Persistence in an Online Master’s Degree Program: Perceptions of Students and Faculty
Saint Francis University
Persistence in online learning experiences has been perceived as chronically lower than in face-to-face learning, but a comprehensive understanding of this phenomenon has proven elusive. As online learning opportunities continue to expand, a better understanding of how learners and faculty perceive persistence is needed to foster this continued growth, and was the objective of this study. This single case study consisted of interviews of eight online master’s degree students and six online faculty members from the same program related to their perceptions of persistence. Interviews were completed initially with the students and were triangulated with faculty interview responses. The results provided insights as to how participants viewed persistence in the online classroom and how each participant experienced and managed persistence. Themes emerged related to characteristics of persistent learners, practices of online faculty and staff, online course design techniques and practices, and program-level student support strategies. The results suggest that persistence in the OLE can be attained with structured policies infused with flexibility, open communication, and an engaged learning community. Additional research is recommended with different groups of learners, longitudinal studies, and to relate these findings to existing theory.
IntroductionReview of the Literature
Enrollment persistence in online graduate programs is a complex phenomenon (Haydarov, Moxley, & Anderson, 2013; Park, Perry, & Edwards, 2011). Defined as “a multi-faceted phenomenon that leads to completion of an online program of study” (Hart, 2012, p. 29), persistence is tracked continually as a key outcomes measure and an indicator of a quality educational offering (Park et al., 2011). The opportunities offered by online learning experiences, those in which 80% or more of the content is delivered online, have demonstrated steady growth for at least the last decade and this growth has outpaced traditional higher education (Allen & Seaman, 2015). As outcomes in the online learning environment (OLE) are shown to be at least competitive with the traditional classroom (Allen & Seaman, 2015; Means, Toyama, Murphy, & Baki, 2013; Park et al., 2011; Shachar & Neumann, 2010), the OLE is uniquely poised to address many of the contemporary concerns related to higher education, particularly access and ongoing educational needs (Heyman, 2010). Yet, despite the achievement of these critical milestones, the OLE consistently is believed to retain students at a lower rate than traditional, face-to-face learning environments (Boston, Ice, & Gibson, 2011; Cochran, Campbell, Baker, & Leeds, 2014; Hart, 2012; Heyman, 2010). The extent of this lower retention rate ranges from 10% to 80% less for online endeavors (Cochran et al., 2014; Pittenger & Doering, 2010).
Many strategies have been implemented to assist learners in successfully achieving their academic goals (Fetzner, 2013; Hart, 2012; Roby, Ashe, Singh, & Clark, 2013), yet persistence concerns remain. Numerous researchers have provided empirical evidence of retention and attrition trends to the extent that predictions can be made related to persistence in the OLE (Boston et al., 2011; Hachey, Wladis, & Conway, 2012; Hart, 2014; Ice, 2012). However, even when the data predict dropout, learners can persist. Taken together, the researcher is left to interpret a maze of data offering conflicting conclusions about the nature of persistence in online programs.
Some have identified that the lower retention is due more to inadequate academic preparation than to the online learning environment (Cochran et al., 2014; Lee & Choi, 2011; James, Swan, & Daston, 2016; Wilson & Allen, 2011). Further complicating this issue is the nature of adult online learners, who are balancing multiple life responsibilities, necessitating that the achievement of educational goals may follow an unconventional path (Haydarov et al., 2013). This can make the determination of when to measure persistence cumbersome (Boston, Ice, & Burgess, 2012). As a consequence, lower retention is believed to be a hindrance to growth in online learning opportunities (Allen & Seaman, 2015). So while online learning provides solutions to educational quandaries, its potential is restricted by the retention concern. The purpose of this embedded single case study was to examine perceptions of online learners and faculty related to persistence in the OLE, specifically how persistence is understood, managed, and achieved.
A review of the literature on persistence seemed broadly organized into three areas: personal characteristics of students; those related to the learning environment at the levels of course, program and institution; and external factors. An extensive review of the literature was completed utilizing the key words online, OLE, distance education, persistence, design, retention, attrition, drop out, perceptions, and success. Only peer-reviewed works published since 2010 were considered for inclusion (unless they were germinal) and those using outcome measures other than persistence. ProQuest, EBSCOHost, and ERIC databases were extensively used. Google Scholar was utilized as a source for pertinent literature, as well as the Internet for open source distance-education journals.
Student Traits and Persistence
Individual characteristics that have been shown as related to persistence and success in the OLE include learning styles, motivation, time-management skills, self-awareness, and attitude toward the OLE (Conceicao & Lehman, 2012). The student’s sense of self and his or her inherent capabilities were identified as significant to online persistence (Gomez, 2013; Hart, 2012) as was the integration of the role of learner (Baxter, 2012: Carroll, Ng, & Birch, 2013; Heyman, 2010). Carroll et al. (2013) found that learners who integrated their academic commitment with their work and family responsibilities were more persistent than students who did not. Heyman (2010) found that the students who identified with and were committed to their educational institution were less likely to drop out. Baxter (2012) demonstrated that recognition of the learner’s changing identity related to the program is important in effectively managing transitions, and thereby important to persistence.
Self-determination (Beaudoin, Kurtz, & Eden, 2009; Street, 2010), self-direction (Mayes, Ku, Akarasriworm, Luebeck, & Korkmaz, 2011), self-discipline (Deimann & Bastiaens, 2010; Gomez, 2013; Heyman, 2010; Truell, Alexander, Zhao, & Davis, 2013), and self-motivation (Hart, 2012; Mayes et al., 2011; Street, 2010) were found to be essential characteristics of persistent students throughout the online persistence literature. Taken together, these characteristics constitute the self-regulation possessed by the learner (Gomez, 2013). High levels of self-regulated behavior are fundamental to academic achievement and persistence. Persistent learners possessed significantly higher critical thinking skills and leadership behaviors, especially behaviors leading to the achievement of goals and those concerning how to interact with peers (Gomez, 2013). Other themes identified throughout the literature include effective time-management skills (Street, 2010; Truell et al., 2013), a responsibility for one’s learning (Heyman, 2010; Mayes et al., 2011), autonomy (Street, 2010), resilience (Hart, 2012), a high academic locus of control (Lee, Choi, & Kim, 2013), academic optimism (Bressler, Bressler, & Bressler, 2010) and organizational skills (Truell et al. 2013). Conceicao and Lehman (2012) found that persistent learners prioritize and plan their time appropriately, indulge in small rewards, and adapt their learning strategies to the learning environment. Truell et al. (2013) added that strong reading, computer, and technology skills are necessary for course completion.
