Retention of Women in Online Education: An Exploratory Study of Factors That Aid in Retention in an Accelerated, Online, Teacher Education Program

Research has explored retention from many perspectives, and several theoretical models have sought to explain the characteristics of adult learners and how they may relate to retention. Aljohani (2016) discussed Tinto’s groundbreaking institutional departure model (1975), explaining that it is one of the most cited retention models and has been revised and tested multiple times. This model helped indicate the role that the institution can play in student retention (Meyer, Bruwelheide, & Poulin, 2009), but it focused on traditional students. Roberts (2012) highlighted Tinto’s revised model (1993) that claims academic and social integration improves retention and that integration occurs through positive experiences.

According to Alijohani (2016), Bean and Metzner’s (1985) model focused on nontraditional, commuting students, and while prior models focused on the importance of social integration, the researchers found that nontraditional students appeared to be influenced more by environmental factors or factors involving responsibilities outside of the institution. Meyer et al. (2009) pointed to how this finding differs from Tinto’s model by showing that social interaction has less of an influence on nontraditional students than with traditional students.

In their review of empirical articles focusing on student dropout in online courses, Lee and Choi (2011) found psychological attributes to consist of 20%of the listed factors that were found to influence the decision of online students to drop out of a program. Research indicated that the addition of psychological factors to models helping explain retention is critical. Roberts (2012) explains that Bean and Eaton’s (2000) model builds on Tinto’s work by adding an essential component—student psychological factors, and shifts to a focus on retention instead of withdrawal. The lack of models and frameworks for adult learners who study online is apparent, but it is possible that with continuing research, new components can be added to these existing models, or can help create new ones.

Adults learn differently than children. This concept is a driving factor in andragogy, an educational framework which points to unique learner characteristics and needs in education and can be summarized by stating that adult learners (a) are internally motivated, (b) want to learn directly applicable content, and (c) come to learning with the knowledge and experiences they have already gained (Miller, 2017). These guiding assumptions point to specific characteristics of adult learners that institutions must be aware of to create supports and design programs and courses that allow for greater success.

The framework of andragogy points to the difference in characteristics between adult learners and children. While not all adults learn in the same way, research does show several characteristics that can generally be applied to adult learners. Adults typically enter programs voluntarily, have multiple responsibilities, and “are autonomous, independent, and self-reliant, and they are self-directed toward goals” (Cercone, 2008, p. 143). Ross-Gordon (2011) stated that adult learners need flexibility and structure, prefer active learning that can immediately be applied, and appreciate being able to self-direct. The need for flexibility appeared several times in the research regarding instructors being flexible (Mupinga, Nora, & Yaw, 2006), and the need for flexibility in scheduling (Müller, 2008; Walsh, Abi-Nader, & Poutiatine, 2005).

The need to have authentic, readily applicable instruction also appeared in the literature. Genco (2007) found that adult learners required real-world learning and that they are time conscious. While correlation was not established, these characteristics may be related. Walsh et al.’s (2005) research showed that adult learners wanted course information to be practical and directly applicable to their profession. Providing a clear understanding of how all the knowledge learned fits together was also cited for increasing retention in a study exploring the applicability of Tinto’s institutional action model to students in accelerated programs who were employed full-time and had children (Lo, Reeves, Jenkins, & Parkman, 2016).

Several other characteristics were identified, including the desire to receive course information in advance and having completed sample assignments provided (Mupinga et al., 2006), and wanting frequent feedback from instructors (Lo et al., 2016). Clear and frequent communication with instructors is vital to adult learners (Mupinga et al., 2006), and communication with peers also seems essential because adult learners prefer the cohort model where they can go through classes together with the same peers (Lo et al., 2016; Walsh et al., 2005). These results are consistent with Cercone’s (2008) findings in a review of adult learning theories of the need for adult learners to have communication and interaction with peers.

Female-Specific Findings.Chyung (2007) sought to determine how age and gender played a role in self-efficacy, online posting, and academic performance of adult learners. Self-efficacy is important, especially in accelerated online programs where much of the learning is independent. Chyung (2007) found that women and younger students (22–39 years old) started a specific course with lower selfefficacy than other demographic groups; however, they were able to improve in self-efficacy to the point that they scored higher than other groups at the end of the study. Women also scored significantly higher in academic performance than men. The study was not able to conclude causation or even correlation, but the researcher suggested that the data may imply that different demographic groups may need specific forms of instruction.

