The predictive relationship among the community of inquiry framework, perceived learning and online, and graduate students' course grades in online synchronous and asynchronous courses

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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.

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Rockinson-Szapkiw, A. J., Wendt, J., Wighting, M., & Nisbet, D. (2016). The predictive relationship among the community of inquiry framework, perceived learning and online, and graduate students’ course grades in online synchronous and asynchronous courses. International Review of Research in Open and Distributed Learning, 17(3), 18–35. https://doi.org/10.19173/irrodl.v17i3.2203

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