Socio-Semantic Network Motifs Framework for Discourse Analysis

Paper presented at LAK '22

By Bodong Chen, Xinran Zhu, Hong Shui in publications

March 13, 2022

ABSTRACT

Effective collaborative discourse requires both cognitive and social engagement of students. To investigate complex socio-cognitive dynamics in collaborative discourse, this paper proposes to model collaborative discourse as a socio-semantic network (SSN) and then use network motifs – defined as recurring, significant subgraphs – to characterize the network and hence the discourse. To demonstrate the utility of our SSN motifs framework, we applied it to a sample dataset. While more work needs to be done, the SSN motifs framework shows promise as a novel, theoretically informed approach to discourse analysis.

Posted on:
March 13, 2022
Length:
1 minute read, 90 words
Categories:
publications
Tags:
network analysis learning analytics discourse analysis
See Also:
Network Motifs as Codes
Learning Analytics for Understanding and Supporting Collaboration
Networks in Learning Analytics: Where Theory, Methodology, and Practice Intersect