Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 395–423 |
| Journal | International Journal of Computer-Supported Collaborative Learning |
| Volume | 10 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 30 Nov 2015 |
| Externally published | Yes |
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Keywords
- Computer supported collaborative learning
- Dialogism
- Collaboration assessment
- Automated feedback
- Learning analytics
- Cohesion-based discourse analysis
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ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism. / Dascalu, Mihai; Trausan-Matu, Stefan; McNamara, Danielle S.; Dessus, Philippe.
In: International Journal of Computer-Supported Collaborative Learning, Vol. 10, No. 4, 30.11.2015, p. 395–423.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism
AU - Dascalu, Mihai
AU - Trausan-Matu, Stefan
AU - McNamara, Danielle S.
AU - Dessus, Philippe
PY - 2015/11/30
Y1 - 2015/11/30
N2 - As Computer-Supported Collaborative Learning (CSCL) gains a broader usage, the need for automated tools capable of supporting tutors in the time-consuming process of analyzing conversations becomes more pressing. Moreover, collaboration, which presumes the intertwining of ideas or points of view among participants, is a central element of dialogue performed in CSCL environments. Therefore, starting from dialogism and a cohesion-based model of discourse, we propose and validate two computational models for assessing collaboration. The first model is based on a cohesion graph and can be perceived as a longitudinal analysis of the ongoing conversation, thus accounting for collaboration from a social knowledge-building perspective. In the second approach, collaboration is regarded from a dialogical perspective as the intertwining or synergy of voices pertaining to different speakers, therefore enabling a transversal analysis of subsequent discussion slices.
AB - As Computer-Supported Collaborative Learning (CSCL) gains a broader usage, the need for automated tools capable of supporting tutors in the time-consuming process of analyzing conversations becomes more pressing. Moreover, collaboration, which presumes the intertwining of ideas or points of view among participants, is a central element of dialogue performed in CSCL environments. Therefore, starting from dialogism and a cohesion-based model of discourse, we propose and validate two computational models for assessing collaboration. The first model is based on a cohesion graph and can be perceived as a longitudinal analysis of the ongoing conversation, thus accounting for collaboration from a social knowledge-building perspective. In the second approach, collaboration is regarded from a dialogical perspective as the intertwining or synergy of voices pertaining to different speakers, therefore enabling a transversal analysis of subsequent discussion slices.
KW - Computer supported collaborative learning
KW - Dialogism
KW - Collaboration assessment
KW - Automated feedback
KW - Learning analytics
KW - Cohesion-based discourse analysis
U2 - 10.1007/s11412-015-9226-y
DO - 10.1007/s11412-015-9226-y
M3 - Article
VL - 10
SP - 395
EP - 423
JO - International Journal of Computer-Supported Collaborative Learning
JF - International Journal of Computer-Supported Collaborative Learning
SN - 1556-1607
IS - 4
ER -