. (2020, November 5). Employers boosting programs that cover tuition amid

pandemic. Inside Higher Ed

https://www.insidehighered.com/news/2020/11/05/employers-boostingprograms-

cover-tuition-amid-pandemic

StataCorp. (2023). Stata: Release 18. Statistical Software.

Statista (2023, May). Monthly civilian labor force in the united states from may 2021 to

may 2023. https://www.statista.com/statistics/193953/seasonally-adjusted-

monthly-civilian-labor-force-in-the-us/

Strada Education. (2020, May 7). Public viewpoint: COVID-19 work and education

survey. https://cci.stradaeducation.org/wp-content/uploads/sites/2/2020/11/Public-

Viewpoint-Report-Week-7.pdf

Stulberg, L. M., & Chen, A. S. (2014). The origins of race-conscious affirmative action in

undergraduate admissions: A comparative analysis of institutional change in

higher education. Sociology of Education, 87(1), 36-52.

132
Summerskill, J. (1962). In N. Sanford (Ed.), The American college. Wiley.

Swail, W. S. (2003). Retaining Minority Students in Higher Education : A Framework for

Success. ASHE-ERIC Higher Education Report. Jossey-Bass Higher and Adult

Education Series /. Distributed by ERIC Clearinghouse.

Thelin, J. (2004). A history of American higher education. John Hopkins University

Press.

Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent

research. Review of Educational Research, 45(1), 89-125.

www.jstor.org/stable/1170024

Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition.

The University of Chicago Press.

Toussaint, K. (2020, April 28). How Guild Education is making continuing education a

workplace perk. https://www.fastcompany.com/90490028/how-guild-education-is-

making-continuing-education-a-workplace-perk

Tran, H., & Smith, D. (2017). The impact of employer-sponsored educational assistance

benefits on community college student outcomes. Journal of Student Financial

Aid, 47(2), 1-19.

University College Enrollment Reports. (2022, February 20).

University College Enrollment Reports. (2020, June 5).

UPCEA. (2017, July 10). Hallmarks of excellence in professional and continuing

education.

Waste Management Announces First-of-its-Kind ‘Your Tomorrow’ Program Providing

No-Cost Education to Employees, with Planned Extension to Dependents Later

133
 This Year, to Upskill Workforce and Advance Position in Competitive Job Market.

(2021, May 13). https://investors.wm.com/node/25301/pdf

Wiggam. (2004). Predicting adult learner academic persistence: Strength of relationship

between age, gender, ethnicity, financial aid, transfer credits, and delivery

methods. ProQuest Dissertations Publishing.

Yoo, S. J., & Huang, W. D. (2013). Engaging online adult learners in higher education:

Motivational factors impacted by gender, age, and prior experiences. The Journal

of Continuing Higher Education, 61(3), 151-164.

134
APPENDIX A: VISUAL REPRESENTATION OF THEORETICAL FRAMEWORK

135
 APPENDIX B: BEAN AND METZNER (1985) CONCEPTUAL MODEL OF

NONTRADITIONAL UNDERGRADUATE STUDENT ATTRITION

From: Bean, J., & Metzner, B. (1985). a conceptual model of nontraditional

undergraduate student attrition. Review of Educational Research, 55(4), 485-540.

136
 APPENDIX C: SUMMARY OF PERSISTENCE/RETENTION MODELS,

FRAMEWORKS AND KEY IDEAS

Models Framework Contributing Factors to Retention Key Reference(s)

Dismissal for failure in work; financial

Student difficulties, death/sickness; needed at McNeely (1937)
Mortality Model home, & lack of interest.
Interaction
between student & Intellectual development, social Spady (1970,
Student Attrition college integration, satisfaction, and institutional 1971)
Model(s) environment commitment.
Academic & non-academic factors
including pre-college variables. Tinto (1975,
Combination of personal goals and 1982)
Social transition institutional commitment.
Institutional commitment, GPA,
development, institutional quality,
Bean (1980, 1983)
Organizational student intentions, motivations, and
workplace experiences.
Non-traditional students are impacted by
environmental factors (finances, hours of
employment, outside encouragement, Bean and Metzner
family obligations, & opportunity to (1985)
Non-Traditional transfer). These factors play a larger role
Undergraduate than social impacts.
Cabrera et al.
Integration of Tinto Environmental factors play a more
(1993)
and Bean complex role than perceived by Tinto.
Students’ navigation of stages
Student (separation, transition, and Tinto (1987,
Integration incorporation). Integration into the 1993)
Models academic and social systems.
Pascarella &
Student social life and academic life. Terenzini (1979)
Adult Personal issues of the adult learner,
Persistence in learning process issues, and MacKinnon-
Learning Model environmental issues. Slaney (1994)
Enhancing student
Student development & The greater the student's involvement in Astin (1968,
Involvement learning their academic institution the greater the 1985)
Theory environment rate of their persistence.
Student-Faculty Informal interactions between students Pascarella (1980)
Interactions and faculty.
Dropout
Syndrome Combination of student's intent to leave, Bean (1985)
Model actually leaving, and actual attrition.
The level of external commitments
College Dropout (family & jobs) affects goals and Tinto (1975)
Model commitments.

137
 Synthesis of Astin Student precollege characteristics and
Terenzini and
(1985, 1993), Tinto experiences, organizational context, peer
Reason (2005)
Conceptual (1975, 1993), and environment, and student's individual
Framework Pascarealla (1985) experiences.

138
APPENDIX D: HISTORICAL LOOK AT RETENTION

139
 APPENDIX E: HALLIE PRESKILL (2012) THE MUTUALLY REINFORCING

RELATIONSHIP BETWEEN STRATEGY AND PROCESS

Figure 1: The Mutually Reinforcing Relationship between Strategy and Process (Alkin,
2012, p. 332).

140
APPENDIX F: LETTER REQUESTING USE OF ARCHIVED DATA

141
 ProQuest Number: 30633094

INFORMATION TO ALL USERS

The quality and completeness of this reproduction is dependent on the quality
and completeness of the copy made available to ProQuest.

Distributed by ProQuest LLC ( 2023 ).

Copyright of the Dissertation is held by the Author unless otherwise noted.

This work may be used in accordance with the terms of the Creative Commons license
or other rights statement, as indicated in the copyright statement or in the metadata
associated with this work. Unless otherwise specified in the copyright statement
or the metadata, all rights are reserved by the copyright holder.

This work is protected against unauthorized copying under Title 17,

United States Code and other applicable copyright laws.

Microform Edition where available © ProQuest LLC. No reproduction or digitization

of the Microform Edition is authorized without permission of ProQuest LLC.

ProQuest LLC
789 East Eisenhower Parkway
P.O. Box 1346
Ann Arbor, MI 48106 - 1346 USA