The combination of age and gender was found to play a role in several factors. Justice and Dornan (2001) concluded that older women (at least 24 years old) had more intrinsic motivation than other demographics and that while there was not a significant difference in performance due to age or gender, older students were less confident in their ability to succeed. Müller (2008) asserted that being motivated and engaged, and appreciating the convenience of the online format increased persistence. Most importantly, she found that these factors were able to outweigh barriers when looking at persistence.

In one of the most extensive quantitative studies of undergraduate, online studies examined in this review, Cochran et al. (2014) found there to be no support for the hypothesis that age played a significant role in withdrawal with comparing older and younger students of the same gender, or when comparing similarly aged participants of the opposite genders. Markle’s (2015) study also showed no significant difference in persistence relating to gender, but found women to have a higher degree of persistence if they only attended part time, and the closer they got to graduation, the more women considered withdrawing. Contradicting conclusions showed that being female was a characteristic that led to the most significant risk of dropping out (Stoessel et al., 2015). The lowest risk was applied to older students and those who were parents, although there were no data to show the risk of attrition for older female students who are parents. Stoessel et al. (2015) also found that when compared to men, women attributed dissatisfaction with the program and an insufficient amount of social support as significant reasons for dropping out. Aljohani (2016) found evidence that gender can also play a role in attrition and satisfaction and reported that a difference between the genders regarding satisfaction is that men are more likely than women to leave a program if they still claimed to be satisfied.

Lee and Choi (2011) reviewed data from 10 years of research studies on retention in online programs and suggested three categories of factors that may play a significant role in the retention of adult online students: (a) student factors, (b) course/program factors, and (c) environmental factors. Student factors include factors such as academic background, skills, and psychological attributes like motivation and satisfaction. Course/program factors include factors such as institutional supports, interaction, and orientation, and environmental factors include factors such as work commitments and support systems.

Satisfaction. Satisfaction was found to be a potential indicator of student retention (Herbert, 2006). Using the Priorities Survey for Online Learners created by Ruffalo Noel Levitz (RNL), Herbert (2006) sought to determine factors that were significant for retention for students who had taken at least one online course. He found that satisfaction with their online experience was linked to student retention. Weber and Farmer (2012) also found a connection between retention and satisfaction and reported that students indicated satisfaction in course delivery to be a key reason for their decision to return (as cited in Bawa, 2016).

Schreiner (2009) agreed that satisfaction could be linked to retention, but asserted that even with a common belief that the two are connected, empirical research linking them was lacking. In her quantitative study using RNL’s Student Satisfaction Inventory, Schreiner found that one of the most predictive indicators of student retention in a student’s first year was their global (overall) satisfaction rating. However, she found that the linkage between satisfaction and retention did diminish over subsequent years.

Park and Choi (2009) indicated that the perception of student satisfaction was significantly related to retention and that retention improved as the rate of the level of student satisfaction increased. Lee and Choi (2011) concluded that satisfaction, along with selfmotivation, self-efficacy, computer skills, and an internal locus of control, were all contributing factors in retention in online courses. Giancola et al. (2009) reported that the perception of work, school, and personal stressors were related to well-being and satisfaction and that adults who viewed stressors as something that could be overcome used adaptive instead of maladaptive coping strategies more frequently.

Program and institutional design can significantly impact the experience of adult learners. These experiences then help to drive persistence and retention, making it a critical component for institutions to consider. In calling for institutions to consider the unique needs of adult learners, and especially those of women, O'Shea and Stone (2011) stated: “Higher education means much more to these students [women] than simply improved vocational opportunities. An understanding of this at an institutional level may encourage a more flexible approach by academics and administrators” (p. 14). This flexible approach may help improve retention with women in higher education.

Accelerated Learning Model. Accelerated learning programs shorten the length of time students spend in each class. In a traditional model—both on-campus and online courses— would typically last a full semester or close to 16 weeks, but in an accelerated model, courses may take as little as 4 weeks to complete. In his review of the literature on accelerated learning, Richards (2008) explained that there is an appreciation for the accelerated model because it allows students to focus on one class at a time instead of several courses simultaneously. Studies comparing the effectiveness of accelerated learning to the traditional schedule found no difference in effectiveness and found that outcomes or achievement rates are sometimes better in accelerated learning than in the traditional format (Richards, 2008; Tatum, 2010). There is a higher level of student satisfaction with the faster paced schedule (Tatum, 2010), and time and convenience are factors in the selection of this model, which adults evaluate as positive (Richards, 2008). These findings are consistent with the characteristics of adult learners and their desire for timely instruction that is focused only on real-world knowledge.

