RESUMO
PURPOSE: The purpose of this study was to test the efficacy of the Teaching Early Literacy and Language (TELL) curriculum package for improving the early literacy and oral language skills of preschoolers from low-income families. METHOD: In a randomized controlled trial (RCT), TELL was implemented in 30 TELL and 28 business-as-usual classrooms. TELL is a Tier 1 whole-class curriculum package that includes a scope and sequence of instruction, lesson plans and materials, high-quality books, curriculum-based measures (CBMs), and professional development training and coaching. RESULTS: Implementation fidelity was high; however, due to COVID-19 school closures, we did not collect end-of-year data for our third cohort of teachers. Results indicated significant TELL effects on all code-related CBMs and two code-related distal measures as well as receptive and expressive vocabulary CBMs. No significant differences were found on distal measures of oral language/vocabulary or listening comprehension. CONCLUSIONS: Results of the present study, paired with findings from an earlier TELL RCT with children with developmental speech and/or language impairments, suggest that children enrolled in TELL classrooms achieve higher outcomes on a variety of code-related and vocabulary measures by the end of their final preschool year. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25345708.
RESUMO
PURPOSE: The purpose of this study was to use an established model of working memory in children to predict an established model of word learning to determine whether working memory explained word learning variance over and above the contributions of expressive vocabulary and nonverbal IQ. METHOD: One hundred sixty-seven English-speaking second graders (7- to 8-year-olds) with typical development from two states participated. They completed a comprehensive battery of working memory assessments and six word learning tasks that assessed the creation, storage, retrieval, and production of phonological and semantic representations of novel nouns and verbs and the ability to link those representations. RESULTS: A structural equation model with expressive vocabulary, nonverbal IQ, and three working memory factors predicting two word learning factors fit the data well. When working memory factors were entered as predictors after expressive vocabulary and nonverbal IQ, they explained 45% of the variance in the phonological word learning factor and 17% of the variance in the semantic word learning factor. Thus, working memory explained a significant amount of word learning variance over and above expressive vocabulary and nonverbal IQ. CONCLUSION: Results show that working memory is a significant predictor of dynamic word learning over and above the contributions of expressive vocabulary and nonverbal IQ, suggesting that a comprehensive working memory assessment has the potential to identify sources of word learning difficulties and to tailor word learning interventions to a child's working memory strengths and weaknesses. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.19125911.
