# The role of statistical learning in predicting child language outcomes.

> **NIH NIH F32** · YALE UNIVERSITY · 2022 · $32,856

## Abstract

Project Summary
A key component in the development of linguistic proficiency is the capacity to learn from the regularities present
in the environment. This basic cognitive process enables the discovery of the words and grammatical relations
present in speech, and also enables the identification of these structures in written text.
 While previous research has established key connections between statistical learning – the ability to learn
from distributional patterns – and language skills in literate children, fewer studies have explored its contribution
to language outcomes in speaking, pre-literate children, and how this connection changes as a function of
reading development. The goal of the proposed research is to better understand how statistical learning impacts
two fundamental precursors to literacy: spoken word recognition and letter identification, as well as their
contribution to vocabulary and syntactic development.
 Over three sets of experiments, the proposed research will employ a cross-sectional, individual differences
approach to studying linguistic development. Our specific aims are to: 1) track the development of auditory and
visual statistical learning in pre-readers (children 4–6 years old) and early readers (children 6–8 years old), and
2) establish the contribution of individual differences in statistical learning in different modalities to online
language processing and the development of native language proficiency. We will deploy a battery of cognitive
tasks to gain a thorough understanding of the impact of statistical learning on burgeoning language skills. In
addition, we will leverage eye-tracking (one of the grant’s main training goals) to develop novel tasks that can
be used across-age groups to probe reading precursors, and how they inform general language outcomes.

## Key facts

- **NIH application ID:** 10810207
- **Project number:** 7F32HD104542-03
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Erin Isbilen
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $32,856
- **Award type:** 7
- **Project period:** 2023-04-01 → 2024-08-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10810207

## Citation

> US National Institutes of Health, RePORTER application 10810207, The role of statistical learning in predicting child language outcomes. (7F32HD104542-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10810207. Licensed CC0.

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