Contribution of Learner–Instructor Interaction to Sense of Community in Graduate Online Education
Instructors striving to facilitate the building of community in online courses must make evidence-based decisions in choosing the most effective interaction types during the course-design process. The study reported in this paper sought to identify which types of interaction contribute most to students’ sense of community (SoC) in online graduate courses at a regional comprehensive university. Rovai’s Classroom Community Scale was used to measure SoC, and Likert-scale questions were employed to measure frequency and perceived importance of seven kinds of learner–instructor interaction. The results indicate that the interactions that are most predictive of SoC include instructor modeling, support and encouragement, facilitating discussions, multiple communication modes, and required participation. Instructor modeling was found to offer the greatest yield to instructors as a balance between effort and benefit. Implications for online course design are discussed.
MERLOT Journal of Online Learning and Teaching
