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.
|Original language||English (US)|
|Title of host publication||LAK 2022 - Conference Proceedings|
|Subtitle of host publication||Learning Analytics for Transition, Disruption and Social Change - 12th International Conference on Learning Analytics and Knowledge|
|Publisher||Association for Computing Machinery|
|Number of pages||7|
|State||Published - Mar 21 2022|
|Event||12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022 - Virtual, Online, United States|
Duration: Mar 21 2022 → Mar 25 2022
|Name||ACM International Conference Proceeding Series|
|Conference||12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022|
|Period||3/21/22 → 3/25/22|
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