[2305.16262] Understanding Idea Creation in Collaborative Discourse through Networks: The Joint Attention-Interaction-Creation (AIC) Framework
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Computers and Society

arXiv:2305.16262 (cs)
[Submitted on 25 May 2023]

Title:Understanding Idea Creation in Collaborative Discourse through Networks: The Joint Attention-Interaction-Creation (AIC) Framework

Authors:Xinran Zhu, Bodong Chen
View PDF
Abstract:In Computer-Supported Collaborative Learning, ideas generated through collaborative discourse are informative indicators of students' learning and collaboration. Idea creation is a product of emergent and interactive socio-cognitive endeavors. Therefore, analyzing ideas requires capturing contextual information in addition to the ideas themselves. In this paper, we propose the Joint Attention-Interaction-Creation (AIC) framework, which captures important dynamics in collaborative discourse, from attention and interaction to creation. The framework was developed from the networked lens, informed by natural language processing techniques, and inspired by socio-semantic network analysis. A case study was included to exemplify the framework's application in classrooms and to illustrate its potential in broader contexts.
Subjects: Computers and Society (cs.CY); Social and Information Networks (cs.SI)
Cite as: arXiv:2305.16262 [cs.CY]
  (or arXiv:2305.16262v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2305.16262
Journal reference: Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023

Submission history

From: Xinran Zhu [view email]
[v1] Thu, 25 May 2023 17:18:19 UTC (364 KB)
Full-text links:

Access Paper:

  • View PDF
  • Other Formats
license icon view license
Current browse context:
cs.CY
< prev   |   next >
new | recent | 2023-05
Change to browse by:
cs
cs.SI

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)