Quantitatively, Boston, Ice, & Gibson (2011) and Cochran et al. (2014) found that the more credits earned or courses completed in a curriculum, the less likely a student is to drop out. Likewise, Lee and Choi (2013) found that students with previous online learning experience are less likely to drop out of online learning experiences. Numerous studies have shown that learners with previous W or F grades have a higher frequency of dropping out (Boston et al., 2011; Cochran et al., 2014; Hachey et al., 2012). Learners with lower GPAs had a higher drop out frequency from the OLE (Cochran et al., 2014; Lee & Choi, 2011; Leeds et al., 2013).
Persistence Support Within the Learning Environment
This section will consider specifically the role of the instructor’s in course management and persistence as well as how online courses can be constructed to optimize persistence. There is essentially unanimous evidence in the literature of the paramount role of the instructor in the online teaching-learning relationship (Bonnel & Boehm, 2011; Conceicao & Lehman, 2012; Hart, 2012; He, 2014; Heyman, 2010; Lee & Choi, 2011). Conceicao and Lehman (2012) and Lee and Choi (2011) contended that the instructor is a central figure in the dynamic OLE, uniquely positioned to provide a holistic view of the course while attending to the ongoing maintenance needs within the course. The instructor should lead the learning community by synthesizing the content and the group’s activities throughout the course (Bonnel & Boehm, 2011; Poll, Widen, & Weller, 2014) and provide an overview of what is to come (He, 2014). Taken together, these measures serve to personalize the learning experience and create a sense of instructor presence, which many studies have identified as vital to engagement and persistence (Casey & Kroth, 2013; Conceicao & Lehman, 2012; Heyman, 2010; Poll et al., 2014; Russo-Gleicher, 2013). It has been also been found almost unanimously that instructors should be accessible and responsive to their learners, addressing the changing needs of the dynamic online classroom regularly and consistently (Bonnel & Boehm, 2011; Hart, 2012; He, 2014; Heyman, 2010; Mayes et al., 2011; Poll et al., 2014; Rajesh, 2011). Casey and Kroth (2013) and Park et al. (2011) found that regular communication is important for the learning community, particularly at the beginning of a new online course.
A main component of a responsive instructor is the provision of feedback both to individuals and to the learning community (He, 2014). Review and critique of the learners’ work should be as close to immediate as is possible, but at least within the stated time expectation policy (Bonnel & Boehm, 2011; Mayes et al., 2011; Poll et al., 2014; Rajesh, 2011). High-quality feedback is characterized as actionable, timely, meaningful, and developmental in nature (Heyman, 2010). The instructor's feedback should be proactive in nature, anticipate the needs of learners, and serve to encourage and guide (Bonnel & Boehm, 2011). Multiple types of feedback should be offered, both formative and summative, and also feedback in response to varied learning activities.
Many authors have found that course design can impact leaners’ persistence in the OLE (Bekele, 2010; Park et al., 2011; Poll et al., 2014). The design of the online course is the structure for the development of quality interactions, meaningful social connections, and the nurturing of the learning community (Conceicao & Lehman, 2012; He, 2014; Park et al., 2011). Design helps to establish the expectations for performance. Intuitive design can make the achievement of learning objectives simple and foster optimal performance (Poll et al., 2014) whereas poor design can impart artificial barriers to attaining learning objectives and can cause frustration for learners (Hart, 2012).
The course content must be considered inherent to the context of course design. Content must be meaningful and relevant to learners (Beaudoin et al., 2009). Content should be sequenced gradually, beginning with fundamental knowledge and building to more complex interactions with the content and peers (DeLottell, Milliam, & Reinhart, 2010). Content that students connect with, find value in, and can apply is best. This is optimally done by problem and case-based activities (Bonnel & Boehm, 2011; DeLottell et al., 2010; He, 2014).
Online courses should utilize a consistent navigational structure and appearance (Casey & Kroth, 2013; Conceicao & Lehman, 2012; He, 2014). Consistency permits an initial familiarity with the course, which lessens the cognitive load for learners (Casey & Kroth, 2013; He, 2014). Orientation resources for courses should be made available to help support new learners, particularly if an associated outcome is expected, such as completion of a quiz on the course syllabus (Casey & Kroth, 2013). The organization of the online course should be logical and intuitive, and should require only a few clicks to access content (Beaudoin et al., 2009; Bekele, 2010: He, 2014). Technology requirements should be sequenced from basic to more complex (Conceicao & Lehman, 2012; DeLottell et al., 2010). Interaction being fundamental to learning, the expected level of participation and interaction should be clearly articulated and mandated in the course as part of the design (He, 2014; Park et al., 2011) and facilitate student to student, student to faculty, and faculty to faculty interaction (He, 2014; Hubbard, 2013; Beaudoin et al., 2009; Poll et al., 2014: Rovai & Downey, 2010).
The planning of content and design should anticipate what student concerns may be and seek to address them proactively (Casey & Kroth, 2013; Rovai & Downey, 2010). To this end, expectations must be clearly articulated by detailed instructions (Casey & Kroth, 2013; Poll et al., 2014) and by grading rubrics (Casey & Kroth, 2013). The posting of good examples of work also helps students visualize and understand what is required.
A mix of technology tools is recommended to help achieve varied learning goals (He, 2014; Poll et al., 2014). Best practices include large- and small-group activities, synchronous and asynchronous tasks (Bekele, 2010; He, 2014; Poll et al., 2014), the use of social media (Jackson, 2012), and the utilization of multimedia (Poll et al., 2014). The use of a variety of technology tools provides for varied feedback and requires specific methods of manipulation of the content and response by the parameters of the technology tool, and each has favorable and unfavorable attributes (Bonnel & Boehm, 2011).
