Knowledge Co-Construction in Online Learning

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A01=Charlotte Nirmalani Gunawardena
A01=Damien M. Sanchez
A01=Nick V. Flor
advanced social learning analytics methods
Author_Charlotte Nirmalani Gunawardena
Author_Damien M. Sanchez
Author_Nick V. Flor
Category=JNAM
Category=JNC
Category=JNM
Category=JNQ
Category=JNU
computer-supported collaborative learning
computers & technology
distance education
educational data mining
educational psychology
eLearning
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
higher education
instructional design research
open education
qualitative quantitative analysis
research
sociocultural learning theory
sociology of education
technology in education
theories of learning
virtual classroom dynamics

Product details

  • ISBN 9781032349190
  • Weight: 613g
  • Dimensions: 178 x 254mm
  • Publication Date: 18 Apr 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Knowledge Co-Construction in Online Learning is a comprehensive, foundational resource that explores the study of social construction of knowledge through platforms, social dynamics, and other aspects of today’s technology-enhanced education. The interactive spaces, from formal computer-supported collaborative learning settings to informal social media-integrative environments, that comprise asynchronous online learning offer a rich source of data for analyzing teaching and learning. How, then, can researchers and designers in educational technology, instructional design, the learning sciences, and beyond most effectively analyze the content and data generated by these complex co-creations of knowledge?

Grounded in sociocultural and social constructivist theories of learning and driven by the globally renowned Interaction Analysis Model, this book applies statistical and computational methods to study the group interactions and social networks that yield newly constructed knowledge during virtual learning experiences. Its unique Social Learning Analytic Methods enhance the analysis of social dynamics that support knowledge construction so often missing from mainstream learning analytics. Holistic and cyclical in its approach to online learning experiences, this essential volume written for novice and experienced researchers transcends the field’s research paradigm conflicts, blends qualitative and quantitative approaches with new digital media tools, and exemplifies how research questions and designs can incorporate and automate evolving forms of inquiry.

Charlotte Nirmalani Gunawardena is Distinguished Professor Emerita of Online Education and Instructional Technology in the Organization, Information, and Learning Sciences Program at the University of New Mexico, USA.

Nick V. Flor is Associate Professor of Information Systems in the Anderson School of Management at University of New Mexico, USA.

Damien M. Sánchez is the owner of Puerta Abierta Performance Consulting, Associate with the Return on Investment Institute, and Adjunct Faculty in the Organization, Information, and Learning Sciences Program at the University of New Mexico, USA.

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