Centre for Social Learning and Cognitive Evolution, School of Biology, University of St Andrews, St Andrews, UK.
Faculdade de Psicologia, Universidade de Lisboa, Lisbon, Portugal; School of Psychology, University of East London, London, UK.
Cognition. 2020 Aug;201:104314. doi: 10.1016/j.cognition.2020.104314. Epub 2020 May 23.
Observational learning is a form of social learning in which a demonstrator performs a target task in the company of an observer, who may as a consequence learn something about it. In this study, we approach social learning in terms of the dynamics of coordination rather than the more common perspective of transmission of information. We hypothesised that observers must continuously adjust their visual attention relative to the demonstrator's time-evolving behaviour to benefit from it. We eye-tracked observers repeatedly watching videos showing a demonstrator solving one of three manipulative puzzles before attempting at the task. The presence of the demonstrator's face and the availability of his verbal instruction in the videos were manipulated. We then used recurrence quantification analysis to measure the dynamics of coordination between the overt attention of the observers and the demonstrator's manipulative actions. Bayesian hierarchical logistic regression was applied to examine (1) whether the observers' performance was predicted by such indexes of coordination, (2) how performance changed as they accumulated experience, and (3) if the availability of speech and intentional gaze of the demonstrator mediated it. Results showed that learners better able to coordinate their eye movements with the manipulative actions of the demonstrator had an increasingly higher probability of success in solving the task. The availability of speech was beneficial to learning, whereas the presence of the demonstrator's face was not. We argue that focusing on the dynamics of coordination between individuals may greatly improve understanding of the cognitive processes underlying social learning.
观察学习是一种社会学习形式,其中演示者在观察者的陪同下执行目标任务,观察者可能因此了解到一些相关内容。在本研究中,我们从协调的动态而非更常见的信息传递角度来研究社会学习。我们假设观察者必须不断调整其视觉注意力,使其与演示者的时变行为相对应,从而从中受益。我们让观察者多次观看演示者在解决三个操纵性难题之一之前观看视频。视频中演示者的面部和口头指导的可用性被操纵。然后,我们使用递归定量分析来衡量观察者的明显注意力和演示者的操纵动作之间的协调动态。贝叶斯分层逻辑回归用于检验:(1)观察者的表现是否可以通过这些协调指标来预测;(2)随着他们积累经验,表现如何变化;(3)演示者的言语和有意注视是否介导了这一点。结果表明,更能协调观察者眼球运动与演示者操纵动作的学习者,在解决任务时成功的可能性越来越高。言语的可用性对学习有益,而演示者的面部存在则不然。我们认为,关注个体之间的协调动态可能会极大地提高我们对社会学习背后认知过程的理解。