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Collaboration in virtual reality (VR) across heterogeneous devices poses challenges for effectively supporting manipulation, navigation, and communication through different interfaces. We explored these in the design and development of a collaborative VR system that allows interaction through a mobile touchscreen device (Handheld User) and a head-mounted display (HMD User). In a qualitative evaluation, we further analyzed how these interfaces affect social roles and user interactions during collaboration. Our observations reveal that Handheld Users achieved presence in the virtual environment, despite the non-immersive interface, and assumed similar spatial positions in a conversational scenario as they would in the real world. In a collaborative building task, we found leadership roles not tied to immersion, but potentially influenced by users’ eye-level. Further, Handheld Users exhibited stronger movement patterns than HMD Users. Based on such behavioral patterns, we contribute a classification framework for Handheld Users that facilitates future analysis of interactions in shared virtual environments through handheld devices. Finally, we offer several design considerations for collaborative cross-device VR, which are based on our observations and exemplified in our presented system.

We present MatchNMingle, a novel multimodal/multisensor dataset for the analysis of free-standing conversational groups and speed-dates in-the-wild. MatchNMingle leverages the use of wearable devices and overhead cameras to record social interactions of 92 people during real-life speed-dates, followed by a cocktail party. To our knowledge, MatchNMingle has the largest number of participants, longest recording time and largest set of manual annotations for social actions available in this context in a real-life scenario. It consists of 2 hours of data from wearable acceleration, binary proximity, video, audio, personality surveys, frontal pictures and speed-date responses. Participants' positions and group formations were manually annotated; as were social actions (eg. speaking, hand gesture) for 30 minutes at 20fps making it the first dataset to incorporate the annotation of such cues in this context. We present an empirical analysis of the performance of crowdsourcing workers against trained annotators in simple and complex annotation tasks, founding that although efficient for simple tasks, using crowdsourcing workers for more complex tasks like social action annotation led to additional overhead and poor inter-annotator agreement compared to trained annotators (differences up to 0.4 in Fleiss' Kappa coefficients). We also provide example experiments of how MatchNMingle can be used.

International audience; Mobile devices offer great opportunities in the field of collaborative learning. They are especially interesting in their ability to provide digital information while still supporting social interactions between group members, which are essential elements of coordinated and shared activities. However, in truly mobile conditions, e.g. outdoors, the high variability of groups spatial configurations can potentially modify coordination mechanisms. We designed and tested an orienteering mobile learning game to better understand how device use shaped collaboration in highly mobile conditions. The study involved four groups of three students all equipped with tablets. We focused our analysis on the relationship between participants' arrangements (F-formations), their device usage and coordination mechanisms (i.e. awareness, regulation, information sharing, and discussion). Our results emphasize the importance of considering the transitions between arrangements more than F-formations per se. We discuss the implications of these findings for the design and analysis of mobile collaborative activities.

International audience; Mobile devices offer great opportunities in the field of collaborative learning for providing digital information while still supporting social interactions between group members. We designed and tested an orienteering mobile learning game to better understand how device use shaped collaboration in highly mobile conditions. The study involved four groups of three students all equipped with tablets. We focused our analysis on the relationship between participants’ arrangements (F- formations), their device usage and coordination mechanisms (i.e. awareness, regulation, information sharing, and discussion). Our results emphasize the importance of considering the transitions between arrangements. From these observations we derive recommendations for the design of relevant interactions techniques for mobile collaborative activities.