Marc-Antoine Nüssli

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This paper presents an algorithm that detects misunderstandings in collaborative work at a distance. It analyses the movements of collaborators' eyes on the shared workspace, their utterances containing references about this workspace, and the availability of 'remote' deictic gestures. This method is based on two findings: 1. participants look at the points(More)
In an empirical study, eye-gaze patterns of pairs of students were recorded and analyzed in a remote situation where they had to build a concept map collaboratively. They were provided (or not), with a knowledge awareness tool that provided learner A with learner B's level of knowledge measured through a pre-test. Previous results showed that the awareness(More)
This study aims to explore the possibility of using machine learning techniques to build predictive models of performance in collaborative induction tasks. More specifically, we explored how signal-level data, like eye-gaze data and raw speech may be used to build such models. The results show that such low level features have effectively some potential to(More)
We present a dual eye-tracking study that demonstrates the effect of sharing selection among collaborators in a remote pair-programming scenario. Forty pairs of engineering students completed several program understanding tasks while their gaze was synchronously recorded. The coupling of the programmers' focus of attention was measured by a cross-recurrence(More)
The use of dual eye-tracking is investigated in a collabora tive game setting. The automatic collection of information about partner's gaze will eventually serve to build adaptive interfaces. Following this agenda, and in order to identify stable gaze patterns, we investigate the impact of social and task related context upon individual gaze and action(More)
In the present study, participants working in dyads were asked to build a concept map collaboratively. While interacting, they were able to access visualizations (individual concept maps) of both their own and their partner's prior knowledge (own and peer maps). Eye movements of both learning partners were recorded during the course of collaboration. Our(More)
Little is known of the interplay between deixis and eye movements in remote collaboration. This paper presents quantitative results from an experiment where participant pairs had to collaborate at a distance using chat tools that differed in the way messages could be enriched with spatial information from the map in the shared workspace. We studied how the(More)