Service Orientation to Needs of Online Learners
The needs of online graduate students differ from other learners in institutions of higher learning (Heyman, 2010; Stevenson, 2013). The unique needs of online learners, who tend to be adults, generally older, and possessing multiple other life responsibilities, require services tailored to their accessibility needs (time constraints and geographical distance). Programs and institutions that recognize and serve these differences foster students’ degree completion for these learners. The pursuit of online persistence should be a high priority, begin in the preadmission phase (Carroll et al., 2013), and continue throughout the lifecycle of the learner (Newberry & DeLuca, 2014). Best practice dictates that a student-centered institutionally-integrated system be implemented to foster online student persistence (Brito & Rush, 2013; Conceicao & Lehman, 2012; Heyman, 2010; Lee & Choi, 2011; Newberry & DeLuca, 2014; Park et al., 2011; Stevenson, 2013). Heyman (2010) defined institutional support as procedures developed specifically to support the needs of distance students with respect to institutional requirements such as financial aid, counseling, and billing. Persistence in this ideal situation is believed to be the result of a long-term partnership between the student, academic, and the social environments of the institution; a relationship that fosters trust in learners and provides a sense of caring and support to learners (Park et al., 2011).
But even in non-integrated learning environments, many interventions have been found to support persistence. Persistence begins with effective enrollment counseling that establishes realistic expectations related to the rigors of the program (Baxter, 2012; Carroll et al., 2013; Cockrell & Shelley, 2011; Conceicao & Lehman, 2012; Heyman, 2010; Rajesh, 2011). This permits students to assess their ability to meet the articulated requirements and modify behaviors accordingly. Exploration of the learners’ educational and career goals is necessary to assure alignment (Carroll et al., 2013). Learners should possess clearly articulated goals and confidence that the online program can contribute to the attainment of those goals. These insights provide a source of motivation for successful management of the rigors of the program.
Pre-assessment of the characteristics possessed by persistent learners is indicated to achieve a sense of baseline and to assess the learners’ unique strengths and weaknesses related to the OLE (Carroll et al., 2013; Gaytan, 2013; He, 2014; Lee & Choi, 2011; Heyman, 2010). Assessments and training for time management (Beaudoin et al., 2009; Heyman, 2010), perseverance (Beaudoin et al., 2009), computer skills (He, 2014; Heyman, 2010; Gaytan, 2013), self-discipline (Gaytan, 2013; Heyman, 2010), self-regulation (Gomez, 2013), volition (Deimann & Bastiaens, 2010), self-directedness (Hubbard, 2013), life stressors (Gaytan, 2013; Lee & Choi, 2011), procrastination (Michinov, Brunot, le Bohec, Juhel, & Delaval, 2011), and health concerns (Lee & Choi, 2011), in addition to more traditional academic support (Lee & Choi, 2011), have been recommended. Identified areas of weakness may be amenable to proactive intervention thereby lessening the risk to persistence (Gaytan, 2013; Heyman, 2010; Hubbard, 2013; Lee & Choi, 2011).
Mandatory orientation modules are recommended throughout the literature to provide a favorable initial experience for new online learners (Aversa & MacCall, 2013; Cockrell & Shelley, 2011; Gaytan, 2013; Heyman, 2010; Jones, 2013; Lee & Choi, 2011). An early alert process has been recognized as beneficial to persistence efforts in the OLE (Brito & Rush, 2013; Lee & Choi, 2011; Park et al., 2011). Online instructors or other support personnel should monitor participation in courses on an ongoing basis. Early recognition of difficulties permits appropriate, proactive support measures to be arranged so that small concerns do not become unmanageable and culminate in attrition (Brito & Rush, 2013; Heyman, 2010; Hubbard, 2013).
The literature demonstrates the utilization of various online student support personnel to foster persistence. Each functioned specific to the needs of the institution, but all shared the objective of persistence and successful completion of the online program. The support personnel identified included an academic support coordinator (Aversa & MacCall, 2013), distance education coordinator (Aversa & MacCall, 2013), mentors (Park et al., 2011), academic advisor (Cockrell & Shelley, 2011; Gravel, 2012), academic tutors (Heyman, 2010); and a case manager (Brito & Rush, 2013). For institutions in which online learner support is not comprehensive, the above personnel can bridge the service gaps and be the difference between loss to attrition and persistence.
Regardless of their title, a responsive distant academic advisor was found to be critical to success and persistence for students struggling and isolated in the OLE (Cockrell & Shelley, 2011; Lee & Choi, 2011; Waldner, McDaniel, & Widener, 2011). Effective advisors address student questions related to the institution, program, and course work, and counsel learners in balancing academic and personal demands (Rajesh, 2011). Stevenson (2013) found that proactive measures initiated by academic advisors support persistence. Gravel (2012) added that learners preferred an individualized developmental partnership with their advisor with the aim of matching program requirements to the learner’s goals.
Additional recommendations offered in the literature include academic advising and support interventions which utilize multi-media tools for academic advising such as synchronous chat rooms and orientation videos (asynchronous) (Waldner et al., 2011); self-service support interventions such as handbooks, seminars, online tutorials, written or video instructions, podcasts, blogs, or peer mentoring (Cockrell and Shelley, 2011; Crawley & Fetzner, 2013); and one-on-one meetings when feasible (Gravel, 2012). Other recommendations include an online advising portal (Gravel, 2012), online referral forms (Russo-Gleicher, 2013), and online interfaces for critical services should be established (Sullivan & Pagano, 2012). These varied structures can permit open access to assistance; attend to varied learning styles, technologies, and preferences; and provide for a learner-centered experience (Crawley & Fetzner, 2013).
Despite the inherent complexity of these interventions, Rajesh (2011), Gaytan (2013), and Rovai and Downey (2010) advocated for support interventions being simple and student-oriented. To meet these evolving expectations, Rajesh (2011) recommended that with growth of distance-education initiatives, commensurate expenditures are made to maintain the quality of services for online students including ongoing training for faculty and staff members and investments in emerging technologies.
