论文标题

基于人工智能的分析对COVID-19和在线学习对大学生心理健康的影响

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

论文作者

Rezapour, Mostafa, Elmshaeuser, Scott K.

论文摘要

Covid-19是由新型冠状病毒(SARS-COV-2)引起的疾病,于2019年12月下旬首次在中国武汉出现。不久之后,该病毒在全球范围内传播,并于2020年3月被世界卫生组织宣布为大流行。这引起了世界各地的许多变化,包括在美国和包括在线学习在内的全世界变化。在本文中,我们试图了解Covid-19-19的大流行和在线学习的增加如何影响大学生的情感福祉。我们使用几种机器学习和统计模型来分析卢布尔雅那大学公共行政学院,斯洛文尼亚大学,与国际大学,其他高等教育机构和学生协会一起收集的数据。我们的结果表明,与学生的学术生活有关的特征对他们的情感健康产生了最大的影响。其他重要因素包括学生对大学和政府对大流行的处理以及学生的财务安全的满意。

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.

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