Characterizing School Recovery After Disasters: Can We Optimize Academic Recovery?

描述灾后学校恢复的特征：我们可以优化学业恢复吗？

• 批准号: 1929860
• 负责人: Betty Lai
• 金额: $ 10.79万
• 依托单位: Boston College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1929860&HistoricalAwards=false
• 关键词: Characterizing; Recovery; After; Disasters; Optimize

Schools have significant impacts on large sectors of the population in disaster situations. During and immediately after any kind of disaster affecting the greater public, schools provide communities with access to shelter, food, medical resources, and psychological resources. However, despite the important role that schools play, very little research has been conducted to understand how and why disaster-affected schools differ in their post-disaster recovery patterns. This work will identify factors that may hinder or support school academic recovery after disasters. Findings from this research will position us to advise stakeholders (e.g., school administrators, teachers, policy makers) on the potential trajectory of schools, particularly in areas vulnerable to extreme events. Pre-disaster preparedness and response planning initiatives can in turn be customized to minimize the effects of natural disasters on school academic functioning. The project's interdisciplinary team will disseminate study findings through multiple outlets (e.g., webinars targeted to superintendents in the study area, lectures to pre-service teachers, scholarly papers and presentations). To increase the educational impact of this work, the research team will actively involve and mentor undergraduate and graduate students in research and integrate study findings into multiple courses. This project has two specific aims: (1) to identify patterns of school recovery after Hurricane Ike and (2) to examine potential risk factors associated with school recovery patterns. To address Aim 1, we will examine patterns of academic recovery among approximately 400 Texas public schools in the path of Hurricane Ike (2008) by examining the pre-/post-Ike periods from 2003-2011. Growth mixture modeling techniques will be used to examine a rich dataset of public school performance outcomes in Texas in order to obtain empirical insights into the landscape of school recovery after disasters. To address Aim 2, we will examine potential risk factors and their associations with school recovery patterns, utilizing a vulnerability perspective. Specifically, we will test the relationship between school institutional infrastructure and socioeconomic and demographic factors and school recovery patterns. We will then examine the role of physical vulnerability in school recovery by mapping spatial clusters of school recovery patterns in relation to location (e.g., school district and county location, coastal location, evacuation zone, urbanized/non-urbanized area) and exposure (e.g., storm surge and flood-zone areas). The methodological approach developed here may be generalized for use after other disasters in other locations. The outcomes of the research are expected to transform future studies of disaster impacts on school functioning and improve cross-study and cross-model examinations of disaster impacts.

在灾难情况下，学校对人口的大部门产生了重大影响。在影响大公众的任何形式的灾难之后，学校都为社区提供了获得住所，食物，医疗资源和心理资源的机会。但是，尽管学校发挥了重要作用，但很少进行研究以了解如何以及为什么受灾后的灾后恢复模式有所不同。这项工作将确定可能阻碍或支持灾难后学校学术康复的因素。这项研究的结果将使我们建议利益相关者（例如学校管理人员，教师，政策制定者）​​就学校的潜在轨迹，特别是在容易受到极端事件的领域的潜在轨迹。可以定制污点前准备和响应计划计划，以最大程度地减少自然灾害对学校学术功能的影响。该项目的跨学科团队将通过多个媒体（例如，针对研究领域的负责人的网络研讨会，向职前教师的讲座，学术论文和演讲讲座）传播研究结果。为了增加这项工作的教育影响，研究团队将积极参与和指导本科生和研究生研究研究，并将研究结果纳入多个课程。该项目具有两个具体的目标：（1）识别艾克飓风后的学校恢复模式和（2）检查与学校恢复模式相关的潜在风险因素。为了解决AIM 1，我们将通过检查2003 - 2011年的前/后期时期，研究飓风Ike（2008）的大约400所得克萨斯公立学校中的学术恢复模式。增长混合物建模技术将用于检查得克萨斯州公立学校表现成果的丰富数据集，以便获得对灾难后学校康复景观的经验见解。为了解决目标2，我们将利用脆弱性观点来研究潜在的风险因素及其与学校恢复模式的关联。具体而言，我们将测试学校机构基础设施与社会经济和人口统计学因素以及学校恢复模式之间的关系。然后，我们将通过绘制与位置（例如，学区和县位置，沿海地区，疏散区，城市化/非城市化地区）和暴露（例如，风暴涌现和洪水区域）相关的学校恢复模式的空间恢复模式来研究身体脆弱性在学校恢复中的作用。此处开发的方法学方法可能被推广，以便在其他位置其他灾难后使用。这项研究的结果有望改变对灾难对学校功能的影响的未来研究，并改善对灾难影响的跨研究和跨模型检查。