Orientation Program. Throughout the research, it was suggested that an orientation program would be beneficial for adult learners (Lo et al., 2016; Miller, 2017). Bawa (2016) reported that orientation programs could help students be aware of the expectations and demands of online programs, helping them to more realistically view the skills and time needed, which can improve retention. She cautioned that students might feel the orientation unnecessary due to possible misconceptions about their skills. The Dunning-Kruger effect offers insight into why students overestimate their abilities and feel that orientation programs are unnecessary (Dunning, 2011). In describing a model based on the Zinn’s Philosophy of Adult Education Inventory and Knowles’ andragogy approach, Miller (2107) found that a student orientation program before starting online courses should outline the differences in a traditional and an accelerated program format, should state the expectations and responsibilities of the students and the faculty, and should allow students access to support services.

Instructor Interaction. Instructors have a responsibility to meet the needs of adult learners and assist them in being successful, which can require differences in course design and interactions from traditional students. Course design and structure were found to be related to student success as well as instructor behavior (Gray & DiLoreto, 2016; Wake & Bunn, 2015). Instructor presence was found to impact student satisfaction and perceived student learning (Gray & DiLoreto, 2016), and learner-instructor interaction was found to be connected to student satisfaction (Kuo, Walker, Belland, & Schroder, 2014). Müller (2008) reported that meaningful interactions were important to persistence, and disappointment in faculty caused a low satisfaction level. This interaction should come in part through regular communication and feedback (Mupinga et al., 2006).

Several studies indicated different ways that instructors could promote student success in their interactions. Wake and Bunn (2015)suggested that instructors provide clear expectations and model professional communication for students. Lo et al. (2016) agreed that providing students with information about course expectations is valuable, and that adult learners desire to be held to high expectations, but that those expectations need to be reasonable and instructors need to be fair. Course communication should be planned for, thought out, and express the policies and expectations for the course (Serdyukov & Sistek-Chandler, 2015).

Vann (2017) found that empathy was critical to determining challenges that adult learners may have in courses and in effective course design. Additionally, Vann (2017) asserted that instructional designers needed to understand the characteristics of students, create relevancy in the course, and have an understanding that online courses have to be different from traditional courses. Being empathetic to the needs of students and attempting to help them mitigate issues helps to affirm students and recognizes their worth. Edwards, Perry, and Janzen (2011) found that exemplary online instructors were not only influential, but also challenged and supported students. Challenging students to go beyond their expectations and holding them to high standards were identified as positive attributes for online instructors. Showing respect was vital.

Several common themes appeared regarding barriers to adult learner success. In a study exploring persistence in an online program, researchers found that individual characteristics such as age and gender did not play a significant role in retention, but showed that factors such as family support and organizational support did (Park & Choi, 2009). Stone and O’Shea (2013) discussed the barriers of financial concerns, prioritizing, finding time to accomplish everything, and changes in relationships as significant in adult learners. Their focus was to explore the influence of gender on experiences of managing home and school life, and they stated, “All the participants had faced substantial challenges in combining their new lives as students with their existing responsibilities as parents, partners, and employees. Meeting these challenges required considerable personal and financial sacrifice” (Stone & O’Shea, 2013, p. 99).

Interrole Conflict. Interrole responsibilities, having multiple responsibilities outside of being a student, play a significant role in women’s persistence in higher education. Markle (2015) discovered that interrole conflict was a contributor to women considering withdrawing because of their fear that they would be unsuccessful in all roles. Both Markle (2015) and Giancola et al. (2009) found work and family conflicts to be the most significant stressors for adult learners. Markle (2015) discovered that participants experienced interrole conflict at varying levels with a majority experiencing at least a moderate level of conflict and 43%experiencing at least a high level of conflict. The most frequent interrole conflict was between work and school, followed by conflict between school and family. Giancola et al.’s (2009) results differed slightly, suggesting that school-family conflict was the highest interrole stressor.