External Factors and Online Persistence
Conceicao and Lehman (2012) acknowledged the effect of external factors on persistence. External factors can include hours of employment, family responsibilities, life roles, the availability of support and encouragement, life crises, and financial concerns (Conceicao & Lehman, 2012; Hart, 2012). Lint (2013) specifically recommended, based on the evidence, that online learners minimize distracting external attributions to the greatest extent possible. The impact of external factors is difficult to perceive, as each learner has a unique set of external factors, values each factor differently, and possesses finite resources with which to cope (Conceicao & Lehman, 2012). External factors can be supportive or disruptive, and how they are perceived can vary over time. Hart (2012) and Street (2010) found near unanimous agreement that positive external support fosters persistence. How external factors are managed, then, depends on the learner’s personal characteristics and the program/institutional considerations. Specific interventions noted in the literature that accommodate external factors include flexible policies (Aversa & MacCall, 2013; Beaudoin et al., 2009; Hart, 2012; Heyman, 2010; C. L. Park et al., 2011); the convenience of being able to work as the learner’s schedule permits (Hart, 2012); accessible and responsive instructors (Casey & Kroth, 2013; Conceicao & Lehman, 2012; Lee & Choi, 2011; Pittenger & Doering, 2010; Poll et al., 2014), academic support services (Bekele, 2010; Conceicao & Lehman, 2012; Stevenson, 2013); technology support (Conceicao & Lehman, 2012; Street, 2010), integrated institutional support (Newberry & DeLuca, 2014; Stevenson, 2013), and feeling part of a learning community (Beaudoin et al., 2009; Gannon-Cook & Sutton, 2013; Park et al., 2011).
Persistence is a multifactorial phenomenon subject to the perception and interpretation of each learner (Hart, 2012; Lee & Choi, 2011; Stevenson, 2013). It is also influenced by temporal and contextual circumstances, as well as the compounded effects of these elements (Baxter, 2012; Lee & Choi, 2011). Effective balancing of life responsibilities weighed with the optimization of the referenced interventions can provide learners the means to endure in the OLE until their educational goals are realized.
Because the ability to persist appears to be impacted by a number of factors and how these factors are perceived, this qualitative study was designed to gather the perspectives of online learners and faculty on the issue of persistence in the OLE. The design was a single case study with two embedded units of analysis. The case was the subject online master’s degree program and the embedded units of analysis were the two groups of participants interviewed, students and faculty members of this same program.
The population for this study consisted of learners and faculty from an online master of health science (MHS) degree program, housed at a private university in Pennsylvania. All of the MHS course work is online and almost all students (> 95%) are enrolled in the program on a part-time basis. The average age of an MHS student was 41 years, with an age range of 22 to 62 years. The gender ratio for MHS students is 5:1, female to male students. There are approximately 40-50 MHS graduates each year.
The sample for this study included eight eligible MHS learners and six MHS faculty members. Eligible student candidates were persistent MHS students who had completed at least six of 10 MHS courses, verified by the unofficial MHS program transcript. Because the principal investigator was also the MHS department chair, ideal candidates would not be planning to enroll in any of the courses the researcher teaches prior to completing the program; this was verified with a review of the unofficial transcript. The student participant age range was 37 to 51 years with a mean of 47.3 years. The participant gender distribution was 5:3, female to male, which represent male student perspectives more than the typical gender distribution for the program. Six of the eight students worked full time while enrolled and none were caring for dependents at the time of enrollment. The faculty participants’ age range was 44 to 61 years. The faculty gender distribution was 5:1, female to male. The online teaching experience represented by the faculty participants ranged from six months to seven years and all were online students at one time.
After securing permission through the IRBs at the involved universities, an all-user announcement was posted in a Blackboard course site that serves as an online repository and the main means of communication for the students and administrative staff of the MHS program. The posted message provided a brief overview of the proposed study, its objectives, and the request for volunteer participants. MHS faculty members were sent a group email through the university email system asking for their voluntary participation approximately one month later. An invitation to participate was extended to those expressing a willingness to engage in the study; the first eight qualified respondents from the learner group and the first six faculty members who verbally agreed to the terms of participation were enrolled in this study.
As the perception and understanding of persistence in the OLE were the primary data in this study, interviews with both online learners and faculty were conducted to acquire this data. An interview tool (Appendix A) was developed based on the findings from the literature review and included open-ended questions related to the impact of internal, external, and learning environment factors on persistence, and the skills, attitudes, and behaviors needed for persistence in the OLE. Prior to the start of the study, the interview protocol was field tested with two online faculty members. The responses collected as part of the field test were not included in the results of this study. The same interview tool was used for both participant groups. The faculty interviews were supplemented with a compilation of student responses to each question and faculty members were asked to comment upon the student perceptions. Most of the interviews were conducted over the telephone as a scheduled call; one of the student interviews and two faculty interviews were conducted as an in-person interview. Each interview lasted 60-90 minutes and were recorded for transcription. The transcribed interview was emailed to each participant for member checking and returned. The approved transcripts were then blinded to the researcher prior to coding. Data analysis was completed using NVivo. At the conclusion of the faculty interviews, and after receipt of the member-checked transcripts, the researcher’s notes and observations were included in the collected data for analysis. The transcripts were auto-coded by interview question and then further sub-coded by themes organic to the interview responses.
A summary of the results is provided below organized by common themes that emerged from the interview responses. The themes identified included characteristics of learners, things that instructors do, course design elements, and online program features. There were common responses from all participants in many areas but particularly related to the nature of the persistent student. For example, all participants referenced in some way that persistent learners were organized, self-disciplined, and in possession of sound foundational academic abilities including reading, writing, research, and information literacy skills. In addition, persistent learners were perceived to know themselves as learners and asked questions when an issue was unclear. As such, the reported faculty results below will identify mainly unique perspectives or areas of disparity with student participants. The results below provide useful insights on how to create a learning environment that fosters persistence.
Characteristics of Persistent Students
Many similar characteristics were identified by participants as supportive of persistence in the MHS program. All eight student-participants stressed the importance proactive planning and time management in order to complete the tasks required by their work, academic, and personal commitments. Students reported downloading each course’s source documents and making a comparison of assignment due dates to their personal schedules. Mapping their activities in this way permitted an appreciation of weeks where there would be less time to complete their academic assignments. Behavior could then be modified to assure that the work was completed prior to the deadline or alternate arrangements could be made. Three of the eight student participants reported prioritization of “down time” and special events in order to achieve life balance.
