Collaborative Use of a Shared System Interface: The Role of User Gaze—Gaze Convergence Index Based on Synchronous Dual-Eyetracking

Abstract

<jats:p>Gaze convergence of multiuser eye movements during simultaneous collaborative use of a shared system interface has been proposed as an important albeit sparsely explored construct in human-computer interaction literature. Here, we propose a novel index for measuring the gaze convergence of user dyads and address its validity through two consecutive eye-tracking studies. Eye-tracking data of user dyads were synchronously recorded while they simultaneously performed tasks on shared system interfaces. Results indicate the validity of the proposed gaze convergence index for measuring the gaze convergence of dyads. Moreover, as expected, our gaze convergence index was positively associated with dyad task performance and negatively associated with dyad cognitive load. These results suggest the utility of (theoretical or practical) applications such as synchronized gaze convergence displays in diverse settings. Further research perspectives, particularly into the construct’s nomological network, are warranted.</jats:p>

The state of the art of diagnostic multiparty eye tracking in synchronous computer-mediated collaboration

“…Experimental tasks associated with CSCL included the collaborative solving of mathematical problems using educational collaboration tools (24%) and the joint creation of concept maps based on previously processed learning materials (12%). The three tasks described as artificial included a psychological change blindness task (4%; Tchanou et al, 2020) and two tangram puzzle games (8%; Dale et al, 2011;Kuriyama et al, 2011). Dimension 2: Remote Interaction.…”

“…The computation methods used in the examined studies were based on either the position or duration of gaze points (92%). Two studies performed additional calculations with pupil size data (8%; Sharma et al, 2021b;Tchanou et al, 2020). In order to compute group-level metrics, data processing followed a similar procedure based on the synchronized eye movement data of individual participants.…”

“…Most studies performed the group-level computation methods to quantify joint attention (76%). Two studies additionally operationalized the extent of joint mental effort (8%) by calculating a group's cognitive load based on synchronized pupil size data (Sharma et al, 2021b;Tchanou et al, 2020). Vrzakova et al (2021), on the other hand, also analyzed social gaze dynamics, such as mutual gaze (4%) and gaze aversion (4%).…”

“…Rather than examining the extent of visual coupling based on spatial gaze data, two studies measured the similarity in cognitive load between team members, defined as joint mental effort. Cognitive load describes the extent of cognitive resources expended while processing a task (Tchanou et al, 2020). In contrast to joint attention, mutual gaze, and gaze aversion, joint mental effort is calculated from pupil-based data, since cognitive load and pupil size are positively correlated (Sharma et al, 2021b).…”

Communication Objectives Model (COM): A Taxonomy of Face-to-Face Communication Objectives to Inform Tele-Presence Technology Adoption

“…Consider, for example, a listener's eye gaze behavior. A listener tracking and following the speaker's eye gaze onto an object is more likely to be associated with the objective of building a shared mental model as opposed to the objective of assessing the speaker's emotion (Tchanou et al, 2020), which is often associated with gaze upon facial and gestural features.…”