Meyer et al. (2009) referenced a work by Willging and Johnson (2004) that found online students and traditional students had similar reasons for dropping out, and that most of those reasons were related to personal issues such as family concerns or changes in employment. They concluded that the online program itself was often not a primary reason for withdrawing, pointing to the crucial need for institutions to understand the personal barriers that adult students face.

Stone and O’Shea (2013) explored gender and how it related to school responsibilities and home-life responsibilities. They found that gender expectations impacted responsibilities and time commitments. Stone and O’Shea (2013) suggested,

Online learning is growing in popularity among adult learners as a result of offering a more flexible schedule than traditional oncampus programs. Accelerated learning is becoming more prevalent as well, allowing programs to shorten completion time, creating a significant draw for adult learners. With research showing accelerated programs are equivalent to traditional programs in student outcomes, this type of programming will likely become more popular. With more and more adult learners in these courses, instructors must be aware of the unique characteristics, potential barriers to success, and needs of adult learners to tailor the program, courses, and instructional components to promote success and retention.

More research is needed about accelerated programs and the successes and barriers to the retention of women in those programs. Research does point to the need to tailor the educational experience to help adult learners thrive, so more specific data is needed to determine the unique needs of this population. The purpose of this study is to examine factors that aid in the retention of women in an online, accelerated teacher education program.

The study used case study methodology which allowed for the mixed methods collection of quantitative data with a larger sample size that sought to determine factors that aid in retention, and then a collection of qualitative data with a smaller sample size that allowed for an in-depth study in how the factors aided in retention. According to Yin (2009), the case study method allows for an in-depth study of a complex phenomenon. The mixed methods format for data collection allowed for “a richer and stronger array of evidence than can be accomplished by any single method alone” (Yin, 2009, p. 63). In this exploratory case study, the phenomenon of retention, within the bounds of gender and a particular accelerated, online teacher education program, was explored.

The participants for the case study included current students and recent graduates of a small, private, Christian university in the southeastern region of the United States who were in an online, accelerated teacher education program. Being an instructor in this program for over 6 years, and working with most of the students near the beginning of the program and then a few students at the end of the program, allowed me to observe differences in enrollment between the beginning courses and final courses. For instance, in spring 2019, there were 28 registered students in my online course that occurs near the beginning of the program, but only 10 students in the final course. The participants for this study were in their final or penultimate semester, signifying completion, or near completion of their program, and none were directly under my supervision at the time of participation. Participants were women who were at least 24 years old, and a total of 19 students met this criterion.

The study occurred between May and October 2019. After electronically receiving informed consent by means of a document sent to all potential participants, the eight willing to participate were emailed a link to the Priorities Survey for Online Learners from RNL, the creators and administrators of the questionnaire. The consent document was emailed three times to both classes of students, and the researcher also spoke virtually with both groups. The professor of both courses and others in the program also reached out to students to inform them about the study and seek interest in participating. Follow-up emails were sent through RNL to any student not completing the initial questionnaire, and the researcher sent emails to those who had agreed to participate, but had not yet completed the questionnaire near the deadline for participation. The deadline was extended for one participant who agreed to take the survey, but then selected not to participate.

Questionnaire. The use of a questionnaire was to explore a broad range of factors with retention, but also to help corroborate interview data. According to Yin (2009), using additional sources to help with the corroboration of interview data is a “reasonable approach” (p. 109). The questionnaire measured online student satisfaction with academic, enrollment, instructional, and student services as well as institutional perceptions on a 7-point Likert scale. Questions such as, “Faculty provide timely feedback about student progress” and “Student-to-student collaborations are valuable to me” were included on the Priorities Survey for Online Learners for participants to rate on importance and satisfaction (RNL, 2019). Additionally, there were five questions included in the questionnaire piloted by the researcher. These questions followed the same format and rating scale as the standard questions provided by RNL, but focused on participants’ perceptions of an accelerated teacher education program.

RNL compiled data from the seven participants who completed the survey and provided it to the researcher, along with limited demographic information. The demographic information provided was not needed for the scope of this study. Data were compiled as an aggregate report per contractual agreement with the researcher to ensure no identifying information such as names or IP addresses were shared per terms of the informed consent document.

