|Exploring Heterogeneity Among the U.S. Latino Dual Language Learner Head Start Population: A Secondary Data Analysis
|University of South Florida
|Early Learning Programs and Policies [Program Details]
|2 years (08/01/2021 – 07/31/2023)
Co-Principal Investigator: Foster, Matthew
Purpose: The purpose of this project is to explore the heterogeneity of the Latino dual language learner (DLL) population within Head Start. Specifically, secondary data collected with a sample of Latino DLLs attending Florida Head Start programs will be used to 1) identify subgroups based on their levels of cognitive, linguistic, literacy, and math achievement in both English and Spanish prior to kindergarten entry; 2) identify subgroups based on growth trajectories for language, literacy, and math in English and Spanish as they transition into kindergarten; and 3) identify subgroups based on initial levels and growth trajectories for their positive play interactions, problem behaviors, and approaches to learning. Home and malleable classroom factors associated with the subgroups will be examined.
Project Activities: The data for this secondary data analysis includes 396 Latino DLLs who were enrolled in Head Start programs in Florida between 2009-2011. The children were divided into cohorts and a cross-sectional longitudinal design was employed. The younger cohort (n = 128) were followed from Spring of 3-year-old pre-k through the Spring of 4-year-old pre-k. The older cohort (n = 258) were followed from the Spring of 4-year-old pre-k through the Spring of Kindergarten. Each cohort was assessed at three timepoints. In this project, Latent Profile Analysis will be used to identify profiles of DLL learners at the end of the 4-year-old pre-k year including the full sample. Then, Growth Mixture Models will be used to identify growth profiles for the older cohort through the spring of kindergarten, as well as to identify growth profiles of social-emotional development as the older cohort transitions from the spring of pre-k through the spring of kindergarten.
Products: The researchers will produce information about the different profiles of DLLs at the end of Head Start. They will also disseminate their findings at conferences and in peer-reviewed publications.
Setting: The data were collected in Head Start and kindergarten classrooms serving Latino DLLs in five large urban districts in the South and Central regions of Florida.
Sample: This sample includes 396 Latino DLLs, across two cohorts, enrolled in Florida Head Start programs from 2009–2011. Cohort 1 attended Head Start and kindergarten. Cohort 2 attended Head Start for the two years.
Factors: Factors expected to relate to learner outcomes include maternal education, maternal years in the U.S., language use at home, language use in the classroom, teacher ethnicity, percent DLLs in the classroom, and the three CLASS dimensions (i.e., emotional support, classroom organization, instructional support).
Research Design and Methods: In this two-year project, researchers will use secondary data to explore the 1) cross-linguistic school readiness profiles of the entire sample of Latino DLLs at the end of Head Start; 2) cross-linguistic growth profiles for achievement as DLLs transition from Head Start and into kindergarten for cohort 1; and 3) profiles of change in social emotional development as DLLs transition into kindergarten for cohort 1. In Year 1, the researchers will prepare the dataset and conduct analysis in response to research question 1. In Year 2, they will conduct analysis in response to research questions 2 and 3. In addition, the researchers will disseminate findings to policymakers, researchers, and practitioners, as well as present findings at national research conferences and write journal articles across the two years.
Key Measures: The key cognitive, linguistic, and academic child-level outcomes are W scores from the following subtests of the Woodcock-Johnson III/ Batería III Woodcock-Muñoz administered in both English and Spanish: picture vocabulary, oral comprehension, letter-word id, spelling, applied problems, quantitative concepts, spatial relations, visual matching, and picture recognition. The key social-emotional child-level outcomes are T scores from the Penn Interactive Peer Play Scale (PIPPS) and the Preschool Learning Behavior Scale (PLBS). Malleable classroom factors include CLASS scores and responses from a teacher demographic survey. Home factors were obtained from a parent demographic survey.
Data Analytic Strategy: The researchers will account for the nesting of DLLs within classrooms in all statistical models (i.e., multilevel modeling). Latent profile analysis will be used to examine cross-linguistic school readiness profiles. To examine profiles of latent growth trajectories for language, literacy, math, and social emotional development, growth mixture modeling will be used. After deciding on the number of profiles, the researchers will include home and classroom covariates in that model.