The Role of Interaction in Successful Online Courses

Literature Review: The Role of Interaction in Successful Online Courses.

By

John J. McKeown

Overview


Perhaps like no other time, there is currently a great emphasis in education and training circles on creating quality distance learning programs. Already prominent, online courses continue to gain significance in academic, corporate, and military sectors. Their ability to provide opportunities without the constraints of space and proximity while allowing for asynchronous communication make them useful for learning at a distance under primary control of the learner. The optimization of this process is a focus of developing research which attempts to explain the aspects of this mechanism that support deep learning and understanding of course content. Issues associated with this mode of learning include questions of how to create rich learning experiences, optimally present content, and promote learner engagement. This engagement occurs in various forms of interaction.


A useful first step in considering these issues is to frame the overall process of online learning in terms of a system. One model for conceptualizing this is as a “community of inquiry” (Garrison, Anderson and Archer, 1999). This system is characterized in terms of “questioning, reasoning, connecting, deliberating, challenging, and developing problem solving skills” (p. 8). This community is composed of three main sections; cognitive presence, social presence, and teaching presence. Cognitive presence refers to constructing meaning through sustained communication, integrating knowledge, and resolving the underlying maladjustment. Social presence suggests personalizing the environment, expressing emotion, and is typified by open communication. Teaching presence refers to issues of design, facilitation of instruction, and building meaning.


Clearly, in this system of relationships the interaction between and among learners, instructors and ideas is prominent and critical. It is characterized as collaborative and constructivist in nature (Swan, Day, and Bogle, 2014). This fact is the focus of the following sections which will endeavor to explain, define, and measure such interaction for successful online learning.


Definitions


Literature pertaining to interaction most frequently cites Moore (1998) which contemplates three types of interaction; learner-instructor, learner-learner, and learner-content. Unique factors are identified in each that support learning. Learner-instructor interaction should include prompt feedback, instructor engagement/accessibility, and clarity in design and learning purpose. Learner-learner interaction is the process of socially creating meaning; “positive interdependence” (Moallem, 2003, p.100). Moore (1998) describes learner-content interaction as “the process of intellectually interacting with content that results in changes in the learner’s understanding, the learner’s perspective, or the cognitive structure of the learner’s mind” (p. 2).


Research


Although all types of interaction are recognized as being important, literature presents different points of view about the relative importance of each and the extent to which they influence each other. Crawford-Ferre and Wiest (2012) tell us that it is there is too much emphasis on learner-instructor and learner-learner interaction. They suggest that this has neglected the importance of engaging first with content and that it is the instructional design of the activities that foster reasoned argument in the other types of interaction.


Maintaining a focus on content interaction, Murray, Pérez, Geist, and Hedrick (2013) suggest that research so far has only contemplated measuring the impact after student interaction with content rather than examining why interaction occurs. It does not examine whether learners will access resources if given the choice. They focus on measures associated with access rates for core materials, direct support, indirect support, and other materials to obtain insight into these choices.

Moallem (2003) provides a look into the design characteristics of activities that promote collaborative learner-learner interaction. Here, the focus is on the concept of using generative tasks and ill-defined (multiple solution) problems to initiate interaction. An interesting suggestion is that this facilitates knowledge construction while intellective exercises serve to validate the learner making them more apt to engage. Specifically, there are four classifications of activities that require interaction, prompting students to: generate (i.e., plans, ideas), choose (i.e., an answer), negotiate (i.e., resolve conflicts, decision making), and execute (i.e., perform task) (Moallem, 2003, p.87).


The presence of interaction alone may not guarantee quality engagement. Crawford-Ferre and Wiest (2012) go further to examine the quality and clarity of these exercises as being key to allowing students to project themselves socially and emotionally. Garrison and Cleveland-Innes (2010) report three results of their examination of the question of what constitutes quality interaction. They find that first, designating the quality of interaction as a design objective is key to achieving high quality results. Second, that teaching presence specifically contributes to deep learning whereas interaction alone does not. Finally, they introduce the notion of the magnitude of interaction and find it significantly affected by social presence.

With an eye toward quality, Yukselturk and Yildirim (2008) discuss the concept of student satisfaction as a function of interaction and identify it as an extension that is key to course success. Their study identified and measured trends in factors affecting satisfaction.


Throughout the literature there were references to study design limitations. Among these were a lack of clarity and consistency about the definition of interaction. Also, there was noted an insufficient specification of the learning environment as a context to understand the interaction. Thorpe (2008) suggests that, although grounded in sound constructivist concepts, studies were limited by the use of tightly controlled experiments or subjective observations.


In addition, there is a heavy use of self-reporting and questionnaires in developing understanding and conclusions. These were employed for both gathering student perceptions as well as reporting changes in how learners made strategic choices in deciding which supports to access, etc.

Future Research


Topics for further research should focus on further conceptualizing interaction types and recognizing the limitations in its analysis. In addition, an understanding of learner attributes that maximize interaction should crystalize into a model for students to emulate. For example, Swan, Day, and Bogle (2014) indicate that self-regulated learners interact more. That, together with the noted analysis method dependence on self -reporting and questionnaires, makes that attribute of learners a key one to understand and design for in the facilitation of interaction in online learning. Still other attributes can be identified through research, continually developing a comprehensive framework for successful interaction.


About the author: John McKeown is prior service civil affairs with many years of experience in education administration and public finance. John has earned a BS, MS, CAS and completed PhD work in the learning sciences. He is currently an adjunct professor of finance and economics at the University of Maryland Global Campus.


References


Garrison, D. R., Anderson, T., & Archer, W. (1999). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2), 87-105.

Swan, Karen; Day, Scott L; Bogle, Leonard Ray. 2014. A collaborative, design-based approach to improving an online program. The Internet and Higher Education, Volume 21

Moore, M. (1998). Three Types of Interaction. The American Journal of Distance Education., 3 (2), 1-6.

Moallem, M. (2003). An Interactive Online Course: A Collaborative Design Model. Educational Technology Research and Development, 51(4), 85-103. Retrieved from http://www.jstor.org.gate.lib.buffalo.edu/stable/30221186

Student Interaction with Content in Online and Hybrid Courses: Leading Horses to the Proverbial Water. Meg Coffin Murray, Jorge Pérez, Debra Geist, Alison Hedrick

Informing Science: The International Journal of an Emerging Transdiscipline Volume 16 2013 pp. 099 – 115. https://doi.org/10.28945/1779

Crawford-Ferre, H. G., & Wiest, L. R. (2012). Effective online instruction in higher education. Quarterly Review of Distance Education, 13(1), 11+. Retrieved from http://link.galegroup.com.gate.lib.buffalo.edu/apps/doc/A297555182/AONE?u=sunybuff_main&sid=AONE&xid=1cade27b

Yukselturk, E., & Yildirim, Z. (2008). Investigation of interaction, online support, course structure and flexibility as the contributing factors to students' satisfaction in an online certificate program. Educational Technology & Society, 11(4), 51+. Retrieved from http://link.galegroup.com.gate.lib.buffalo.edu/apps/doc/A193084631/AONE?u=sunybuff_main&sid=AONE&xid=644b0a1f

D. Randy Garrison & Martha Cleveland-Innes (2010) Facilitating Cognitive Presence in Online Learning: Interaction Is Not Enough, American Journal of Distance Education, 19:3, 133-148, DOI:10.1207/s15389286ajde1903_2

Thorpe, M. M. (2008). Effective online interaction: Mapping course design to bridge from research to practice. Australasian Journal Of Educational Technology, 24(1), 57-72.

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