by John Sener

Class size is a key component of course design, delivery cost, learning effectiveness, faculty and student satisfaction, and many other important factors in fully online and blended courses. One widely held view is that the “ideal” maximum class size is relatively small (10 to 25 students). Although plenty of opinion and anecdotal experience support this view of class size, such conventional wisdom is typically a reflexive application of classroom design mores and principles that have been applied to online and blended learning environments.

Class Size as a Function of a Variety of Factors
In reality, there is no such thing as an “ideal” class size for an online or blended course. Optimal class size is a function of a variety of factors, including course design, desired outcomes, and delivery costs. Of course, it could be said that traditional class sizes are necessary to re-create traditional class experiences, particularly since using instructor-centered learning designs usually increases instructor workload. However, these days there are many new innovative methods and strategies available to design online or blended courses that effectively support large class sizes.

For example, the Finance, Credit, and International Business (FCIB) trade association utilizes an instructor-facilitated online learning approach in its International Credit and Risk Management course, which has consistently attained high completion rates (80%) and learner satisfaction rates while serving 60 to 80+ students at a time with a single facilitator.

This FICB course utilizes a tutorial model of instruction where student-instructor interaction is conducted primarily through instructor feedback to frequent course assignments that students are required to submit. Surprisingly, a study of online information technology courses offered at Northern Virginia Community College (NVCC) indicated that this approach supported course sizes of 10 to 100 students with generally favorable results.

Additionally, the Indiana University School of Education’s Learning to Teach with Technology Studio (LTTS) utilizes a teaching and learning model that supports larger class sizes by enabling a combination of student self-pacing and mentoring support. Mentors report requiring an average of 3.5 hours per student per course to support students effectively, while students report high levels of satisfaction with the flexibility that self-pacing affords.

At Northern Arizona University, the late Guy Bensusan employed a model (Collaborative Online Learning Algorithm) that emphasized a combination of learner self-directedness and reliance on student-to-student feedback. Bensusan reported using this model for 250 students in each of his blended courses.

Re-framing Student/Teacher Ratio
It is interesting to note that moving the instructor off center stage and into a different role is a common theme in all of the aforementioned approaches. It is also interesting to note that the very idea of defining class size in terms of student/teacher ratio can be overly limiting.

One way to increase class size is to aggregate faculty workload, i.e., give multiple workload credit for large course sections. For example, only two online courses have typically made up Maria Rynn’s entire teaching workload per term. Rynn has had 200 to 300 students at any given time in two information technology courses she teaches at NVCC, for which she receives full-time workload credit.
 
Other course designs render meaningless the concept of class size in relation to student/teacher ratio. Another case in point can be found at the Institute for Healthcare Improvement (IHI), which uses a collaborative approach called the “Breakthrough Series Collaborative.” This blended model is a 6- to 15-month learning system that brings together a large number of teams from hospitals or clinics to seek improvement in a focused topic area. Three face-to-face meetings over the course of the collaborative are team-taught by expert faculty supported by IHI staff. A typical IHI collaborative involves a large number of healthcare professionals (40 to 700) in 20 to 40 teams that comprise IHI’s target audience. The IHI collaborative teams enable knowledge and best-practice sharing based on an “all teach, all learn” philosophy.

For another example, Ohio State University’s Introductory Statistical Concepts course enrolls 3,000 students each year using a “Statistical Buffet” model that “provides students a choice of content delivery strategies” and “optimizes each student’s experience and success,” according to Professor of Mathematical and Physical Sciences Dennis Pearl. This model enables students to get even more personalized instruction than students in smaller classes.

Using Innovative Technologies
For the IHI and Ohio State University course designs, class size ratios could be calculated, but they would not be particularly relevant. The more salient characteristic is the use of innovative technologies and course design to create more effective learning experiences that bear little resemblance to the traditional classroom model.

Two Strategies for Selecting Appropriate Class Sizes
Recently, the Teaching, Learning, and Technology Learning Group (TLT Group) conducted an online workshop that explored class size issues in blended and online courses. The workshop focused on two particular strategies for selecting appropriate class sizes:

1. Engage learners without overloading them or overworking faculty.
Asynchronous discussion boards effectively engage learners when designed and managed correctly. Plus, the available knowledge on managing online discussions has become much more sophisticated in recent times.

