Award Abstract #2030106

RAPID: Collaborative Research: A "Citizen Science" approach to COVID-19 social distancing effects on children's language development

NSF Directorate:
SBE - Directorate for Social, Behavioral, and Economic Sciences
NSF Division:

Division of Behavioral and Cognitive Sciences

Initial Amendment Date:

Latest Amendment Date:

Award Number:

2030106

Award Instrument:

Grant

Program Manager:

Soo-Siang Lim

Start Date:

End Date:

Awarded Amount to Date:

$151,942.00

Investigator(s):

Joshua Hartshorne [email protected] (Principal Investigator)

Sponsor:

Boston College
140 Commonwealth Avenue
Chestnut Hill MA 024673800

NSF Program:
Sci of Lrng & Augmented Intel
Program Reference Code(s):
059Z
096Z
7914
Program Element Code(s):
127Y
Abstract:

The COVID-19 pandemic is a significant threat to learning and language development for large numbers of children. Such challenges are compounded for those facing social and economic adversity, factors that are associated with decreased parental interactions, child development, and school achievement. This study examines the scope and magnitude of learning impacts from COVID19 pandemic by engaging families as “Citizen Scientists” who will track their children’s language use during the crisis. Social-distancing policies vary by state, enabling the researchers to compare how these different decisions affect children’s language development. This will help policymakers and educators make more informed decisions, both about crisis management and strategies to mitigate negative effects of crisis-related policies. More broadly, this work will make important contributions to the science of language learning, which in turn will help clinicians and educators best address the needs of children from varying demographics. Finally, by using a Citizen Science paradigm, this project establishes a conduit for science outreach and education.

This project will recruit thousands of “volunteer researchers” to record data about their own family environment, parent-child conversations, and child language development using a web-based application accessible through a laptop or mobile phone. In addition to collecting survey responses, this app enables parents to make short audio recordings of their child’s speech and build a scrapbook of developing language abilities over time. When paired with comprehensive recruitment, this platform will assemble speech samples that are both broad and deep and will support more accurate models of relations between children’s learning and long- vs. short-term adversity. Additionally, the varied timing of social disruptions across locations permits both between-family and within-family comparisons of COVID-19 impacts, and yields estimates of effect sizes and modulation by race and socioeconomic status. The data will address questions of urgent societal interest, including a) how COVID-19 policies impact language-learning environments; b) how family stress changes children’s language and communication behavior; and c) what impacts the COVID-19 crisis has on developmental outcomes. Moreover, since social disruptions affect a wide demographic and are largely outside family control, this project leverages the COVID-19 crisis as an unusually clean manipulation of social and economic adversity. This avoids confounds that are persistently problematic in existing research, and will deepen theoretical insight into the factors that affect children’s language learning.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.