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How to Improve Student Success and Retention in
Online Education Programs
Dr. RS Hubbard
Center for Management Communication
Marshall School of Business
University of Southern California
Los Angeles, California USA
[email protected]
Abstract: Most of the literature about online education programs offers descriptions about how certain
practices impact students, faculty and the programs themselves, and generally posit approaches that
could improve student success and program goals. The literature might also include a comparison with
traditional face-to-face instruction to show how the inherent differences between the two, and the
methodology associated with them, demand different approaches. Very few, however, offer specific
solutions to problems encountered by online faculty and students, e.g., how to keep students on track to
fulfilling personal and programs goals. This paper posits five specific interventions that, if implemented
with the input of faculty, students, administrators and support staff, should improve student success and
retention.
Key words: online learning, self-directed learning, team charters, teaching presence, social presence, group
identify, intercultural communication, faculty mentoring, peer observation
Introduction
Online education has received a lot of attention for many years, and even as early as 2001, “there were over
986 distance-learning institutions in 107 countries” (Sprague, et al, 2007), and by 2013 about 70% of all higher
education institutions reported that online education “is critical to their long term strategy” (Allen & Seaman, 2013).
As a natural outgrowth of web-enhanced courses (Hermans, et al, 2009), or in an effort to increase
enrollment, reduce adjunct instructors, and offer flexible course schedules (Borstorff & Lowe, 2007), higher
education institutions are concerned about how to improve online education programs, and are even considering the
possibilities of offering Massive Open Online Courses (Allen & Seaman, 2013). This is borne out by the fact that
almost 7 million students are currently taking at least one online course, which represents approximately 32% of all
students enrolled in institutions of higher education (Allen & Seaman, 2013).
The literature on online education tends to be organized around the following topics: student demographics,
student perceptions of online education, quality of online education, and the perceptions related to that quality (Cao
& Sakchutchawan, 2011); course availability, program quality, length, cost, and courses in the curriculum
(Rydzewski, et al, 2010); and, student learning outcomes, student characteristics, and professor pedagogy (Fillion et
al, 2007).
When considering the quality of online education, there is a tendency to make comparisons with traditional
face-to-face instruction. However, Howell, et al, (2004) posit that this tendency is inherently flawed because of
“limitations in the research design itself, differences in student demographics, and inconsistent methods of
calculating and reporting completion.” In essence, they believe that it is like comparing apples to oranges (their
analogy).
Be that as it may, Phipps & Merisotis (1999), Russell (1999), and Daymont & Blau (2008) find that the
outcomes of online education and traditional face-to-face instruction are about the same, which is consistent with
Cao & Sakchutchawan (2011), Lu, et al (2003), Priluck (2004), Haney & Newvine (2006), Watters & Robertson
(2009), and Borstorff & Lowe (2007). While Fillion, et al, (2007) find that student performance is higher in face-toface classes, they also find that student satisfaction, motivation and participation are higher in online classes
(however, reasons for their conclusions are not provided). In addition, 77% of academic leaders report that the
learning outcomes of online courses are “the same or superior to … face-to-face courses (Allen & Seaman, 2013).
There are several other advantages that online education provides. Borstorff & Lowe (2007) note that
online courses are non-linear, so students can return to previously covered material as they need to without worrying
about interrupting the natural flow of a class. Borstorff & Lowe (2007) also point out that institutions can have “a
higher level of consistency” in the training students receive, and that online education eliminates the two most
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common barriers to students seeking higher education—time and distance, which is consistent with Tanner, et al
(2003), Tanner, et al (2009), and Brown (2001).
However, it is the independent nature of online education that is also a major disadvantage. Brown (2001)
finds that with a choice of how and when online learners could spend their time, they often do not use their time
wisely. Weaver (2002) posits that this may be due to the absence of regular interactions with faculty, which is also
supported by Anstine & Skidmore (2005) and Conway, et al (2005). In fact, Arbaugh & Benbunan-Fich (2007),
Borstorff & Lowe (2007), and Totaro, et al, (2005) also posit that faculty interaction is “one of the strongest
predictors of [student] success.” Cervantez (2010) finds that the inherent independency required of online learners
also has an impact on completion rates; however, this drawback can be mitigated by “building a sense of community
through student-to-student and/or student-to-faculty interactions.”
