Adolescent Health and Academic Achievement

这个项目将为浪潮收集高中成绩单 全国青少年健康纵向研究样本成员(新增 健康)。这些新收集的数据，加上大量的变量， 总结并描述成绩单，将成为公开的一部分 分布式添加健康数据集。Add Health旨在探索 青少年的健康行为，强调社会的影响 包括家庭、同龄人、社区和学校的背景，但它有 学术活动和成就的衡量标准有限。成绩单数据 在技术上具有挑战性的分析，但它们可以导致理解 学生的学业经历，以及机会和分层。这 成绩单研究将为学术研究提供丰富的新数据 成就和机遇，这将增强当前ADD的效用 健康数据集。 这是一个庞大而复杂的项目，分两个主要阶段和一个 跨学科研究团队，由咨询委员会监督。第一阶段 涉及高中成绩单的收集和编码以及相关的 约18,700名Wave Ill添加健康样本成员的数据，外加一个样本 他们的2,000名合伙人。一家经验丰富的数据收集公司Westat将 进行数据收集和初始编码。我们会特别注意 以确保被调查者和学校的安全。项目的第二阶段， 在德克萨斯大学进行的，涉及建造额外的 衡量教育分层和成就的变量，适用于 Add Health设计。这些额外的变量对于刺激是必不可少的 广泛使用文字记录数据，并支持初步分析。 与Add Health对社会背景的强调一致，变量 将对多层次分析有用。Westat编码的衡量标准将包括 课程作业、标准化考试分数和出席率。UT将构建措施 学业成绩(包括课程顺序状况和成绩)， 课程背景、学校过渡和学校背景。 除了提供公共访问数据外，调查人员还将提供 关于数据和用于产生数据的程序的大量文档。 他们将在多个环境中举办公开工作坊，介绍 向用户提供数据，并鼓励他们使用。他们还将出版各种不同的 对不同主题的初步分析。

This project will collect high school transcripts for the Wave of sample members of the National Longitudinal Study of Adolescent Health (Add Health). These newly collected data, plus a large number of variables that summarize and describe the transcripts, will be made part of the publicly distributed Add Health data set. Add Health was designed to explore adolescents' health behaviors, with an emphasis on the influence of social context that includes families, peers, neighborhoods and school, but it has limited measures of academic activities and achievement. Transcript data are technically challenging to analyze, but they can lead to an understanding of students' academic experiences, as well as opportunity and stratification. This transcript study will provide rich new data for the study of academic achievement and opportunity, and it will enhance the utility of the current Add Health data set. This is a large and complex project with two major phases and an interdisciplinary research team, overseen by an Advisory Board. The first phase involves the collection and coding of high school transcripts and associated data for approximately 18,700 Wave Ill Add Health sample members, plus a sample of 2,000 of their partners. Westat, an experienced data collection firm, will conduct the data collection and initial coding. Special attention will be paid to ensuring respondent and school security. The second phase of the project, conducted at The University of Texas, involves the construction of additional variables to measure educational stratification and achievement, adapted for the Add Health design. These additional variables are essential to stimulate wide use of the transcript data, as well as to support initial analyses. Consistent with the emphasis of Add Health on social context, the variables will be useful for multilevel analyses. Westat coded measures will include coursework, standardized test scores and attendance. UT will construct measures of academic achievement (including course sequence status and grades), the course taking context, school transitions, and school context. In addition to producing public access data, the investigators will produce extensive documentation about the data and the procedures used to produce them. They will conduct public workshops in a number of settings to introduce the data to users and encourage their use. They will also publish a variety of initial analyses on diverse topics.