Sampling can be used for deciding what to include in a learning experience. The TLT Group's Steve Gilbert notes that “every teacher makes sampling decisions about almost every aspect of teaching and learning.” Sampling is thus a strategy for setting reasonable limits for interaction while simultaneously selecting learning activities which will engage students and faculty without overwhelming them.

Rubrics help clarify student expectations and can effectively facilitate the assessment process when used properly.

2. Match design models with appropriate class sizes and ratios.
A number of strategies are being used effectively to support large class sizes. Some of these strategies focus on effective course design. For instance, clear course structure and guidelines are frequently mentioned as key contributing factors to course success. Turoff and Hiltz propose the careful structuring of course activities into manageably-sized conferences or discussion forums (“information organization and retrieval”) as a principle that can enable faculty to effectively manage large enrollment courses (40 to 80 students). In addition, providing clear navigational instructions, which reduce student questions and thus instructor workload, is another frequently cited design principle that supports large class sizes.

Other principles of organization and participation, proposed by Turoff and Hiltz, that support large enrollment courses and focus more on course delivery strategies include:

Establish and enforce clear guidelines for completing course activities (class synchronization).

Facilitate active student interaction and collaboration by establishing an active instructor presence along with a “socially welcoming environment” to encourage trust and open expression of views (coordination, collaboration, socializing).

Enable students to share their knowledge and real life experiences with each other.

Allow students to learn other students’ representations of knowledge and to demonstrate their understanding of concepts by stating them in their own frame of reference (sharing learning and feedback).

Grade students on the quality and timeliness of their contributions (requiring participation).

Finally, some strategies are better suited to reducing class size. For instance, when the Defense Acquisition University decided to convert some of its faculty professional development courses from web-based training to an instructor-facilitated online delivery format, they improved the quality of these courses by adding project-based learning assignments that required more extensive instructor feedback than the previous versions. This strategy increased the amount of instructor time required to deliver the course. Consequently the revamped course design facilitated a relatively low teacher/student ratio (12 to 20:1) for a more effective teaching and learning environment.

In conclusion, the issue of class size is an excellent “portal” for exploring the potential of utilizing online technologies and strategies to improve and transform education. Through close reflection on effective strategies and models for successful courses with both large small enrollments, faculty and instructional designers can create innovative delivery alternatives for effective online and blended teaching and learning environments.

Resources:
Bensusan, G. (2001). Distance COLA (Collaborative Online Learning Algorithm): Effervescent Learning Online. KnowMap, 1 (6), September 2001. Retrieved March 30, 2006 at: http://www.knowmap.com/open/bensusan_distance_cola.html

Del Valle and Duffy (2005). LTTS: A Course Management System for Online Inquiry Learning. Proceedings of the 21st Annual Conference on Distance Teaching and Learning, Madison, WI, August 2005. Retrieved March 30, 2006 at:
http://www.uwex.edu/disted/conference/Resource_library/proceedings/05_1805.pdf

LTTS web site:
http://ltts.indiana.edu

IHI Breakthrough Collaborative model:
http://www.ihi.org/IHI/Results/WhitePapers/TheBreakthroughSeriesIHIsCollaborativeModelforAchieving+BreakthroughImprovement.htm

Examples of IHI’s emphasis on measuring improvement:
http://www.ihi.org/IHI/Topics/Improvement/ImprovementMethods/Measures/

OSU “Statistical Buffet” approach: http://oncampus.osu.edu/v32n21/thisissue_2.html (search on “buffet”)

Sener, J. (2001). Bringing ALN Into the Mainstream: NVCC Case Studies. Online Education, Volume 2: Learning Effectiveness, Faculty Satisfaction, and Cost Effectiveness Proceedings of the 2000 Sloan Summer Workshop on Asynchronous Learning Networks, 2001.

TLT Group website resources on sampling and class size Issues: http://www.tltgroup.org/ProFacDev/DangerousDiscussions/ClassSizeSampling.htm

Turoff, M., and Hiltz, S.R. (2001). Effectively Managing Large Enrollment Courses: A Case Study. Online Education, Volume 2: Learning Effectiveness, Faculty Satisfaction, and Cost Effectiveness Proceedings of the 2000 Sloan Summer Workshop on Asynchronous Learning Networks, 2001.

John Sener is founder of Sener Learning Services: http://www.senerlearning.com