2021
DOI: 10.1037/xhp0000935
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Interpersonal coordination in joint multiple object tracking.

Abstract: People often perform visual tasks together, for example, when looking for a misplaced key. When performing such tasks jointly, people coordinate their actions to divide the labor, for example, by looking for the misplaced key in different rooms. This way, they tend to perform better together than individually-they attain a group benefit. A crucial factor determining whether (and to what extent) individuals attain a group benefit is the amount of information they receive about each other's actions and performan… Show more

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Cited by 3 publications
(11 citation statements)
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“…If this was true, the same drop in selected targets should occur if the first Solo condition was followed by a second Solo (rather than Joint) condition, because participants should be equally fatigued over time. We addressed this possibility by drawing on data from an earlier study conducted by the first author ( [17]; see "No Information" condition). In that study, 32 participants performed the same MOT task as in the present study for 100 trials; the present study consisted of 75 trials in total.…”
Section: Plos Onementioning
confidence: 99%
See 1 more Smart Citation
“…If this was true, the same drop in selected targets should occur if the first Solo condition was followed by a second Solo (rather than Joint) condition, because participants should be equally fatigued over time. We addressed this possibility by drawing on data from an earlier study conducted by the first author ( [17]; see "No Information" condition). In that study, 32 participants performed the same MOT task as in the present study for 100 trials; the present study consisted of 75 trials in total.…”
Section: Plos Onementioning
confidence: 99%
“…We addressed this question by conducting two behavioral experiments in which participants performed a multiple object tracking (MOT) task [15]. We chose this task because it has been reliably used in earlier research to test the limitations of attentional processing [16] and to investigate human-human [17] as well as human-AI collaborations [18,19]. In the MOT task, participants are required to track a subset of moving target objects among distractor objects on a computer screen.…”
Section: Introductionmentioning
confidence: 99%
“…This task was chosen because it is frequently used to investigate the limits of attentional processing (Alvarez & Franconeri, 2007 ). Moreover, it has been previously used in studies on human–human (Wahn et al, 2021a ) and human–computer collaboration (Wahn & Kingstone, 2021 ; Wahn et al, 2021b ). In the MOT task, participants are asked to track a subset of moving target objects among distractor objects on a computer screen.…”
Section: Introductionmentioning
confidence: 99%
“…This task is ideal for linear modeling as it allows one to systematically vary a wide range of factors, which have been found to be relevant for group benefits in several joint tasks (such as the availability of individual performance feedback, team performance feedback, or information about the performed actions of group members) (Wahn et al., 2018c , b ). Also, the coordination mechanisms in the joint MOT task are well understood (Wahn et al., 2017 , 2021 ). From past studies we know that group members devise efficient labor division strategies within only a few trials, and that these divisions are very frequently of a left-right nature (Wahn et al., 2017 ) such that group members use the midpoint of the screen as an external reference to divide the labor into left targets (tracked by one co-actor) and right targets (tracked by the other co-actor).…”
Section: Introductionmentioning
confidence: 99%
“…In the present study, we thus apply a linear modeling approach on our data from an extensive, eight experiment study, using a between-subjects design to examine the abovementioned factors’ impact on group benefits in a joint MOT task (Wahn et al., 2021 ). In particular, we assessed 1) how much variance factors explain collectively ( 1st Modeling Objective ), 2) to what extent they are redundant or complementary in their explanatory power ( 2nd Modeling Objective ), and 3) investigate the performance of the model in predicting group benefits on a separate test data set, which was not used when fitting the model, to assess the model’s potential to anticipate future group benefits ( 3rd Modeling Objective ).…”
Section: Introductionmentioning
confidence: 99%