Guest Column: Designing and developing courses that prioritise online student support

Educators argue that the provision of support is a vital element for online students’ success. A design of online courses that prioritise online student support is possible when support interventions are planned and implemented strategically rather than in an ad-hoc way. With such an approach, support is “embedded” into the learning curriculum and delivered “where and when it is most needed” (Stone, 2017, p. 10). 

This article provides an overview, backed up by academic scholarship, of the areas of online student support that require attention when designing and developing online programmes. It suggests that embedded support strategies and services that embrace all the aspects of the university experience hold great potential for ensuring student success.  

Provide student support from the onset

It is always best to offer prospective students advising before the enrollment period. A lack of comprehensive information may lead students to misconceptions about requirements and the level of difficulty for a chosen online course. Clay et al. (2009) advocate a gated and comprehensive advisement and orientation, explaining that “simply providing online quizzes that seek to determine whether or not a student is suited to the online learning environment is not enough” (p. 101). The importance of adequate preparation for online learning has also been emphasised by Stone (2019). Stone argued that a “scaffolded entry” to the learning environment through the early connection with the students and a provision of preparation and orientation programmes are “vital to their future success” (p. 5). Examples of such scaffolding are mandatory orientation programmes before enrollment to the first online course (Gaytan, 2015) and a provision of online tester experiences. Among support strategies that can be offered to students prior to or during the orientation programmes are time management, study management and online study skills workshops (Grant, Olivier, Rawlings, & Ross, 2006), as well as pre-class training sessions on internet-based interactions (Kuo & Belland, 2016). These interventions aim to assist students in developing skills required for successful online learning, including skills for self-direction, and allow gathering data to inform the development of adequate support systems. 

 Another essential facet of setting students up for success is the early identification of those who are at risk. Distinctive features of students at risk are a lack of motivation, unrealistic expectations regarding time management, a hesitation to request help (McKavanagh & Purnell, 2007), and the absence of an online learning experience (Netanda, Mamabolo, & Themane, 2019). As Simpson (2008) emphasised, establishing a model of targeted support to those students has great potential in situations of scarce institutional resources. 

Focus on proactive support and student outreach measures

Current research identified a noticeable turn towards proactive rather than reactive support to maintain student course completions and retention rates. Whitelock et al. (2015) summarised recent recommendations for proactive support developed by the Open University in the United Kingdom. Core strategies for proactive tutor support include pacing students’ learning against milestones, monitoring students to identify those who are at risk of drop out, establishing communication with students prior to the submission of the first assignment to support those who struggle academically or have fallen behind. Other effective outreach strategies include motivational emails (Robb & Sutton, 2014), an individual offer to re-submit the assignment (Pinchbeck & Heaney, 2017), motivational calls, and proactive encouragement and an interest in the students’ activities (Rendon, 1994). 

The time when support is offered is critical, particularly during the periods of transition between different elements or parts of courses and programmes. If students are not supported during these transitional stages, they may experience exclusion and fail to progress (Baxter, 2012; Gibbs et al., 2006). Furthermore, online students’ multiple priorities and workload should be recognised and, if appropriate, integrated into the course design. Whitelock et al. (2015) proposed a workload modeller that calculates the time required for completing a particular task and translates that data to ensure a more flexible approach to managing workload, such as scheduling “build in catch-up weeks, or review weeks, where little or no new material was set” (p. 165).

Lastly, the availability of counselling has a notable impact on online learners’ satisfaction and course retention (Cain & Lockee, 2002). Although advising and counselling services are easily accessible on campus, there is a need to provide equal access to online students through a variety of alternative technological means, e.g., support with general welfare, mental health issues, emotional and practical support for incidents of bullying or harassment through online self-help resources, phone calls or video-conferencing tools. 

Build a community of learners and peer-support networks

Online course design that, in addition to considering students’ personal goals, aims to establish online learning communities positively influences student retention (Fisher & Baird, 2005). An example of a successful course design provided by Kumar and Coe (2017) is a cohort model of learning that allows students to form meaningful interpersonal connections during the study. 

Peer support and mentoring also proved to be cost-effective strategies that facilitate students’ adaptation to the online environment and improve retention, resulting in a better academic performance (Ashwin, 2003), development of communication skills and a higher persistence. Through mentoring from senior academics, students receive not only academic support but also “socio-emotional support” (Franke & Arvidsson, 2011, p. 129) since mentors are often aware of the personal situations of their mentees. 

A shift from depersonalised and pure academic support to a culture of care is highlighted by Chen and Jang (2010). The authors explained that a caring atmosphere allows students to express their “feelings, thoughts, and concerns” (p. 750).) Students’ perception of a “caring instructor” (Robb & Sutton, 2014, p. 6) or “caring professor” (Tippens, 2012) can add a personal touch to their learning. An example of building such safe spaces are online caring groups and caring connections sites designed alongside the online course to facilitate the development of a sense of community and to promote intentional caring (Brown & Wilson, 2019).

