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Title: Synthesizing Quantitative Predictors for Interaction in an Asynchronous Online Course
Authors: Zingaro, Daniel
Oztok, Murat
Hewitt, Jim
Issue Date: Jul-2012
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Zingaro, D., Oztok, M., & Hewitt, J. (2012). Synthesizing Quantitative Predictors for Interaction in an Asynchronous Online Course. In van Aalst, J., Thompson, K., Jacobson, M. J., & Reimann, P. (Eds.), The Future of Learning: Proceedings of the 10th International Conference of the Learning Sciences (ICLS 2012) – Volume 2, Short Papers, Symposia, and Abstracts (pp. 485-486). Sydney, NSW, AUSTRALIA: International Society of the Learning Sciences.
Abstract: The effectiveness and potential of asynchronous online courses hinge on sustained, purposeful collaboration. And while many factors affecting interaction have been uncovered by prior literature, there are few accounts of the relative importance of these factors when studied in the same online course. In this paper, we develop a literature-informed model of six predictors on the likelihood that a note receives a reply. We corroborate earlier findings (such as the impact of the date that the note was posted) but also obtain one contradictory result (that reading ease does not appear to be a significant predictor). We offer hypotheses for our findings and suggest future directions for this type of research.
Appears in Collections:ICLS 2012

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