Interviews. Additionally, the researcher conducted private interviews to take a deeper dive into factors that aid in retention. Yin (2009) explained the importance of interviews in the case study methodology because they are “targeted” and “insightful” (p. 102) and can provide valuable information. Participants consenting to interviews scheduled times with the researcher via email, and the researcher sent follow-up emails to a participant who agreed to participate, but did not attend the interview. Interviews consisted of open-ended questions to allow for dialogue and exploration into retention factors and allowed participants to tell their story and explain factors that helped them continue in the program instead of responding to predetermined factors as they did on the survey. The three interviews, each lasting between 16–20 minutes, occurred over several weeks. The interviews were conducted through online meeting software (Zoom) and were recorded to be transcribed and then coded to be analyzed for emerging themes.

The Priorities Survey for Online Learners data presented a listing of factors with the mean importance score, mean satisfaction score, the gap score between each factor’s rating of importance and rating of satisfaction, and the standard deviation in the satisfaction scores. Participants could complete an open-ended question asking them to provide comments for the institution (in this case, researcher). Participants were allowed up to 2048 characters for this response.

Coding. The researcher transcribed each interview by using the recorded interview data and then sent the transcription to the participant to check for correctness and be approved. This helped monitor for clarity and validity through the triangulation of the data (Yin, 2009). After receiving approval from interview participants, the transcriptions were read multiple times. Using Creswell’s (2013) steps of qualitative analysis, memoing was done after the initial read-throughs. After another round of watching/listening to the recorded sessions with additional memoing, first cycle analysis using descriptive coding—summarizing a topic (Saldaña, 2016) and in vivo coding—a word or phrase from the transcriptions (Saldaña, 2016) was completed on both the transcribed interview data and the data from the questionnaire. Revisions, deletions, and merging of codes were completed during each round. For the second cycle analysis, focused coding was used to create categories which were then color coded. Adjustments were made during subsequent reviews of the transcripts using focused coding, and through Saldaña’s (2016) steps of synthesis and transition from codes toward “consolidated meaning,” (p. 10) distinct themes began to emerge. The statistical data were compared with the codes and then the emerged themes to search for commonalities and disagreements.

Several themes emerged from the data that demonstrate a range of factors that may aid in retention. The most prominent themes include: (a) instructor factors, (b) outside (nonprofessor) interpersonal factors, (c) student factors, and (d) course/program factors. To ensure confidentiality, all references to specific interview participants are pseudonyms.

The most prominent theme appearing throughout all data sources focused on interpersonal relationships between the instructor and student. The role of instructor included both professors and supervisors in this context. Each woman interviewed credited instructors as being a key factor in her decision to remain in the program. In explaining what universitybased factors she credited with helping her retain, Emma stated:

Participants shared that instructors were “motivating,” “helpful,” encouraging, and that they “truly care.” Like Emma, Joan shared that instructors were her most important university factor when she explained that she felt “like that we could, um, come to them with whatever. I mean ... whether it be something academic or whether it be a prayer request, or, I mean, you know, just anything.” As a part of the confidential online survey, one participant wrote, “The professors truly care about you and want you to pass in the [program name redacted] program. They are understanding that you have a life outside of school and they were very accommodating when needed.”

Survey data also indicated that participants felt that interactions with instructors were important and that they were satisfied with the interactions they had had. All participants felt that the faculty were responsive to their needs. As a group, participants felt like the frequency of the interactions was not as important as the responsiveness of instructors, and they were also less satisfied with the frequency of interactions compared with responsiveness.

In speaking of interactions at the institution, Elise brought up a specific instructor who demonstrated responsiveness to her needs. She explained, “I mean, I had one instructor that was, she was good to have because she pushed you, and that’s what I think I needed.”Elise went on to speak of the importance of instructors being aware of the needs of future students so they can provide extra accountability for students who need more structure to remain in the program. She stated that the communication for accountability “needs to be personal for them,” further demonstrating the importance of both interaction and instructor responsiveness.

When analyzing the data about instructor factors, the two common subthemes of communication and support consistently emerged. As the participants described their experiences and factors for staying in the program, they each kept coming back to interactions that demonstrated communication between themselves and instructors or others and instructors, and the idea of instructors being supportive to students. When describing the communication from instructors, participants often commented on the instructors’ willingness to answer questions, including staying online after the regular synchronous sessions to ensure students could get their questions answered.