Interestingly, all students acknowledged the value of the course syllabus. Each downloaded the document and used it as a resource throughout the semester. Student participant # 2 described a detailed planning process which included a study all of the course documents including the syllabus, assignment table, assignment specifications, and grading rubrics. The student intentionally published his shared works later than many of his classmates (still prior to the due date) so that an assessment of his anticipated work effort could be made and identification of any knowledge gaps could be ascertained to provide focus for his research This student also professed an expectation of earning an A grade in each of his courses and reportedly calculated each week the number of points needed in order to achieve this goal. This detailed and specific planning was a strong motivator for this student.
Daily attention to and completion of course work was advocated by all participants. All student participants reported enjoying the course work and stated that they were “always thinking” and seeking to apply their newly acquired knowledge in their clinical or professional roles.
A common theme with the all of the participants was a long-term objective of enhanced career opportunities as a consequence of earning the MHS degree and this goal contributed to their daily motivation to complete course work. While this larger goal was always relevant, it was perceived as overwhelming or too far in the future to be of immediate concern. The MHS learner participants reported a focus on the completion of each individual assignment and expressed the belief that consistent effort and achievement of each smaller task would culminate in the conferral of the MHS degree. Faculty member #1 observed that short terms goals become more important when a student is struggling. In such instances, success can be viewed as completing one week or assignment at a time. Faculty member # 6 explained that her perception of student persistence was on a course by course (shorter term orientation) basis by virtue of the observation that this “is how they [students] introduce themselves in a new class,” that is, by identifying how many courses have been completed in the curriculum. All faculty members identified the vital importance of the longer-term goal so, as faculty member # 1 stated, “they know what they are sacrificing for.” Faculty member # 4 believed that the lack of a long-term goal can make the process confusing.
Five of the eight students surveyed, when asked how they managed obstacles during their enrollment, denied the existence of obstacles. When pressed, conflicting commitments were acknowledged throughout the duration of the MHS Program. However, these were not perceived as barriers and the learners spontaneously modified their behavior, through planning and effective time management, to complete their work. Faculty member # 3 specifically addressed the resiliency of persistent learners and how dedication to long term goal provided the motivation to persist. Student # 3 also addressed resilience by stating that “You didn’t have to be the smartest person in the program but you did have to keep going”. Six of the eight student participants reported working a consistent schedule and none of the students cared for dependent family members, either small children or others requiring physical care.
Faculty participant # 6 reported that each student has unique support needs that require an individualized approach, that is, some students need only general reinforcement of their efforts, while others need more specific assistance. Four faculty participants reported that persistent learners believed that instructors and the institution were invested in them personally and were dedicated to their success, but equally important, according to faculty member # 1, was the students’ honest self-assessment of their readiness for and ability to function in the OLE as “it’s not for everyone.”
Interaction within the online classroom was universally cited by the MHS students as supportive of persistence. However, interaction was important for persistence for a number of reasons. Peer and instructor support and clarification of questions were reported as the primary purposes of interaction. Also noted was comradery and the achievement of a sense of community, with peers sharing the same experiences, stressors, and successes. Four of the eight participants reported using interaction in the form of discussion-board postings to gauge the level of discourse in order to inform their work effort and products. In this manner, interaction was used as a measure of acceptable work standards, both personally and for the group, which then informed their approach to course work. An openness to try new things and to learn, the willingness to communicate with diverse others, and the ability to communicate respectfully online, were also attributes believed to foster persistence according to four of six participating faculty members.
How Instructors Foster Persistence
All of the MHS learners surveyed found the course instructor to be vitally important in persistence efforts, particularly with regard to the timeliness and quality of feedback and their openness to questions and communication. Prompt and encouraging communication on the part of faculty members permitted students to minimize stress, modify performance, and provide their highest level of work. Timely, individualized,
and corrective feedback was particularly valued. The best feedback included positive commentary, which acknowledged how learners met the assignment expectations, as well as actionable constructive criticism that helped learners identify what could be improved. Half of the faculty participants (three of six) noted that an unresponsive instructor could discourage distant learners and aggravate difficult situations.
The MHS students appreciated the efforts faculty and staff provided to connect with them on a personal level. The learners expressed that an openness and willingness to communicate provided for a sense that faculty and staff were “here for you” as a student; that this perceived personal interest “helped keep me driven” (student # 8), “made me want to learn” (student # 1), and two students, # 6 and # 8, voiced a reciprocal responsibility to “not let the instructor down.” An additional observation, offered by two of the six faculty participants, was that a feedback loop of “mutual support” can be created which serves as a motivator for faculty members to engage in ongoing communication.
Further, the openness to communication through multiple channels made interaction convenient, prompt, and less encumbered. Faculty members who were invested in their students’ success and offered the uniqueness of their personalities made the online courses “less linear” and more dynamic. All students stressed the importance of clear expectations to permit planning and modification to the needs of the instructor/course. The supportive nature of the faculty and staff dominated the faculty responses in this section with faculty member # 1 deeming this quality, “personal service at a distance”. Faculty member # 3 explained that teaching online is different for instructors, because “the access and time structures are less restricted and are outside the traditional paradigm.” Not all faculty members may be able or willing to be this involved in their courses but persistence is enhanced when this commitment can be made.
Faculty member # 1 addressed the need for continuity of the faculty and staff so that personal connections with learners could be established. Continuity was also believed to demonstrate the stability of the online program. Finally, two faculty members (# 2 and 4) advocated for instructors, “setting their egos aside” and engaging graduate students in sharing their content expertise to provide for authentic learning experiences.
Course Design Considerations for Persistence
There were numerous course design considerations identified as supportive of persistence. All participants believed that the MHS curricular content was relevant to their personal goals and student # 3 observed that content and assignments were gradually sequenced, with each week building upon the previous week. This made assignments seem more feasible. All eight participants added that interaction in the courses supported their persistence. Without interaction, student # 8 stated, “I felt alone in the course”. Most MHS courses require a designated number of postings per online discussion. This required level interaction with diverse others provided for new the appreciation of perspectives and challenged learners to view topics more deeply than can be achieved in the traditional classroom. All student-participants acknowledged and appreciated this aspect of the MHS Program in retrospect, with participants # 6 and 8 citing specific examples of challenging communication situations that were perceived, upon reflection, as growth opportunities.