To conclude, there are a variety of forms in which support can be offered to online students. These cover not only academic but also administrative and pastoral aspects of the online learning experience and include pre-enrollment advising and orientation programmes, development of peer support networks, targeted proactive support and student outreach. What is worth having in mind is that the time of delivery and the relevancy of provided support may influence the effectiveness of the intervention. Thus, when designing and developing online courses and programmes, educators and online learning designers are invited to consider how student support can be embedded into a learning curriculum.

References:

• Ashwin, P. (2003). Peer Support: Relations between the context, process and outcomes for the students who are supported. Instructional Science, 31, 159–173.
• 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 Distributed Learning, 13(4), 107-129.
• Brown, C. J., & Wilson, C. B. (2016). One university making a difference in graduate education: caring in the online learning environment. Journal of Holistic Nursing, 34(4), 402-407.
• Cain, D. L., & Lockee, B. (2002). Student support services at a distance: Are institutions meeting the needs of distance learners? (ED ED468729).
• Chen, K. C., & Jang, S. J. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741-752.
• Clay, M. N., Rowland, S., & Packard, A. (2008). Improving undergraduate online retention through gated advisement and redundant communication. Journal of College Student Retention: Research, Theory & Practice, 10(1), 93-102.
• Fisher, M., & Baird, D. (2005). Online learning design that fosters student support, self–regulation, and retention. Campus-Wide Information Systems, 22(2), 88–107
• Franke, A., & B. Arvidsson. (2011). Research supervisors’ different ways of experiencing supervision of doctoral students. Studies in Higher Education, 36(1), 7-19
• Gaytan, J. (2015). Comparing Faculty and Student Perceptions Regarding Factors That Affect Student Retention in Online Education. American Journal of Distance Education, 29(1), 56-66
• Gibbs, G., Regan, P., & Simpson, O. (2006). Improving student retention through evidence based proactive systems at the Open University (UK). Journal of College Student Retention: Research, Theory & Practice, 8(3), 359-376.
• Grant, R., Olivier, G., Rawlings, C., & Ross, C. (2011). Enhancing the engagement and success of distance students through targeted support programmes. Lower Hutt, New Zealand: The Open Polytechnic of New Zealand.
• Kumar, S., & Coe, C. (2017). Mentoring and student support in online doctoral programs. American Journal of Distance Education, 31(2), 128-142.
• Kuo, Y. C., & Belland, B. R. (2016). An exploratory study of adult learners’ perceptions of online learning: Minority students in continuing education. Educational Technology Research and Development, 64(4), 661-680.
• McKavanagh, M. & Purnell, K. (2007). Student learning journey: supporting student success through the student readiness questionnaire. Studies in Learning, Evaluation, Innovation and Development, 4(2) 27- 38.
• Netanda, R. S., Mamabolo, J., & Themane, M. (2019). Do or die: student support interventions for the survival of distance education institutions in a competitive higher education system. Studies in Higher Education, 44(2), 397-414.
• Pinchbeck, J., & Heaney, C. (2017). Case report: the impact of a resubmission intervention on level 1 distance learning students. Open Learning: The Journal of Open, Distance and e-Learning, 32(3), 236–242. 
• Rendon, L. I. (1994). Validating culturally diverse students: Toward a new model of learning and student development. Innovative Higher Education, 19(1), 33-51.
• Robb, C. A., & Sutton, J. (2014). The importance of social presence and motivation in distance learning. The Journal of Technology, Management, and Applied Engineering, 31(2), 2–10.
• Simpson, O. (2008). Guide to proactive motivational student support (PaMS). Retrieved from http://www.mrsite.co.uk/usersitesv31/94669.mrsite.com/wwwroot/USERIMAGES/PROACTI VE%20MOTIVATIONAL%20SUPPORT%20GUIDE%20non%20OU.pdf
• Stone, C. (2017). Opportunity through online learning: Improving student access, participation and success in higher education (NCSEHE 2016 Equity Fellowship Final Report). Perth: Curtin University, National Centre for Higher Education. Retrieved from https://www.ncsehe.edu.au/publications/opportunity-online-learning-improving-student-access- participation-success-higher-education/ 
• Stone, C. (2019). Online learning in Australian higher education: Opportunities, challenges and transformations. Student Success, 10(2), 1-11
• Tippens, D. (2012). Technology Has Its Place: Behind a Caring Teacher [Blog]. Retrieved from https://www.chronicle.com/article/technology-has-its-place-behind-a-caring-teacher/
• Whitelock, D., Thorpe, M., & Galley, R. (2015). Student workload: a case study of its significance, evaluation and management at the Open University. Distance Education, 36(2), 161-176.

About the author

Olga Rotar is a Research Consultant for the FASS, Lancaster University, and an affiliated consultant with insendi, where she co-leads an ESRC-funded project that aims to examine the experiences of being a learning designer during the pandemic, in addition to the longer term impacts of the acceleration of online learning holds for learning designers.

Olga completed a research degree programme in National Economy at the Saint-Petersburg State University of Civil Aviation, Russia, and holds a Masters in Finance from the Saint-Petersburg State University of Economics. Olga’s PhD, conducted at Lancaster University, focused on experiences of learning and conceptualisations of success among the adult student population in online postgraduate programmes. Her additional research interests include online learning in higher education and economics of education.