Title: A Framework For Evaluating Class Size in Online Education
Authors: Susan H. Taft, Perkowski, and Lorene S. Martin
Study Design: Considering the impressive upsurge of online courses in recent years, educators are asking important questions about how to maximize learning opportunities in cyberspace. One important factor that impacts learning outcomes is class size. In an effort to shed light on the optimal class size for distance learning, the authors of Evaluating Class Size and Online Education reviewed research from multiple disciplines on the ideal enrollment number for online courses.
Findings: Upon completing a thorough literature review, the authors concluded that there is no definitive answer. What was clear from the most up-to-date literature was that different class sizes will create distinct group dynamics, as well as affect faculty and student relationships.
Instead of looking for a "magical class size number," the authors encourage instructors to think about educational frameworks when designing an online course. They describe how objectivist-constructivist teaching strategies, Bloom's taxonomy, and the community of inquiry model can inform online class size. Using such frameworks offers insights into the levels of necessary interaction and teaching intensity. The objectivist model, for example, encompasses students passively consuming information from an instructor, who is considered an expert on a particular topic. Math and science courses traditionally are taught using the objectivist approach. Constructivist learning models, on the other hand, assume that learning is an innately social process and is more about individual "meaning-making." The community of inquiry model in online education is grounded in the belief that the instructor’s role is critical for optimizing student learning. In addition to the central role of teaching, the model assumes that social and cognitive presence (the extent to which students construct and integrate new meaning through continuous learning activities) are critical to learning effectiveness in the online learning context. Finally, Bloom’s taxonomy is a classification made up of six levels of learning that range in complexity of thinking. They include: knowledge acquisition, comprehension, application, analysis, synthesis and evaluation. Instructors design courses by pulling from various levels of Bloom’s taxonomy.
So how can these models inform class size? The authors of the study concluded that when embracing an objectivist approach, course enrollment has no limit. For any interactive constructivist educational approach, the authors advocate class enrollments between 20 to 25 students. When utilizing a community of inquiry model, no more than 20 students would be ideal. Bloom’s taxonomy is more nuanced. The authors suggests that course enrollment can accommodate 30 or more students when they are simply absorbing and obtaining new information, 16-40 students when application of new knowledge is part of the course, and no more than 15 students when more complex learning that entails analysis and evaluation is included in the mix.
Moving Forward: Online learning is well established in higher education and current research suggests that this trend will continue to grow. Understanding factors that influence distance-learning outcomes is an important issue that demands deeper understanding. While this paper offers some interesting guidelines on class size depending on the learning approach of the instructor, the authors encourage future research to further analyze learning outcomes of students enrolled in courses of varying size and that utilize distinct learning models.
Image: Student on computer by Cpl. Lucas Vega (via Wikimedia Commons).