Student #4 perceived rigor and discourse in the MHS Program as elevated in the OLE compared to a face-to-face classroom. The student observed that in the OLE, the course design and technology options provided by the LMS and the Internet make access to multiple scholarly resources convenient and provide students with ample opportunities (time beyond a prescribed class meeting) to support their views and arguments. This student stated that she completed more research for the MHS program (typical time of enrollment is 20 months) than in her entire undergraduate program. Student # 4 explained that in her undergraduate classes, course resources were to limited primarily to the course textbook and instructor, and the instructor’s access was limited mainly to the scheduled class time. In the OLE, unrestricted access was provided to the course textbook, the instructor, classmates, a link to scholarly library resources, the Internet and its content, and the reference lists from classmates’ work. In addition, the nature of asynchronous courses permitted time to process information and formulate a response making for a much richer learning experience.
All of the faculty participants agreed with the observations of the richness and potential of the OLE. Faculty member # 6 added that this also is what makes teaching and learning in the OLE more difficult specifically “because there are so many resources.” All MHS courses possess a similar design, organizational and navigational structure, and pace. Faculty member # 3 acknowledged this as simpler for students in terms of navigation and understanding how courses work but for a successful course, the learning activities, technology, and content must be aligned to foster best outcomes.
As noted in previous sections, all students reported that clear course expectations and access to course documents prior to the start of courses facilitated proactive planning and strategizing for the completion of course work in context with other life responsibilities. Faculty member # 1 advocated that instructors make changes to courses once underway only if necessary as changes impact students’ planning and can cause unnecessary stress for learners. Three of the six faculty participants advocated for multiple means of communication within courses to permit best access between students and the instructor.
Online Program Features to Foster Persistence
The student and faculty participants identified several approaches that programs can undertake in order to foster persistence. The faculty, in particular, offered specific observations related to program policies. Three of six faculty members asserted that consistent application of program policies supported students through difficult times while four of six faculty participants acknowledged the flexibility inherent to program policies was also critical. Faculty member # 3 explained that flexible policies, such as the use of an incomplete grade, permit students to balance external demands and persist in their online program, asserting that, “the work can’t change but how it’s done can”. Faculty participants # 2 and 4 advocated for the student to have an active role in the grade appeal process such that “students have a voice” in the implementation of program policy and that, as faculty member # 4 added, “the people component comes into everything”. Faculty member # 2 described such policies as evidence of the university’s mission and further classified such policy approaches as an investment of faculty, staff, and the university in the learners’ success.
The articulation of clear program expectations was voiced by faculty as critical, as well as proactive engagement of faculty and staff to struggling support students. Communication was a common theme in each of the finding areas for this study. Persistent students valued and engaged in communication; instructors influenced communication in courses by their example; course design fostered ease in communication, and communication as it related to program policies helped learners manage conflicting commitments.
The results of this study align and contribute to the body of knowledge in terms of how students persisted in the OLE and seem to add support to existing theory particularly the Community of Inquiry and the concepts of instructor and social presence (Garrison, Anderson, & Archer, 2000). The case study method, specifically the interview process, provided insights as to how persistent learners managed their course, work, and life roles. As a result, this study may contribute to greater understanding of how students persist and the function of iterative deep planning, both how the planning is done and the critical nature of planning to optimally manage simultaneous commitments.
In viewing the results and recommendations, it is recognized that the participants of this study were highly motivated volunteers from one online master’s degree program. As a consequence, the results may not represent all online graduate learners. Despite this fact and by virtue of the MHS participant responses, a number of best practices can be recommended:
a). The characteristics of persistent learners could be screened in the admissions phase so that supportive measures can be prescribed proactively to foster a successful experience. For example, a learner who is identified as weak in time management could be provided resources to improve in this area.
b). Clear course and program expectations, which learners identified as critical to effective planning, must be articulated early and often so students can ascertain their ability to meet them.
c). Conscious attention to the student’s external factors should be part of ongoing student support measures prior to and during enrollment. These learners did not perceive conflicting responsibilities as obstacles and spontaneously managed them. The presence of flexible policies coupled with the fostering of open communication can make managing external commitments less burdensome for learners and thereby foster persistence.
d). The fostering of a vibrant social community was valued by both faculty and staff and was believed to make learning more dynamic and authentic. A sense of community also made a more pleasing and meaningful virtual learning environment. This should include
- careful consideration of technology tools and learning activities that foster interaction with peers and the content.
- required, frequent, and consistent interaction between classmates. Students should be mandated to respond to several peers, for example, in discussion boards. A mandated level of interaction assures that students must interact in a respectful manner with ideas contrary to their own, which provides for growth opportunities.
- encouragement of learners to share their expertise. This provides an additional level of application of content and contributes to the social environment in an authentic manner.
e). An actively-engaged and responsive instructor facilitating the online community was identified as fundamental. The selection of content experts who genuinely enjoy teaching seems to be a key component in this regard.Taken together, the findings support the OLE as a rigorous, dynamic, and feasible way of achieving graduate education goals. Attention to what we know at this time, specifically the characteristics of the best performing online learners, the behaviors demonstrated by superior online faculty and staff, and the effective design of online learning spaces, can help foster persistence and the achievement of personal and professional goals today and for the foreseeable future.
f). A stable staffing pattern of faculty and staff permits continuity for the program and provides the opportunity for connections with the learners to develop. Inherent to this recommendation is an investment by institutions in “human resources” to foster this stability.
g). Course design that is thoughtfully sequenced in content and technology skills; an intuitive and consistent navigational structure within courses; and technology choices aligned to articulated learning objectives.
h). Consistent adherence to program policies (clear expectations) while permitting flexibility within those policies to accommodate the evolving needs of graduate online learners. The flexibility fosters persistence when students are challenged by external factors.