Furthermore, there are concerns about team projects within academic environments. Even in traditional
face-to-face classes, students are concerned about the lack of instruction they receive about team work, control over
the composition of their teams, and the ability of the team to manage goals, processes, assigned tasks, and noncontributing team members (Hubbard, 2003; Brown, et al, 2006). Other concerns include the demands made by
task-centered members (Grzeda, et al, 2008), and the need for synchronous and asynchronous online delivery
systems that provide real-time and on-demand team interactions (Gapp & Fisher, 2012). Similar concerns are also
present in organizations and businesses (Birchall & Giambona, 2007; Giambona & Birchall, 2008; Petersen &
Hillkirk, 1991). And, this is even more critical for organizations that have international operations (Earley &
Gibson, 2002; Shams & Jackson, 2006).
Global virtual teams have the additional impact of cultural diversity on team member relationships and
their ability to complete tasks (Kankanhalli, et al, 2007), which leads to a lack of team identification—the extent to
which team members view themselves as part of a group (Fiol & O'Connor, 2005). And, it is the lack of team
identification that is one of the main causes of conflict and failure in global virtual teams (Hubbard, 2013b).
Findings and Recommendations
Overall it appears that in order for students to be successful online learners, they must be self-directed,
identify with their groups, and possess the skills that facilitate team goals, processes and tasks. Based on the above,
the following interventions are recommended to improve student success and retention:





Improve students’ ability to direct their own learning
Facilitate practices that keep students on track
Increase students’ ability to identify with their groups
Enable student groups to achieve goals
Create opportunities for faculty to share best practices
Intervention #1 - Improve students’ ability to direct their own learning
It is important to recognize that online learning might not be for everyone (Tanner, et al, 2009), and that
successful online learners need to be self-directed (Hasler-Waters & Napier, 2003; Allen & Seaman, 2013; Tanner,
et al, 2003; Tanner, et al, 2009). According to Guglielmino (1978), a highly self-directed learner is:
… one who exhibits initiative, independence, and persistence in learning; one who accepts responsibility
for his or her own learning and views problems as challenges, not obstacles; one who is capable of selfdiscipline and has a high degree of curiosity; one who has a strong desire to learn or change and is selfconfident; one who is able to use basic study skills, organize his or her time and set an appropriate pace for
learning, and to develop a plan for completing work; one who enjoys learning and has a tendency to be
goal-oriented.
It is obvious that not all online students are self-directed learners, let alone “highly self-directed”. And, because it is
difficult to understand the impact of a specific learning context on self-direction (Song & Hill, 2007), an
intervention is needed to identify the students who are not naturally self-directed, and provide them with the skills
and tools to become self-directed.
To improve students’ ability to direct their own learning, faculty could schedule a lecture and class
discussion during the first week of class, and have students complete a Self-Directed Learning Readiness Scale
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survey. The lecture and class discussion on self-directed learning serve as an “orientation” to this skill (Howell,
2004), especially if it focuses on how to take control of learning, how to manage deadlines and other responsibilities,
and the resources available to students outside of class.
The most widely used assessment is the Self-Directed Learning Readiness Scale (SDLRS) (also known as
Learning Preference Assessment) developed by Guglielmino & Guglielmino (1991a), which identifies eight broad
factors of self-direction. The SDLRS is a self-reporting questionnaire with 58 Likert-type questions and a guide for
interpreting the scores (Learning, 2013).
Although the SDLRS is widely used and supported (Delahaye & Smith, 1995; Durr, 1992), and is quite
comprehensive in terms of instructions and guides, there has also been some criticisms mostly concerning a number
of items on the instrument that do not correlate well to the total score (Field, 1991; Straka & Hinz, 1996). Another
criticism is that it includes too many questions, which might make it cumbersome to conduct.
In fact, the SDLRS’s problems relating to construct validity and reliability were so great that Fisher, et al
(2001) developed their own self-directed learning assessment tool. Based on a questionnaire with 40 questions, they
posit that self-directedness can be viewed within the following subscales: self-management, desire for learning, and
self-control.
So, with the different models that are available, a decision has to be made about which model to use. If the
primary purpose is to know how cohorts relate to those at other institutions, it is only wise to use the Self-Directed
Learning Readiness Scale (Guglielmino & Guglielmino, 1991a). If, however, an institution is interested in having a
manageable, institution-specific assessment, it would be very useful to develop a model that focuses on subscales,
such as self-management, desire for learning, and self-control (Fisher, et al, 2001).
