How to Categorize Collaboration During a Collaborative Puzzle-Solving Task? Validation of Collaboration Profiles Using Multimodal Data in Virtual Reality Context

DOI

The following dataset presents 11 collaborative scenarios during a dyadic collaborative puzzle-solving task in VR. Each scenario represents specific collaboration profiles and their implication in the realisation of the collaborative task.

The data was recorded using the Microsoft \psi framework. This framework allows the synchronization and recording of multimodal data. One of the advantages of this framework is that datasets can be replayed and processed as if they were currently being recorded. This feature makes it possible to test the effectiveness of tools or methods for evaluating collaboration processes in real time. This functionality is the reason why we share datasets in the format specific to the data acquisition framework.

The datasets comes with sample code and documentation, so that researchers can exploit the dataset. Researchers can also generate CSV or JSON files when replaying the dataset. Examples are provided in the sample code.

\psi, 0.18.72.1-beta

Identifier
DOI https://doi.org/10.57745/EXEE2Z
Related Identifier IsCitedBy https://doi.org/10.1145/3710996
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/EXEE2Z
Provenance
Creator Léchappé, Aurelien ORCID logo; Fleury, Cédric ORCID logo; Chollet, Mathieu ORCID logo; Dumas, Cédric ORCID logo
Publisher Recherche Data Gouv
Contributor Léchappé, Aurelien; Laboratoire des Sciences du Numérique de Nantes; IMT Atlantique; Centre National de la Recherche Scientifique; Entrepôt-Catalogue Recherche Data Gouv
Publication Year 2025
Funding Reference Région Pays de la Loire 2021-12881 ; Agence Nationale de la Recherche ANR-20-CE33-0007
Rights etalab 2.0; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/etalab-2.0.html
OpenAccess true
Contact Léchappé, Aurelien (IMT Atlantique, LS2N, UMR CNRS 6004, Lab-STICC, UMR CNRS 6285)
Representation
Resource Type Dataset
Format application/zip; text/plain
Size 747148148; 23267
Version 1.0
Discipline Computer Science; ['dyadic data analysis']; ['collaborative process']; ['virtual reality']; ['puzzles']