Annotations of maps in collaborative work at a distance

This thesis inquires how map annotations can be used to sustain remote collaboration. Maps condense the interplay of space and communication, solving linguistic references by linking conversational content to the actual places to which it refers. This is a mechanism people are accustomed to. When we are face-to-face, we can point to things around us. However, at a distance, we need to recreate a context that can help disambiguate what we mean. A map can help recreate this context. However other technological solutions are required to allow deictic gestures over a shared map when collaborators are not co-located. This mechanism is here termed Explicit Referencing. Several systems that allow sharing maps annotations are reviewed critically. A taxonomy is then proposed to compare their features. Two filed experiments were conducted to investigate the production of collaborative annotations of maps with mobile devices, looking for the reasons why people might want to produce these notes and how they might do so. Both studies led to very disappointing results. The reasons for this failure are attributed to the lack of a critical mass of users (social network), the lack of useful content, and limited social awareness. More importantly, the study identified a compelling effect of the way messages were organized in the tested application, which caused participants to refrain from engaging in content-driven explorations and synchronous discussions. This last qualitative observation was refined in a controlled experiment where remote participants had to solve a problem collaboratively, using chat tools that differed in the way a user could relate an utterance to a shared map. Results indicated that team performance is improved by the Explicit Referencing mechanisms. However, when this is implemented in a way that is detrimental to the linearity of the conversation, resulting in the visual dispersion or scattering of messages, its use has negative consequences for collaborative work at a distance. Additionally, an analysis of the eye movements of the participants over the map helped to ascertain the interplay of deixis and gaze in collaboration. A primary relation was found between the pair's recurrence of eye movements and their task performance. Finally, this thesis presents an algorithm that detects misunderstandings in collaborative work at a distance. It analyses the movements of collaborators' eyes over the shared map, their utterances containing references to this workspace, and the availability of "remote" deictic gestures. The algorithm associates the distance between the gazes of the emitter and gazes of the receiver of a message with the probability that the recipient did not understand the message.

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