Projects per year
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.
|Journal||Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science|
|Publication status||Published - Oct 2017|
- Computer Supported Collaborative Learning
- pause analysis
- automatic evaluation of participation and collaboration
Denisleam (Molomer), S., Dascalu, M., & Trausan-Matu, S. (2017). Predicting Collaboration based on Students' Pauses in Online CSCL Conversations. Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science, 79(2), 83-92. https://www.researchgate.net/publication/320430956_Predicting_collaboration_based_on_students'_pauses_in_online_CSCL_conversations