Overcoming Challenges in Online Learning: Retention Factors and Prime Persistence Practices 

Distance online learning for adult learners

Online learning continues to grow and evolve. In fact, in the fall of 2022, there were 18,580,026 adult learners participating in distance education (National Center for Education Statistics 2022). Adult learners find it desirable due to its variety, flexibility, and ease of access, yet despite its popularity, retention rates of online education are not comparable to traditional face-to-face learning institutions (Akers, Carter, and Coder 2021, p. 1). Three overall categories emerge as major contributing reasons for lack of online persistence: student factors, course or program factors, and environmental factors (Lee and Choi 2011, p. 593). As instructors, we are somewhat limited in influencing many factors that result in student dropout rates. For instance, we have little control over the backgrounds, psychological makeups, and skillsets students bring to our classroom. Likewise, we are often limited in adjusting curriculum outcomes, assessments, and methodology, as many online programs are subject to strict accreditation requirements; finally, we have little control over the pressures our students face regarding juggling their educational, personal, and professional obligations. We, however, are in more powerful positions to aid in student retention than we may realize. Pairing a problem negatively attributing to persistence with a high-impact teaching practice may offer ways to improve retention. 

Prioritization Problems and Time-management Solutions 

One factor resulting in lower persistence rates in online students involves the inability to prioritize and plan. In fact, in a study reporting reasons students withdrew from an online for-profit college, it was reported that the number one reason for their lack of persistence in courses was due to becoming too busy with work or family (Donovan and Sorenson 2017, 216). The challenges faced by many adult online learners, which so often include balancing full-time work or multiple jobs, children, ailing parents, and so many individualistic situations, are real. Likewise, the need to support students in this balancing act is every bit as real. A counterweight to the dysregulation faced by so many of our students is regulation, and research indicates that students who have strong self-regulation skills persist at higher rates in the online environment (Wandler and Imbriale 2017, p. 6). With the inability to balance school, work, and family accounting for so many withdrawals, the teaching of time-management skills emerges as an obvious way to support students in persistence. In fact, when directly taught, time management skills aided in retention and success rates (Gay and Betts 2020, p. 114). When it comes to capitalizing on time-management tools to promote, an emphasis on prioritization and organization are key, and the following tools provide sound options for students to consider when prioritizing and scheduling their workload.  Artful Agenda is a digital planner with a paper look to aid in deadline accountability. Asana is a comprehensive project manager meant to ease work flow. Google Calendar is a scheduling program to be shared amidst family members for ease of scheduling.  Pomofocus is an app supporting the use of the task completion using the Pomadora Technique. Time Timer is an app to heighten awareness of the passing of time and aid in transitions. All such apps present themselves as solutions to time-management problems too often contributing to online student withdrawal rates. 

Motivation Problems and Mental Contrasting Solutions 

While prioritization was the most prominent deterrent to persistence reported from one source, in another study published even more recently, lack of motivation was the number one reason accounting for withdrawal rates (Rahmani, Groot, and Rahmani 2024, p. 9). Motivation is an important factor in persisting in the online environment. To give emphasis to the important role motivation plays in retention, a student’s motivation directly correlates with their successful completion of each online course (Lee and Choi 2011, p. 608). Specifically, goal setting and problem-solving can be a way to help students stay motivated. One study tried to capture the results of generating self-motivation by setting up mental contrasting and implementation intentions (MCII). With this practice students examined the benefits and barriers to their goals and developed a plan for overcoming any obstacles. This practice was implemented in a study with two courses and the completion rates improved by 15% and 32% respectively (Kizilcec et al. 2020, p. 14901). Importantly, in order to produce higher completion rates, the results indicate that MCII should be used multiple times across a course of learning rather than as a one-off event at the onset of a course (Wong et al. 2021, p. 12). Below, I created an example of an MCII exercise to illustrate how it might be used each week. Since the practice helps students identify benefits and barriers while creating an action plan, a student is more vested in altruistic reasons for completing the task and prepared for obstacles that may arise, hopefully generating motivation and resulting in higher retention rates. 

