Open AccessUsing a three-layered social-cognitive network analysis framework for understanding online collaborative discussions
Author(s) -
Fan Ouyang,
Xinyu Dai
Publication year - 2021
Publication title -
australasian journal of educational technology
Language(s) - English
Resource type - Journals
eISSN - 1449-5554
pISSN - 1449-3098
DOI - 10.14742/ajet.7166
Subject(s) - social network analysis , online discussion , learning analytics , psychology , collaborative learning , social learning , citizen journalism , summative assessment , perspective (graphical) , student engagement , cognition , social network (sociolinguistics) , agency (philosophy) , social media , mathematics education , pedagogy , sociology , computer science , formative assessment , data science , world wide web , social science , artificial intelligence , neuroscience
Understanding the relationship between social and cognitive engagement has critical implications for collaborative learning theory, pedagogy and analytics. This study proposed a three-layered social-cognitive network analysis framework for examining the relationship between students’ social and cognitive engagement from summative, epistemic and micro-level perspectives within online collaborative discussions. A multi-method approach was used, consisting of social network analysis, quantitative content analysis, statistical analysis, epistemic network analysis and social-cognitive network visualisation. The results showed that from a summative perspective, students’ social participatory roles were critical indicators of their level of cognitive engagement. From an epistemic perspective, socially active students tended to shift towards more group-level cognitive structure, while inactive students showed a decreasing individual-level cognitive structure throughout the discussion duration. From a micro-level perspective, a large proportion of individual students showed continually changing social participatory roles with fluctuating cognitive engagement levels. The findings have implications for collaborative learning theory, pedagogy support and learning analytics.
Implications for practice or policy:
Researchers can use the three-layered social-cognitive network analysis framework to examine student engagement.
Instructors should encourage student agency for facilitating high-quality online collaborative discussion.
Instructors should consider students’ different engagement levels in online discussions.