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Understanding Deep Learning in Asynchronous Online Discussions
PROCEEDINGS

, Mississippi State University, United States ; , University of New Mexico, United States

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Vancouver, Canada ISBN 978-1-880094-76-1 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

Abstract

Asynchronous online discussions provide opportunities for communication and interactions among students and instructors in distance education to collaborate on knowledge construction learning activities. Although the text records of the discussion content allow instructors and researchers to perceive students’ learning behaviors, the need for an analytical framework to investigate students’ knowledge construction and deep learning in collaborative learning activities is obvious. This paper introduces an Online Learning Interaction Model that captures the knowledge construction and deep learning aspects of collaborative learning in asynchronous online discussions. 68 students participated in asynchronous online discussions in this study. Their discussion contents were coded and analyzed.

Citation

Xie, K. & Ke, F. (2009). Understanding Deep Learning in Asynchronous Online Discussions. In T. Bastiaens, J. Dron & C. Xin (Eds.), Proceedings of E-Learn 2009--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 3262-3266). Vancouver, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved July 20, 2019 from .

Keywords