 Mental Contrasting and Implementation Intentions Exercise 
Week 1 Objective  
Benefits  
Barriers  
Action Plan  

 A final key area instructors have control over is student persistence as it relates to support-related factors. Specifically, the absence of instructor presence has emerged as a significant reason for decreased persistence (Rahmani, Groot, and Rahmani 2024, p. 14). To address this factor, the practice of high-touch nudging emerges. Light-touch nudging includes email or text message reminders whereas high-touch nudging involves outreach with restrictive choices and includes interaction. With regard to nudging nuances, light-touch nudging has been found to influence one-time actions, whereas high-touch nudging practices show much greater promise for inspiring long-term changes in behavior while more greatly impacting retention (Azzolini et al. 2023, p. 303). In the world of online educators, this translates to nudging that invites action vs. nudging that invites action and interaction.  

Light-touch Nudging: Please post your Week 1 Summative Assessment as soon as possible. I hope to hear from you soon!  

High-touch Nudging: I noted your Week 1 Summative Assessment is missing. I would like to schedule a time to meet with you on Skype or talk on the phone about completing it. What time works for you? I hope to hear from you soon! 

The influence we wield as educators is not negligible; there are many ways we can elicit action and interactions from our students that can improve persistence and learning. While there will always be problems in education, in using high-impact practices we more powerfully position ourselves to provide solutions to aid students in their ability to fully chase down dreams of an education and turn them into reality. 


Amy Winger is an online instructor for the University of Phoenix and American InterContinental University. She holds a BA in English from the University of Iowa and an MEd in English Education from the University of Minnesota. For over 18 years, she has taught English and general education courses and enjoys pioneering the use of tech tools. Prior to that, she taught English at the secondary level. Her academic research primarily focuses on retention strategies, multimedia, and social media implementation in the online classroom. She is also a freelance fiction writer. 

References 

Akers, Richards, John Carter, and Dawn Coder. 2021. “Academic Advising at a Distance: Proactive Programming to Assist with Student Success.” Online Journal of Distance Learning Administration 24 (2): 1-10.  https://search.ebscohost.com/login.aspx?direct=true&AuthType=shib&db=eue&AN=151015807&site=eds-live&scope=site 

Kizilcec, René F., Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph Jay Williams, and Dustin Tingley. 2020. “Scaling up Behavioral Science Interventions in Online Education.” Proceedings of the National Academy of Sciences of the United States of America 117 (26): 14900–905. https://search.ebscohost.com/login.aspx 

Lee, Youngju, and Jaeho Choi. 2011. “A Review of Online Course Dropout Research: Implications for Practice and Future Research.” Educational Technology Research and Development 59 (5): 593. doi:10.1007/s11423-010-9177-y. 

National Center for Education Statistics. 2022. “Distance Learning Fast Facts.” Accessed April 24, 2024. https://nces.ed.gov/programs/digest/d22/tables/dt22_311.15.asp  

Amir Mohammad Rahmani, Wim Groot, and Hamed Rahmani. 2024. “Dropout in Online Higher Education: A Systematic Literature Review.” International Journal of Educational Technology in Higher Education 21 (January). doi:10.1186/s41239-024-00450-9. 

Wandler, J. Brad, and William J. Imbriale. 2017. “Promoting Undergraduate Student Self-Regulation in Online Learning Environments.” Online Learning Journal (OLJ) 21 (2). doi:10.24059/olj.v21i2.881. 

Wong, Jacqueline, Martine Baars, Min He, Björn B. de Koning, and Fred Paas. 2021. “Facilitating Goal Setting and Planning to Enhance Online Self-Regulation of Learning.” Computers in Human Behavior 124 (November): N.PAG. doi:10.1016/j.chb.2021.106913. 

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