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RAPID: Understanding the Impact of Abrupt Changes to Instructional Methods on Underrepresented Engineering Students

RAPID：了解教学方法突然改变对代表性不足的工程学生的影响

基本信息

批准号：
2029564
负责人：
Racheida Lewis
金额：
$ 15.25万
依托单位：
University of Georgia Research Foundation Inc
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：
2020-05-15 至 2022-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029564&HistoricalAwards=false
关键词：
RAPID Understanding Impact Abrupt Changes

项目摘要

The 2020 global pandemic caused by COVID-19 has forced higher education institutions in the United States to immediately stop face-to-face teaching and transition to virtual instruction. While this transition has not been easy for any instructor, the shift to online learning has been especially difficult for students in STEM courses, particularly engineering, which has a strong practical/laboratory component. This project investigates how the pandemic is impacting students historically underrepresented in engineering. There is an urgency to collect this data in the midst of the crisis. Through the use of an online data collection platform, SenseMaker, short stories will be collected from underrepresented engineering students to describe how they are experiencing the COVID-19 crisis during the transition to online learning. These stories will be used to help provide institutions with tools necessary to ensure minority students are not left out of decisions made with the majority in mind. This RAPID project will adopt the SenseMaker approach to investigate how underrepresented college students cope in times of crisis. This study builds on a previous investigation of community experiences in a crisis context; namely the SenseMaker approach was used to investigate how stakeholder groups in Puerto Rico adapted in the aftermath of Hurricane Maria (NSF #1832678).The overarching research question that guides this project is: How has the abrupt transition to online instruction due to COVID-19 affected students historically underrepresented in engineering? More specifically, the investigators are interested in understanding how the transition has impacted underrepresented students based on the following factors: 1) year in school (underclassmen vs. upperclassmen); 2) Predominately White Institution attendance vs Minority Serving Institution attendance; 3) socioeconomic status; and, 4) geographical location. This RAPID project will collect data until December 2020. The approach is to continuously collect micro-narratives of participants’ experiences (qualitative data) and responses to a survey questions that prompt participants to make sense of their experiences (quantitative data). These data will be analyzed for patterns to inform actions to improve the experiences of underrepresented engineering students. These data will inform future work that will focus on the development of empirically informed policies to aid institutions as we continue to navigate this current pandemic and reduce the disruption of such transitions in the future. Additionally, an outcome of conducting this research is to inform institutions of challenges faced by this particular population to highlight that diversity and inclusion efforts must be attended to in virtual learning environments and activities.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.

2020年COVID-19全球大流行迫使美国高等教育机构立即停止面对面教学并过渡到虚拟教学。虽然这种转变对任何教师来说都不容易，但对于STEM课程的学生来说，转向在线学习尤其困难，特别是工程学，它具有很强的实践/实验室成分。该项目调查了大流行病如何影响历史上在工程领域代表性不足的学生。在危机期间，迫切需要收集这些数据。通过使用在线数据收集平台SenseMaker，将从代表性不足的工程专业学生中收集短篇故事，描述他们在向在线学习过渡期间如何经历COVID-19危机。这些故事将被用来帮助机构提供必要的工具，以确保少数民族学生不会被排除在考虑到大多数人的决定之外。这个快速项目将采用SenseMaker的方法来调查代表性不足的大学生如何科普危机。本研究建立在之前对危机背景下社区经验的调查基础上;即SenseMaker方法用于调查波多黎各的利益相关者群体如何在飓风玛丽亚（NSF #1832678）之后适应。指导本项目的首要研究问题是：由于COVID-19导致的突然过渡到在线教学如何影响历史上工程专业代表性不足的学生？更具体地说，调查人员有兴趣了解过渡如何影响代表性不足的学生基于以下因素：1）在学校的一年（低年级与高年级）; 2）主要是白色机构出勤与少数服务机构出勤; 3）社会经济地位;和，4）地理位置。该RAPID项目将收集数据至2020年12月。方法是不断收集参与者经历的微观叙述（定性数据）和对调查问题的答复，促使参与者理解他们的经历（定量数据）。这些数据将被分析为模式，以通知行动，以改善代表性不足的工程专业学生的经验。这些数据将为未来的工作提供信息，这些工作将侧重于制定经验丰富的援助机构政策，因为我们将继续应对当前的大流行病，并减少未来这种过渡的破坏。此外，开展这项研究的一个成果是告知机构，这一特定人群所面临的挑战，以强调多样性和包容性的努力，必须参加在虚拟学习环境和活动。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。