Instructional Design Summit - Part 2: Course Design And Revisions Considerations For Large-Enrollment Courses
Concurrent Session 5
Many colleges and universities have been considering the implementation of large-enrollment online courses to meet the online education demands. For course designers, these large-enrollment courses can present certain challenges. What role does learning analytics and the new RSI (regular and substantive interaction) play in designing and revising large enrollment courses? Join the discussion to better understand the challenges and to explore possible strategies for addressing them.
Many colleges and universities have been considering the implementation of large-enrollment online courses to meet the online education demands. For course designers, these large-enrollment courses can present certain challenges. What role does learning analytics and the new RSI (regular and substantive interaction) play in designing and revising large enrollment courses?
While the meaning of large-enrollment class varies from college to college, from discipline to disciple, and even from one faculty to another, many of the papers are using the following definition that centers on the student success as the main benchmark: "Any class where the numbers of students pose both perceived and real challenges in the delivery of quality and equal learning opportunities to students" (Maringe & Sing, 2014, p. 763).
The available research on the effect of class size in online courses is somewhat scarce and provides mixed results (Lowenthal, et al., 2019):
- Cavanaugh (2005) found that adding a single student to an online course increased instruction time dramatically.
- Another study found that increasing the class size by ten percent or even more doesn't significantly affect student grades, enrollment in the next term, or credits attempted (Bettinger, Doss, Loeb, Rogers, and Taylor, 2017). Please note that the course size in this study was considered to be regular if it had 31 students, so the increase by 10% brought the enrollment to 34 students.
- Taft, Perkowski, & Martin (2011) suggested that faculty workload expands with the number of students and that it is hard to achieve positive student outcomes while maintaining faculty workload in large-enrollment online courses.
While the research on the effects of class size in online courses is incomplete and inconclusive, there are some helpful tools and strategies to help us make the decisions about the large-enrollment courses and guide us through the design of these courses. One such tool in our toolbox is learning analytics. “Learning analytics is defined as the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs” (Siemens, 2011). In other words, learning analytics can inform the design of learning experience to improve its quality.
While the importance and potential of learning analytics in course and curriculum design is obvious since it helps us make well-informed design decisions, there are different approaches to the implementation of these new instructional design processes and considerations.
- Bettinger, E., Doss, C., Loeb, S., Rogers, A., & Taylor, E. (2017). The effects of class size in online college courses: Experimental evidence. Economics of Education Review, 58,68–85. doi:10.1016/j. econedurev.2017.03.006
- Cavanaugh, J. (2005). Teaching online–A time comparison. Online Journal of Distance Learning Administration, 8(1). Retrieved from https://www.westga.edu/~distance/ojdla/spring81/cava naugh81.htm
- Lowenthal, P. R., Nyland, R., Jung, E., Dunlap, J. C., & Kepka, J. (2019). Does Class Size Matter? An Exploration into Faculty Perceptions of Teaching High-Enrollment Online Courses. American Journal of Distance Education, 33(3), 152–168
- Siemens, G. (2011, August 5). Learning and Academic Analytics. Retrieved from https://www.learninganalytics.net/uncategorized/learning-and-academic-analytics/
- Taft, S., Kesten, K., & El-Banna, M. (2019). One Size Does Not Fit All: Toward an Evidence-Based Framework for Determining Online Course Enrollment Sizes in Higher Education. Online Learning, 23(3). doi:http://dx.doi.org/10.24059/olj.v23i3.1534
- Taft, S., Perkowski, T., & Martin, L. (2011). A framework for evaluating class size in online education.Quarterly Review of Distance Education,12(3), 181–197.