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

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.