Early Head Start Children's Language and Cognitive Development in the Midst of the COVID-19 Pandemic: An Analysis Using Natural Language Processing Measures (Poster 41)

• In Event: AERA Poster Session Seven
  In Poster Session: Early Education and Child Development SIG Posters

Abstract

A growing body of evidence documents the impact of the COVID-19 pandemic on school-aged children, but few studies to date have investigated cognitive growth in infants and toddlers during the pandemic-affected school year. In this study, we provide evidence on infants’ and toddlers’ language growth, holistic development, and parent involvement during the pandemic-affected 2020-21 SY using data from a novel machine-learning natural language processing measure of children’s language environment. Our sample consists of 310 children attending Early Head Start (EHS) child care centers who participated in assessments that recorded children’s live vocalizations and language interactions. We examine language acquisition during the pandemic-affected year accounting for child demographic characteristics, in-person attendance, parental beliefs, and prior assessments.

Authors

• Monica G. Lee, Stanford University
  Presenting Author

• Kathleen Lynch
  Non-Presenting Author