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

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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.