To explore persistence further, a similar study could be conducted with other online learners including undergraduate, doctoral, and different master’s degree learners, persistent and non-persistent. Longitudinal case studies could provide an understanding of persistence viewed over time and permit exploration of the persistence issue at multiple points, particularly at high-stress times. This could yield information related to the persistence decision-making process.
Q1. Tell me about how you/how students have persisted in the online learning environment (OLE).
Q2. What are the critical behaviors, attitudes, and skills that learners need to successfully complete an online master’s degree program?
Q3. Do you view persistence as related to completion of each course, to the program, to the achievement of the career or personal objective that prompted your enrollment, or in some other way? Tell me about that.
Q4. What personal attributes foster persistence in the OLE?
Q5. What characteristics of the online classroom and program foster persistence in the OLE?
Q6. What characteristics of the faculty or staff foster persistence in the OLE?
Q7. Can you think of any obstacles that you encountered that hindered your persistence/students’ persistence during this online master’s degree program? How did you/students overcome them?
Q8. How do factors inherent to the program (such as policies, assignments, etc.) and factors outside of the program (life events, work or parenting responsibilities) interact to affect persistence? Tell me about that.
Q9. Do you have anything to add related to persistence in online learning environment?
Allen, I. E., & Seaman, J. (2015). Grade level: Tracking online education in the United States. Retrieved from http://onlinelearningconsortium.org/read/survey-reports/
Aversa, E., & MacCall, S. (2013). Profiles in retention part 1: Design characteristics of a graduate synchronous online program. Journal of Education for Library and Information Science, 54(2), 147-161.
Baxter, J. (2012). Who am I and what keeps me going? Profiling the distance-learning student in higher education. International Review of Research in Open and Distance Learning, 13(4), 107-129.
Beaudoin, M. F., Kurtz, G., & Eden, S. (2009). Experiences and opinions of e-learners: What works, what are the challenges, and what competencies ensure successful online learning. Interdisciplinary Journal of E-Learning and Learning Objects, 5, 275-289.
Bekele, T. A. (2010). Motivation and satisfaction in Internet-supported learning environments: A review. Educational Technology, 13(2), 116-127.
Bonnel, W., & Boehm, H. (2011). Improving feedback to students online: Teaching tips from experienced faculty. Journal of Continuing Education in Nursing, 42(11), 503-509.
Boston, W. E., Ice, P., & Burgess, M. (2012). Assessing student retention in online learning environments: A longitudinal study. Online Journal of Distance Learning Administration, 15(2). Retrieved from http://www.westga.edu/~distance/ojdla/summer152/boston_ice_burgess152.html
Boston, W. E., Ice, P., & Gibson, A. M. (2011). Comprehensive assessment of student retention in online learning environments. Online Journal of Distance Learning Administration, 14(1). Retrieved from http://www.westga.edu/~distance/ojdla/spring141/boston_ice_gibson141.html
Bressler, L. A., Bressler, M. E., & Bressler, M. S. (2010). The role and relationship of hope, optimism, and goal setting in achieving academic success: A study of students enrolled in online accounting courses. Academy of Educational Leadership Journal, 14(4), 37-51.
Brito, M., & Rush, S. (2013). Developing and implementing comprehensive student support services for online students. Journal of Asynchronous Learning Networks, 17(1), 29 - 42.
Carroll, D., Ng, E., & Birch, D. (2013). Strategies to improve retention of postgraduate business students in distance education courses: An Australian case. Turkish Online Journal of Distance Education, 14(1), 140-153.
Casey, R. L., & Kroth, M. (2013). Learning to develop presence online: Experienced faculty perspectives. Journal of Adult Education, 42(2), 104-110.
Cochran, J. D., Campbell, S. M., Baker, H. M., & Leeds, E. M. (2014). The role of student characteristics in predicting retention in online courses. Research in Higher Education, 55, 1-22. doi: 10.1007/s11162-013-9305-8
Cockrell, C. N., & Shelley, K. (2011). The relationship between academic support systems and intended persistence in doctoral education. Journal of College Student Retention, 12(4), 469-484. doi:10.2190/CS.12.4e
Conceicao, S., & Lehman, R. (2012). Persistence model for online student retention. In Jan Herrington et al. (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia, and Telecommunications 2013 (pp. 1913-1922).
Crawley, A., & Fetzner, M. (2013). Providing service innovations to students inside and outside of the online classroom: Focusing on student success. Journal of Asynchronous Learning Networks, 17(1), 7-12.
Deimann, M., & Bastiaens, T. (2010). The role of volition in distance education: An exploration of its capacities. International Review of Research in Open and Distance Learning, 11(1), 1-16.
DeLottell, P. J., Milliam, L. A., & Reinhart, M. M. (2010). The use of deep learning strategies in online business courses to impact student retention. American Journal of Business Education, 3(12), 49-55.
Fetzner, M. (2013). What do unsuccessful online students want us to know? Journal of Asynchronous Learning Networks, 17(1), 13-27.
Gannon-Cook, R., & Sutton, R. (2013). More hard lessons learned in online student retention. In R. McBride & M. Searsons (Eds.), Proceedings of Society for Information Technology and Teacher Education International Conference 2013 (pp. 2659-2673). Chesapeake, VA: AACC. Retrieved from http://www.editlib.org/p/48513
Garrison, D., Anderson T. & Archer, W (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2, 87–105.
Gaytan, J. (2013). Factors affecting student retention in online courses: Overcoming this critical problem. Career and Technical Education Research, 38(2), 147-155. doi:10.5328/cter38.2.147
Gomez, D. (2013). Leadership behavior and its impact on student success and retention in online graduate education. Academy of Educational Leadership Journal, 17(2), 13-37.
Gravel, C. A. (2012). Student-advisor interaction in undergraduate online degree programs: A factor in student retention. NACADA Journal, 32(2), 56-67.
Hachey, A. C., Wladis, C. W., & Conway, K. M. (2012). Is the second time the charm?
Investigating trends in online re-enrollment, retention, and success. Journal of Educators Online, 9(1), 1-25.
Hart, C. (2012). Factors associated with student persistence in an online program of study: A review of the literature. Journal of Interactive Online Learning, 11(1), 19-42.
