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Updated: Oct 28, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Building theories of consistency and variability in children's language development: A large-scale data approach
Angeline Sin Mei Tsui1, Virginia A Marchman1, Michael C Frank1
1Department of Psychology, Stanford University, Stanford, CA, United States.
Abstract:
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.
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