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Collaborative Research RAPID: Matriculation and Well-Being Under Emergent Events (MWEE): Using Data to Empower Campus Communities in Times of Crisis

协作研究 RAPID：紧急事件下的入学和福祉 (MWEE)：利用数据在危机时期为校园社区提供支持

基本信息

批准号：
2040072
负责人：
Julie Ivy
金额：
$ 10.65万
依托单位：
North Carolina State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-15 至 2022-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2040072&HistoricalAwards=false
关键词：
Collaborative Research RAPID Matriculation Well

项目摘要

Each of the nearly 20 million students that attended American colleges and universities in Fall 2019 had his or her education disrupted due to the COVID-19 pandemic. Colleges and universities responded quickly and dynamically to help mitigate disease spread while continuing to deliver a high-quality learning experience. Mitigation strategies involved rapid transitions to online learning, closure of on-campus housing with little to no notice, and drastic changes to student and university life over several weeks. The disruption has drastically changed our communities, and these changes may be particularly challenging for our most vulnerable students, including ones with housing and hunger insecurity or behavioral health issues. This RAPID project, Matriculation and Well-Being Under Emergent Events (MWEE), will utilize time-sensitive data associated with the COVID-19 pandemic to study student well-being. MWEE will focus on engineering students in undergraduate programs where a component of course success is often hands-on labs and teamwork. MWEE will harness data from five campuses, engage communities and encourage the development of processes and actions to address this global challenge. The institutions include a private university, a public university, and three land-grant universities, one of which is a historically black college and university (HBCU). Geographic regions include the South, Midwest and Pacific Northwest. A better understanding of critical factors that influence the success of vulnerable students can provide insight for developing effective interventions for reducing college attrition associated with COVID-19. The knowledge can also potentially inform university decisions regarding response to other emergent events. MWEE aims to (i) collect and synthesize structured and unstructured data from multiple sources that relate to the health and behavior of students and (ii) utilize machine learning and optimization techniques to learn from the data to identify best practices, identify students at risk, and inform potential policies and interventions. The MWEE methodology will create a new convergent scientific paradigm to understand, assess, and measure individual and community well-being and resilience during complex and novel situations such as the COVID-19 pandemic. It is expected that universities will be able to layer the results with data from their campuses to predict retention and graduation rates given emergent events including COVID-19.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

2019年秋季，由于COVID-19大流行，近2000万名就读于美国高校的学生中的每一个人的教育都受到了干扰。学院和大学迅速做出动态反应，帮助减轻疾病传播，同时继续提供高质量的学习体验。缓解策略包括快速过渡到在线学习，在几乎没有通知的情况下关闭校园住宿，以及在几周内对学生和大学生活进行剧烈改变。这种破坏极大地改变了我们的社区，这些变化可能对我们最脆弱的学生尤其具有挑战性，包括那些有住房和饥饿不安全或行为健康问题的学生。这个名为“紧急事件下的入学和福祉”（MWEE）的快速项目将利用与COVID-19大流行相关的时间敏感数据来研究学生的福祉。MWEE将专注于本科课程的工程专业学生，其中课程成功的一个组成部分通常是动手实验室和团队合作。MWEE将利用来自五个校区的数据，与社区互动，并鼓励制定流程和行动，以应对这一全球挑战。这些机构包括一所私立大学，一所公立大学和三所赠地大学，其中一所是历史上的黑人学院和大学（HBCU）。地理区域包括南部、中西部和太平洋西北部。更好地了解影响弱势学生成功的关键因素，可以为制定有效的干预措施提供见解，以减少与COVID-19相关的大学减员。这些知识也可能为大学对其他紧急事件的反应提供信息。MWEE旨在（i）收集和综合来自多个来源的与学生健康和行为相关的结构化和非结构化数据;（ii）利用机器学习和优化技术从数据中学习，以确定最佳实践，识别有风险的学生，并为潜在的政策和干预措施提供信息。MWEE方法将创建一个新的融合科学范式，以理解、评估和衡量个人和社区在复杂和新颖的情况下（如COVID-19大流行）的福祉和复原力。预计大学将能够将结果与来自校园的数据分层，以预测包括COVID-19在内的紧急事件的保留率和毕业率。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。