%0 Journal Article
%@ 2369-3762
%I JMIR Publications
%V 5
%N 1
%P e10464
%T Faculty and Student Interaction in an Online Master’s Course: Survey and Content Analysis
%A Aylwin,Christopher
%+ Imperial College Healthcare NHS Trust, Praed Street, London, W2 1NY, United Kingdom, 44 2033125865, c.aylwin@imperial.ac.uk
%K online learning
%K faculty & student interaction
%K Community of Inquiry
%K medicine
%D 2019
%7 4.4.2019
%9 Original Paper
%J JMIR Med Educ
%G English
%X Background: The provision of online educational courses has soared since the creation of the World Wide Web, with most universities offering some degree of distance-based programs. The social constructivist pedagogy is widely accepted as the framework to provide education, but it largely relies on the face-to-face presence of students and faculty to foster a learning environment. The concern with online courses is that this physical interaction is removed, and therefore learning may be diminished. Objective: The Community of Inquiry (CoI) is a framework designed to support the educational experience of such courses. This study aims to examine the characteristics of the CoI across the whole of an entirely online master’s course. Methods: This research used a case study method, using a convergent parallel design to study the interactions described by the CoI model in an online master’s program. The MSc program studied is a postgraduate medical degree for doctors or allied health professionals. Different data sources were used to corroborate this dataset including content analysis of both asynchronous and synchronous discussion forums. Results: This study found that a CoI can be created within the different learning activities of the course. The discussion forums integral to online courses are a rich source of interaction, with the ability to promote social interaction, teaching presence, and cognitive learning. Conclusions: The results show that meaningful interaction between faculty and student can be achieved in online courses, which is important to ensure deep learning and reflection. 
%M 30958274
%R 10.2196/10464
%U http://mededu.jmir.org/2019/1/e10464/
%U https://doi.org/10.2196/10464
%U http://www.ncbi.nlm.nih.gov/pubmed/30958274