Hart, C. (2014). Development of a persistence scale for online education in nursing. Nursing Education Perspectives, 35(3), 150-156. doi:10.5480/12-993-1
Haydarov, R., Moxley, V., & Anderson, D. (2013). Counting chickens before they are hatched: An examination of student retention, graduation, attrition, and dropout measurement validity in an online master’s environment. Journal of College Student Retention, 14(4), 429-449. doi:10.2190/CS.14.4.a
He, Y. (2014). Universal design for learning in an online teacher education course: Enhancing learners’ confidence to teach online. MERLOT Journal of Online Learning and Teaching, 10(2), 283-298.
Heyman, E. (2010). Overcoming student retention issues in higher education online programs. Online Journal of Distance Learning Administration, 13(4). Retrieved from http://www.westga.edu/~distance/ojdla/winter134/heyman134.html
Hubbard, R. S. (2013). How to improve student success and retention in online education programs. World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education, 2013(1), 784-793.
Ice, P. (2012). Assessing student retention and progression: A multi-modal approach. Proceedings of eLearning and Software for Education, 2, 170-176. doi:10.5682/2066-026X-12-119.
Jackson, V. (2012). The use of a social networking site with pre-enrolled Business School students to enhance their first year experience at university, and in doing so, improve retention. Widening Participation and Lifelong Learning, 14, 25-41.
James, S., Swan, K., & Daston, C. (2016). Retention, progression, and the taking of online courses. Online Learning, 20(2). Retrieved from http://onlinelearningconsortium.org/
Jones, K. R. (2013). Developing and implementing a mandatory online student orientation. Journal of Asynchronous Learning Networks, 17(1), 43-45.
Lee, Y., & Choi, J. (2011). A review of online course dropout research: Implications for practice and future research. Education Technology Research and Development, 59, 593-618. doi:10.1007/s11423-010-9177-y
Lee, Y., & Choi, J. (2013). A structural equation model of predictors of online learning retention. Internet and Higher Education, 16, 36-42. doi:10.1016/j.heduc.2012.01.005
Lee, Y., Choi, J., & Kim, T. (2013). Discriminating factors between completers of and dropouts from online learning courses. British Journal of Educational Technology, 44(2), 328-337. doi:10.1111/j.1467-8535.2012.01306.x
Leeds, E., Campbell, S., Baker, H., Ali, R., Brawley, D., & Crisp, J. (2013). The impact of student retention strategies. International Journal of Management in Education, 7(1/2), 23-43.
Lint, A. H. (2013). E-learning student perceptions on scholarly persistence in the 21st century with social media in higher education. Creative Education, 4(11), 718-725. doi:10.423/ce2013.411102
Mayes, R., Ku, H. Y., Akarasriworm, C., Luebeck, J., & Korkmaz, O. (2011). Themes and strategies for transformative online instruction: A review of literature and practice. Quarterly Review of Distance Education, 12(3), 151-166.
Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115, 1-47.
Michinov, N., Brunot, S., le Bohec, O., Juhel, J. & Delaval, M. (2011). Procrastination, participation, and performance in online learning environments. Computers & Education, 56, 243-252. doi: 10.1016/j.compedu.2010.07.025
Newberry, R., & DeLuca, C. (2014). Building a foundation for success through student services for online learners. Journal for Asynchronous Learning Networks, 17(4), 25-39.
Park, C. L., Perry, B., & Edwards, M. (2011). Minimizing attrition: Strategies for assisting students who are at risk of withdrawal. Innovations in Education and Teaching International, 48(1), 37-47. doi: 10.1080/14703297.2010.543769
Pittenger, A., & Doering, A. (2010). Influence of motivational design on completion rates in online self-study pharmacy-content courses. Distance Education, 31(3), 275-293. doi:10.1080/01587919.2010.513953
Poll, K., Widen, J., & Weller, S. (2014). Six instructional best practices for online engagement and retention. Journal of Online Doctoral Education, 1(1), 56-72.
Rajesh, M. (2011). Student retention in an era of globalization: A case study of IGNOU regional center, Mumbai. Turkish Online Journal of Distance Education, 12(2), 128-139.
Roby, T., Ashe, S., Singh, N., & Clark, C. (2013). Shaping the online experience: How administrators can influence student and instructor perceptions through policy and practice. Internet and Higher Education, 17, 29-37.doi:10.1016/j.iheduc.2012.09.004
Rovai, A. P., & Downey, J. R. (2010). Why some distance education programs fail while others succeed in a global environment. Internet and Higher Education, 13, 141-147. doi:10.1016/j.iheduc.2009.07.001
Russo-Gleicher, R. J. (2013). Qualitative insights into faculty use of student support services with online students at risk: Implications for student retention. Journal of Educators Online, 10(1), 58-90. Retrieved from: http://www.thejeo.com/Archives/Volume10Number1/RussoGleicher.pdf
Shachar, M., & Neumann, Y. (2010). Twenty years of research on academic performance differences between traditional and distance learning: Summative meta-analysis and trend examination. MERLOT Journal of Online Learning and Teaching, 6(2), 318-334. Retrieved from http://jolt.merlot.org/vol6no2/shachar_0610.pdf
Stevenson, T. (2013). Online student persistence: What matters is outside the classroom. Journal of Applied Learning Technology, 3(1), 21-25.
Street, H. (2010). Factors influencing a learner’s decision to drop out or persist in higher education distance learning. Online Journal of Distance Learning Administration, 13(4), 1-5.
Sullivan, E. B., & Pagano, R. V. (2012). Relevant adult programs, resilient students, and retention-driven administration. New Directions for Higher Education, 159, 21-29. doi:10.1002/he.20023
Truell, A. D., Alexander, M., Zhao, J., & Davis, R. (2013). Online courses: Prospective student structure preferences and perceived skills needed/possessed. Issues in Information Systems, 14(1), 415-420.
Waldner, L., McDaniel, D., & Widener, M. (2011). E-advising excellence: The new frontier in faculty advising. MERLOT Journal of Online Learning and Teaching, 7(4), 551-561.
Wilson, D., & Allen, D. (2011). Success rate of online versus traditional college students. Research in Higher Education Journal, 14, 1-9.