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五岁儿童在二阶错误信念任务中的系统性错误源于一阶心理理论策略选择:一项计算建模研究

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

作者信息

Arslan Burcu, Taatgen Niels A, Verbrugge Rineke

机构信息

Institute of Artificial Intelligence, University of Groningen Groningen, Netherlands.

出版信息

Front Psychol. 2017 Feb 28;8:275. doi: 10.3389/fpsyg.2017.00275. eCollection 2017.

Abstract

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

摘要

二阶错误信念推理的研究重点通常是通过相关研究来探究执行功能和语言的作用。与这些研究不同的是,我们关注的问题是5岁儿童如何在二阶错误信念任务中选择和修正推理策略,为此构建了关于这一过程的两个计算认知模型:一个基于实例的学习模型和一个强化学习模型。与强化学习模型不同,基于实例的学习模型预测,在二阶错误信念任务中失败的儿童会基于一阶心理理论(ToM)推理给出答案,而不是零阶推理。我们对72名5至6岁儿童进行的实证研究证实了这一预测。结果显示,17%的答案是正确的,83%的答案是错误的。与我们的预测一致,65%的错误答案基于一阶ToM策略,而只有29%基于零阶策略(其余6%的受试者未给出任何答案)。基于我们的基于实例的学习模型,我们提出,当儿童得到“错误”的反馈时,他们会明确地将策略修正到更高水平,而不是隐含地选择现有的ToM策略之一。此外,我们预测儿童的失败是由于缺乏经验,并且随着接触二阶错误信念推理,儿童可以将其错误的一阶推理策略修正为正确的二阶推理策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1b/5329038/f2e1c4457c8b/fpsyg-08-00275-g001.jpg

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