“Model age-based” and “copy when uncertain” biases in children’s social learning of a novel task
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Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N = 140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children’s continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of model.
Wood , L A , Harrison , R A , Lucas , A J , McGuigan , N , Burdett , E R R & Whiten , A 2016 , ' “Model age-based” and “copy when uncertain” biases in children’s social learning of a novel task ' Journal of Experimental Child Psychology , vol 150 , pp. 272-284 . DOI: 10.1016/j.jecp.2016.06.005
Journal of Experimental Child Psychology
© 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
This work was supported by a John Templeton Foundation grant (40128).
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