Dataset Information

Variations in Classroom Language Environments of Preschool Children Who Are Low Income and Linguistically Diverse.

ABSTRACT: Research Findings:This study aimed to (a) provide an in-depth description of the frequency and type of language interactions that children who are low-income and/or dual language learners (DLL) experience in their classrooms and (b) examine whether differenceFor instance, in a randomized control trial with 461 first grade s exist in children's language experiences based on children's DLL status and level of English proficiency. Using the Language Interaction Snapshot, we observed four focal children in each of 72 early childhood classrooms: one monolingual English-speaking child (i.e., non-DLL), one Spanish-dominant DLL child, and two bilingual Spanish-English DLL children. Findings indicate that both lead and assistant teachers predominantly spoke in English and implemented few evidence-based language practices. Children spoke more often to peers than to teachers. Little variation was noted in the quality of the language environment for children based on their DLL status or language proficiency. Practice:Results suggest clear directions for professional development (PD). PD must include both lead and assistant teachers and should focus on evidence-based language strategies for facilitating children's language development, including how to effectively teach DLLs. Teachers may also benefit from PD that supports use of small group activity and peer strategies.

SUBMITTER: Sawyer B

PROVIDER: S-EPMC6484442 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundVery preterm children are at increased risk of language delays. Concerns have been raised about the utility of standardised English language tools to diagnose language delay in linguistically diverse children. Our study investigated the incidence of language delay at 4 years in linguistically diverse very preterm children.MethodsVery preterm children born in South Western Sydney, Australia, between 2012 and 2016, were assessed with the Clinical Evaluation of Language Fundamentals Preschool-2 (CELF-P2) tool at 4 years of age. We sought to determine the incidence of language delay in this cohort using language scores from the CELF-P2 assessment tool, and explore potential predictors associated with language delay.ResultsOne hundred and sixty very preterm children attended the 4-year assessment out of the included 270 long-term survivors. At 4 years, 76 (52%) very preterm children had language delay diagnosed using the CELF-P2 assessment tool. Children who preferred a language other than English had lower average core language scores on the CELF-P2 assessment tool (75.1±14.4) compared with children that preferred English (86.5±17.9); p=0.002. Very preterm children growing up in households that preferenced a language other than English and those who were born from multiple births had higher odds of language delay at 4 years (AOR 10.30 (95% CI 2.82 to 38.28); p<0.001 and AOR 2.93 (95% CI 1.20 to 7.14); p=0.018, respectively). Assessing these children using an English language tool may have affected language scores at 4 years.ConclusionsIn this metropolitan setting, very preterm children from linguistically diverse backgrounds were found to be vulnerable to language delays at 4 years. Further large-scale studies evaluating the language outcomes of linguistically diverse preterm children with more culturally appropriate tools are warranted. We question the utility of standardised English language tools to assess language outcomes of linguistically diverse populations.

Project description:BACKGROUND:Sleep disturbances and low-quality diets are prevalent among children in low-income settings, yet the nature of their relationship remains unclear. In particular, whether aspects other than sleep duration, including timing and quality, are associated with dietary patterns has rarely been examined, especially among preschool-aged children. OBJECTIVE:To evaluate whether nightly and total sleep duration, sleep timing, differences in timing and duration from weekdays to weekends, and sleep quality were related to dietary patterns. DESIGN:A cross-sectional analysis of children attending preschool. Parents completed questionnaires about children's sleep habits as well as a semiquantitative food frequency questionnaire. PARTICIPANTS/SETTING:Three hundred fifty-four English-speaking children (49.9% boys) with no serious medical conditions aged 3 to 5 years who were enrolled in Head Start in Michigan (2009-2011) with complete information on sleep and diet. MAIN OUTCOME MEASURES:Dietary pattern scores derived from food frequency questionnaire. STATISTICAL ANALYSES PERFORMED:Principal component analysis was used to identify dietary patterns. Separate linear regression models with dietary pattern scores as the dependent variable and continuous sleep measures as independent variables were used to evaluate associations between sleep and diet, adjusting for sex, age, parent education level, and sleep hygiene. RESULTS:Three dietary patterns were identified: Vegetables, Healthy Proteins, and Sides; Breads and Spreads; and Processed and Fried. Longer average weekend sleep duration and a greater difference in weekend-to-weekday sleep duration was related to lower Vegetables, Healthy Proteins, and Sides pattern scores. Later sleep midpoint during weekdays was related to lower Vegetables, Healthy Proteins, and Sides pattern scores, whereas later sleep midpoint on the weekend was associated with higher Processed and Fried pattern scores. Similarly, a larger weekend-weekday midpoint difference was associated with higher Processed and Fried pattern scores. CONCLUSIONS:Later sleep timing and differences in sleep duration and timing from weekends to weekdays were related to less-optimal dietary pattern scores in young children.

Dataset Information

Variations in Classroom Language Environments of Preschool Children Who Are Low Income and Linguistically Diverse.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets