Artificial Intelligence-Based Analytics for Impacts of COVID-19 and Online Learning on College Students' Mental Health

TL;DR

This study employs machine learning and statistical models to analyze how COVID-19 and online learning affect college students' mental health, highlighting academic, institutional, and financial factors as key influences.

Contribution

It introduces a data-driven approach to understanding the mental health impacts of COVID-19 on students, emphasizing the role of academic and institutional factors.

Findings

Academic life features significantly impact emotional wellbeing.

Students' satisfaction with pandemic management influences mental health.

Financial security is a crucial factor in students' emotional wellbeing.

Abstract

COVID-19, the disease caused by the novel coronavirus (SARS-CoV-2), first emerged in Wuhan, China late in December 2019. Not long after, the virus spread worldwide and was declared a pandemic by the World Health Organization in March 2020. This caused many changes around the world and in the United States, including an educational shift towards online learning. In this paper, we seek to understand how the COVID-19 pandemic and increase in online learning impact college students' emotional wellbeing. We use several machine learning and statistical models to analyze data collected by the Faculty of Public Administration at the University of Ljubljana, Slovenia in conjunction with an international consortium of universities, other higher education institutions, and students' associations. Our results indicate that features related to students' academic life have the largest impact on their emotional wellbeing. Other important factors include students' satisfaction with their university's and government's handling of the pandemic as well as students' financial security.