Projects per year
The massive student participation in Computer Supported Collaborative Learning (CSCL) sessions from online classrooms requires intense tutor engagement to track and evaluate individual student participation. In this study, we investigate how the time evolution of messages predicts students’ participation using two models – a linear regression and a Random Forest model. A corpus of 10 chats involving 47 students was scored by 4 human experts and used to evaluate our models. Our analysis shows that students’ pauses length between consecutive messages within a discussion is the strongest participation predictor accounting for R2 ¼ :796 variance in the human estimations while using a Random Forest model. Our results provide an extended basis for the automated assessment of student participation in collaborative online discussions.
|Title of host publication||The Interplay of Data, Technology, Place and People for Smart Learning|
|Subtitle of host publication||Proceedings of the 3rd International Conference on Smart Learning Ecosystems and Regional Development|
|Editors||Hendrik Knoche, Elvira Popescu, Antonio Cartelli|
|Number of pages||9|
|Publication status||Published - 1 Jun 2018|
|Event||3rd Int. Conf. on Smart Learning Ecosystems and Regional Development (SLERD 2018): The Interplay of Data, Technology, Place and People for Smart Learning - Aalborg, Denmark|
Duration: 23 May 2018 → 25 May 2018
|Series||Smart Innovation, Systems and Technologies (SIST)|
|Conference||3rd Int. Conf. on Smart Learning Ecosystems and Regional Development (SLERD 2018)|
|Period||23/05/18 → 25/05/18|
- Time series analysis
- Automated evaluation of participation
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- 1 Finished
Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19