Co-actors represent each other's task regularity through social statistical learning

心理学 任务(项目管理) 考试(生物学) 动作(物理) 交错 认知心理学 社会心理学 序列(生物学) 计算机科学 量子力学 经济 生物 操作系统 古生物学 物理 遗传学 管理
作者
Zheng Zheng,Jun Wang
出处
期刊:Cognition [Elsevier]
卷期号:235: 105411-105411 被引量:2
标识
DOI:10.1016/j.cognition.2023.105411
摘要

Numerous joint action studies have demonstrated that certain low-level aspects (e.g., stimuli and responses) of a co-actor's task can be automatically and implicitly represented by us as actors, biasing our own task performance in a joint action setup. However, it remains unclear whether individuals also represent more abstract, high-level aspects of a co-actor's task, such as regularity. In the first five experiments, participants participated alongside their co-actors and responded to a mixed shape sequence generated by randomly interleaving two fixed order sequences of shapes in both the pre- and post-test sessions. But different intermediate practice sessions were undergone by participants across experiments. When practicing their own fixed order sequences in a mixed shape sequence, either together with another person (Experiment 1) or alone but informed that their partner was performing the same practice task in a different room (Experiment 4), participants exhibited a learning effect on their co-actors' practiced sequences. This indirect learning effect was absent when one of the co-actors did not participate due to either being removed from the practice (Experiment 2) or sitting still without offering responses (Experiment 3), as well as when the two co-actors practiced together but responded to two distinct properties of stimuli (e.g., colour and shape, respectively), with one having regularity and the other not. Finally, participants exhibited comparable direct learning effects on their own practiced sequences for Experiments 1-5 as when performing the pre-test, practice, and post-test sessions alone for Experiment 6. These results demonstrate that, when practicing together, or even when believing that they are acting together with a partner, co-actors do represent the task regularity of one another through social statistical learning and transfer this learned regularity to subsequent task performances. The present study extends our understanding of co-representation in the joint action context in terms of the more abstract and high-level task features people co-represent, such as a co-actor's task regularity.
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