While positive communication was found to be a factor in retention, unsatisfactory communication was pointed to as a reason for withdrawal. Inconsistency and lack of clarity were mentioned as examples of poor communication. When asked about what might help future students retain, Emma shared about the importance of instructors communicating and being upfront with course expectations and scheduling. She explained:

Survey data also highlighted participants’ views on the importance of consistency and clarity from the instructor. Both shown assessment questions pointed to the need for upfront communication of expectations, and the percentage importance scores suggest that all participants viewed this as being “important” or “very important,” but that not all participants were satisfied with the upfront communication of student assignments in the syllabus. This dissatisfaction was reflected in the interviews from Emma:

Both Emma and Elise spoke positively about instructors who communicate expectations clearly in the syllabus as a factor in retention.

Instructors were also discussed as being supportive. When asked about the most significant factor in her retention in the program, Joan stated that it was professors. She followed with a description of the support that instructors provide:

Elise also described how important instructor support was in her decision to retain in the program.

It was through forms of positive communication that this support was often demonstrated. Elise finished the previous explanation with, “it was just, their very communication ... being able to have those conversations with your professors was a strong point to stay with [institution name redacted].”

Other relationships appeared in the data to also influence the participants and their decision to remain in the program outside of interactions with instructors. Both Emma and Joan discussed having positive interactions with the dean of the university’s online programs. Both explained that he had helped them from the beginning, showing a positive relationship from some of the earliest encounters with the program.

As with interactions they described with their instructors, Emma and Joan highlighted the importance of communication and support in this relationship as well. Joan elaborated by saying:

Both felt that the connection they had with the dean was helpful and credited him with that experience occurring from the start of the program.

Two survey questions indicated the importance of the program advisor in providing communication and support. Both scored the highest possible rating for importance, but both had a standard deviation of over one and were flagged as an area of challenge by RNL, indicating the desire for this type of supportive interaction and assistance, but the feeling that it may not have always been satisfactory. Interview data did not substantiate this as no participants mentioned their advisor, and the only survey participant to mention them declared them to be “great.”

Outside of instructors and the dean of the online program, only one participant discussed another person or group with whom they had interactions with at the university that they felt helped in their choice to continue in the program. Emma shared that positive interactions with peers was helpful, but stated that the interaction had occurred within the last year, signifying that it was not a significant factor throughout the program. Joan and Elise both denied that peer interactions were helpful in their retention. Elise explained that she had a peer that she “related” to because they both had children, but said that she did not think she really had any peer interactions. When asked if she felt that more peer interaction would be a benefit, Elise told of where else she found positive interactions:

Survey data presented an interesting look into participants’ views on peer interactions. Only 83%of participants indicated that peer-to-peer collaboration was at least “important” to them, the second-lowest score on factors measured for both importance and satisfaction. This factor also scored the lowest satisfaction score of the entire survey. This seems to corroborate the interview data that shows a lack of importance for peer interaction in retention.

Participants used different words to describe the internal motivation that they felt propelled them to completion of the program. Words such as “goal oriented,” “passion,” and “driven” were used to describe personal factors that helped in retention. Throughout the interviews, it was apparent that a large reason for the push to succeed was not only completion of the program and retention of a teaching position after graduation, but also to satisfy deep internal desires.

Both Emma and Elise discussed the importance of being a role model for their children as being a key motivating factor. Elise said that her children were the most important environmental factor—according to Lee and Choi’s (2011) definition— in her retention.

Interrole balance appeared in each interview and in the open-ended question of the survey. While not specifically spoken of as being a factor in their retention, participants did discuss taking time off in prior school attempts due to family responsibilities, working while attending classes, and having family responsibilities while in their current program. Participants shared of having to balance their multiple roles and the difficulty that could bring, but also of how they were able to remain in the program despite interrole conflicts. Emma expressed, “The course load and being a parent on top of that, and just all the responsibilities of it ... was just taxing at times and it was very tempting to just not do it.” A survey participant shared, “I worked throughout my time at [institution name redacted]. I also have a 5-year-old child and am a single parent, so I didn't have the luxury of having someone else to help with my child.” She went on to explain that the program helped her be able to work and be with her child. Participants’ ability to balance their multiple roles assisted in their retention.

