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Different Coping Patterns among US Graduate and Undergraduate Students during COVID-19 Pandemic: A Machine Learning Approach.
Zhao, Yijun; Ding, Yi; Shen, Yangqian; Failing, Samuel; Hwang, Jacqueline.
  • Zhao Y; Computer and Information Sciences Department, Fordham University, New York, NY 10023, USA.
  • Ding Y; Graduate School of Education, Fordham University, New York, NY 10023, USA.
  • Shen Y; Graduate School of Education, Fordham University, New York, NY 10023, USA.
  • Failing S; Computer and Information Sciences Department, Fordham University, New York, NY 10023, USA.
  • Hwang J; Graduate School of Education, Fordham University, New York, NY 10023, USA.
Int J Environ Res Public Health ; 19(4)2022 02 19.
Article in English | MEDLINE | ID: covidwho-1699174
ABSTRACT
COVID-19 caused unprecedented disruptions to regular university operations worldwide. Dealing with 100% virtual classrooms and suspension of essential in-person activities resulted in significant stress and anxiety for students coping with isolation, fear, and uncertainties in their academic careers. In this study, we applied a machine learning approach to identify distinct coping patterns between graduate and undergraduate students when facing these challenges. We based our study on a large proprietary dataset collected from 517 students in US professional institutions during an early peak of the pandemic. In particular, we cast our problem under the association rule mining (ARM) framework by introducing a new method to transform survey data into market basket items and customer transactions in which students' behavioral patterns were analogous to customer purchase patterns. Our experimental results suggested that graduate and undergraduate students adopted different ways of coping that could be attributed to their different maturity levels and lifestyles. Our findings can further serve as a focus of attention (FOA) tool to facilitate customized advising or counseling to address the unique challenges associated with each group that may warrant differentiated interventions.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19042430

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Observational study Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijerph19042430