构建儿童语言发展中一致性和变异性的理论：一种大规模数据方法。
Building theories of consistency and variability in children's language development: A large-scale data approach.
作者信息
Tsui Angeline Sin Mei, Marchman Virginia A, Frank Michael C
机构信息
Department of Psychology, Stanford University, Stanford, CA, United States.
Department of Psychology, Stanford University, Stanford, CA, United States.
出版信息
Adv Child Dev Behav. 2021;61:199-221. doi: 10.1016/bs.acdb.2021.04.003. Epub 2021 Jun 14.
Young children typically begin learning words during their first 2 years of life. On the other hand, they also vary substantially in their language learning. Similarities and differences in language learning call for a quantitative theory that can predict and explain which aspects of early language are consistent and which are variable. However, current developmental research practices limit our ability to build such quantitative theories because of small sample sizes and challenges related to reproducibility and replicability. In this chapter, we suggest that three approaches-meta-analysis, multi-site collaborations, and secondary data aggregation-can together address some of the limitations of current research in the developmental area. We review the strengths and limitations of each approach and end by discussing the potential impacts of combining these three approaches.
幼儿通常在其生命的头两年开始学习单词。另一方面，他们在语言学习方面也存在很大差异。语言学习中的异同需要一种定量理论，该理论能够预测和解释早期语言的哪些方面是一致的，哪些是可变的。然而，由于样本量小以及与可重复性和可复制性相关的挑战，当前的发展研究实践限制了我们构建此类定量理论的能力。在本章中，我们建议元分析、多地点合作和二次数据汇总这三种方法可以共同解决发展领域当前研究的一些局限性。我们回顾了每种方法的优缺点，并在最后讨论了将这三种方法结合起来的潜在影响。
Zotero 插件