A factor in retention that was discussed positively in each data source was the flexibility of the program design. The online, accelerated model allowed for student flexibility in the completion of work. Emma appreciated that she was able to access assignments from home and even while at the beach. Joan explained that the program flexibility was part of what drew her to the program because of her ability to work at the times she needed, and Emma agreed because of her ability to do what she needed in the program even late at night after work and taking care of children. One survey participant wrote:

The synchronous sessions required by the program were brought up by Joan as an example of when the program was not flexible and Emma expressed that the sessions were not helpful, but then mentioned how instructors’ communication was helpful during and after the sessions. There were no comments directly connecting the view of the inflexibility of the synchronous sessions with retention issues, and frustration expressed regarding these sessions surrounded issues of individual professors and their methods of instruction.

The accelerated nature of the program was addressed positively as it allowed participants to finish quickly. Both Emma and Elise expressed that getting into the workforce faster was a reason for being in an accelerated program, while Joan claimed that she did not take the accelerated nature of the program into consideration because she did not have any other frame of reference. To her, it was just “normal.”

Two piloted survey questions focusing on the accelerated nature of the program presented unique results. All participants found the accelerated program to be important to achieving their goal of graduation, and all participants were satisfied that it had. This item was the only one on the survey to have no deviation in any score indicating the importance that the accelerated nature of the program has had on participants. Scores for the convenience of the accelerated format showed a higher satisfaction score than importance score (only one of two in the study to do so), indicating that participants were more satisfied with the convenience of the accelerated nature of the program than they viewed it as being important.

This data corroborates the interview data showing the importance to retention that the flexibility and accelerated nature of the program bring to participants.

This study examined factors that aided in the retention of women in an accelerated, online teacher education program. The data suggests that multiple factors play an extensive role in retention, with the most prominent being, (a) instructor interactions, (b) student drive, (c) course/program flexibility, and (d) interpersonal relationships with others at the institution.

The data points to the importance of positive instructor interactions, especially interactions involving clear and supportive communication. Each woman interviewed claimed that instructors were a main factor in their retention. According to Lee and Choi (2011), instructor interactions fall under the course/program category factors aiding in student retention. Positive interaction with instructors has been found to improve student satisfaction (Gray & DiLoreto, 2016; Müller, 2008), which has been linked to retention (Bawa, 2016; Herbert, 2006; Lee & Choi, 2011; Park & Choi, 2009; Schreiner, 2009).

Communication appeared throughout the data as a part of instructor interactions that influenced student retention. While positive communication appeared in the data, especially regarding instructors’ willingness to answer questions, examples of negative communication appeared throughout the interview data as well. Inconsistencies and a lack of communication regarding course expectations and instructors not answering questions were given as reasons for leaving the program. This is consistent with Müller’s (2008) findings that disappointment in faculty can reduce satisfaction in students.

Supportive communication was also vital to retention. Data showed that instructors “pushing” students toward success, encouraging students, being open to listening to students about issues inside and outside of the classroom, and being accommodating to student needs were all viewed as positive and supported the importance of the instructor relationship. Meyer et al. (2009) stated that potentially, the characteristics of online programs entice students to enroll and remain in the program, but, in part, it was the relationships with faculty that help students retain. This study corroborates existing research and promotes the idea that positive instructor interaction promotes retention.

Student drive or motivation is another prime factor in retention. Data showed that the primary source of the motivation may differ between students, but that an internal push is a driving factor in retention. This motivation may come from a desire to be a role model to others, to work in a profession they love, or because of an inward drive to be successful. Self-motivation was found to help keep students retained (Lee & Choi, 2011; Meyer et al., 2009). This study helped to build on existing literature by pinpointing specific motivations that may help promote retention. By encouraging students to discover their motivations for being in the program and encouraging continued awareness of the motivation, program leaders and instructors can tap into a powerful force for retention. Internal motivation is a component of Lee and Choi’s (2011) student factor category.

A key element of Lee and Choi’s (2011) course/program category that appeared throughout the data is the factor of flexibility within the program. Müller (2008) found that appreciating the convenience of online scheduling was a factor that improved the possibility of persistence, enough so, that it outweighed potential barriers to persistence. This finding agrees with other research demonstrating the need for flexibility for adult learners. Participants agreed that flexibility in the program helped them to be able to accomplish their work because they were not tied down to a specific time and location. Kauffman (2015) states that flexibility is especially important for online learners because of the interrole responsibilities that many have, which is corroborated by the findings that showed a connection between the appreciation of flexibility and in this study, also having additional roles such as parent and employee.

