Migrant and Seasonal Head Start (MSHS) is responsible for serving children with or without disabilities and families of migrant and seasonal farmworkers across 38 states. High-quality teaching interactions in Head Start programs have long been recognized to support children’s emergent language, and this may be especially true for children with disabilities and dual language learners. However, much of the evidence supporting this is from primarily monolingual traditional Head Start settings, not MSHS, which are required to provide bilingual instruction. Preliminary reports suggest MSHS teacher interaction quality is similar to or higher than ratings in traditional Head Start programming, indicating that MSHS may serve as a promising context for understanding program features that can contribute to dual language learner’s emergent language and literacy skills. Despite the many systematic disadvantages experienced by MSHS children, their average standardized language scores were marginally higher than scores reported in other Head Start populations of Spanish-English bilingual children, indicating a potentially positive impact of MSHS programming. Despite these potentially positive aspects of MSHS programming, few studies have explored the program and teaching practices to inform quality improvement efforts across Head Start settings serving similar populations of dual language learners. Thus, we need to identify program features and teaching practices that may contribute to promoting these children’s language and literacy development.
This study aims to:
- identify unobserved heterogeneity and capture complex patterns of program and classroom characteristics to inform targeted program quality improvement and teacher professional development; and
- identify program quality features and instructional practices that are beneficial for the MSHS children’s language and literacy development.
We will use the 2017 MSHS dataset for the proposed study. The MSHS dataset is the first such national study to include program quality measures, instructional practices, and direct child assessments on children enrolled in MSHS, which will provide valuable information about MSHS children that can inform program, center, and classroom practices. The target samples are 122 classrooms and 873 children nested within those classrooms. We will use latent class analysis (LCA) with the observed classroom and instruction quality measures, and other classroom-level observed variables (e.g., class size, teacher-child ratio, educational background, years of experience) to infer if latent subgroups with distinct patterns of scores exist in MSHS data. Furthermore, we will conduct weighted hierarchical linear modeling (HLM) with children representing level-one, classrooms representing level two, and if sufficient variance exists, programs representing level-three units. If sufficient variance in level-three program units doesn’t exist, cluster-robust standard errors will be used.
Results from this study will inform MSHS program quality and instructional practices improvement to promote young children’s language and literacy development.