In any case, the main goal of the institution’s assessment tool regardless of which model is used should be
to identify the following ranges of scores:



High SDLRS Scorers (people who are “highly successful at recognizing their learning needs and can often
plan and implement individual learning projects”);
Average SDLRS Scorers (people who are “likely to be successful in more independent learning situations,
but may not be fully comfortable with planning and implementing individual learning projects”); and,
Below Average SDLRS Scorers (people who “usually prefer very structured learning options such as
lecture and traditional classroom settings”) (Learning, 2013).
For students with low Self-Directed Learning Readiness Scale scores, faculty could encourage or require students to
complete an action plan that focuses on the five areas identified by Codde (2006), Knowles (1989) and Knowles, et
al, (2005):
1.
2.
3.
4.
5.
Learning objectives - the knowledge, skills, attitudes, and values to be acquired by the learner;
Learning resources and strategies - how these objectives will be accomplished;
Deadlines - consulting the syllabus to identify target dates for their accomplishment;
Specific assignments or projects - evidence presented to demonstrate that the objectives have been
accomplished; and,
Grading criteria - how this evidence will be judged or validated.
Having students complete an action plan enables them to identify the learning objectives, learning resources and
strategies, deadlines, and the specific assignments or projects that fulfill those objectives, and work with faculty to
understand how those assignments or projects will be evaluated.
In summary, taking these initial steps at the beginning of each course will stress the importance of selfdirected learning and give students the tools to become more independent learners. In addition, the lecture and class
discussion will also give students and faculty opportunities to identify attitudes about online learning, the benefits of
online learning (especially if faculty include testimonials from former students—Tanner, et al, 2003), and
expectations about course goals, assignments and tasks (Tanner, et al, 2009).
Intervention #2 - Facilitate practices that keep students on track
Although self-directedness is very important for online learners, faculty’s role in keeping students on track
is instrumental to student success and retention. There are several ways that faculty can accomplish this goal.
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Hricko (2003), Lazarevic (2011), and Howell, et al (2004) identify five specific practices that faculty could take to
keep students on track:
1.
2.
3.
4.
5.
Keep class size small (perhaps, 20-30 students maximum)
Track students’ online activities
Establish goals (i.e., target retention rate)
Post an introduction video
Interact with students as much as possible, either synchronously or asynchronously
It is the last suggestion about faculty-student interaction that is contentious. While it is supported by Hsu & Shiue
(2005), Shea, et al (2006), Arbaugh & Hwang (2006), and Laves (2010), it seems to contradict the basic proposition
that online students need to be competent self-directed learners (Hasler-Waters & Napier, 2003; Allen & Seaman,
2013; Tanner, et al, 2003; Tanner, et al, 2009).
Be that as it may, faculty-student interaction is directly related to the concept of “teaching presence”, the
extent to which faculty direct the cognitive and social processes that enable meaningful learning outcomes
(Anderson, et al, 2001). Teaching presence has a profound impact on how well students perform, how much they
are satisfied with the course, how much they feel they learn, and how much they feel a sense of community
(Anderson, et al, 2001; Bush, et al, 2010; Cervantez, 2010; Garrison, 2003 & 2007; Jinks, 2009; Lazarevic, 2011;
Shea, et al, 2006).
Shea, et al (2006) posit that teaching presence can be displayed through directed facilitation, the “strong
and active presence on the part of the instructor—one in which she or he actively guides and orchestrates the
discourse”. Anderson, et al (2001) also identify the components of directed facilitation, which include: whether the
instructor is seen as drawing in participants, creating an accepting climate for learning, keeping students on track,
diagnosing misperceptions, identifying areas of agreement and disagreement, helping to resolve these by looking for
areas of consensus the students report higher levels of connectedness and learning, and reinforcing student
contributions, injecting their own knowledge, and confirming student understanding.
For Ekmekci (2013) teaching presence focuses on the use of online communication protocols and
interactions that highlight the questions that need to be answered in order to design, organize and deliver instruction,
and the stages along the way when discourse facilitation is necessary. Stein & Wanstreet (2013) find that teaching
presence can be exhibited through “e-coaching”, the process of staying connected with students synchronously and
asynchronously, and guiding them through the steps, processes, activities, etc. they have to undertake.
