Disparities in Self Regulation and School Readiness: Kindergarten Follow-up

自我调节和入学准备方面的差异：幼儿园后续行动

基本信息

批准号：
8594939
负责人：
MARGARET O CAUGHY
金额：
$ 56.48万
依托单位：
UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-07-01 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8594939
关键词：
2 year old 21 year old Academic achievement Achievement Address African American Age American Behavior Behavioral Characteristics Child Child Behavior Child Development Competence Conflict (Psychology)County Data Data Collection Development Ecology Enrollment Environment Equation European Failure Family Father-Child Relations Fathers Funding Growth Health Home environment Home visitation House Call Individual Differences Informal Social Control Interview Knowledge Latino Linear Regressions Location Low income Measures Mediating Methods Mexican Americans Minority Modeling Mothers Parents Performance Population Positioning Attribute Race Readiness Research Risk Sampling Schools Socioeconomic Status Structure Student Dropouts Texas Time cohort early experience effective intervention elementary school first grade follow-up high school kindergarten member public health relevance skills social skills teacher

项目摘要

DESCRIPTION (provided by applicant): Self regulation and race/ethnic disparities in school readiness: Kindergarten Follow Up although the importance of behavioral self regulation skills for school readiness is widely accepted, little is known about the development of these skills among low income African American and Latino children. These children are significantly more likely to experience early academic failure, and deficits in early achievement have long-term implications, including greater risk of high school dropout and poor health. Further, no studies have examined the combined impact of both of a supportive home environment and a supportive kindergarten classroom on emerging self regulation and early academic performance among minority children. This study builds upon an ARRA-funded project that established a cohort of 404 low income Latino (predominantly Mexican American) and African American children who were originally enrolled at 21/2 years of age. The proposed project will follow the sample into kindergarten and first grade to examine the relation of individual differences in self regulation development to differences in early academic performance. We will address the following specific aims in this sample of low income Latino and African American children: Aim 1. Examine how individual differences in the emergence of behavioral self regulation are related to differences in academic performance in kindergarten and first grade. Aim 2. Identify how family-level risk and protective factors contribute to the emergence of behavioral self regulation and academic performance in kindergarten and first grade. Aim 3. Examine how the kindergarten classroom environment contributes to the development of self regulation as well as moderates the relation between self regulation and academic performance in kindergarten and first grade. Data collection methods will include home visits and teacher interviews. Measures include child self regulation tasks, assessments of academic performance and social competence, family environment, classroom environment, teacher-child relationship, and child behavior in the classroom. Analytic methods will include multiple linear regression, structural equations modeling, and latent growth curve analysis.

描述（由申请人提供）：学校准备就绪的自我调节和种族/种族差异：幼儿园随访，尽管行为自我调节技能对学校准备的重要性已被广泛接受，但对低收入的非裔美国人和拉丁裔儿童的这些技能的发展知之甚少。这些孩子更有可能经历早期的学术失败，并且早期成就的赤字具有长期影响，包括更大的高中辍学风险和健康状况不佳。此外，尚无研究检查支持性家庭环境和支持性的幼儿园教室对新兴自我调节和少数族裔儿童的早期学业表现的综合影响。这项研究建立在一个由ARRA资助的项目基础上，该项目建立了404个低收入拉丁裔（主要是墨西哥裔美国人）和最初在21/2岁时入学的非洲裔美国儿童。拟议的项目将遵循样本进入幼儿园和一年级，以研究自我调节发展中个体差异与早期学术绩效差异的关系。我们将在低收入拉丁裔和非裔美国儿童的样本中解决以下特定目标：目标1。检查行为自我调节的出现中个体差异与幼儿园和一年级的学术表现差异有关。目标2。确定家庭一级的风险和保护因素如何促进幼儿园和一年级的行为自我调节和学习成绩的出现。目标3。检查幼儿园的课堂环境如何促进自我调节的发展，并在幼儿园和一年级的自我调节与学习成绩之间的关系。数据收集方法将包括家庭访问和教师访谈。措施包括儿童自我调节任务，对学业成绩和社会能力的评估，家庭环境，课堂环境，教师关系以及教室中的儿童行为。分析方法将包括多个线性回归，结构方程建模和潜在生长曲线分析。