The Role of Prediction Error in 4-Year-Olds’ Learning of English Direct Object Datives

Author:

Gambi Chiara12ORCID,Messenger Katherine1ORCID

Affiliation:

1. Department of Psychology, University of Warwick, Coventry CV4 7AL, UK

2. School of Psychology, Cardiff University, Cardiff CF10 3AT, UK

Abstract

Is children’s acquisition of structural knowledge driven by prediction errors? Error-driven models of language acquisition propose that children generate expectations about upcoming words (prediction), compare them to the input, and, when they detect a mismatch (i.e., prediction error signal), update their long-term linguistic knowledge. But we only have limited empirical evidence for this learning mechanism. Using a novel touch-screen app and a pre-post training between-subjects design, we tested the effect of prediction errors on 120 English-learning 4-year-olds’ understanding of challenging direct object datives. We hypothesized that children who are exposed to input that encourages the generation of prediction error signals should show greater improvements in their post-test comprehension scores. Consistent with error-driven models of language learning, we found that children exposed to sentences that encouraged the generation of incorrect linguistic predictions improved numerically more than those who were exposed to sentences that did not support predictions. However, we caution that these preliminary findings need to be confirmed by additional testing on much larger samples (we only tested 20–30 children per training condition). If confirmed, these findings would provide some of the strongest empirical support to date for the role of prediction error in the acquisition of linguistic structure.

Funder

British Academy/Leverhulme Small Research Grant

Publisher

MDPI AG

Subject

Linguistics and Language,Language and Linguistics

Reference31 articles.

1. When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias;Albers;Journal of Experimental Social Psychology,2018

2. The development of Japanese passive syntax as indexed by structural priming in comprehension;Arai;Quarterly Journal of Experimental Psychology,2014

3. What can frequency effects tell us about the building blocks and mechanisms of language learning?;Arnon;Journal of Child Language,2015

4. Preschoolers’ Acquisition of Novel Verbs in the Double Object Dative;Arunachalam;Cognitive Science,2016

5. Bates, Douglas, Maechler, Martin, Bolker, Ben, and Walker, Steve (2023). Lme4: Linear Mixed-Effects Models Using Eigen and S4, R Development Core Team. R Package Version 1.1-33.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3