To evaluate the level of “teaching presence”, Shea, et al (2006) and Jinks (2009) provide a model list of
Teaching Presence Scale survey, a 17-question survey using a five-point Likert scale. However, what stands out is
the absence of directions for interpreting the results of the survey. Fortunately, it uses a five-point Likert scale to
identify responses but the scale uses referents that are difficult to use for administrative or program purposes (i.e.,
Scale: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree).
It would be easy to modify the scale as follows: 1 = unacceptable, 2 = below expectation, 3 = meets
expectation, 4 = exceeds expectation, 5 = superior. This way, a response of “3 - meets expectation” could be used as
a base point. Any scores below “3” could indicate areas where faculty should pay attention to see how well they are
“present”, and any scores above “3” could be used to indicate “best practices” that all faculty could adopt.
An additional feature that is missing from this survey is the inclusion of student input. In other words, it
does not include open-ended questions to solicit how to improve teaching presence from the students’ perspective.
One way to invite students to offer their suggestions is simply to add a question similar to the following:
For any response that you have marked below a score of 3, please describe the types of changes you
feel the professor could make to give you and your classmates a greater sense that he or she is actively
engaged in your learning.
In summary, teaching presence is a critical factor in keeping students on track, and having students complete a
Teaching Presence Scale survey by, for example, the 5th week of a 15-week class, both faculty and students will
have ample time to have a sense of how the class is going, and there could be adequate time to make any corrections
if needed.
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Intervention #3 - Increase students’ ability to identify with their groups
Online learners have two groups that they have to identify with: their classmates as a whole and the
members of their team project groups. As noted by Fiol & O’Conner (2005) and Kankanhalli, et al (2007), virtual
teams have the most uncertainty, least visibility, most diversity and fewest opportunities to engage in politeness
rituals. This in turn leads to a great difficulty of team members to “identify” with the team or have a “sense of
belonging” to the team (Ashforth & Mael, 1989; Mannix, et al, 2002). So, some specific interventions are necessary
to improve team cohesiveness (O’Hair, et al, 2010; West, 1998).
To improve a student’s identification with classmates as a whole, Hubbard (2013a) suggests having each
student give a 2-3 minute introductory presentation during the first week of class that covers the goals of their action
plan, highlights from their professional life, and a summary of a significant life experience. If the class has too
many students, the class could be divided into smaller groups (perhaps, 15-25).
These presentations should occur during real time (Fiol & O’Conner, 2005), which could be achieved using
web-conferencing platforms like GoToMeeting, WebEx, or Adobe Connect. The students could also provide a link
to a personal website or professional networking site, like LinkedIn, in addition to posting information about
themselves on the course management system.
Whenever team projects are assigned, the team members could give a 6-7 minute introductory presentation
(in real time) that covers the member’s perspective on team goals and the skills the member will bring to the team to
accomplish those goals (Hubbard, 2013b). In addition to helping each team member identify with the team, it also
aids in the team formation stage.
Perhaps, the most significant factor in increasing students’ ability to identify with both groups lies within
the “social presence” of the class (Lazarevic, 2011; Cervantez, 2010; Ekmekci, 2013). According to Garrison
(2007), the three main aspects of social presence are effective communication, open communication and group
cohesion. The lack of social presence and its impact on student perceptions about how well they are performing or
have performed in online classes is described by Tanner, et al (2009), Picciano (2002), and Song, et al (2004). And,
Richardson & Swan (2003) examine how it improves student perceptions of online courses and their instructors,
showing that as a sense of social presence increases, the students will have a greater perception of learning and the
presence of faculty.
Social presence can also be based on the premise that a “community can exist independently from
geography, physical neighborhoods, and campuses” (Wellman, 1999), and feelings of connectedness, cohesion,
spirit, trust, and interdependence among members (Rovai, 2002). To measure social presence Rovai (2002)
developed the Classroom Community Scale. However, it is difficult to interpret the results of the Class Community
Scale because of the same reasons noted above for the Teaching Presence Scale. Therefore, in addition to the
modifications to the five-point Likert scale suggested above for the Teaching Presence Scale Survey, some of the
questions on the Classroom Community Scale Survey would have to be modified, because this survey has a mixture
of positive and negative questions (e.g., Question 1, “I feel that students in this course care about each other” vs.
