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Assessing Collaborative Physical Tasks Via Gestural Analysis
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DOI：10.1109/THMS.2021.3051305.png)
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摘要
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Recent studies have shown that gestures are useful indicators of understanding, learning, and memory retention. However, and specially in collaborative settings, current metrics that estimate task understanding often neglect the information expressed through gestures. This work introduces the physical instruction assimilation (PIA) metric, a novel approach to estimate task understanding by analyzing the way in which collaborators use gestures to convey, assimilate, and execute physical instructions. PIA estimates task understanding by inspecting the number of necessary gestures required to complete a shared task. PIA is calculated based on the multiagent gestural instruction comparer (MAGIC) architecture, a previously proposed framework to represent, assess, and compare gestures. To evaluate our metric, we collected gestures from collaborators remotely completing the following three tasks: block assembly, origami, and ultrasound training. The PIA scores of these individuals are compared against two other metrics used to estimate task understanding: number of errors and amount of idle time during the task. Statistically significant correlations between PIA and these metrics are found. Additionally, a Taguchi design is used to evaluate PIA's sensitivity to changes in the MAGIC architecture. The factors evaluated the effect of changes in time, order, and motion trajectories of the collaborators' gestures. PIA is shown to be robust to these changes, having an average mean change of 0.45. These results hint that gestures, in the form of the assimilation of physical instructions, can reveal insights of task understanding and complement other commonly used metrics.
Keyword:
Task analysis
Collaboration
Taxonomy
Semantics
Trajectory
Pragmatics
Shape
Collaboration
gestures
knowledge representa-tion
task understanding
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