Abstract:
Closed campuses, working remotely, and physical distancing have changed the way we work, teach, learn, shop, attend conferences, and interact with family and friends. But the Covid-19 pandemic has not changed what we know about creating high-end online education. Two decades of research has shown that online education often fails to fulfill its promise, and the emergency shift to remote instruction has, for many, justified their distrust and dislike of online learning. Low interactivity remains a widely recognized short-coming of current online offerings. Low interactivity results, in part, from many faculty not feeling comfortable being themselves online. The long-advocated for era of authentic assessments is needed now more than ever. Finally, greater support is needed for both underrepresented students and for faculty to move beyond basic online instruction to create a strong continuum of care between the teaching and learning environment and the student support infrastructure. For those who have been long-term champions of online education, it has never been more important to confront the three biggest challenges that continue to haunt online education – interactivity, authenticity, and support. Only by confronting these challenges squarely can instructors, educational developers, and their institutions take huge steps towards better online instruction in the midst of a pandemic and make widespread, high-quality online education permanently part of the “new normal.”
Abstract:
The Community of Inquiry framework has been widely supported by research to provide a model of online learning that informs the design and implementation of distance learning courses. However, the relationship between elements of the CoI framework and perceived learning warrants further examination as a predictive model for online graduate student success. A predictive correlational design and hierarchical multiple regression was used to investigate relationships between community of inquiry factors and perceived learning to determine the predictive validity of these variables for students' course points (N = 131), while controlling for demographic and course variables. The results of this study clearly supported the foundational constructs of Community of Inquiry (CoI) theory (Garrison et al., 2000) and the role of perceived learning to predict final course points. The entire predictive model explained 55.6% of the variance in course points. Implications, limitations, and recommendations are discussed.