Open Universiteit

Please use this identifier to cite or link to this item:
Title: Predicting Collaboration based on Students' Pauses in Online CSCL Conversations
Authors: Denisleam, Sibel
Dascalu, Mihai
Trausan-Matu, Stefan
Keywords: Computer Supported Collaborative Learning
pause analysis
automatic evaluation of participation and collaboration
Issue Date: Oct-2017
Publisher: University Politehnica of Bucharest
Citation: Denislam, S., Dascalu, M., & Trausan-Matu, S. (2017). Predicting Collaboration based on Students' Pauses in Online CSCL Conversations. University Politehnica of Bucharest Scientific Bulletin Series C-Electrical Engineering and Computer Science, 79(2), 83–92.
Abstract: As Computer Supported Collaborative Learning (CSCL) gains a broader usage as a viable alternative to traditional educational scenarios, the need for automated tools capable of evaluating active participation and collaboration among peers in online discussions increases. In this study, we validate a quantitative model of predicting involvement in CSCL chats based on student’s pauses throughout the timeline of the conversation. Starting from a corpus of 10 chat conversations, our proposed model explains 55% of the variance in terms of student participation and 42% in terms of collaboration, although relying on simple quantitative indices.
Appears in Collections:1. RAGE Publications

Files in This Item:
File Description SizeFormat 
full8e5_282026.pdf620.24 kBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons