Week 5: The Online Instructor as a Microsystem

In my systems thinking PhD course, I have recently been tasked with identifying a Microsystem and then evaluating the components that it is comprised of. In this effort, I have chosen to evaluate “The Online Instructor” as a Microsystem and analyze internal and external factors that influence or impact this system.  This blog post is one in a series of posts that will continue to analyze the online instructor as a microsystem and should be considered a work in progress.  You comments and suggestions for improvement are greatly appreciated.

At the micro level, the factors that directly influence the online instructor include: the institution where the faculty member is employed, the students, peer faculty, instructional design and course content, and the instructor’s own facilitation skills.  Due to the complexity of the system and the details surrounding the elements that influence it, this week’s post will focus primarily on the elements of the institution and the online instructor’s students.

The Online Instructor as a Microsystem

The Online Instructor as a Microsystem

By exploring these areas in detail, we find that they each impact the online instructor in a number of ways.


Institutional support and readiness related to online learning are key factors that directly impact an online faculty member.  In order for an institution to be prepared to support online education, there are many key factors that must be considered. Institutions that have successfully implemented online campuses or virtual course offerings usually have several things in common.  As a first example, successful implementation of these types of programs typically begins with senior leadership support. In these cases distance education is seen as a key element of the strategic plan for the university. Secondly, these have the needed support from their legal department, faculty committee or senate, and administration to enable them to create and implement policies that support distance education and the faculty who teach online.  Policies may already exist or may need to be developed related to intellectual property, the family education rights and privacy act or FERPA, the American’s with disabilities act or ADA, copyright compliance and others.

The third example related to an institution’s online programs are the degree to which they are supported with technology infrastructure, support staff (help desk), professional development programs, training, and instructional design support which can all impact and assist faculty in the creation of high quality online courses.


Students may enter higher education with a variety of skills and abilities, varying financial pressures, and very different levels of motivation.  When students choose an online program of study, they need to consider their level of technology readiness as well as their ability to self regulate their own learning.

As students enter online education for the first time after being taught in the traditional classroom they need new skills to adapt to the change in learning environment. As similar tale is told of the young student going off to college, as she enters the lecture hall filled with 500 students rather than being one of 25 receiving personalized attention.  Yes, the online environment can lead to feelings of isolation, but when faculty utilize facilitation skills that truly “humanize” their online course and establish a rich forum for communication with the instructor and peers it transforms the online course into a rich and robust online learning community.

The rising cost of higher education and the growing student debt bubble is putting additional financial pressures on potential students as they consider the true costs and the ROI of a degree.  No longer is it simple mathematics (student X + education Y = increased earnings over time Z).  The changing job market is adding pressure to the situation, making the choice regarding whether or not to pursue a degree a difficult one.

Motivation is a psychological driving force that supports or compels actions toward a desired result.  A review of the literature regarding learner motivation reveals the need for extrinsic and intrinsic elements, self-regulated learning, a feeling of connectedness, and the use of motivational messages.  These needs also exist for students attending classes virtually or in online settings. According to industry leaders “There is no doubt that there are serious motivational challenges among distance learners.  The attrition rate alone can be viewed as an indication of motivational problems (Keller, 1999).”

Extrinsic motivation comes from outside of the individual. Whether a threat of punishment or receipt of a reward, extrinsic motivations can be powerful.  However, in the absence of the external stimuli some learners often become less motivated.  Engaging learners in competition is one way to draw them in and tap into their extrinsic motivations.

Interest or enjoyment in a task is often referred to as an intrinsic motivator. Intrinsically motivated students are motivated to learn for a variety of reasons. These students may want answers to their own unanswered questions, may be competitive in nature, or might simply desire self-improvement.  Students who are intrinsically motivated prefer being autonomous, are usually self-regulating learners, are often determined, and are interested in mastery of topics.

Self-regulated learning refers to the learning that comes from the influence of students’ own feelings, thoughts, and behaviors that are oriented toward reaching their personal goals (Artino, 2008).  Self-regulated learners are sometimes quite determined to achieve a goal and will bounce back from failures more easily.  These leaners are more likely to engage in tasks for a greater length of time, and think deeply about the tasks in which they are engaging (Cheng & Yeh, 2008). 


Artino, A., (2008) Promoting academic motivation and self-regulation: practical guidelines for online instructors, TechTrends, 52(3), 37-45.

Banathy, B. (1999). Systems thinking in higher education: Learning comes to focus. Systems Research and Behavioral Science, 16(2), 133-145.

Banathy, B. (1992). Chapter two: The systems-environment model. In A Systems View of Education Concepts and Principles for Effective Practice (pp. 25-58). Englewood Cliffs, NJ: Educational Technology Publications.

Cheng, Y., & Yeh, H., (2009) From concepts of motivation to its application in instructional design: Reconsidering motivation from an instructional design perspective, British Journal of Educational Technology, 40(4), 597-605.

Eoyang, G. (1996). A brief introduction to complexity in organizations. Chaos Limited, Inc.,

Keller, J., (1999) Using the ARCS motivation process in computer-based instruction and distance education, New Directions for Teaching and Learning, 78.

Reigeluth, C. (2004). Chaos theory and the sciences of complexity: Foundations for transforming education. Informally published manuscript, Instructional Systems Technology, Indiana University, Bloomington, IN, Retrieved from http://www.indiana.edu/~syschang/decatur/documents/chaos_reigeluth_s2004.pdf