Quantity-Focused Language Input Intervention: Impact on Adult Words Delivered to At-Risk Dual Language Learners

Abstract

ABSTRACT Spanish-English-speaking dual language learners (SE-DLLs) from low-income backgrounds are at risk for experiencing academic difficulty compared to peers of ethnic-majority, middle- and high-income backgrounds. Caregiver language input is a consistent predictor of later developmental and academic outcomes. The current study targeted caregivers (n = 9) of young SE-DLLs from low-income backgrounds in a language input intervention using a quantitative feedback device called Starling by Versame and its corresponding smartphone application that provided caregiver word counts and visual displays of caregiver input. In a multiple-baseline design, three cohorts of participating families tracked daily adult word counts. Researchers selected high-priority, 15-minute segments of interaction in naturalistic settings to characterize the intervention’s effect. Results indicated a limited effect of the Starling intervention on quantity of adult words across selected high-priority contexts in visual analysis and hierarchical linear modeling. Participants rated the intervention as socially and culturally valid. Null findings of intervention importantly contributed unique evidence about the use of technology-based, quantity-focused language input feedback and its social validity with families of Spanish-English-speaking backgrounds in low-income conditions.