用潜在马尔可夫模型测试 3 岁幼儿在基于规则的反馈学习任务中的策略使用情况

IF 5.3 3区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Multivariate Behavioral Research Pub Date : 2024-11-01 Epub Date: 2023-02-10 DOI:10.1080/00273171.2023.2170963
L Lichtenberg, I Visser, M E J Raijmakers
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引用次数: 0

摘要

本研究首次利用幼儿卡片分类任务(TCST)研究 3 岁幼儿如何从反馈中学习简单规则。为了考虑学习过程中个体内部和个体之间的差异,我们使用最大似然法(Visser 等人,2002 年)对准确性反应的时间序列拟合了潜在马尔可夫模型。在第一项探索性研究(N = 110,3-5 岁儿童)中,相当一部分 3 岁儿童采用了假设检验学习策略。第二项研究通过一项预先登记的研究(3 岁儿童,N = 60)证实了这些结果。在支持性学习条件下,大多数 3 岁幼儿都能进行假设检验。此外,年龄较大和工作记忆能力较强的儿童更有可能进行假设检验,尽管他们比年龄较小或工作记忆能力较弱的儿童更容易坚持不懈。3 岁儿童的反馈学习能力比假定的更强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Latent Markov Models to Test the Strategy Use of 3-Year-Olds in a Rule-Based Feedback-Learning Task.

This study is the first to investigate how 3-year-olds learn simple rules from feedback using the Toddler Card Sorting Task (TCST). To account for intra- and inter- individual differences in the learning process, latent Markov models were fitted to the time series of accuracy responses using maximum likelihood techniques (Visser et al., 2002). In a first, exploratory study (N = 110, 3- to 5-years olds) a considerable group of 3-year olds applied a hypothesis testing learning strategy. A second study confirmed these results with a preregistered study (3-years olds, N = 60). Under supportive learning conditions, a majority of 3-year- olds was capable of hypothesis testing. Furthermore, older children and those with bigger working memory capacities were more likely to use hypothesis testing, even though the latter group perseverated more than younger children or those with smaller working memory capacities. 3-year-olds are more advanced feedback-learners than assumed.

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来源期刊
Multivariate Behavioral Research
Multivariate Behavioral Research 数学-数学跨学科应用
CiteScore
7.60
自引率
2.60%
发文量
49
审稿时长
>12 weeks
期刊介绍: Multivariate Behavioral Research (MBR) publishes a variety of substantive, methodological, and theoretical articles in all areas of the social and behavioral sciences. Most MBR articles fall into one of two categories. Substantive articles report on applications of sophisticated multivariate research methods to study topics of substantive interest in personality, health, intelligence, industrial/organizational, and other behavioral science areas. Methodological articles present and/or evaluate new developments in multivariate methods, or address methodological issues in current research. We also encourage submission of integrative articles related to pedagogy involving multivariate research methods, and to historical treatments of interest and relevance to multivariate research methods.
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