Online learners are a diverse group, and while many online learners also attend classes on campus, there are a cluster of characteristics, traits, and preferences that figure more prominently in this group of learners as a whole. Understanding the range of characteristics, some of the common reasons students are motivated to take online courses, and what common barriers they face, provide useful insight as you step into facilitating online.
There is some evidence that there are consistent differences between learners who choose in-person courses relative to those who choose online courses (Roddy et al., 2017; Bailey et al., 2014). Online learners comprise a somewhat older and a more mature population, typically ranging from about 25–50 years old (Moore & Kearskey, 2005). They can bring rich life experience to the online course (Bostin & Ice, 2011; O’Shea et al., 2015), but they also have more commitments outside their academic life, such as busy work schedules, that can pose a challenge for these students (Greenland & Moore, 2014). Some online learners are completing their entire degree remotely and could be living many time zones away, while others are local and taking on-campus courses or are in a co-op work-term.
Given the amount of flexibility and control online learners have over their learning, they must take responsibility for their own learning. Adopting effective learning strategies is a positive predicter of higher grades (NSSE, 2013). However, online facilitators very much contribute to student success (Hughes, 2014). In the following units we’ll explore this important role more closely and provide you with strategies and approaches that contribute to student success.
In a larger-scale factor analysis study, Muilenburg and Berge (2005) identified eight barriers to student success in online courses:
As will be outlined in the following units, the facilitator can have a significant impact on helping students to overcome these barriers (Lovitts & Nelson, 2000; Beaudoin, 2002; Muilenburg, & Berge, 2005; Dennen, 2008; Oomen-Early & Murphy, 2009; Joyner et al., 2014; Jaggars & Xu, 2016; Roddy et al., 2017).
Another important issue to consider here is the possibility that during the term some students, in both in-person and online courses, will experience a disruption to their mental health and wellness, such as anxiety, depression, or an exacerbation of a pre-existing condition during the term. While many of the principles around student mental health and wellness that have been explored in the on-campus context apply to the online learning context, identifying and offering support to online students, who may not be local, poses additional challenges. In Unit 3: student-facilitator interaction we provide more detailed guidance on identifying students at risk and addressing mental health and wellness issues. Most of the approaches and strategies we suggest throughout this resource to enhance student engagement, interactions, presence, and a sense of community also positively contribute to student well-being.
If you are creating learning materials, resources, or experiences (e.g., labs or tutorials) for your online course, it is important to remember that some of your students may be hearing or visually impaired and video is not an accessible format. If you have included a video in the course (e.g., asynchronous presentation, demo, or announcement) or a virtual classroom session (e.g., synchronous tutorial) you may be required to provide a transcript and/or verbal description of what is being displayed in a video.
References
Bailey, M., Ifenthaler, D., Gosper, M., & Kretzschmar, M. (2014). Factors influencing tertiary students’ choice of study mode. Rhetoric and Reality: Critical Perspectives on Educational Technology, 251-261.
Beaudoin, M. F. (2002). Learning or lurking? Tracking the “invisible” online student. Internet Higher Educ., 5, 147–155.
Bolliger, D. U., and Martindale, T. (2004). Key factors for determining student satisfaction in online courses. International Journal of E-Learning, 6, 61–67.
Boston, W. E., & Ice, P. (2011). Assessing retention in online learning: An administrative perspective. Online Journal Distance Learning. Administration, 14, 1–12.
Braun, T. (2008). Making a choice: The perceptions and attitudes of online graduate students. Journal of Technology and Teacher Education, 16, 63–92.
Brown, V. (2011). Changing demographics of online courses. US-China Education Review, 8, 460–467.
Dennen, V. P. (2008). Pedagogical lurking: Student engagement in non-posting discussion behavior. Comput. Human Behav., 24, 1624–1633.
Greenland, S. J., & Moore, C. (2014). Patterns of online student enrolment and attrition in Australian open access online education: A preliminary case study. Open Praxis, 6, 45–54.
Hughes, P. W. (2014). Teaching scientific inquiry: Inquiry-based training for biology graduate teaching assistants improves undergraduate learning outcomes. Higher Education Quality Council of Ontario. http://www.heqco.ca/SiteCollectionDocuments/Carleton%20Scientific%20Inquiry%20ENG.pdf
Jaggars, S. S., & Xu, D. (2016). How do online course design features influence student performance?. Computers & Education, 95, 270-284.
Joyner, S. A., Fuller, M. B., Holzweiss, P. C., Henderson, S., & Young, R. (2014). The importance of student-instructor connections in graduate level online courses. Journal of Online Learning and teaching, 10(3), 436-445.
Johnson, G. M. (2015). On-campus and fully-online university students: comparing demographics, digital technology use and learning characteristics. Journal of University of Teaching and Learning Practice, 12, 11–51.
Khiat, H. (2015). Measuring self-directed learning: a diagnostic tool for adult learners. Journal of University of Teaching and Learning Practice, 12. http://ro.uow.edu.au/jutlp/vol12/iss2/2
Kırmızı, Ö. (2015). The influence of learner readiness on student satisfaction and academic achievement in an online program at higher education. Turkish Online Journal of Educational Technology, 14, 133–142.
Lovitts, B. E., & Nelson, C. (2000). The hidden crisis in graduate education: Attrition from Ph.D. programs. Academe, 86(6), 44-50.
Moore, M. G., & Kearskey, G. (2005). Distance Education: A Systems View. Belmont: Wadsworth Publishing.
Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance Education, 26, 29–48.
National Survey of Student Engagement. (2013). A fresh look at student engagement – Annual results 2013. Bloomington, IN: Indiana University Center for Postsecondary Research. http://nsse.indiana.edu/NSSE_2013_Results/pdf/NSSE_2013_Annual_Results.pdf
Oomen-Early, J., & Murphy, L. (2009). Self-actualization and e-learning: A qualitative investigation of university faculty’s perceived barriers to effective online instruction. International Journal of E Learning. 8, 223–240.
O’Shea, S., Stone, C., & Delahunty, J. (2015). “I ’feel’ like I am at university even though I am online.” Exploring how students narrate their engagement with higher education institutions in an online learning environment. Distance Education, 36, 41–58.
Roddy, C., Amiet, D. L., Chung, J., Holt, C., Shaw, L., McKenzie, S., ... & Mundy, M. E. (2017). Applying best practice online learning, teaching, and support to intensive online environments: An integrative review. Frontiers in Education, 2, p. 59.
Roper, A.R. (2007). How students develop online learning skills. EDUCAUSE Quarterly, 30(1). https://er.educause.edu/articles/2007/1/how-students-develop-online-learning-skills.
Troop, M., White, D., Wilson, K.E., & Zeni, P (2020). The user experience design for learning (UXDL) framework: The undergraduate student perspective. The Canadian Journal for the Scholarship of Teaching and Learning, 11(3). https://doi.org/10.5206/cjsotl-rcacea.2020.3.8328