Limits...
Look together: analyzing gaze coordination with epistemic network analysis.

Andrist S, Collier W, Gleicher M, Mutlu B, Shaffer D - Front Psychol (2015)

Bottom Line: In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice.We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows.In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Sciences, University of Wisconsin-Madison Madison, WI, USA.

ABSTRACT
When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique-epistemic network analysis-to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1) properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2) optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3) differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

No MeSH data available.


Center: Each circular point represents the centroid of a network for one dyad in a particular phase, collapsed across all reference-action sequences produced by that dyad. The centroid of the mean network for each phase is also plotted as a solid square surrounded by a larger square denoting the confidence interval. A cyclical relationship through the ENA space can be observed. Boxes in periphery: The mean network for each of the five sequences is fully plotted. A representative timeline of an example gaze sequence from the raw gaze data is shown beneath the mean networks to illustrate each phase. A view of the worker's and instructor's scan paths in that phase (same data as in the timeline) is also shown.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4508484&req=5

Figure 3: Center: Each circular point represents the centroid of a network for one dyad in a particular phase, collapsed across all reference-action sequences produced by that dyad. The centroid of the mean network for each phase is also plotted as a solid square surrounded by a larger square denoting the confidence interval. A cyclical relationship through the ENA space can be observed. Boxes in periphery: The mean network for each of the five sequences is fully plotted. A representative timeline of an example gaze sequence from the raw gaze data is shown beneath the mean networks to illustrate each phase. A view of the worker's and instructor's scan paths in that phase (same data as in the timeline) is also shown.

Mentions: We analyzed the entirety of our collected data using ENA (Figure 3). For our first analysis, we considered each dyad (n = 26; 13 dyads × two interactions each) and phase (n = 5; pre-reference, reference, post-reference, action, or post-action) as the units of analysis. Each point in the central plot of Figure 3 represents the centroid of a network for a single dyad's interaction in one of the five phases, collapsed across all reference-action sequences that occurred in the interaction. Solid squares represent the centroid of the mean network for all dyads in each of the five phases. These mean network centroids are surrounded by squares representing the confidence interval along both dimensions. A clear separation between each of the five phases can be observed, indicating that the patterns of gaze coordination are significantly different in each of the five phases. We can also observe a clear cyclical pattern through the two-dimensional ENA space as we progress through each of the five phases in the reference-action sequence.


Look together: analyzing gaze coordination with epistemic network analysis.

Andrist S, Collier W, Gleicher M, Mutlu B, Shaffer D - Front Psychol (2015)

Center: Each circular point represents the centroid of a network for one dyad in a particular phase, collapsed across all reference-action sequences produced by that dyad. The centroid of the mean network for each phase is also plotted as a solid square surrounded by a larger square denoting the confidence interval. A cyclical relationship through the ENA space can be observed. Boxes in periphery: The mean network for each of the five sequences is fully plotted. A representative timeline of an example gaze sequence from the raw gaze data is shown beneath the mean networks to illustrate each phase. A view of the worker's and instructor's scan paths in that phase (same data as in the timeline) is also shown.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508484&req=5

Figure 3: Center: Each circular point represents the centroid of a network for one dyad in a particular phase, collapsed across all reference-action sequences produced by that dyad. The centroid of the mean network for each phase is also plotted as a solid square surrounded by a larger square denoting the confidence interval. A cyclical relationship through the ENA space can be observed. Boxes in periphery: The mean network for each of the five sequences is fully plotted. A representative timeline of an example gaze sequence from the raw gaze data is shown beneath the mean networks to illustrate each phase. A view of the worker's and instructor's scan paths in that phase (same data as in the timeline) is also shown.
Mentions: We analyzed the entirety of our collected data using ENA (Figure 3). For our first analysis, we considered each dyad (n = 26; 13 dyads × two interactions each) and phase (n = 5; pre-reference, reference, post-reference, action, or post-action) as the units of analysis. Each point in the central plot of Figure 3 represents the centroid of a network for a single dyad's interaction in one of the five phases, collapsed across all reference-action sequences that occurred in the interaction. Solid squares represent the centroid of the mean network for all dyads in each of the five phases. These mean network centroids are surrounded by squares representing the confidence interval along both dimensions. A clear separation between each of the five phases can be observed, indicating that the patterns of gaze coordination are significantly different in each of the five phases. We can also observe a clear cyclical pattern through the two-dimensional ENA space as we progress through each of the five phases in the reference-action sequence.

Bottom Line: In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice.We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows.In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Sciences, University of Wisconsin-Madison Madison, WI, USA.

ABSTRACT
When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique-epistemic network analysis-to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1) properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2) optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3) differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

No MeSH data available.