Online Teaching and Learning

Online teaching and learning consists of many facets: based upon research, theories, and praxis. While there are a plethora of avenues to explore in this vast topic, I will be considering the importance of online learning (i.e. statistical data), and what the factors assist in online learning (i.e. motivation and social presence).


Surveys and Statistical Data on Online Learning

Statistics identifying online learning trends as well as surveys of student, teacher and administrator satisfaction can be helpful resources for isolating needs and learning outcomes within the online learning environment. Allen and Seaman (2011; 2008; 2005) and Allen et al. (2012) from the Babson Survey Research Group have completed annual surveys identifying the number of students involved in online learning at over 2,500 American higher educational institutions over the past decade. Along with importance of understand the increasing enrollment, Allen et al. (2012) have surveyed students, teachers and administrators regarding conflicted attitudes regarding online learning practices and outcomes.



Motivation is a key indicator of online learning outcomes as evidenced by various studies (Jones, 2010; Mashaw, 2012). Such studies connect to previously established human motivational behaviors (i.e. Maslow’s Hierarchy of Motivation). Through the psychological perspective, Maslow (1943) identified five different hierarchical levels of motivation. Connections of Maslow’s motivation hierarchy can be established with online learning research in motivation as the understanding of levels two through five, (i.e. individual feelings of security and making relationships, as well as feelings of accomplishment and achievement can be key items) display clear connections.


Connections to Social Presence

Hannum (2007) described the need for students in online environments to experience social connection. Research that identifies the social presence within online learning is helpful in identifying communication tools and design ideas to align with motivation (Garris, Ahlers & Driskell, 2002; Oztok & Brett, 2011; Swan, 2001; Twigg, 2004).


Support Motivation through Online Learning Design

A number of articles (Lin et al., 2004; Dabbagh & Bannan-Ritland, 2005; Wilging & Johnson, 2004; Tyler-Smith, 2006) assist with presenting guides and strategies to help bridge the understanding of online learning design structures to help facilitate motivation for students.



Allen, Elaine & Seaman, Jeff.  (2011). Going the Distance Online Education in the United States, 2011. Babson Survey Research Group. Retrieved from

Allen, Elaine & Seaman, Jeff. (2008). Staying the course: Online education in the United States, 2008. The Sloan Consortium. Retrieved from

Allen I. E., & Seaman, J. (2005). Growing by degrees: Online education in the United States. Retrieved from

Allen, Elaine, Seaman, J., Lederman, D., and Jaschik, S.. (2012). Digital faculty: Professors, teachers and Technology. Inside Higher Ed. Retrieved from

Bailey, B. L., Bauman, R.K., & Lata, K. A. (1998). Student retention and satisfaction: The evolution of a predictive model. Paper presented at the meeting of the Association for Institutional Research Conference, Minneapolis, MN. (ERIC No. 424797)

Dabbagh, N. & Bannan-Ritland, B. (2005). Online learning: Concepts, strategies, and application web companion. Chapter 6 – Instructional strategies and their role in online learning. Upper Saddle River, NJ: Pearson Education, Inc.

Garris, R., Ahlers, R., & Driskell, J. E. (2002). Games, motivation, and learning: A research and practice model. Simulation & Gaming, 33, 441–467. doi:10.1177/1046878102238607

Hannum, W. H. (2007). When computers teach: A review of the instructional effectiveness of computers. Educational Technology, 47(2), 5-13.

Jones, B. D. (2010). An examination of motivation model components in face-to-face and online instruction. Electronic Journal of Research in Educational Psychology, 8(3), 915–944.

Lin, C.-B., Young, S. S.-C., Chan, T.-W., & Chen, Y.-H. (2005). Teacher-oriented adaptive Web-based environment for supporting practical teaching models: a case study of “school for all”. Computers & Education, 44(2), 155–172. doi:10.1016/j.compedu.2003.11.003

Mashaw, B. (2012). A Model for Measuring Effectiveness of an Online Course. Decision Sciences Journal of Innovative Education, 10(2), 189–221. doi:10.1111/j.1540-4609.2011.00340.x

Maslow, A. H. (1943). A theory of human motivation. Psychological Review 50(4), 370-396. Retrieved from

Oztok, M., & Brett, C. (2011). Social Presence and Online Learning: A Review of Research. Journal of Distance Education (Online), 25(3), 1–10.

Swan, K. (2001). Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education 22(2), 306-331.

Tello, S. F. (2007). An analysis of student persistence in online education. International Journal of Information and Communication Technology Education, 3(3), 47-62.

Twigg, C. A. (2004). Using asynchronous learning in redesign: Reaching and retaining the at-risk student. Journal of Asynchronous Learning Networks 8(1), 7-15. Retrieved from

Tyler-Smith, K. (2006, June). Early attrition among first time eLearners: A review of factors that contribute to drop-out, withdrawal and non-completion rates of adult learners undertaking eLearning programmes. Journal of Online Learning and Teaching 2(2), 73-85.

Wilging, P. A., & Johnson, S. D. (2004, December). Factors that influence students’ decision to dropout of online courses. Journal of Asynchronous Learning Networks 8(4), pp. 105-118. Retrieved from

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