A final prominent factor that emerged from the data was that of interactions with others at the university. These interactions would also fall under Lee and Choi’s (2011) description of course/program factors. Schreiner (2009) found there to be a connection between supportive and communicative advisors and retention. The survey data demonstrated that participants did view this as important, but that not all students were equally as satisfied with their experiences. There may have been a lack of clarity in the question because participants are likely to have had at least two advisors, with the most recent one being an instructor in the program and the former being a part of the online programs department. Interview data showed that participants viewed interactions with the dean of the online program to be positive and an important factor in their retention. Much like with instructors, they cited communication and support as being driving factors in the positive interaction.

Interestingly, and contrary to other research, peer interaction was not found to be a significant factor in retention. Studies such as Lo et al. (2016) and Walsh et al. (2005) found peer communication to be essential, while this exploratory study did not. Serdyukov and Sistek-Chandler (2015) presented data that suggested that a majority of students prefer independent work and are not interested in peer collaboration. This contradiction brings up an interesting question of context. When discussing other relationships, participants spoke of communication and support, or social qualities. The participant that did find some benefit with peer interaction focused more on the social supports that it provided, as opposed to academic supports, as seen through group work and peer collaboration in the classroom setting. The survey data indicated participants felt that peer interaction was somewhat important, but indicated they were less than satisfied with their experience. It is possible that when taking the survey, participants were looking more at peer collaboration in an academic way, while interview participants were focusing on it in a more social context because of how they spoke of other interactions. It is also possible that these participants were not satisfied with their peer interactions, so in turn, they did not view them as a factor in retention. This study expands the research on the implication of peer interaction and collaboration in retention and brings to the forefront the need for additional exploration.

More research is needed on peer-to-peer interactions in accelerated online programs. With contradicting research, it is not currently clear if peer interaction is a significant factor in retention. By focusing on certain programs or populations in a large-scale study, researchers may provide stronger data supporting or disproving the need for peer interactions for specific program types, age groups, genders, or learning styles. Defining terms and exploring interactions from a social and academic viewpoint is necessary.

Orientation programs appeared in the literature as an important factor in retention. Interestingly, this did not appear in the data. The participants were not involved in an orientation program as a component of their course of study, despite one occurring for others at the same university. Orientation programs were not shown to be a factor in retention for participants, nor did they suggest they may be a factor to help future students. The contradiction in data creates an opportunity for future study about the importance of, or lack of need for, orientation programs in accelerated, online teacher education programs.

Additional research is needed to explore retention at different stages across the program. This study explored only factors that helped retention for students near completion, but students at the beginning of the program may have different needs regarding factors that help with retention. A longitudinal study following students from enrollment until graduation would also be able to provide a more indepth examination of retention over time.

A limitation of this study is that participants may have felt uncomfortable discussing negative experiences with an instructor in the program. I was not an instructor or supervisor to any of the participants at the time of the study, but was still serving in those roles and had professional and familiar ties to others who were instructors and supervisors to participants. Participants may also have struggled to discuss aspects that may have led to their questioning continuing until graduation. A lack of transparency could have influenced the data. While having an interviewer whom participants know may improve their comfort level and openness, it may also hinder it. An impartial interviewer may elicit different responses.

Online education, especially with an accelerated format, is growing in popularity in large part to the flexibility it provides for students. The adult student population in higher education is also growing, and it is becoming vital that leadership looks at how nontraditional programs and nontraditional students are different from the long-established traditional programs. Retention is not only an issue for students who may delay graduation or not finish, but also for institutions both financially and in reputation. Exploring factors that aid in the retention of specific groupings of students can help institutions prepare for and support the growing body of nontraditional students.

A critical task of institutions to help retention is in their hiring and course assignment process. Both Miller (2017) and Müller (2008) suggested a focus on hiring online instructors who can meet the unique needs of adult learners. Instructors need to be aware of and capable of meeting the needs of adult, female learners through positive interactions, clear communication, and support. Additional support staff should also be aware of these needs and expectations. As evidenced in the research, positive interactions with others outside of the classroom setting proved to be a factor in retention.

Training is an important component for instructors in working with online learners (Gutman, 2012). Miller (2017) reported that faculty members should be trained on the needs of adult learners and on creating an effective environment for them. Training helps to teach the specific skills online instructors need to improve student success. A key element of training is that it does not have to be static. As additional research clarifies and expands the understanding of adult learners, especially that of women in online education, training can be modified and new practices adopted.