Student perceptions of online active learning practices and online learning climate predict online course engagement

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Abstract
Student engagement in online courses may be more ambiguous, and complex to understand than in face-to-face (FtF) classrooms settings. Without regular FtF interaction, instructors may feel unable to accurately gauge student engagement, and respond accordingly. This research explored student perceptions of online active learning practices (Koohang, Paliszkiewicz, Nord, & Ramim, 2014 Koohang, A. , Paliszkiewicz, J. , Nord, J. H. , & Ramim, M. (2014). Advancing a theoretical model for knowledge construction in e-learning. Online Journal of Applied Knowledge Management, 2, 12–25. [Google Scholar] , Advancing a theoretical model for knowledge construction in e-learning. Online Journal of Applied Knowledge Management, 2, 12–25), student uncertainty about social belonging in college (Walton & Cohen, 2011 Walton, G. M. , & Cohen, G. L. (2011). A brief social-belonging intervention improves academic and health outcomes of minority students. Science, 331, 1447–1451. doi: 10.1126/science.1198364 [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] , A brief social-belonging intervention improves academic and health outcomes of minority students. Science, 331, 1447–1451. doi: 10.1126/science.1198364) and a course’s online learning climate (Kaufmann, Sellnow, & Frisby, 2016 Kaufmann, R. , Sellnow, D. D. , & Frisby, B. N. (2016). The development and validation of the online learning climate scale (OLCS). Communication Education, 65, 307–321. doi: 10.1080/03634523.2015.1101778 [Taylor & Francis Online], [Web of Science ®] , [Google Scholar] , The development and validation of the online learning climate scale (OLCS). Communication Education, 65, 307–321. doi: 10.1080/03634523.2015.1101778), as potential predictors of online student engagement. Results from hierarchical multiple regression models provide evidence of the predictive potential for these elements on online student engagement. Some possible evidence for the predictive potential of student GPA and age is provided as well. Implications of these findings, and future research opportunities are discussed.

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