Please use this identifier to cite or link to this item:
Title: Detecting Micro-Creativity in CSCL Chats
Authors: Trausan-Matu, Stefan
Keywords: CSCL
Issue Date: 2022
Publisher: International Society of the Learning Sciences
Citation: Trausan-Matu, S. (2022). Detecting micro-creativity in CSCL chats. In Weinberger, A. Chen, W., Hern├índez-Leo, D., & Chen, B. (Eds.), Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022 (pp. 601-602). International Society of the Learning Sciences.
Abstract: The paper presents an approach for detecting micro-creativity moments in CSCL chats, starting from the polyphonic model, which considers important concepts in the conversation as voices, which enter into inter-animations generated by divergent and convergent utterances. The main idea is that micro-creativity moments take place when several divergences among the voices are followed by a convergence. Four experimental implementations of the detection of the divergent and convergent utterances using artificial intelligence are introduced.
Description: Poster
Appears in Collections:ISLS Annual Meeting 2022

Files in This Item:
File SizeFormat 
CSCL2022_601-602.pdf435.94 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.