| Title: |
Toward a Precision Science of Word Learning: Understanding Individual Vocabulary Pathways |
| Language: |
English |
| Authors: |
Samuelson, Larissa K. (ORCID 0000-0002-9141-3286) |
| Source: |
Child Development Perspectives. Jun 2021 15(2):117-124. |
| Availability: |
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: |
Y |
| Page Count: |
8 |
| Publication Date: |
2021 |
| Sponsoring Agency: |
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (DHHS/NIH) |
| Contract Number: |
HD045713 |
| Document Type: |
Journal Articles; Reports - Evaluative |
| Descriptors: |
Vocabulary Development; Learning Processes; Toddlers; Language Acquisition; Learning Problems; Cognitive Processes |
| DOI: |
10.1111/cdep.12408 |
| ISSN: |
1750-8592; 1750-8606 |
| Abstract: |
Toddlers vary widely in the rate at which they develop vocabulary. This variation predicts later language development and school success at the group level; however, we cannot determine which children with slower vocabulary development in the second year will continue to have difficulty. In this article, I argue that this is because we lack theoretical understanding of how multiple processes operate as a system to create individual children's pathways to word learning. I discuss the difficulties children face when learning even a single concrete noun, the multiple general cognitive processes that support word learning, and some evidence of rapid development in the second year. I present work toward a formal model of the word learning system and how this system changes over time. The long-term goal of this work is to understand how individual children's strengths and weaknesses create unique vocabulary pathways, and to enable us to predict outcomes and identify effective interventions. |
| Abstractor: |
As Provided |
| Entry Date: |
2022 |
| Accession Number: |
EJ1344396 |
| Database: |
ERIC |