Validating the Automated Assessment of Participation and of Collaboration in Chat Conversations

International audienceAs Computer Supported Collaborative Learning (CSCL) gains a broader usage as a viable alternative to classic educational scenarios, the need for automated tools capable of supporting tutors in the time consuming process of analyzing conversations becomes more stringent. Moreover, in order to fully explore the benefits of such scenarios, a clear demarcation must be made between participation or active involvement, and collaboration that presumes the intertwining of ideas or points of view with other participants. Therefore, starting from a cohesion-based model of the discourse, we propose two computational models for assessing collaboration and participation. The first model is based on the cohesion graph and can be perceived as a longitudinal analysis of the ongoing conversation, thus accounting for participation from a social knowledge-building perspective. In the second approach, collaboration is regarded from a dialogical perspective as the intertwining or overlap of voices pertaining to different speakers, therefore enabling a transversal analysis of subsequent discussion slices

Voices' inter-animation detection with ReaderBench. Modelling and assessing polyphony in CSCL chats as voice synergy

International audienceStarting from dialogism in which every act is perceived as a dialogue, we shift the perspective towards multi-participant chat conversations from Computer Supported Collaborative Learning in which ideas, points of view or more generally put voices interact, inter-animate and generate the context of a conversation. Within this perspective of discourse analysis, we introduce an implemented framework, ReaderBench, for modeling and automatically evaluating polyphony that emerges as an overlap or synergy of voices. Moreover, multiple evaluation factors were analyzed for quantifying the importance of a voice and various functions were experimented to best reflect the synergic effect of co- occurring voices for modeling the underlying discourse structure

Voices' inter-animation detection with ReaderBench. Modelling and assessing polyphony in CSCL chats as voice synergy

International audienceStarting from dialogism in which every act is perceived as a dialogue, we shift the perspective towards multi-participant chat conversations from Computer Supported Collaborative Learning in which ideas, points of view or more generally put voices interact, inter-animate and generate the context of a conversation. Within this perspective of discourse analysis, we introduce an implemented framework, ReaderBench, for modeling and automatically evaluating polyphony that emerges as an overlap or synergy of voices. Moreover, multiple evaluation factors were analyzed for quantifying the importance of a voice and various functions were experimented to best reflect the synergic effect of co- occurring voices for modeling the underlying discourse structure

Dialogism: A Framework for CSCL and a Signature of Collaboration

International audienceAs Computer Supported Collaborative Learning (CSCL) gains a broader usage in multiple educational scenarios facilitated by the use of technology, the need for automated tools capable of detecting and stimulating collaboration increases. We propose a computational model using ReaderBench that assesses collaboration from a dialogical perspective. Accordingly, collaboration emerges from the intertwining of different points of view or, more specifically, from the inter-animation of voices pertaining to different speakers. Collaboration is determined from the intertwining or overlap of voices emitted by different participants throughout the ongoing conversation. This study presents a validation of this model consisting of a comparison between the output of our system and human evaluations of 10 chat conversations, selected from a corpus of more than 100 chats, in which Computer Science students debated on the advantages and disadvantages of CSCL technologies (e.g., chat, blog, wiki, forum, or Google Wave). The human evaluations of the degree of collaboration between the participants and the automated scores showed good overlap as measured by precision, recall, and F1 scores. Our overarching conclusion is that dialogism derived from the overlapping of voices can be perceived as a signature for collaboration

Technology supported collaborative learning.

"This research is supported by le ministère de l'Éducation, du Loisir et du Sport dans le cadre du Programme d'aide à la recherche sur l'enseignement et l'apprentissage (PAREA)"Titre de la couv.: Technology supported collaborative learning.Titre de l'écran-titre (visionné le 10 sept. 2009).Également disponible en format papier.Bibliogr