Abstract
We present WoNoWa, a novel multi-modal dataset of small group interactions in collaborative tasks. The dataset is explicitly designed to elicit and to study over time a Transactive Memory System (TMS), a group's emergent state characterizing the group's meta-knowledge about "who knows what". A rich set of automatic features and manual annotations, extracted from the collected audio-visual data, is available on request for research purposes. Features include individual descriptors (e.g., position, Quantity of Motion, speech activity) and group descriptors (e.g., F-formations). Additionally, participants' self-assessments are available. Preliminary results from exploratory analyses show that the WoNoWa design allowed groups to develop a TMS that increased across the tasks. These results encourage the use of the WoNoWa dataset for a better understanding of the relationship between behavioural patterns and TMS, that in turn could help to improve group performance.
Author supplied keywords
Cite
CITATION STYLE
Biancardi, B., Maisonnave-Couterou, L., Renault, P., Ravenet, B., Mancini, M., & Varni, G. (2020). The WoNoWa Dataset: Investigating the Transactive Memory System in Small Group Interactions. In ICMI 2020 - Proceedings of the 2020 International Conference on Multimodal Interaction (pp. 528–537). Association for Computing Machinery, Inc. https://doi.org/10.1145/3382507.3418843
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.