ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism


Autoria(s): Dascalu, Mihai; Trausan-Matu, Stefan; McNamara, Danielle; Dessus, Philippe
Data(s)

21/02/2016

21/02/2016

01/10/2015

Resumo

Dascalu, M., Trausan-Matu, S., McNamara, D.S., & Dessus, P. (2015). ReaderBench – Automated Evaluation of Collaboration based on Cohesion and Dialogism. International Journal of Computer-Supported Collaborative Learning, 10(4), 395–423. doi: 10.1007/s11412-015-9226-y

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.

This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.

Identificador

Dascalu, M., Trausan-Matu, S., McNamara, D.S., & Dessus, P. (2015). ReaderBench – Automated Evaluation of Collaboration based on Cohesion and Dialogism. International Journal of Computer-Supported Collaborative Learning, 10(4), 395–423. doi: 10.1007/s11412-015-9226-y

10.1007/s11412-015-9226-y

http://hdl.handle.net/1820/6483

Publicador

International Society of the Learning Sciences, Inc.

Relação

info:eu-repo/grantAgreement/EC/H2020/644187/EU/Realising an Applied Gaming Eco-system/RAGE

International Journal of Computer-Supported Collaborative Learning, 10(4), 395–423;

Palavras-Chave #Computer supported collaborative learning #Dialogism #Collaboration assessment #Automated feedback #Learning analytics #Cohesion-based discourse analysis
Tipo

article

Direitos

openAccess