Questions 5, “I do not feel a spirit of community”).
So, in order to interpret the responses, the questions would have to be re-phrased so that a score of “3 meets expectation” would have the same meaning for all questions. That being done, the score of “3 - meets
expectation” could be used as a base point. Any scores below “3” could indicate where faculty should pay attention
to see why students do not have a stronger social presence, and any scores above “3” could be used to identify “best
practices” that all faculty could adopt.
Again, what is missing from this survey is the inclusion of student input, which could be obtained by
adding a question similar to the following:
For any response that you have marked below a score of 3, please describe the types of changes you
think could be made to give you and your classmates a greater sense of identifying with your groups.
The timing of the survey is also critical, and conducting the survey by the end of the first third of the class (e.g., by
the 5th week of a 15-week class), would give both faculty and students ample time to have a sense of how the class is
going and adequate time to make any corrections if needed.
There is one salient point that comes out of Rovai (2001b & 2002): the frequency of faculty-student
communication contacts within a supportive communication climate increases social presence. There has been
much discussion about the value of a supportive communication climate (Hassan, et al, 2011; Keyton & Beck, 2009;
Klenk, & Hickey, 2010; van den Hooff & de Ridder, 2004); however, few other than Gibb (1961) offer specific
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prescriptive actions that can be taken to create such a climate. He posits using language that focuses on:
Description (focus on “what & how), Problem Orientation (task focus, each member does her/his part), Spontaneity
(openness, self-disclosure, without hidden agenda), Empathy (concern for others, perspective taking), Equality (little
status differences, say “we,” “us,” “our”), and Provisionalism (flexibility: “There are different strategies that we
could use to achieve a goal”).
The last practice that enhances students’ identify with the group is to have frequent meetings. Rovai
(2001a) concludes that “monthly face-to-face contact can generate a significantly stronger social presence that a
similar program with only annual face-to-face” meetings. However, in that many online programs have students in
dispersed geographic locations, consideration has to be given to how to manage these monthly meetings in a
synchronous environment rather than trying to have in-person, face-to-face meetings.
Aside from the impact of time zones differences and other logistical problems associated with organizing
such a meeting, the number of students who would be logged on and participating in the meeting also creates
challenges. It is common that undergraduate, required courses or graduate MBA programs, for example, usually
have large cohorts, which makes meeting at the same time fairly impossible or unmanageable, especially
considering the participation constraints of web-conferencing platforms.
One solution could be to treat these “social presence” meetings the same way that discussion sessions are
conducted—with small groups of students from the same class. So, instead of trying to arrange one monthly
meeting with 75 participants, the class could be subdivided into three monthly meetings with 25 participants. And,
that might also make it easier to avoid or reduce the impact of different time zone and other logistical problems.
In summary, taking specific steps to increase “social presence”, measuring the extent of that presence, and
taking appropriate actions where necessary should give students a greater sense of identity with their groups.
Intervention #4 - Enable student groups to achieve their goals
Successful teams are those that are cohesive and move efficiently through the four stages of team
development (West, 1996; O'Hair, et al, 2010), specifically with the use of team management tools (DuFrene &
Lehman, 2002; Hubbard, 2003, 2011). In addition, the teams that have strong communication skills and use those
skills to manage the relationships of team members and external stakeholders are the ones that achieve their goals
(Petska & Berge, 2005). However, in that virtual teams do not have opportunities for actual, real-life interactions
(either formal or informal), a more prescriptive approach is needed to compensate for that deficiency (Hubbard,
2013b).
Effective collaboration on group projects is not simply a matter of dividing classes into groups (Brown, et
al, 2006). These groups need clear organization and open lines of communication to build trust (Hasler-Waters &
Napier, 2002), and they should be relatively small in size, about 4-5 members (Tinker, 2004). More importantly, a
team charter would enable them to manage the processes that lead to team success (Schoenfeld & Berge, 2005;
DOD, 1998; Schoenfeld & Berge, 2005; Hunsaker, et al, 2011; Chung, 2013; Aranda, et al, 1998; Holtham et al,
2006; McDermott, et al, 1998; Willcoxson, 2006).
