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

Date

March 13, 2022

Time

12:00 AM

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