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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.


Right: Each circular point represents the centroid of a network for one dyad in a particular phase with or without a repair occurring in the reference-action sequence. 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. Left: The difference in mean networks between repair and no-repair for each of the first three phases (pre-reference, reference, and post-reference).
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Figure 6: Right: Each circular point represents the centroid of a network for one dyad in a particular phase with or without a repair occurring in the reference-action sequence. 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. Left: The difference in mean networks between repair and no-repair for each of the first three phases (pre-reference, reference, and post-reference).

Mentions: For this analysis, we included “repair” (n = 2; repair or no-repair) as another unit of analysis in addition to the “dyad” and “phase” units we had before. As can be observed in Figure 6, gaze networks are significantly different between repair and no-repair along the y-axis for each of the first three phases in the reference-action sequence. The centroids of the mean networks (solid squares) for these phases are separated along the y-axis, and there is little vertical overlap in their confidence intervals. These phases, which occur before or during any possible repair, are thus potentially distinguishable along this dimension.


Look together: analyzing gaze coordination with epistemic network analysis.

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

Right: Each circular point represents the centroid of a network for one dyad in a particular phase with or without a repair occurring in the reference-action sequence. 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. Left: The difference in mean networks between repair and no-repair for each of the first three phases (pre-reference, reference, and post-reference).
© Copyright Policy
Related In: Results  -  Collection

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

Figure 6: Right: Each circular point represents the centroid of a network for one dyad in a particular phase with or without a repair occurring in the reference-action sequence. 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. Left: The difference in mean networks between repair and no-repair for each of the first three phases (pre-reference, reference, and post-reference).
Mentions: For this analysis, we included “repair” (n = 2; repair or no-repair) as another unit of analysis in addition to the “dyad” and “phase” units we had before. As can be observed in Figure 6, gaze networks are significantly different between repair and no-repair along the y-axis for each of the first three phases in the reference-action sequence. The centroids of the mean networks (solid squares) for these phases are separated along the y-axis, and there is little vertical overlap in their confidence intervals. These phases, which occur before or during any possible repair, are thus potentially distinguishable along this dimension.

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.