There are several versions of team charters that are ideal for building cohesive groups. For example, DOD
(1998) includes: missions and objectives, metrics to evaluate team progress, scope of team responsibilities,
relationships and reporting structures, authority and accountability, resources, and a team membership list.
Schoenfeld & Berge (2005) includes: summary of the team assignment, team participants, rules and responsibilities,
communication tools, and communication guidelines. Hunsaker, et al (2011) includes: mission statement; vision;
boundaries; operating guidelines, norms and expectations; evaluation and discipline; and charter endorsement.
Of the three, Schoenfeld & Berge (2005) address the most critical elements of team success:
communication tools and communication guidelines. While it might seem time-consuming for groups to go through
the process of completing a charter, it allows team members to identify and quantify the skills they bring to the
group (Hubbard, 2013a), in addition to providing team members with an increased level of specificity to team goals,
strategies and processes. Furthermore, it enables global virtual teams to consider the impact of culture and take
appropriate actions to identify any cultural miscommunications and misunderstandings (Morrison & Conaway,
2006; Varner & Beamer, 2011; Hubbard, 2013b).
In summary, to facilitate the use of a team charter, faculty could have discussions about teams, specifically
team development and team management tools before the first team project is assigned. Then, there could be
discussion about the use of a team charter, which would be completed during the forming stage of the team. As part
of the teaching presence, faculty could intervene at specific team deadlines to see how the team is functioning.
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Intervention #5 - Create opportunities for faculty to share best practices
Online teaching differs significantly from face-to-face teaching, and “the growth of online courses and
programs has increased the need for faculty to become comfortable with online teaching and gain the necessary
skills to make online courses a success” (Allen & Seaman, 2011). Because student success in online courses is so
vitally tied to faculty-student interactions, the extent to which faculty can be supported to facilitate the abovedescribed interventions is directly tied to the level of student success and retention.
Duncan & Barnett (2009) and Howell, et al, (2003) have already noted that faculty have feelings of being
isolated from their students. However, considering that faculty are often isolated from other faculty due to the
nature of university teaching, online faculty might be even more isolated from their colleagues. And, as such, their
ability to obtain and disseminate best practices could be quite limited. Therefore, it would be helpful for
administrators to create opportunities for faculty to share ideas and exchange best practices (Tanner et al, 2004).
According to Allen & Seaman (2011), most institutions report that they provide some form of training for
faculty who teach online, which could include internally run training courses (72%), informal mentoring (58%),
formal mentoring programs (about 40%), and externally run training courses (about 21%). Allen & Seaman (2011)
also report that “only six percent of institutions with online offerings report that they have no training or mentoring
programs for their online teaching faculty.”
However, if the intent of such training is to attract, retain, and promote exceptional online faculty and
improve individual and organizational performance and effectiveness, then a commitment to peer-to-peer mentoring
seems to be the approach that would yield the best results if done effectively. Not to be confused with mentoring
junior faculty (Luna & Cullen, 1995; WSU, 2013), peer-to-peer mentoring places the mentor in the role of “coach”
in that faculty members learn from their own and each other’s experiences, mistakes and successes (CET, 2013).
Much attention has been given to the benefits of mentoring, the roles involved in mentoring, qualities of
good mentors, and guidelines for implementing and running mentoring programs. However, not much has been
identified about the element that appears to be missing from all other discussions about mentoring—the benefits of
having both mentor and mentee observe the other while engaged in teaching. Kirk (2013) not only discusses the
merits of mentoring and gives advice about how to manage mentoring programs, but also provides details about how
to include peer observations—the practice of having colleagues visit classes to provide feedback and advice to one
another about subject matter, activities, and teaching performance, which is not part of performance evaluation, but
as an integral part of mentoring.
In summary, online faculty need support in order to share best practices and mentor one another, which can
only happen if administrators enhance that process by creating formal and informal opportunities for them to do so.
Conclusions and Implications for Research
For online education to be successful, it is essential for the technology to provide seamless synchronous
and asynchronous faculty-student, student-student and faculty-faculty interactions. In addition, students have to be
or be willing to become self-directed learners, and faculty have to enable that process by generating a sense of
teaching presence and class community in addition to teaching their subject matter. Furthermore, there needs to be
an environment in which faculty have opportunities to exchange ideas and best practices, and by doing so, it is
anticipated that the barriers to the adoption of online learning will decrease, and the factors that facilitate student
success and retention will increase.
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