Friday, October 30
2:45 PM-3:45 PM
UTC
Grand Ballroom C

Understanding Deep Learning in Asynchronous Online Discussions

Brief Paper ID: 27053
  1. Kui Xie
    Mississippi State University
  2. Fengfeng Ke
    University of New Mexico

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.

Presider: Rob Parsons, Open University (UK)

Topic

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